DEV Community: Alvin

How to Choose a CDN for Asia in 2026: 7 Providers Compared

Alvin — Thu, 24 Sep 2026 06:54:09 +0000

TL;DR

CDN performance in Asia depends on regional routing, ISP connectivity, edge coverage, and cross-border network paths, not global PoP count alone.
CDNetworks is particularly focused on APAC delivery and Mainland China, making it relevant for businesses serving both markets.
Cloudflare, Akamai, and Fastly provide strong global and APAC delivery, with different approaches to security, edge delivery, and developer workflows.
Amazon CloudFront fits teams already invested in AWS, while Tencent Cloud and Alibaba Cloud are strong options for China-focused deployments.
Mainland China delivery requires additional evaluation of local infrastructure, ICP requirements, compliance, and cross-border routing.
The right CDN depends on user geography, traffic patterns, content types, and whether Mainland China is part of the delivery architecture.

What You'll Learn

Why CDN performance varies across Asian markets
How seven major CDN providers compare in APAC
What changes when Mainland China is part of the delivery strategy
Which CDN capabilities matter for e-commerce, media, gaming, and China-focused services
How to evaluate CDN providers beyond global network size

Why Does CDN Performance Vary Across Asia?

CDN performance varies across Asia because internet infrastructure, ISP connectivity, routing, and regulatory requirements differ significantly between countries.

Singapore, Japan, South Korea, Hong Kong, India, Indonesia, Vietnam, Thailand, and Australia can have very different network paths to the same origin server. A CDN with strong global coverage can still produce inconsistent results when traffic crosses congested or indirect routes.

Mainland China adds another layer of complexity. Local infrastructure, ICP requirements, licensing, and cross-border connectivity can materially affect delivery architecture and latency.

For an Asia-focused CDN comparison, regional connectivity matters as much as the total number of global edge locations.

How Were the Best CDN Providers for Asia Evaluated?

The comparison uses five criteria that are especially relevant to Asia-Pacific deployments:

Criteria	What to Evaluate
Geographic coverage	Density of edge PoPs across key APAC markets
Performance	Routing efficiency, delivery speed, cache behavior, and stability under high traffic
Security	DDoS mitigation, WAF, bot protection, API security, and SSL/TLS management
Mainland China delivery	Licensed infrastructure, ICP compliance, and cross-border routing stability
Support	24/7 availability, regional expertise, and incident escalation speed

For businesses spanning Mainland China and wider APAC markets, China delivery is often one of the most important criteria because regulatory, licensing, and cross-border interconnection constraints can affect the architecture.

What Are the 7 Best CDN Providers for Asia in 2026?

Each provider approaches content delivery differently. Some prioritize global reach, while others focus more heavily on enterprise security, cloud integration, developer workflows, or regional performance.

Provider	Best For	CDN Delivery Capability	Asia Coverage	China Delivery	Support
CDNetworks	APAC and Mainland China content delivery	High-performance CDN routing for APAC traffic and cross-border performance in China	Strong APAC coverage with optimized traffic routing	Global platform with Mainland China delivery, regional routing optimization, and compliance support	24/7 vendor support with no extra cost
Cloudflare	Global websites serving users across Asia	Global edge caching with static and dynamic content delivery	Broad regional coverage	Cross-border routing into China through partners; no fully native edge presence in Mainland China	Self-service with paid enterprise support
Akamai	Large enterprises with established operations across Asia	Large-scale CDN performance with origin offload and global cache efficiency	Strong and mature APAC footprint	Compliant or partnered China delivery arrangements; no direct mainland China CDN operation after June 30, 2026	Enterprise support plans
Amazon CloudFront	Applications built on AWS	Deep integration with AWS origins and services	Strong APAC presence through AWS edge PoPs	Available through AWS China regions; separate accounts and legal entity required	Depends on the AWS support plan
Fastly	Developer-centric organizations serving major Asian hubs	Programmable edge delivery, fast cache purging, and dynamic content delivery	Strong in key APAC hubs	No Mainland China PoPs listed on Fastly's current network map	Developer-focused documentation with paid support tiers
Tencent Cloud	Businesses expanding into Mainland China	CDN acceleration, media delivery, and cloud-native integration	Strong but China-centric APAC footprint	Strong domestic Mainland China delivery	Tiered support plans
Alibaba Cloud	Organizations running workloads on Alibaba Cloud	Integrated cloud infrastructure and CDN for Asia and China distribution	Strong coverage across China and Asia	Strong Mainland China delivery	Tiered support plans

Which CDN Providers Stand Out in Asia?

1. CDNetworks

CDNetworks operates more than 3,000 PoPs across more than 90 countries and regions. The network has particularly strong coverage throughout Asia Pacific and Mainland China, including 100% coverage across Southeast Asia.

Key Capabilities

CDNetworks combines intelligent traffic routing, content acceleration, edge caching, and integrated security capabilities.

Security services include:

Web Application Firewall (WAF)
DDoS protection
Bot management
API security

The combination is designed for delivery environments where ISP diversity, last-mile variability, and cross-border routing can affect performance and availability.

Best Use Cases

CDNetworks is particularly relevant for:

E-commerce platforms serving multiple APAC markets
Low-latency live streaming and media delivery
Online gaming
Organizations delivering content across both Mainland China and the wider Asia Pacific region

Asia Considerations

Asia-Pacific traffic can encounter different ISP paths and last-mile conditions from one market to another. CDNetworks' regional delivery capabilities are designed to support more consistent performance across fragmented Asian network environments.

According to DigiCert PerfOps data from April 2026, CDNetworks ranked first for content delivery performance across Asia.

For multinational organizations, CDNetworks' Global-to-China solution provides a way to extend global digital services into Mainland China as part of a broader CDN strategy.

2. Cloudflare

Cloudflare provides a global CDN combined with security and network services such as DNS, DDoS protection, and edge delivery.

Key Capabilities

Cloudflare provides:

Edge caching
Intelligent routing
WAF
Bot management
DDoS protection

Best Use Cases

Cloudflare is commonly used for:

Global websites with users across Asia
E-commerce sites requiring integrated security
Organizations seeking a unified global CDN and security platform

Asia Considerations

Cloudflare maintains broad coverage across Asia Pacific.

For Mainland China delivery, Cloudflare uses a separate China Network through local partners. Organizations with production traffic in China should validate routing, compliance, and operating requirements before deployment.

3. Akamai

Akamai is a long-established provider for large enterprises and high-traffic digital platforms. Its enterprise delivery and security portfolio, together with a long-standing APAC presence, makes it relevant for complex regional and global deployments.

Key Capabilities

Akamai combines large-scale content delivery with security services including:

DDoS protection
API security
Application acceleration
Enterprise content delivery

Best Use Cases

Akamai is commonly evaluated for:

High-traffic e-commerce platforms
Global video streaming services
Online gaming platforms
Enterprise digital applications

Asia Considerations

Akamai maintains extensive coverage across Asia Pacific and is commonly evaluated for complex regional and global deployments.

However, Akamai no longer operates CDN infrastructure directly within Mainland China as of June 30, 2026. Organizations with China delivery requirements should evaluate alternative arrangements and verify the resulting delivery architecture.

4. Amazon CloudFront

Amazon CloudFront is Amazon Web Services' native CDN and a natural fit for teams already using AWS infrastructure, security services, and AWS-hosted origins.

Key Capabilities

CloudFront integrates with AWS services including:

Amazon S3
Elastic Load Balancing
AWS Shield
AWS WAF

The integration supports edge caching, origin shielding, and secure content delivery for web applications, APIs, and video.

Best Use Cases

CloudFront is commonly used for:

AWS-hosted applications
Web applications and APIs
Video delivery

Asia Considerations

CloudFront has a strong APAC presence, but performance in Asia can vary based on user location, ISP connectivity, origin placement, and routing requirements.

For China-specific deployments, AWS China regions require separate accounts and a separate legal entity structure.

5. Fastly

Fastly is a developer-focused edge cloud platform known for fast cache purging, real-time configuration, and dynamic content delivery.

Key Capabilities

Fastly emphasizes:

Programmable edge services
API delivery
Streaming support
Dynamic content delivery
Rapid cache and configuration changes

Best Use Cases

Fastly is commonly considered for:

APIs and developer platforms
Streaming and media services
Applications requiring rapid delivery rule changes

Asia Considerations

Fastly covers key APAC hubs, but no Mainland China PoPs are listed on its current network map.

Organizations serving both wider Asia Pacific and Mainland China should validate Fastly's local reach against actual audience distribution and traffic paths.

6. Tencent Cloud

Tencent Cloud combines extensive Mainland China infrastructure with a growing regional footprint across Asia Pacific.

Key Capabilities

Tencent Cloud provides:

CDN acceleration
Media delivery
Edge security
Cloud-native integration

Best Use Cases

Tencent Cloud is commonly considered for:

China-first applications
Online gaming
Tencent Cloud-native applications

Asia Considerations

Tencent Cloud's regional footprint is weighted heavily toward Mainland China. The architecture can therefore be a better fit for China-first services than for organizations seeking equally deep coverage across a broad mix of APAC and emerging markets.

7. Alibaba Cloud

Alibaba Cloud operates CDN infrastructure across Asia Pacific and is commonly considered by organizations already running workloads on Alibaba Cloud.

Key Capabilities

Alibaba Cloud CDN integrates with the broader Alibaba Cloud platform to support:

Content acceleration
Security services
Cloud-native deployment models
Mainland China delivery

Best Use Cases

Alibaba Cloud is commonly evaluated for:

Alibaba Cloud applications
China-focused services
Organizations expanding from China into nearby Asian markets

Asia Considerations

Alibaba Cloud is commonly evaluated by organizations seeking cloud-native CDN delivery for China-centric workloads and regional expansion across Asia.

Which CDN Is Best for Your Industry?

CDN requirements change significantly by industry. Traffic volatility, latency sensitivity, security requirements, content types, and cross-border traffic can all change which capabilities matter most.

Best for E-Commerce

Recommended CDN Providers: Cloudflare, Akamai, CDNetworks

Key selection criteria for e-commerce CDNs include:

Absorbing flash-sale and promotional traffic spikes without service degradation
Low latency for checkout and payment flows
Strong bot management and WAF capabilities
Efficient caching for dynamic and personalized product content

Cloudflare

Cloudflare is commonly selected by organizations seeking a platform that combines CDN, DNS, and security services. WAF and bot management can help protect online storefronts from automated attacks.

Akamai

Akamai is widely used by large retailers that prioritize resilience, enterprise security, and performance during high-volume shopping events.

CDNetworks

CDNetworks is relevant for e-commerce platforms serving customers across multiple Asian markets, particularly where cross-border traffic, checkout latency, and regional consistency affect the user experience.

Integrated CDN acceleration, DDoS protection, WAF, and bot mitigation support flash-sale traffic and application availability across Asia and Mainland China.

Best for Media & Entertainment

Recommended CDN Providers: Akamai, CDNetworks, Fastly

Key selection criteria for streaming CDNs include:

Stable low-latency delivery for live and on-demand video
Adaptive bitrate (ABR) streaming
Efficient chunk delivery
Origin shielding
Elastic scalability during large live events

Akamai

Akamai is widely used for large-scale broadcast and live sports delivery because of its global edge capacity and long-standing media infrastructure.

CDNetworks

CDNetworks is relevant for live and on-demand media delivery across Asia Pacific and Mainland China, where regional network quality can significantly influence viewer experience.

Low-latency delivery, scalable edge capacity, and regional routing help support stable playback during large live events.

Fastly

Fastly is often considered for interactive streaming and media services that require real-time content updates. Dynamic cache controls and rapid configuration changes can be useful when delivery rules need to adapt during an event.

Best for Gaming

Recommended CDN Providers: CDNetworks, Akamai, Tencent Cloud

Key selection criteria for gaming CDNs include:

Low latency and stable connections for real-time gameplay, matchmaking, and interactive services
Efficient distribution of large game patches, updates, and in-game assets
Scalable capacity for launch-day demand and live-service traffic
Strong DDoS mitigation

CDNetworks

CDNetworks is relevant for latency-sensitive gaming and interactive applications serving users across fragmented Asian networks and cross-region player bases.

Regional delivery capabilities can support connectivity for real-time services while distributing large game files, patches, and updates at scale.

Akamai

Akamai is widely adopted by large game publishers that need global infrastructure stability and capacity for high concurrent user volumes during launches, tournaments, and live events.

Tencent Cloud

Tencent Cloud is commonly considered by game developers targeting Mainland China, particularly when game services are hosted within the Tencent Cloud ecosystem or require domestic network connectivity.

Best for China-Focused Services

Recommended CDN Providers: CDNetworks, Tencent Cloud, Alibaba Cloud

Key selection criteria for China-focused CDNs include:

Compliance readiness, including ICP filing or licensing requirements
ISP peering and delivery quality within Mainland China
Stable cross-border routing between China and other Asian regions
Operational support for architectures serving domestic and international users

CDNetworks

CDNetworks is commonly considered by organizations delivering content inside Mainland China and across the broader Asia-Pacific region.

Its integrated global platform, regional traffic optimization, and Mainland China delivery capabilities can simplify architectures that otherwise require separate regional CDN deployments.

Tencent Cloud

Tencent Cloud is commonly considered for applications primarily targeting Mainland China users or operating within the Tencent Cloud ecosystem.

Domestic infrastructure supports China-first delivery, with regional capacity for selected Asia-Pacific expansion requirements.

Alibaba Cloud

Alibaba Cloud is frequently evaluated for China-centric workloads and applications already integrated within the Alibaba Cloud ecosystem.

Domestic infrastructure and cloud-native integration support deployment models focused on Mainland China performance.

How Should You Choose a CDN for Asia?

Start with your traffic distribution rather than the provider list.

Map users across Southeast Asia, Greater China, Japan and South Korea, India and South Asia, Australia, and other APAC markets that contribute meaningful traffic.

Next, identify workload requirements. A static website, API platform, live-streaming service, e-commerce application, and online game can require very different CDN capabilities.

Finally, test the delivery paths that matter to the business.

Real-world benchmarks across representative regions and ISPs can reveal performance differences that are not obvious from global PoP counts or provider network maps.

Conclusion

Choosing a CDN for Asia is primarily a regional networking problem, not a global PoP-count competition.

CDN performance can vary substantially between Asian markets because ISP connectivity, routing, infrastructure, and regulatory requirements differ. Mainland China introduces additional architectural and compliance considerations.

The seven providers covered in this guide take different approaches:

Provider	Primary Consideration
CDNetworks	APAC and Mainland China delivery
Cloudflare	Global CDN and integrated security
Akamai	Large-scale enterprise delivery
Amazon CloudFront	AWS-native applications
Fastly	Programmable edge delivery
Tencent Cloud	China-focused applications
Alibaba Cloud	Alibaba Cloud and China-centric workloads

The most useful CDN comparison starts with your actual users, traffic patterns, application architecture, and Mainland China requirements.

A CDN that performs well in one Asian market may not produce the same results in another. Testing representative regions, ISPs, and traffic paths is often more informative than comparing global network size alone.

What has your experience been with CDN performance across Asia? Have you seen major differences between countries, ISPs, or cross-border routes that were not obvious from provider benchmarks?

SQL Injection: Detection, Prevention, and Practical Security

Alvin — Mon, 21 Sep 2026 03:12:00 +0000

SQL injection (SQLi) is a long-standing web application vulnerability, but the underlying engineering problem remains highly relevant: untrusted input is allowed to influence the structure or behavior of a database query.

The impact can range from unauthorized data access to authentication bypass, data modification, or deletion. In some database configurations, exploitation may also extend to file access or operating-system functionality.

The key is to prevent user input from becoming SQL syntax in the first place.

Where SQL Injection Happens

SQL injection is not limited to login forms. Any application feature that uses user-controlled data to build database queries can introduce the vulnerability.
Common input sources include:

URL parameters and API requests
Search and account forms
HTTP headers and cookies
JSON or XML request bodies
Uploaded data
Third-party integrations
Background jobs and reporting tools
Previously stored database values

The vulnerable pattern is usually straightforward: application code directly concatenates an input value into an SQL statement.

query = "SELECT * FROM products WHERE category = '" + category + "'"

database.execute(query)

The problem is not the input itself. The problem is that the application allows the input to affect the query structure.
A parameterized query keeps the SQL structure fixed:

query = "SELECT * FROM products WHERE category = ?"

database.execute(query, [category])

The database can then treat the supplied value as data rather than SQL syntax.

The Main Attack Patterns

SQL injection can take several forms.

In-band SQLi uses the same communication channel to submit the attack and receive database results. Error-based and UNION-based techniques are common examples.

Blind SQLi occurs when database results are not directly exposed. Attackers infer information from application behavior, including response differences or timing.

Out-of-band SQLi uses a separate communication channel to return information and depends on database and network configuration.

Second-order SQLi is more subtle: unsafe input is stored first and becomes exploitable later when another process uses that value in a dynamically constructed query.

This is why filtering obvious attack strings alone is not a reliable defense.

What Makes the Vulnerability Dangerous?

The impact depends on the vulnerable query, database configuration, and permissions of the application's database account.

A successful attack may expose customer or authentication data, modify business records, bypass authentication, or delete database objects. Excessive database privileges can further increase the damage.

The 2023 MOVEit Transfer incident illustrates how an SQL injection vulnerability can become the starting point for a broader compromise. The CL0P ransomware group exploited CVE-2023-34362, leading to unauthorized access, web-shell deployment, and data theft from affected systems.

Prevention: Start With the Query

The most important defense is parameterized queries and prepared statements.
Beyond that, several controls should work together:

Avoid SQL string concatenation with untrusted input.
Use stored procedures safely and avoid dynamic SQL inside them.
Apply allow-lists when users need to select structural elements such as sort fields or column names.
Use least privilege so application accounts have only the database permissions they require.
Control error messages so database details are not exposed to users.
Test continuously through code review, SAST, DAST, IAST, regression testing, and authorized penetration testing.

Input validation is useful, but it should support—not replace—parameterized queries. Character-based deny-lists are particularly unreliable because SQL syntax can be represented in different ways.

Detection and Runtime Protection

Prevention should be supported by monitoring.

Useful indicators can include repeated malformed requests, unusual database errors, abnormal query volumes, unexpected response delays, unusually large result sets, unauthorized data changes, and repeated WAF detections.

None of these signals proves an SQL injection attack by itself. Application logs, database logs, WAF events, identity systems, and network telemetry should be correlated during investigation.

A Web Application Firewall (WAF) adds another layer by inspecting HTTP/HTTPS requests and blocking many known SQL injection patterns. It can also provide visibility and virtual patching while a permanent application fix is being developed.

CDNetworks, for example, provides WAF-based SQL injection protection across 3,000+ global PoPs, combining 1,000+ built-in security signatures with AI and machine-learning-based analysis. Its security services also include vulnerability assessment and penetration testing.

A WAF should still be treated as defense in depth. It can reduce exposure, but it does not remove the vulnerable query.

Final Thoughts

SQL injection is fundamentally a problem of how applications handle untrusted data.

The strongest approach is to keep SQL instructions and user input separate throughout the application stack. Parameterized queries provide the foundation, while validation, least-privilege access, secure error handling, continuous testing, monitoring, and WAF protection add further layers.

The goal is not simply to detect malicious SQL. It is to make sure untrusted input never becomes executable SQL in the first place.

5 CDN Providers for DDoS Protection in 2026: What Developers Should Know

Alvin — Wed, 16 Sep 2026 03:44:00 +0000

TL;DR

A security-enabled CDN can stop malicious traffic at distributed edge locations before it reaches your origin.
The best CDN for DDoS protection depends on your workload, attack surface, traffic routing, geographic requirements, and whether you need protection beyond HTTP/S.
CDNetworks is a strong choice for integrated CDN, WAAP, and DDoS protection across web, API, and TCP/UDP workloads.
Akamai is well suited to large enterprises with complex hybrid and network infrastructure.
Cloudflare stands out for automated mitigation across a highly distributed edge.
Fastly is a natural fit for applications and APIs already delivered through its platform.
Imperva combines CDN-backed website protection with broader network DDoS mitigation.

What You’ll Learn

How CDN-based DDoS protection works
The difference between CDN-based and dedicated DDoS mitigation
How I evaluated five leading CDN providers
Where CDNetworks, Akamai, Cloudflare, Fastly, and Imperva differ
How to choose the right DDoS-protected CDN for your application

What Is CDN-Based DDoS Protection?

A CDN normally sits between users and your origin infrastructure.

Instead of every request connecting directly to the origin, traffic first reaches a distributed network of edge servers. This architecture improves content delivery, but it also creates a useful security layer.

During a DDoS attack, the CDN can analyze, rate-limit, challenge, or discard suspicious traffic before it consumes resources at the origin.

                          CDN Edge
                        ┌───────────┐
Legitimate users ──────▶│           │──────▶ Origin
Attack traffic ────────▶│           │
                        └───────────┘
                              │
                              └── Malicious traffic filtered

At Layers 3 and 4, providers can absorb or filter attacks such as UDP floods, SYN floods, and amplification attacks.

At Layer 7, protection becomes more application-aware. HTTP floods can resemble legitimate requests, so providers may use request rates, behavioral patterns, headers, bot signals, TLS fingerprints, WAF policies, and other characteristics to identify malicious traffic.

Caching can reduce load on the origin during traffic spikes, but caching itself is not DDoS mitigation. Effective protection still depends on accurate detection, sufficient mitigation resources, automated response, and the ability to keep legitimate users online.

CDN-Based vs. Dedicated DDoS Mitigation

CDN-based protection works naturally for traffic that can be proxied through an edge network, such as:

Websites
Web applications
APIs
HTTP/S services

But modern infrastructure often includes more than web traffic.

For example:

website.example.com     HTTPS
api.example.com         HTTPS
game.example.com        UDP
vpn.example.com         IPsec
mail.example.com        SMTP

The website and API can easily sit behind a CDN.

The game server, VPN, and other network services may require different protection.

Dedicated DDoS mitigation can extend protection to public IP ranges, data centers, TCP/UDP services, and other infrastructure using technologies such as Anycast routing, BGP diversion, GRE tunnels, cross-connects, or dedicated scrubbing centers.

Some providers combine both approaches.

Their CDN protects proxied web traffic, while additional network security services protect infrastructure outside the normal CDN path.

This distinction matters because putting a website behind a CDN does not automatically protect every internet-facing asset in your environment.

How I Evaluated the Best CDN Providers for DDoS Protection

No CDN is the best choice for every application.

Instead of comparing providers solely by advertised network size, I focused on six characteristics that have the greatest impact on real-world DDoS protection.

Evaluation Criteria	Why It Matters
Attack-layer coverage	Determines whether the platform can mitigate L3, L4, and L7 attacks
Mitigation architecture	Determines where and how attack traffic is filtered
Automated response	Reduces reliance on manual intervention during fast-moving attacks
Workload coverage	Determines whether websites, APIs, TCP/UDP services, and networks can be protected
False-positive control	Helps legitimate users stay online during unusual traffic spikes
Visibility and operations	Gives security teams insight into attacks and mitigation decisions

One important caveat when comparing CDN providers:

Total network capacity and dedicated DDoS scrubbing capacity are not the same measurement.

A large Tbps figure can indicate substantial infrastructure, but it does not tell you everything about detection quality, mitigation speed, traffic routing, or Layer 7 protection.

5 Best CDN Providers for DDoS Protection

Here is how five leading CDN providers compare.

Quick Recommendations

Choose the provider that best matches your architecture.

CDNetworks: Best for integrated CDN, WAAP, and DDoS protection across web, API, and TCP/UDP workloads.
Akamai: Best for large enterprises with complex hybrid and network infrastructure.
Cloudflare: Best for highly automated mitigation across a distributed edge.
Fastly: Best for applications and APIs already running through Fastly.
Imperva: Best for CDN-backed website security alongside broader network protection.

Comparison of the Best CDNs for DDoS Protection

Provider	Best For	Deployment	Key Strength
CDNetworks	Global web, API, and TCP/UDP workloads	CDN edge + always-on scrubbing	Integrated L3-L7 DDoS, WAAP, and adaptive mitigation
Akamai	Complex enterprise and hybrid infrastructure	CDN edge + Prolexic	Flexible dedicated DDoS architecture
Cloudflare	Automated web and network mitigation	Distributed edge + Spectrum/Magic Transit	Autonomous mitigation across a large Anycast network
Fastly	Existing Fastly applications and APIs	Integrated edge protection	Adaptive Threat Engine
Imperva	Website and application security	CDN + network mitigation services	Application security plus SLA-backed network protection

Why Choose CDNetworks for Integrated CDN and DDoS Protection?

CDNetworks combines CDN delivery and DDoS mitigation on the same global edge platform.

Its Flood Shield 2.0 service provides always-on protection for Layers 3, 4, and 7, while its broader application security stack includes WAF, bot management, and API protection.

CDNetworks operates more than 40 DDoS scrubbing centers with over 20 Tbps of global scrubbing capacity.

One of its more interesting capabilities is adaptive mitigation.

Rather than relying entirely on static thresholds, CDNetworks' AI-powered security engine can establish workload-specific traffic baselines and generate adaptive policies based on observed behavior.

For Layer 7 attacks, those controls can use signals such as request rates, request headers, user-agent behavior, and JA4 characteristics.

Pros

Integrated CDN and DDoS mitigation
L3, L4, and L7 protection
20+ Tbps of scrubbing capacity
40+ global DDoS scrubbing centers
AI-powered adaptive mitigation
WAF, bot management, and API security
HTTP/S and TCP/UDP protection
Strong infrastructure across Asia-Pacific, including mainland China

Considerations

Protection is cloud-delivered, so organizations requiring an on-premises DDoS appliance should validate deployment requirements.
Its regional footprint is especially valuable for organizations serving Asia-Pacific markets.

CDNetworks is particularly compelling when you want content delivery, application security, and DDoS mitigation within the same platform, instead of building those capabilities from several separate services.

Why Choose Akamai for Enterprise DDoS Protection?

Akamai combines DDoS protection at its CDN edge with dedicated mitigation through Akamai Prolexic.

For applications already delivered through Akamai, malicious web traffic can be filtered at the edge before reaching the origin.

Prolexic extends that protection to data centers, cloud environments, routed networks, and other infrastructure that does not naturally sit behind a CDN.

Akamai reports more than 20 Tbps of dedicated Prolexic defense capacity distributed across 32 Anycast scrubbing centers.

Pros

Mature enterprise DDoS platform
CDN-edge traffic filtering
20+ Tbps of dedicated Prolexic capacity
Always-on and on-demand protection
Cloud, hybrid, and on-premises deployment models
Proactive mitigation controls
Strong managed security support

Considerations

More advanced routed deployments can require BGP, GRE, and networking expertise.
Its breadth can introduce more operational complexity than simpler CDN-first deployments.

Akamai is particularly strong for large organizations protecting a mixture of CDN applications, cloud environments, data centers, and on-premises networks.

Why Choose Cloudflare for Automated Edge Mitigation?

Cloudflare integrates DDoS mitigation across the same distributed edge network used for CDN delivery.

When an application is proxied through Cloudflare, incoming traffic reaches Cloudflare before the origin, allowing malicious traffic to be identified and suppressed upstream.

Its Autonomous DDoS Protection Edge provides managed protection across Layers 3, 4, and 7. Adaptive DDoS Protection adds behavioral profiling to help identify traffic that deviates from normal application patterns.

Cloudflare also extends protection beyond normal web traffic.

Reverse proxy services protect websites and web applications.
Spectrum extends protection to TCP/UDP applications.
Magic Transit protects routed IP networks.

Pros

Distributed edge mitigation
Automated L3, L4, and L7 protection
Adaptive traffic profiling
Large global Anycast network
TCP/UDP protection through Spectrum
Network protection through Magic Transit
Strong developer and security ecosystem

Considerations

The full set of adaptive and network protections depends on specific products and service levels.
Organizations should determine which Cloudflare product is required for each workload.

Cloudflare is a strong option when automation and distributed edge protection are higher priorities than using dedicated centralized scrubbing architecture.

Why Choose Fastly for Applications and APIs?

Fastly integrates DDoS protection into the same edge platform used to deliver applications and content.

For applications already running through Fastly, this means attack traffic can be identified before it reaches backend infrastructure without introducing an entirely separate traffic path.

Fastly's Adaptive Threat Engine continuously evaluates traffic behavior and generates attack-specific mitigation rules when unusual patterns appear.

Visibility is another useful feature. Security teams can inspect detected events and review the mitigation rules generated by the platform.

Pros

DDoS mitigation at the CDN edge
Adaptive Threat Engine
Automated attack-specific rules
Fast automated response
Visibility into mitigation decisions
Developer-oriented edge platform

Considerations

DDoS Protection requires an eligible paid Fastly Full-Site Delivery, Streaming Delivery, or Compute service.
The strongest fit is for applications already using Fastly.

Fastly makes the most sense for developer and platform teams that already depend on Fastly for application or API delivery.

Why Choose Imperva for Application and Network Protection?

Imperva approaches DDoS mitigation from a strong application-security background.

For websites and web applications, traffic can pass through Imperva's global proxy and CDN infrastructure before reaching the origin. This allows content delivery and security inspection to happen within the same traffic path.

Imperva also provides separate protection for routed networks and individual IP assets using technologies such as GRE and cross-connect connectivity.

Across its broader portfolio, Imperva covers attacks across Layers 3, 4, and 7 and publishes 13 Tbps of global scrubbing capacity.

Pros

Integrated CDN and website DDoS protection
Strong application-security capabilities
L3-L7 protection
Dedicated network mitigation
GRE and cross-connect deployment options
Individual-IP protection
Three-second-or-less L3/L4 mitigation SLA

Considerations

Its CDN role is primarily tied to website and web-application protection.
Network and individual-IP protection use separate mitigation paths.

Imperva is a good fit when web application security is the primary requirement, but network-level DDoS protection is also needed.

How Do You Choose the Right CDN for DDoS Protection?

The best provider depends on your workload rather than the longest feature list.

Here is the evaluation process I'd recommend.

1. Identify Everything You Need to Protect

Start with your internet-facing assets.

Do you only operate websites and APIs, or do you also run gaming servers, VPNs, TCP/UDP applications, and public network ranges?

A standard reverse-proxy CDN may be enough for the first group.

The second group can require additional network-level mitigation.

2. Understand Your Attack Surface

Determine whether you primarily need protection against:

Volumetric attacks
Protocol attacks
HTTP floods
Bot-driven attacks
API abuse
Multi-vector attacks

For modern web applications, Layer 7 detection can be just as important as raw mitigation capacity.

3. Check How Mitigation Works

Ask where attack traffic is actually filtered.

Some providers distribute mitigation across the CDN edge. Others use dedicated scrubbing centers. Some combine both models.

Also determine whether protection is always on or activated on demand.

4. Protect the Origin

If attackers can discover your origin IP and connect directly to it, they may be able to bypass CDN-based protection.

Evaluate origin masking, firewall restrictions, authenticated origin connections, and other controls that keep the CDN in the traffic path.

5. Look Beyond the Biggest Capacity Number

Network size matters, but it should not be the only comparison.

Consider:

Attack detection
Mitigation speed
Layer 7 capabilities
False-positive control
Geographic coverage
Logs and telemetry
SIEM integration
Operational support
Deployment complexity

A large CDN and an effective DDoS mitigation platform are related concepts, but they are not necessarily the same thing.

6. Validate With Your Own Traffic

Specifications and SLAs are useful, but production-like testing provides better insight.

Test how the service behaves during:

Sudden traffic spikes
High request rates
Regional traffic shifts
Application-layer attacks
Origin failures
False-positive scenarios

Also verify latency and application behavior from the regions where your users actually live.

Final Thoughts

There is no universal winner for every DDoS architecture.

If you want CDN delivery, L3-L7 DDoS protection, WAAP, adaptive mitigation, and coverage for web, API, and TCP/UDP workloads within one edge platform, CDNetworks is one of the strongest options to evaluate, particularly for organizations operating across Asia-Pacific.

Akamai is compelling for complex enterprise and hybrid networks. Cloudflare excels at automated, distributed mitigation. Fastly is a natural fit for applications already running on its edge platform, while Imperva is particularly relevant when application security and network DDoS protection need to work together.

The most useful question is therefore not:

Which CDN has the largest network?

It is:

Which CDN can keep my actual applications and infrastructure available when an attack happens?

Answer that first, and the provider comparison becomes much easier.

CDNetworks vs. Akamai vs. Cloudflare: A Technical Guide to Choosing a CDN in 2026

Alvin — Wed, 09 Sep 2026 09:01:06 +0000

Choosing a CDN is often reduced to a simple question: Which provider is fastest?

In production environments, that question is usually too narrow.
CDN performance depends on where users are located, how traffic is routed, what type of workload is being delivered, how security controls are deployed, and how much operational control a team needs. A configuration that works well for a SaaS application in North America may not produce the same results for a live-streaming platform serving users across Asia-Pacific.

This article compares CDNetworks, Akamai, and Cloudflare from a technical and operational perspective, focusing on seven areas that matter when designing an edge delivery architecture.

What Actually Matters When Comparing CDNs?

Network size and brand recognition provide useful context, but they do not tell the whole story.

To evaluate a CDN, here is a list of useful questions to consider:

Where are the users?
What kind of traffic are we delivering?
Where should security controls run?
How much control does the team need at the edge?
How much operational support is required?
How well can the CDN support delivery across different regions and markets?
How predictable is the overall cost?

The answers to these questions can provide a more complete basis for comparison.

1. Regional delivery

A CDN that performs well in North America or Europe may behave differently in APAC, Mainland China, Latin America, or the Middle East.

The relevant variables are not simply PoP count. ISP relationships, regional peering, routing strategy, PoP placement, and cross-border connectivity can all influence latency and consistency.

For globally distributed applications, it is therefore useful to evaluate performance by user region, rather than relying on a single global performance figure.

2. Workload characteristics

Different workloads place different demands on an edge platform.

A marketing website primarily needs static content caching and reliable page delivery. A SaaS application may depend more heavily on dynamic acceleration and API traffic. Gaming, OTT, software distribution, and interactive streaming introduce additional requirements around throughput, connection handling, routing, and protocol support.

The CDN should therefore be evaluated against the actual traffic profile rather than against a generic "website" workload.

3. Security at the edge

Modern CDN architecture increasingly combines delivery and security.

Common controls include:

Web Application Firewall (WAF)
DDoS protection
Bot management
API security
WAAP capabilities

There is a practical engineering advantage to integrating these controls with the delivery layer: traffic can be inspected and filtered closer to the point where it enters the application delivery path.

This also changes the operational model. Instead of managing performance and security as completely separate systems, teams can apply related policies within the same edge architecture.

4. Operational model

There is a meaningful difference between a platform optimized for self-service operation and one designed around guided or managed deployment.

Self-service platforms can reduce deployment friction for teams that already have strong CDN and edge expertise.

Managed models can be useful when teams need assistance with onboarding, configuration, troubleshooting, or ongoing performance optimization.

Neither model is inherently better. The relevant question is how much operational responsibility the engineering team wants to retain.

5. Edge customization

Large-scale applications may require more than basic caching.

Traffic steering, custom routing rules, caching behavior, security policies, and edge logic can become increasingly important as architectures become more complex.

A platform with extensive configuration capabilities can provide more control, but that flexibility also increases the amount of expertise required to operate it safely.

This creates a common trade-off:
More control usually means more operational complexity.

6. Mainland China and cross-border delivery

China delivery deserves separate consideration.

Mainland China has different infrastructure, routing, compliance, and ICP requirements from many other markets. Cross-border traffic can also introduce additional latency and routing variability.

For companies serving both Chinese and international users, the relevant question is therefore not simply whether a CDN "supports China."

The more useful question is:
How is traffic delivered between international users, cross-border paths, and infrastructure inside Mainland China?

The architecture used to answer that question can have a significant impact on both performance and operational complexity.

7. Pricing

CDN pricing is affected by more than the base bandwidth rate.

Traffic volume, geographic regions, security services, support levels, overage charges, and contract structures can all influence the effective cost.

For enterprise workloads, cost modeling should therefore consider the expected production configuration rather than comparing only the headline CDN rate.

CDNetworks vs. Akamai vs. Cloudflare

The three platforms approach edge delivery somewhat differently.

CDNetworks

CDNetworks has more than 20 years of experience and strong roots in the Asia-Pacific market.

Its platform combines CDN delivery, application acceleration, media delivery, and edge security. The network is described as having 3,000+ PoPs across 90+ countries and regions, with particular coverage across APAC, emerging markets, and China.

For media-heavy workloads, the platform supports VOD, OTT, live streaming, downloads, gaming, software distribution, and large-file delivery, including HTTP-FLV, WebRTC, and HLS for media use cases.

Its operating model also emphasizes guided deployment and direct technical support, including 24/7 regional assistance.

From an engineering perspective, the main consideration is less about absolute network size and more about whether the combination of regional connectivity, China delivery, media capabilities, security controls, and managed support matches the workload.

Akamai

Akamai is one of the early pioneers of CDN technology and operates one of the industry's largest edge platforms.

Its positioning is strongly oriented toward large-scale enterprise workloads, with extensive traffic management, routing, caching, security, and edge configuration capabilities.

That flexibility is particularly relevant for organizations with complex infrastructure and dedicated engineering teams.

The trade-off is operational complexity. Advanced configuration provides greater control over delivery behavior, but teams need the expertise and resources to manage that complexity.

Akamai's China CDN situation is also an important consideration for architectures requiring Mainland China delivery, given its scheduled China CDN decommissioning on June 30, 2026.

Cloudflare

Cloudflare takes a different approach by combining CDN, DNS, web performance, and security capabilities through a unified platform.

Its global anycast network and self-service operating model make it attractive to teams that prioritize rapid deployment and centralized management.

Security capabilities include WAF, DDoS protection, bot management, and API security, alongside broader zero-trust functionality.

From an operational perspective, the platform favors automation and developer-driven workflows. This can reduce the amount of manual infrastructure management required for standard web workloads.

For China delivery, however, the architecture follows a partner-based model, which needs to be evaluated separately from Cloudflare's global network.

Side-by-Side Technical Comparison

Evaluation Area	Cloudflare	Akamai	CDNetworks
CDN Capabilities	Broad CDN capabilities designed for relatively easy adoption	Enterprise-grade CDN for large-scale delivery	Full-suite CDN capabilities with CNAME-based and Anycast routing
Global Network	Broad global footprint across major markets	Extensive global presence	3,000+ PoPs across 90+ countries and regions, with strong APAC, emerging-market, and China coverage
Media & Large Files	Video delivery, software downloads, large-object distribution	Strong large-scale media delivery	VOD, OTT, live streaming, downloads, gaming, software distribution, and media platforms with full-stack protocol support
Security	WAF, DDoS protection, bot management, API security	Sub-second to a few seconds	Advanced enterprise security capabilities
China Delivery	Partner-based model	China CDN decommissioning scheduled for June 30, 2026	Global and China delivery through one platform
Setup	Primarily self-service	Enterprise-oriented	Guided setup with vendor support and customized deployment
Support	Tiered support plans	Premium enterprise support	Direct vendor support with 24/7 regional assistance and managed-service options
Pricing Model	Free and self-service tiers available	Primarily contract-based	Solution-based and flexible, with a 14-day free trial

The table provides a side-by-side view of the key similarities and differences across the three platforms.

Matching CDN Capabilities to Workloads

Rather than asking which CDN is "best," it is more useful to start with the workload.

Choose CDNetworks when regional and managed delivery are major requirements

CDNetworks can be considered for organizations that need:

Delivery across APAC, Mainland China, or emerging markets
CDN, security, and media capabilities within one platform
VOD, OTT, interactive live streaming, gaming, or large-file delivery
Direct technical assistance during deployment and operations
A combination of global and China-connected delivery

The technical differentiator to investigate is the relationship between regional connectivity and the workload's actual user distribution.

Choose Akamai when control and enterprise customization dominate

Akamai is particularly relevant when an organization requires:

Enterprise-scale CDN infrastructure
Advanced traffic management and routing
Fine-grained caching and delivery controls
Complex security policies
Teams capable of operating sophisticated edge architectures

The primary engineering consideration is whether the additional control justifies the operational complexity.

Choose Cloudflare when self-service simplicity is the priority

Cloudflare is well suited to teams that prioritize:

Fast deployment
Self-service configuration
Unified CDN, DNS, and security management
Developer-friendly APIs and automation
Centralized management for common web workloads

The main advantage is operational simplicity rather than maximum configuration complexity.

Finding the Right CDN for Your Business

The evaluation should reflect the actual traffic the CDN needs to handle, rather than relying on the provider's feature list.

Testing should account for factors such as user geography, ISP, workload, protocol, security configuration, and origin infrastructure.

For APAC deployments, testing should ideally include multiple markets rather than treating the region as a single network environment.

For media platforms, testing should also consider sustained throughput, connection behavior, protocol support, and live-streaming requirements rather than measuring only cached object latency.

For security-sensitive applications, testing should include the interaction between caching, WAF policies, DDoS mitigation, bot controls, and API traffic.

The goal is not simply to determine which CDN has the fastest network, but which one delivers predictable performance for the application's users, workload, security model, and operational requirements.

Final Takeaway

CDN selection is fundamentally an architecture decision.

Akamai, Cloudflare, and CDNetworks each represent different approaches to operating an edge delivery platform:

Akamai emphasizes enterprise-scale delivery, control, and customization.
Cloudflare emphasizes self-service operation and unified web infrastructure and security.
CDNetworks combines global delivery with a strong APAC and China focus, media delivery capabilities, integrated security, and managed technical support .

As a result, CDN selection should be evaluated based on the actual traffic path, the location of users, workload characteristics, security requirements, and operational needs.

Video Streaming Protocols: HLS vs DASH vs WebRTC vs SRT, RTMP, and RTSP

Alvin — Wed, 02 Sep 2026 02:27:00 +0000

Article Categories

Video Streaming Basics
Protocol Comparison
- HLS
- MPEG-DASH
- WebRTC
- SRT
- RTMP
- RTSP
How to Choose a Video Streaming Protocol
CDNetworks Streaming Solutions
Common Mistakes
FAQs
Conclusion

What are video streaming protocols?

Video streaming protocols define how video data is prepared, transmitted, and delivered from a source to a viewer or application.

Different protocols are designed for different requirements. Some use segmented media files for scalable CDN delivery, while others transmit real-time media packets for applications where latency matters more than scale.

A typical streaming workflow looks like this:

Camera / Video File
        ↓
Encoder
        ↓
H.264 / HEVC
        ↓
Packaging
        ↓
Streaming Protocol
        ↓
Media Server / CDN
        ↓
Player / Application
        ↓
Viewer

Live video usually starts with a camera or encoder, while video-on-demand (VoD) starts with a stored media file.

The video is commonly compressed using codecs such as H.264 or HEVC before being packaged into formats such as MP4 or CMAF.

Which video streaming protocols are most common?

The six protocols you'll encounter most often are HLS, MPEG-DASH, WebRTC, SRT, RTMP, and RTSP.

Protocol	Main use case	Typical latency	Transport
HLS	Large-scale live and VoD delivery	~6–30s; lower with LL-HLS	HTTP/TCP
MPEG-DASH	OTT and adaptive video delivery	~6–30s; lower with LL-DASH	HTTP/TCP
WebRTC	Real-time communication	Typically <500ms	RTP/SRTP, usually UDP
SRT	Live contribution	Sub-second to a few seconds	UDP
RTMP	Encoder ingest	~2–5s	TCP
RTSP	IP cameras and surveillance	Implementation-dependent	RTP over TCP/UDP

These latency figures are typical rather than guaranteed. Encoding, buffering, segment duration, network conditions, and player configuration can significantly affect end-to-end latency.

What is HLS?

HLS (HTTP Live Streaming) is an HTTP-based adaptive streaming protocol developed by Apple. HLS is widely used for large-scale live streaming and video-on-demand delivery.

HLS divides video into smaller media segments and uses playlists to tell the player which segments to request.

Encoder
   ↓
HLS Segments + Playlist
   ↓
HTTP Server / CDN
   ↓
HLS Player

How does HLS compare with other video streaming protocols?

HLS is primarily designed for scalable viewer delivery rather than real-time communication.

Compared with WebRTC, HLS generally has higher latency but is easier to distribute through HTTP infrastructure and CDNs. Compared with RTMP and SRT, HLS is more suitable for viewer playback than live contribution or ingest.

What are the advantages of HLS?

Broad compatibility across mobile devices, smart TVs, and streaming platforms.
Works with standard HTTP infrastructure and CDNs.
Supports adaptive bitrate streaming.
Scales well for large audiences.

What are the limitations of HLS?

Traditional HLS introduces several seconds of latency because the player downloads and buffers media segments.

For interactive applications such as video calls, traditional HLS is usually not appropriate. LL-HLS can reduce latency while retaining HTTP and CDN-based delivery.

What is MPEG-DASH?

MPEG-DASH (Dynamic Adaptive Streaming over HTTP) is an open international adaptive streaming standard developed by MPEG.

Like HLS, MPEG-DASH uses HTTP delivery, media segments, and adaptive bitrate streaming. MPEG-DASH is vendor-neutral and supports multiple codecs and media formats.

How does MPEG-DASH compare with HLS?

HLS and MPEG-DASH use similar HTTP-based delivery models and are both suitable for scalable video distribution.

The main difference is that MPEG-DASH is an open, vendor-neutral international standard, while HLS originated from Apple.

Feature	HLS	MPEG-DASH
Standard	Apple-developed	MPEG international standard
HTTP delivery	Yes	Yes
Adaptive bitrate	Yes	Yes
CDN-friendly	Yes	Yes
Vendor-neutral	No	Yes
Low-latency option	LL-HLS	LL-DASH
Common uses	Live, VoD, OTT	OTT, VoD, multi-device delivery

What are the advantages of MPEG-DASH?

Open, vendor-neutral streaming standard.
Supports multiple codecs and media formats.
Works with HTTP infrastructure and CDNs.
Suitable for OTT, VoD, and multi-device delivery.

What are the limitations of MPEG-DASH?

MPEG-DASH can require additional player support in environments where native browser compatibility is limited.

Its flexibility can also increase implementation complexity across different playback environments.

What is WebRTC?

WebRTC (Web Real-Time Communication) is an open-source framework for real-time audio, video, and data communication between browsers and applications.

WebRTC is designed for applications where low latency and real-time interaction are more important than CDN-oriented one-to-many distribution.

Common use cases include:

Video conferencing.
Online meetings.
Interactive live streaming.
Gaming.
Real-time collaboration.
Browser-based communication.

How does WebRTC compare with HLS and MPEG-DASH?

WebRTC typically provides much lower latency than HLS and MPEG-DASH, making WebRTC better suited to interactive applications.

HLS and MPEG-DASH are generally easier to distribute at large scale through CDNs. WebRTC deployments can require additional media infrastructure such as relay servers or media servers.

What are the advantages of WebRTC?

Typically sub-second latency.
Native support in modern browsers.
Real-time audio, video, and data communication.
Encrypted media transport.
Strong fit for interactive applications.

What are the limitations of WebRTC?

WebRTC can require significantly more media infrastructure as concurrent users increase.

WebRTC is therefore not automatically the best choice for large-scale one-to-many video distribution. HLS or MPEG-DASH may be more practical when scalability is the primary requirement.

What is SRT?

SRT (Secure Reliable Transport) is a low-latency transport protocol designed for reliable video transmission over unpredictable networks.

SRT is commonly used for live contribution and remote production.

Remote Encoder
      ↓
     SRT
      ↓
Production / Media Server
      ↓
HLS / DASH / WebRTC
      ↓
Viewers

How does SRT compare with other video streaming protocols?

SRT is primarily a contribution and transport protocol rather than a viewer playback protocol.

Compared with WebRTC, SRT is more commonly used to transport professional video between production systems. Compared with HLS and MPEG-DASH, SRT is not designed primarily for large-scale viewer distribution.

What are the advantages of SRT?

Reliable transmission over unstable networks.
Packet-loss protection and recovery.
Low-latency transport.
Encryption capabilities.
Suitable for professional contribution workflows.

What are the limitations of SRT?

SRT requires compatible encoders, decoders, gateways, or media servers.

SRT is generally used inside the streaming workflow rather than directly in a viewer's browser.

What is RTMP?

RTMP (Real-Time Messaging Protocol) is a mature streaming protocol that remains widely used for live stream ingest.

RTMP was originally developed for audio, video, and data delivery to Flash-based players. Although Flash playback is obsolete, RTMP remains common for sending live video from encoders to streaming platforms.

Encoder
   ↓
  RTMP
   ↓
Streaming Platform
   ↓
Processing
   ↓
HLS / DASH / WebRTC
   ↓
Viewers

How does RTMP compare with other video streaming protocols?

RTMP is primarily used for ingest, while HLS, MPEG-DASH, and WebRTC are more commonly used for viewer delivery.

RTMP is simpler for encoder-to-platform workflows but lacks the modern browser playback compatibility of HTTP-based streaming protocols.

What are the advantages of RTMP?

Broad compatibility with live encoders.
Supported by many streaming platforms.
Simple encoder-to-server workflow.
Mature and widely adopted ecosystem.

What are the limitations of RTMP?

RTMP is not well suited to direct browser playback because modern browsers no longer support the Flash environment for which RTMP playback was originally designed.

For viewer delivery, HLS, MPEG-DASH, or WebRTC are generally more appropriate.

What is RTSP?

RTSP (Real-Time Streaming Protocol) is a network control protocol used to establish, manage, and control real-time media sessions.

RTSP is widely used with IP cameras, surveillance systems, network video recorders, and professional video equipment.

RTSP typically works with RTP (Real-time Transport Protocol) for actual media transmission.

How does RTSP compare with other video streaming protocols?

RTSP is commonly used for device-level streaming, particularly with IP cameras.

Unlike HLS and MPEG-DASH, RTSP is not designed for large-scale CDN delivery. Unlike WebRTC, RTSP does not provide direct modern browser playback.

A media server can ingest RTSP and convert the stream into HLS or WebRTC for web-based applications.

What are the advantages of RTSP?

Strong compatibility with IP cameras.
Supports real-time media session control.
Widely used in surveillance systems.
Suitable for dedicated streaming environments.

What are the limitations of RTSP?

Modern web browsers generally do not support direct RTSP playback.

Web applications therefore often require a media server or gateway to convert RTSP into a browser-compatible protocol such as HLS or WebRTC.

How do you choose the right video streaming protocol?

The right protocol depends on latency, audience size, compatibility, security, network conditions, and where the protocol is used in the streaming workflow.

Requirement	Recommended protocol
Large-scale live streaming	HLS
Large-scale VoD	HLS / MPEG-DASH
OTT delivery	HLS / MPEG-DASH
Interactive streaming	WebRTC
Video conferencing	WebRTC
Remote production	SRT
Encoder ingest	RTMP
IP cameras	RTSP

Which protocol provides the best compatibility?

Choose HLS when broad device and platform compatibility is important.

Choose WebRTC for modern browser-based real-time applications. MPEG-DASH provides an open adaptive streaming standard but may require a compatible player.

Which protocol provides the lowest latency?

WebRTC is commonly used for the lowest-latency interactive streaming.

SRT is commonly used for reliable low-latency contribution, while HLS and MPEG-DASH prioritize scalable delivery and playback stability.

Which protocol is best for adaptive bitrate streaming?

HLS and MPEG-DASH are the most common choices for adaptive bitrate streaming.

Both protocols can provide multiple video representations and allow the player to switch between bitrates based on bandwidth and device conditions.

How do security requirements affect protocol selection?

SRT provides encryption capabilities for contribution workflows, while WebRTC uses encrypted media transport.

HLS and MPEG-DASH can use HTTPS, access controls, tokenized URLs, and DRM to protect video delivery.

How does CDNetworks support different video streaming protocols?

Choosing a streaming protocol is only part of the architecture. The underlying infrastructure also needs to support different delivery models, from large-scale video distribution to low-latency and contribution workflows.

CDNetworks supports HLS, MPEG-DASH, WebRTC, RTMP, and SRT, allowing streaming workflows to use different protocols at different stages. CDN-based delivery, optimized routing, and scalable infrastructure help support high-concurrency streaming while maintaining stable playback.

Whether you need large-scale live streaming, low-latency streaming, or video-on-demand (VoD) delivery, CDNetworks provides infrastructure for different streaming requirements without forcing every use case into a single protocol.

Large-scale live streaming — scalable delivery for high-concurrency audiences
Low-Latency Streaming — real-time and interactive video delivery
Video-on-Demand (VoD) Delivery — scalable delivery for on-demand content

Need help choosing the right streaming protocol? Contact CDNetworks to explore a streaming solution for your use case.

What are common mistakes when choosing a streaming protocol?

Using WebRTC for every streaming application

WebRTC provides excellent latency, but low latency does not automatically make WebRTC the best choice for large-scale one-to-many delivery.

HLS or MPEG-DASH can provide a more CDN-friendly distribution model for large audiences.

Using RTMP for browser playback

RTMP remains useful for ingest, but modern browsers are not designed for Flash-era RTMP playback.

Use RTMP primarily to move live video from an encoder into a streaming platform.

Expecting HLS to provide real-time interaction

Traditional HLS uses segment-based delivery and buffering.

If viewers need to interact with live video with sub-second latency, WebRTC is generally a better starting point.

Treating RTSP as browser-compatible

RTSP works well with IP cameras but usually requires protocol conversion before browser playback.

A media server can ingest RTSP and convert the stream into HLS or WebRTC.

Choosing only one protocol

Production streaming systems often use multiple protocols.

For example:

IP Camera → RTSP
Remote Encoder → SRT
Live Encoder → RTMP
              ↓
        Media Platform
              ↓
     ┌────────┼────────┐
     ↓        ↓        ↓
    HLS     DASH    WebRTC
     ↓        ↓        ↓
   CDN      CDN   Real-time Users

Using different protocols at different stages is often more practical than forcing one protocol to handle the entire workflow.

Video Streaming Protocols FAQs

What are the most common video streaming protocols?

The most common video streaming protocols are HLS, MPEG-DASH, WebRTC, SRT, RTMP, and RTSP.

HLS and MPEG-DASH are widely used for scalable delivery, WebRTC is designed for real-time communication, SRT is commonly used for contribution, RTMP is widely used for ingest, and RTSP is common with IP cameras.

Which video streaming protocol is best for low-latency streaming?

WebRTC is commonly used for the lowest-latency interactive streaming. SRT is commonly used for reliable low-latency contribution.

Is HLS or WebRTC better for live streaming?

HLS is generally better for large-scale live streaming, while WebRTC is better for interactive live streaming.

Should I use TCP or UDP for video streaming?

HLS and MPEG-DASH commonly use HTTP over TCP. WebRTC and SRT commonly use UDP-based transport because their architectures prioritize low-latency media delivery.

Which protocol should I use for an IP camera?

RTSP is commonly used for IP cameras. A media server can convert RTSP into HLS or WebRTC when the video needs to be displayed in a web browser.

Is SRT a playback protocol?

No. SRT is primarily a secure, reliable contribution and transport protocol. A streaming platform can receive SRT and distribute the processed video through HLS, MPEG-DASH, or WebRTC.

Is RTMP still relevant?

Yes. RTMP remains relevant primarily for live stream ingest.

RTMP is widely supported by encoders and streaming platforms, while HLS, MPEG-DASH, and WebRTC are generally more appropriate for viewer playback.

Conclusion

There is no single best video streaming protocol.

Use HLS or MPEG-DASH for scalable HTTP-based delivery and adaptive bitrate streaming. Use WebRTC for interactive, sub-second video. Use SRT for reliable low-latency contribution, RTMP for encoder ingest, and RTSP for IP cameras and dedicated media systems.

The most practical streaming architecture often combines several protocols:

RTSP, RTMP, or SRT for ingest and contribution → HLS, MPEG-DASH, or WebRTC for viewer delivery.

Choose the protocol based on the requirements of each stage: latency, scale, compatibility, network conditions, security, and infrastructure.

What does your streaming stack use today? Have you had to combine multiple protocols to solve a production streaming problem?

DDoS Attacks Explained for Developers: How They Work and What They Break

Alvin — Thu, 27 Aug 2026 02:38:05 +0000

Your application can be healthy and still become unreachable.

The latest deployment may be fine. Your database may still be running. Your application processes may not have crashed.

Yet users suddenly start seeing timeouts, connection failures, unusually high latency, or 5xx errors.

One possible explanation is that a distributed denial-of-service attack is crowding out legitimate requests.

For developers, SREs, DevOps teams, and anyone responsible for an internet-facing application, it helps to understand DDoS attacks in terms of one simple question:

Which finite resource is the attacker trying to exhaust?

That resource could be bandwidth. It could be TCP connection state. It could be CPU, memory, database connections, or application-processing capacity.

Once you look at DDoS this way, the different attack types become much easier to understand.

TL;DR

A Distributed Denial of Service (DDoS) attack sends traffic or requests from multiple distributed sources toward the same website, server, API, network, or application.

The objective is usually not to break into the system. It is to consume enough available capacity that legitimate users can no longer use the service normally.

There are three broad categories:

Attack type	What it tries to exhaust	Examples
Volumetric	Network bandwidth	UDP floods, DNS amplification
Protocol	Connection and network-device resources	SYN floods, ACK floods
Application layer	Application and backend resources	HTTP floods, Slowloris

A real campaign can use more than one of these at the same time.

What actually happens during a DDoS attack?

Imagine an API that normally handles 10,000 requests per second comfortably.

Under legitimate load, the requests are distributed across endpoints, users, sessions, and normal usage patterns.

Now imagine hundreds of thousands of machines—or reflected third-party services—begin sending traffic toward that API or the infrastructure in front of it.

The attack generally follows a pattern like this:

1. Distributed traffic sources are assembled

Attackers can use compromised computers, routers, IoT devices, cloud systems, or other internet-connected machines.

A collection of compromised devices under remote control is commonly called a botnet.

Attackers can also use reflection attacks. Instead of sending all traffic directly, they cause third-party services to send responses toward the victim.

2. A target is selected

The target could be:

a domain
an IP address
a web application
an API endpoint
a DNS service
a game service
a TCP or UDP service

Attackers may also change targets during a campaign.

3. Traffic arrives at scale

The distributed systems begin generating packets, connections, or application requests.

At this point, the question becomes:

Where does the bottleneck appear first?

4. A finite resource is exhausted

Depending on the attack, the target may run short of:

network bandwidth
connection-table capacity
CPU
memory
worker processes
database connections
application threads
upstream service capacity

Legitimate traffic now competes with malicious traffic for the same resources.

The result can be increased latency, connection failures, application errors, or complete service unavailability.

The three DDoS categories developers should know

1. Volumetric attacks: overwhelm the pipe

A volumetric DDoS attack aims to consume available network capacity.

Think of this as filling the road before legitimate traffic can even reach your application.

Typical examples include:

UDP floods
ICMP floods
DNS amplification
NTP amplification

From an application perspective, this can be frustrating because your origin may technically still be healthy.

It simply becomes difficult or impossible to reach.

These attacks are commonly discussed in bits per second (bps) because the amount of network traffic itself is central to the attack.

2. Protocol attacks: exhaust connection-handling resources

Protocol attacks focus more on how networking systems maintain connections or process packets.

A classic example is the SYN flood.

Normally, establishing a TCP connection involves a handshake. A SYN flood creates large numbers of connection attempts without allowing the normal process to complete.

Enough unfinished connections can consume finite connection-handling resources.

Other examples include:

ACK floods
TCP floods
fragmentation attacks

These attacks are often measured in packets per second (pps).

3. Application-layer attacks: make the application work

This is often the most interesting category from a developer perspective.

An application-layer, or Layer 7, attack can send HTTP requests that look technically valid.

Instead of simply throwing enormous amounts of bandwidth at the target, the attacker may repeatedly request operations that are expensive for the application.

Consider endpoints such as:

POST /login
GET /search?q=...
POST /checkout
GET /api/reports

A single request might be harmless.

But what if each request triggers several downstream operations?

HTTP request
    ↓
Authentication check
    ↓
Application logic
    ↓
Database query
    ↓
Cache lookup
    ↓
Third-party/API call
    ↓
Response

Now multiply that work across a large number of malicious requests.

An attacker can create significant backend pressure without generating the same raw bandwidth as a volumetric attack.

Typical application-layer examples include:

HTTP GET floods
HTTP POST floods
Slowloris-style attacks
attacks targeting login or search functions
attacks targeting expensive API endpoints

These attacks are commonly discussed in requests per second (rps).

Why Layer 7 attacks can be difficult to spot

Blocking obviously malformed traffic is one thing.

Blocking requests that look similar to real users is much harder.

An HTTP request can be syntactically correct and still be malicious in context.

Consider a sudden increase in searches.

Is it:

a successful marketing campaign?
a crawler?
a newly released integration?
an aggressive bot?
a DDoS attack?

This is why application-layer DDoS detection often depends on behavior, not simply individual IP addresses.

Useful signals can include:

request-rate changes
repeated access to particular endpoints
unusual user-agent patterns
session behavior
geographic distribution
request parameters
client reputation
deviation from normal traffic baselines

There is rarely one magic threshold that identifies every DDoS attack.

What might developers see in production?

One reason DDoS incidents can initially be confusing is that they can resemble ordinary reliability problems.

Unexpected request or traffic spikes

Traffic increases quickly without a corresponding campaign, event, release, or other business explanation.

Rising latency

Requests that normally complete quickly begin taking significantly longer.

5xx errors and timeouts

Backend resources become constrained and legitimate requests fail.

Connection exhaustion

Load balancers, proxies, firewalls, or application infrastructure begin approaching connection limits.

One endpoint suddenly becomes very expensive

Highly distributed traffic

Similar behavior appears across many IP addresses, networks, or geographic locations.

Resource pressure

CPU, memory, bandwidth, connection tables, or database connection pools remain unusually high.

The important point is that none of these signals should be evaluated in isolation.

A useful baseline of normal traffic makes abnormal behavior much easier to recognize.

DoS vs. DDoS: what's the practical difference?

Both denial-of-service and distributed denial-of-service attacks are intended to affect availability.

The biggest difference is distribution.

Characteristic	DoS	DDoS
Traffic sources	Usually one or relatively few	Many distributed sources
Scale	Generally more limited	Can become extremely large
Blocking sources	Often more straightforward	Much more difficult
Resilience	Easier to interrupt at source	Distributed infrastructure makes this harder
Mitigation	Usually simpler	Often requires distributed filtering

With a DDoS campaign, blocking one attacking IP address may accomplish almost nothing.

Another thousand—or hundred thousand—sources can continue sending traffic.

What a 1.01 Tbps attack looked like in the real world

The scale stops being abstract when you look at an actual incident.

In a customer case documented by CDNetworks, a major software download platform was targeted by a ransom DDoS campaign.

During the campaign, the largest observed attack reached 1.01 Tbps and primarily combined SYN flood and ACK flood traffic.

The broader campaign lasted for more than a month.

There are several useful engineering lessons in that incident:

DDoS campaigns can be multi-vector.
You may not be defending against one fixed attack pattern.
Attack intensity can change.
A campaign can move between lower-volume and extremely high-volume periods.
Origin infrastructure should not be your only line of defense.
Very large attacks may need to be filtered before they consume the network path to the origin.
Availability means preserving legitimate traffic, not simply blocking traffic.
Dropping everything would technically stop the attack—but it would also accomplish the attacker's goal.

So how does DDoS mitigation work?

There isn't a single universal mitigation rule.

The response depends heavily on the attack layer.

At the network edge

Large volumetric attacks may need distributed capacity and upstream traffic scrubbing so malicious traffic is removed before reaching origin infrastructure.

At the protocol layer

Mitigation may involve connection validation, packet filtering, rate controls, and other mechanisms designed to prevent protocol-resource exhaustion.

At the application layer

Defenses can include:

behavioral analysis
rate controls
WAF policies
bot management
endpoint-specific rules
client reputation signals
adaptive thresholds

The objective is not simply:

Block more traffic.

It is:

Identify and remove malicious traffic while allowing legitimate users to continue reaching the application.

That distinction matters.

A practical DDoS-readiness checklist for engineering teams

Before the incident happens, ask:

Do we know what normal traffic looks like?
Do we monitor bandwidth, packets, connections, and application requests separately?
Which application endpoints are computationally expensive?
Which endpoints can trigger large numbers of database operations?
Are origin IP addresses exposed unnecessarily?
Do we understand our load balancer and connection limits?
What happens when a dependency becomes saturated?
Who makes the decision to activate mitigation?
Can high-volume malicious traffic be filtered before reaching the origin?
Have engineering, networking, security, and incident-response teams agreed on an escalation process?

DDoS resilience is partly a security problem.

It is also an architecture, observability, networking, and incident-response problem.

Quick FAQ

Does DDoS mean the attacker has breached the application?

Not necessarily.

DDoS primarily targets availability rather than confidentiality. A service can be overwhelmed without the attacker gaining access to protected data.

However, security teams should still investigate other activity occurring during the incident. A disruptive attack can coexist with other malicious behavior.

How long can a DDoS attack last?

There is no standard duration.

An attack might last minutes or hours, or repeatedly return over a much longer campaign.

Can autoscaling solve DDoS?

Autoscaling can help applications absorb some legitimate demand and certain resource pressures, but it should not be treated as complete DDoS protection.

If an attacker can simply force you to provision more infrastructure—or saturate capacity upstream of that infrastructure—the fundamental problem remains.

Can small applications be targeted?

Yes.

Any public application, website, API, network service, or online platform can potentially be targeted.

Final thought

The most useful mental model for developers is not simply:

“DDoS means lots of traffic.”

Instead ask:

What resource is being exhausted, where is that resource located, and can malicious traffic be separated from legitimate traffic before it reaches that bottleneck?

Those three questions explain a surprising amount about both DDoS attacks and DDoS defense.

Scaling AI Aggregators: Solving Performance and API Security Challenges

Alvin — Wed, 19 Aug 2026 01:38:00 +0000

AI aggregators, also known as multi-model AI platforms, give users access to multiple AI models such as ChatGPT, Claude, and Gemini through a single interface.

The product experience is simple. The infrastructure behind it isn't.

As these platforms scale, requests may pass through different model providers, regions, and network paths before reaching the user. At the same time, public APIs become targets for unauthorized access, automated scraping, malicious requests, and DDoS attacks.

Two infrastructure challenges become increasingly important:

Maintaining consistent performance across a complex model-routing layer
Protecting public APIs without allowing abuse to consume model resources and increase costs

This is where traffic management becomes part of the scaling strategy.

Why AI Aggregators Become Harder to Scale

Scaling an AI aggregator introduces complexity on both the performance and security sides.

1. Performance Variability Across Providers and Regions

A user request doesn't necessarily travel to a single model in a single location. Depending on model selection, availability, pricing, or workload, traffic may pass through different providers, regions, and network paths.

Each additional network boundary introduces potential latency, congestion, and routing variability.

Adding more compute capacity doesn't necessarily solve this problem. If the request spends too much time crossing inefficient network paths, faster model infrastructure alone won't improve the user experience.

2. API Abuse and Security Exposure

The security surface grows at the same time.

Public AI APIs can be targeted by stolen credentials, automated scripts, scraping, credential stuffing, and other malicious traffic. For usage-based AI platforms, the impact goes beyond availability.

Every abusive request can consume model capacity and generate token costs.

A compromised API key can therefore become both a security problem and an infrastructure cost problem.

Solving the Performance Challenge

Performance problems in AI aggregators don't originate from model inference alone.

A unified API may route requests to different providers depending on the selected model and current availability. This makes network efficiency an important part of overall response performance.

1. Shorten the Request Path

Latency accumulates at every boundary a request crosses.

Public internet routes can expose traffic to congestion, inefficient routing, and jitter. Placing network entry points closer to users can reduce the distance before traffic enters the delivery infrastructure.

Edge PoPs can terminate requests closer to users and select routes based on current network conditions. For longer-distance transmission, private backbone connectivity can provide more predictable paths than the public internet.

The goal isn't simply to reduce network latency. For AI applications, it is also about improving time to first token and keeping response times consistent.

2. Keep Streaming Connections Stable

AI responses are often delivered incrementally rather than as a single payload.

A streaming response may remain open while tokens are generated and transmitted. If the connection becomes unstable halfway through the response, the user experience can degrade even when the underlying model is operating normally.

For this reason, AI traffic optimization needs to consider both:

How quickly the first token arrives
Whether the connection remains stable until the response is complete

3. Managing Traffic Spikes Before They Reach the Origin

Performance is only part of the scaling problem. AI traffic can also change dramatically in a short period of time.

A new model release or sudden increase in user activity can push request volumes from normal to extreme within minutes.

High concurrency puts direct pressure on origin infrastructure. Streaming responses make this harder because connections remain open for the duration of the response.

Instead of allowing every request to reach the origin directly, traffic can be absorbed and controlled before it reaches model-serving infrastructure.

A virtual waiting room, for example, can regulate inbound requests during extreme demand. Real-time monitoring and failover mechanisms can also help maintain service continuity when network conditions change.

The goal is not simply to add more capacity. It is to prevent unpredictable traffic from turning directly into origin overload.

Solving the API Security Challenge

AI API security has an additional dimension that traditional web applications don't always face: the cost of every successful request.

A stolen API key can generate thousands of requests before abnormal usage becomes visible. If those requests are distributed across multiple model providers, the financial impact can accumulate quickly.

This makes early enforcement particularly important.

1. Stop API Abuse Before It Consumes Model Resources

Useful controls include:

Behavioral analysis to identify abnormal request patterns that static rules may miss
API rate limiting to cap usage per credential
Access controls to restrict endpoint exposure
Bot management to identify automated abuse
Origin shielding to prevent direct attacks against backend infrastructure
DDoS mitigation to filter volumetric attacks before they reach the application

The basic principle is simple: stop unnecessary traffic before it consumes expensive model resources.

This is particularly important for AI aggregators because security controls can directly affect infrastructure costs. Preventing abusive requests before they reach model providers means protecting both the application and the model budget.

2. Address Bots and Direct-to-Origin Attacks

API abuse doesn't always look like a large-scale attack.

Modern bots can mimic legitimate activity, rotate identities, and distribute requests across large IP ranges. Static rules and IP-based filtering may therefore be insufficient on their own.

At the same time, exposed origin infrastructure creates another attack path. Attackers that discover the origin IP may bypass controls implemented at the application or edge layer.

This requires multiple layers of protection:

Behavioral bot detection for automated traffic
Origin shielding to reduce direct exposure
DDoS mitigation at the network edge

The objective is to keep legitimate API traffic available while filtering malicious traffic before it reaches backend infrastructure.

Combining Acceleration and API Security at the Edge

For a global AI aggregator, acceleration and API security can be handled together at the edge, where traffic can be optimized and filtered before reaching upstream AI services.

CDNetworks is one example of how this can be implemented. Its Dynamic Web Acceleration infrastructure includes 3,000+ Points of Presence (PoPs) across 90+ countries and more than 200 Tbps of network capacity, supported by Anycast, GSLB, and private backbone connectivity for traffic routing.

For API protection, CDNetworks provides capabilities including API rate limiting, bot management, DDoS mitigation, WAF, and origin shielding through Cloud Security 2.0 and Security Services.

In a reported deployment for a global multi-model AI platform, these capabilities helped reduce latency by more than 70% and lower origin bandwidth consumption by more than 66%. These results are specific to that deployment rather than a general performance guarantee.

For platforms serving users in Mainland China, CDNetworks also provides a China delivery capability with latency below 50ms, regulatory compliance, and no ICP filing requirement.

Final Thoughts

Scaling an AI aggregator isn't only about adding more models or compute. As traffic grows, network paths become more complex, streaming connections become more demanding, and public APIs become more attractive targets for abuse. At the same time, every unnecessary request can translate into additional model and infrastructure costs.

Performance and security therefore need to be considered together. Efficient routing can reduce latency and improve response consistency, while edge-based controls can prevent abusive traffic from consuming model resources.

For AI aggregators, scaling is ultimately about controlling the traffic path—from the first request to the final model response.

What Actually Happens When You Put a CDN in Front of Your Website?

Alvin — Wed, 12 Aug 2026 03:26:53 +0000

If you've worked on web performance for any amount of time, you've probably heard the advice:

“Put it behind a CDN.”

But what does a CDN actually do between the browser and your server?

The simplest way I think about it is this:

A CDN, or Content Delivery Network, is a distributed network of edge servers that delivers content from locations closer to users instead of sending every request back to one origin server.

That shorter path can reduce latency, speed up content delivery, reduce load on the origin, and make an application more resilient when traffic increases.

But the interesting part is what happens after a user hits your URL.

A request without a CDN

Imagine your application is hosted on an origin server in the United States.

A user in Singapore opens your website.

Without a CDN, requests for HTML, JavaScript, CSS, images, downloads, or other resources may have to travel all the way to your origin infrastructure and back.

Conceptually:

User in Singapore
       ↓
Internet
       ↓
Origin server in the US
       ↓
Internet
       ↓
User

That physical and network distance matters.

More distance generally means more network hops and more round trips, which can translate into additional latency.

Now put a CDN in between.

User
  ↓
Nearby CDN edge server
  ↓
Origin server (only when needed)

The CDN becomes a delivery layer between users and your origin.

So how does a CDN decide where requests go?

CDNs operate distributed edge servers across multiple geographic locations.

When a request comes in, technologies such as DNS-based routing, Anycast, and global traffic management can help direct that request toward an appropriate edge location.

Then the edge checks whether it can serve the content itself.

This is where caching becomes important.

Cache hit vs. cache miss

Two terms explain a large part of basic CDN behavior.

Cache hit

A cache hit means the requested resource is already stored on the edge server.

For example:

GET /images/product.png

If that image is already cached at a nearby edge location, the CDN can send it directly to the user.

The origin doesn't need to handle that request.

Cache miss

A cache miss means the requested content isn't currently available in that edge cache.

The CDN requests the resource from the origin, returns it to the user, and—depending on your cache rules—may store a copy for future requests.

So the flow becomes:

First request:
User → Edge → Origin → Edge → User

Later request:
User → Edge → User

This is one of the main reasons CDNs can reduce origin traffic as well as latency.

What controls how long something stays cached?

One important setting is TTL, or Time to Live.

TTL determines how long a cached resource can remain at the edge before it expires.

Assets that rarely change—such as logos, versioned JavaScript bundles, CSS, fonts, or software files—can often use longer cache durations.

Frequently changing resources may need shorter TTLs.

And if something needs to disappear from cache immediately, CDNs typically provide a cache purge mechanism.

This sounds simple, but cache policy can have a huge impact on CDN performance.

A CDN isn't just “cache everything forever.”

The real goal is deciding:

what can be cached;
where it should be cached;
how long it should stay cached;
and when it needs to be refreshed.

What about dynamic content?

This is where the idea that “CDNs are just caches” starts to break down.

Not everything can be cached.

API responses, authenticated pages, personalized content, shopping carts, and other dynamic requests may need to reach the origin.

A modern CDN can still help.

Even when a response isn't served from cache, CDN infrastructure can optimize the network path through techniques such as persistent connections, TCP/TLS optimization, dynamic acceleration, and newer protocols such as HTTP/2, HTTP/3, and QUIC.

So there are really two related ideas:

Caching reduces how often the origin is needed.

Network acceleration makes requests faster when the origin is needed.

Does a CDN replace web hosting?

No.

This is a distinction that sometimes gets lost.

Web hosting stores and runs your website or application. A CDN sits between users and that origin infrastructure to improve how content is delivered.

You still need an origin.

Think of it roughly like this:

	Web Hosting	CDN
Main job	Host the application/content	Deliver and accelerate content
Location	Origin infrastructure	Distributed edge locations
Handles	Original application and files	Cached and accelerated requests
Goal	Run the site	Get content to users efficiently

A CDN complements your hosting architecture rather than replacing it.

Do you actually need a CDN?

Not every side project needs an enterprise CDN setup.

But I'd start seriously considering one when:

users are distributed across multiple countries or regions;
performance varies significantly by geography;
your application serves lots of images, video, JavaScript, downloads, or other large assets;
your origin is handling a high volume of repeat requests;
traffic spikes are becoming difficult to manage;
availability and DDoS protection matter to the application.

The more geographically distributed your audience becomes, the more useful the edge model tends to become.

A CDN is also part of your reliability and security architecture

Performance gets most of the attention, but CDNs can do more than make pages load faster.

Because traffic passes through the CDN before reaching the origin, that network layer can also help with traffic distribution, origin protection, DDoS mitigation, web application security, and handling sudden spikes.

That makes the CDN an important infrastructure decision—not just a frontend optimization.

The short version

If I had to summarize CDN architecture in a few lines:

A CDN puts distributed edge infrastructure between users and your origin.

It can:

route users toward an appropriate edge location;
serve cached content without contacting the origin;
retrieve and cache content when there's a cache miss;
accelerate dynamic traffic that still needs the origin;
reduce origin load;
improve performance, scalability, reliability, and security.

Once you see the request flow, “use a CDN” stops feeling like a magic performance trick.

It's really a question of moving content and network processing closer to the people requesting it.

If you want a deeper breakdown of CDN caching, edge servers, common use cases, and how to evaluate a CDN provider, I found this more comprehensive guide useful:

What Is a CDN? — CDNetworks

Quick FAQ

What does CDN stand for?
CDN stands for Content Delivery Network.

What is a CDN in simple terms?
It's a distributed network of servers that helps deliver web content from locations closer to users.

Does a CDN host my website?
Not usually. Your hosting infrastructure remains the origin; the CDN works in front of it.

Can a CDN accelerate APIs?
Yes. Even when API responses aren't cached, CDNs can improve delivery through optimized routing and connection acceleration.

Is CDN caching the same as browser caching?
No. Browser caching stores content on an individual user's device, while CDN caching stores content at shared edge servers that can serve many users.

What 2025 Attack Traffic Means for Developers and Security Teams

Alvin — Thu, 06 Aug 2026 03:37:56 +0000

Security reports often lead with large numbers.

Billions of malicious requests. Terabit-scale DDoS attacks. Millions of automated bot requests every day.

The numbers matter, but the more useful question for developers is this:

What do these traffic patterns reveal about how applications are being attacked?

Based on traffic observed and mitigated by CDNetworks during 2025, one pattern stands out. Many attacks are designed to resemble legitimate activity.

They use standard protocols, expected application paths, authenticated sessions, and technically valid API requests. Detecting them requires more than matching signatures or blocking unusual IP addresses.

Here are four signals engineering and security teams should pay attention to.

1. DDoS Protection Must Cover More Than Bandwidth

CDNetworks blocked more than 227 million network-layer DDoS attack requests in 2025.

Among them:

329 attacks exceeded 1 Tbps
The largest attack reached 1.55 Tbps
Software and IT Services was the most targeted sector for network-layer DDoS attacks

Terabit-scale attacks are becoming a repeatable operational scenario.

However, network capacity represents only part of the problem.

Application-layer DDoS attacks can target expensive operations such as:

Login and authentication
Search
Checkout
Dynamic content generation
API requests
Database-intensive queries

A relatively small HTTP request can trigger several backend operations. Enough requests to a resource-intensive endpoint may degrade an application without saturating the network.

For engineering teams, DDoS testing should therefore examine application dependencies, worker pools, database capacity, caching behavior, and third-party services, alongside bandwidth.

2. Web Attacks Require End-to-End Request Visibility

CDNetworks blocked more than 21.51 billion web application attack requests during 2025.

Almost 60% occurred during the second half of the year, while HTTP protocol anomalies accounted for 45% of the total.

Modern application requests often travel through several components:

Client
  ↓
CDN or security edge
  ↓
Load balancer
  ↓
Reverse proxy or API gateway
  ↓
Application server
  ↓
Database and internal services

Each component may interpret malformed headers, encodings, request lengths, or protocol behavior differently.

This creates opportunities for attackers to test inconsistencies between systems.

Edge logs alone may not provide enough context. Teams should be able to connect a suspicious request with:

The targeted endpoint
Authentication status
Session history
Application response
Upstream latency
Backend errors
Related requests from the same identity or device

Consistent request IDs across the delivery path make this investigation significantly easier.

3. Bot Management Is a Policy Problem

In 2025, 74% of classified bot traffic came from bad bots.

CDNetworks also observed an average of 1.64 million AI bot requests per day, with data scrapers accounting for more than 72% of recorded AI bot activity.

The technical challenge is that automated traffic can serve very different purposes.

A bot may be:

A search crawler
A monitoring service
An AI agent
A commercial scraper
A credential-stuffing tool
An inventory-hoarding bot
An account-abuse system

Blocking all automation would disrupt legitimate services. Allowing all automation would expose applications, data, accounts, and infrastructure resources.

Bot policies should therefore reflect the purpose of each endpoint.

For example:

routes:
  /public-docs:
    verified-crawlers: allow
    unknown-bots: rate-limit

  /account:
    crawlers: block
    suspicious-automation: challenge

  /api/inventory:
    authentication: required
    behavioral-monitoring: enabled

The exact syntax depends on the security platform, but the underlying principle remains the same. Public content, account systems, APIs, and transactional workflows should not share one universal bot policy.

4. API Abuse Can Look Technically Valid

CDNetworks blocked an average of more than 15 billion malicious API requests per month during 2025.

API attacks can be difficult to identify because individual requests may appear legitimate.

A malicious request may:

Use valid JSON
Match the expected schema
Include a valid token
Target a documented endpoint
Stay below an IP rate limit
Receive a successful response

The risk appears when the request is connected to behavior over time.

Consider an authenticated user querying an inventory API. One request may be expected. Thousands of queries distributed across several accounts, devices, and IP addresses may indicate scraping or automated purchasing activity.

Traditional IP-based rate limiting may miss this pattern.

Sensitive APIs should also evaluate:

account_id
api_key
session_id
device_id
organization_id
endpoint
resource_id
action_frequency
historical_behavior

Security controls need to measure both request volume and business impact.

Examples include the number of accounts created, coupons redeemed, items reserved, records accessed, or payment methods tested.

The Shared Engineering Challenge

DDoS attacks, web attacks, bots, and API abuse affect different parts of the technology stack, but they reveal the same challenge:

Attack traffic often uses legitimate-looking behavior.

This makes context essential.

Security teams need infrastructure data, while developers understand application workflows. Platform teams understand dependencies, while identity teams understand users, sessions, and permissions.

These signals become more valuable when they are connected.

What Teams Should Review

Based on the 2025 traffic patterns, engineering and security teams should review five areas:

Expensive endpoints
Identify requests that consume substantial compute, database, or third-party resources.
Cross-layer observability
Connect edge, application, API, identity, and backend telemetry.
Identity-aware limits
Apply controls across accounts, tokens, sessions, devices, and organizations, rather than relying solely on IP addresses.
Endpoint-specific bot policies
Define which automated agents can access each application workflow.
Long-term behavioral analysis
Look for attack activity developing over days or weeks, as well as sudden traffic spikes.

Final Thought

Blocking malicious requests remains necessary, but request-level inspection alone cannot explain every attack.

Developers and security teams also need to understand who is performing an action, how the behavior changes over time, which resources are affected, and whether the outcome aligns with expected business use.

That context is becoming a core part of application resilience.

The figures in this article are drawn from the 2025 CDNetworks State of Web Application and API Protection Report and reflect traffic observed and mitigated by the CDNetworks security platform during 2025.

Best CDN for Live Streaming in 2026: A Developer’s Guide to Choosing the Right Provider

Alvin — Fri, 31 Jul 2026 02:33:03 +0000

TL;DR

A live streaming CDN improves video delivery by serving content from edge servers closer to viewers.
The best CDN depends on your audience location, latency requirements, streaming protocols, and operational needs.
CDNetworks is a strong choice for global live streaming, especially when Asia-Pacific performance and ultra-low latency matter.
Akamai excels at large-scale enterprise broadcasting with a mature global network.
Cloudflare, Fastly, and AWS each offer advantages for specific deployment models and development workflows.

What you'll learn

What a live streaming CDN does and why it matters
How a CDN improves streaming performance
How I evaluated the top CDN providers
A side-by-side comparison of five leading live streaming CDNs
A practical framework for choosing the right CDN for your streaming platform

What is a live streaming CDN?

A live streaming CDN (Content Delivery Network) is a distributed network of edge servers that delivers live video from locations closer to viewers instead of relying on a single origin server.

Instead of sending every request back to the origin, the CDN replicates and distributes the live stream across multiple edge locations. Viewers connect to the nearest edge server, reducing network distance and improving playback quality.

Live streaming CDNs are commonly used for:

Sports broadcasts
OTT streaming platforms
Live commerce
Online education
Enterprise events
Gaming and esports

Why Live Streaming Needs a CDN

A live streaming CDN improves video delivery by distributing content through geographically distributed edge servers instead of forcing every viewer to connect directly to a centralized origin server.

When thousands or even millions of viewers join a live event, sending every request to a single origin server can quickly become a bottleneck. A CDN solves this problem by spreading traffic across multiple edge locations (also known as Points of Presence or PoPs), allowing viewers to receive video content from a server closer to their location.

                     Broadcaster
                         |
                         |
                    Origin Server
                         |
                         |
                 CDN Edge Network
                         |
        ┌────────────────┼────────────────┐
      US PoP           EU PoP          Asia PoP
        |                |                |
     Viewer A         Viewer B         Viewer C

This distributed architecture helps reduce delivery latency, minimize buffering, improve stream reliability, and support large-scale audiences across different regions.

Common use cases

Live streaming CDNs are widely used for scenarios that require high-quality video delivery, global reach, and the ability to handle sudden spikes in audience traffic.

Sports and esports broadcasting
OTT and media streaming platforms
Live commerce
Virtual classrooms
Enterprise live events
Gaming livestreams

How I evaluated the best live streaming CDNs

No CDN is the best choice for every streaming platform.

Instead of focusing on marketing claims, I evaluated providers using the technical characteristics that have the greatest impact on production live streaming.

The evaluation focused on six areas.

Evaluation Criteria	Why It Matters
Global edge network	Reduces latency by serving viewers from nearby locations
Live streaming performance	Improves playback quality, startup time, and latency
Scalability	Handles sudden traffic spikes during live events
Origin offload	Reduces origin bandwidth costs and improves reliability
Security & availability	Protects against DDoS attacks and service disruptions
Integration	Simplifies deployment with modern streaming protocols and APIs

I also considered compatibility with common streaming technologies, including:

RTMP
FLV
HLS
DASH
WebRTC
SRT
CMAF
QUIC

5 best CDN providers for live streaming

Many CDN providers support live video delivery, but only a handful consistently provide the combination of low latency, scalability, and operational reliability required for production streaming.

Here's how the 5 leading CDN providers compare.

Quick recommendations

Choose the provider that best matches your priorities.

CDNetworks — Best for global streaming with strong Asia-Pacific performance and ultra-low latency.
Akamai — Best for enterprise broadcasters operating at global scale.
Cloudflare — Best for developer-focused streaming platforms.
Fastly — Best for programmable edge delivery and low-latency HTTP streaming.
AWS — Best for teams already building on AWS services.

Comparison of best CDN for live streaming

Provider	Global Coverage	Best For	Streaming Protocols	Indicative Latency*	Security	Scalability
CDNetworks	3,000+ PoPs in 90+ countries	OTT, gaming, media, live commerce	RTMP, FLV, HLS, DASH, SRT, CMAF, WebRTC, QUIC	<500 ms (WebRTC)	DDoS, WAF, Bot Management, API Security	200+ Tbps
Akamai	Extensive global network	Enterprise media delivery	HLS, DASH, CMAF	2–5 s	DDoS, WAF, API Security, Zero Trust	Enterprise scale
Cloudflare	Large global edge network	Interactive streaming and developer platforms	HLS, LL-HLS, WebRTC	<1 s (WebRTC Beta)	DDoS, WAF, Zero Trust	Highly scalable
Fastly	Global edge network	Real-time streaming	HLS, DASH, CMAF	2–4 s	DDoS, WAF	High-performance edge
AWS	AWS global infrastructure	AWS-native streaming	HLS, DASH, CMAF	3–6 s	AWS Shield, AWS WAF	Elastic AWS scaling

Latency figures are indicative and depend on protocol selection, encoder settings, player buffering, network conditions, and overall streaming architecture. WebRTC deployments typically achieve sub-second latency, while LL-HLS workflows generally operate in the multi-second range.

Why choose CDNetworks for live streaming?

CDNetworks is a strong option for organizations that need reliable global delivery while maintaining excellent performance in Asia-Pacific.

Its combination of network coverage, protocol support, media services, and integrated security makes it suitable for:

OTT platforms
Live commerce
Sports broadcasting
Gaming
Online education
Enterprise streaming

Pros

3,000+ PoPs across 90+ countries
200+ Tbps network capacity
Strong Asia-Pacific and Mainland China optimization
Supports RTMP, FLV, HLS, DASH, SRT, CMAF, WebRTC, and QUIC
WebRTC streaming with glass-to-glass latency below 500 ms
Flexible ingest and Player SDKs
4K-ready cloud transcoding
Live recording and real-time screenshot services
Built-in DDoS protection, WAF, and access control

Considerations

Advanced media capabilities are primarily designed for enterprise deployments.
Smaller streaming projects may not need the full breadth of the platform.

Why choose Akamai for enterprise streaming?

Akamai is best suited for organizations running large-scale broadcasts where reliability is more important than minimizing operational complexity.

Pros

Extensive global edge infrastructure
Supports HLS, DASH, CMAF, and Low-Latency HLS
Mature enterprise security stack
Proven performance during high-profile live events

Considerations

Premium pricing
More operational overhead than lightweight CDN platforms

Why choose Cloudflare for developer-focused streaming?

Cloudflare combines CDN delivery, networking, and security into a unified platform, making it attractive for engineering teams building modern applications.

Pros

Large global network
Supports HLS, LL-HLS, and WebRTC
Built-in DDoS protection, WAF, bot management, and Zero Trust
Developer-friendly APIs

Considerations

Video delivery is not as specialized as providers focused primarily on streaming.
Some advanced streaming capabilities require additional Cloudflare services.

Why choose Fastly for low-latency HTTP streaming?

Fastly focuses on real-time content delivery with a programmable edge platform.

If your application requires fast cache updates and customizable request handling, Fastly is worth considering.

Pros

Low-latency delivery
Supports HLS, DASH, and CMAF
Programmable edge platform
Fast cache invalidation

Considerations

Smaller network footprint than some competitors
Edge programming features are most valuable for teams with in-house engineering expertise

Why choose AWS for AWS-native streaming?

AWS is a natural fit for organizations already running their infrastructure on AWS.

It integrates closely with Amazon S3, AWS Elemental Media Services, AWS Shield, and AWS WAF.

Pros

Global AWS infrastructure
Supports HLS, DASH, and CMAF
Tight integration with AWS media services
Elastic scaling

Considerations

Building a complete streaming workflow usually involves multiple AWS services.
Pricing and architecture can become complex at scale.

How do you choose the right live streaming CDN?

The right CDN depends on your workload rather than the longest feature list.

Here's the evaluation process I'd recommend.

1. Define your latency requirements

Start by identifying your application.

Interactive applications such as gaming, live commerce, auctions, and video calls typically require sub-second latency, making WebRTC a strong candidate.

Traditional OTT streaming usually prioritizes scalability and playback quality over the lowest possible latency.

2. Know where your viewers are

Audience location directly affects CDN performance.

If most viewers are concentrated in a particular region, prioritize providers with strong regional coverage.

For global audiences, choose a provider with broad geographic reach.

For Asia-Pacific users, evaluate regional routing performance in addition to overall network size.

3. Verify protocol compatibility

Your CDN should support the protocols used throughout your streaming workflow.

Common protocols include:

HLS
DASH
RTMP
WebRTC
LL-HLS
CMAF
SRT

Protocol compatibility can simplify deployment while improving playback across different devices.

4. Consider long-term operations

Streaming reliability depends on more than video delivery.

Evaluate additional capabilities such as:

DDoS protection
WAF
Analytics
Monitoring
APIs
Technical support
Media workflow services

These features become increasingly important as audience size grows.

5. Validate with production-like traffic

Specifications are useful, but real-world testing is more valuable.

Before committing to a provider, benchmark performance using traffic that resembles your production workload.

Measure metrics such as:

Startup time
Time to First Byte (TTFB)
End-to-end latency
Rebuffering rate
Playback stability
Regional performance

Real traffic often reveals differences that product documentation cannot.

What Is RTMP? Understanding RTMP Streaming and Live Ingest

Alvin — Thu, 30 Jul 2026 03:29:45 +0000

Live streaming looks simple from the viewer side: click play and watch.

Behind that experience is a complex pipeline involving encoding, media transport, processing, packaging, and delivery. Among the many protocols involved, RTMP (Real-Time Messaging Protocol) remains one of the most widely supported technologies for live streaming ingest.

Although RTMP is no longer used for browser playback, it continues to play an important role in connecting encoders with streaming platforms.

What Is RTMP?

RTMP is an application-layer protocol designed to transmit audio, video, metadata, and control messages between connected systems.

Originally associated with Adobe Flash streaming, RTMP was historically used for both media transport and playback. However, after Adobe ended Flash Player support on December 31, 2020, modern browsers stopped supporting native RTMP playback.

Today, RTMP is mainly used for live ingest.

A typical streaming workflow looks like this:
Camera or video source → Encoder → RTMP or RTMPS ingest → Media server → Transcoding and packaging → CDN → Viewer

In this architecture, RTMP handles the contribution side of streaming, while protocols such as HLS, DASH, or WebRTC are commonly used for viewer delivery.

This separation explains why RTMP remains relevant in modern streaming systems.

How RTMP Streaming Works

RTMP streaming starts when an encoder establishes a connection with a media server and continuously sends encoded media data.

1. Capture and Encode the Source

The process begins with a video source such as cameras, screen capture systems, gaming devices, and broadcast production systems

The encoder compresses raw audio and video into a stream suitable for transmission.

Important encoding parameters include:

Video codec
Audio codec
Resolution
Frame rate
Bitrate
Keyframe interval

Incorrect encoder settings can cause unstable ingest, processing failures, or playback problems.

2. Establish an RTMP Connection

The encoder connects to an RTMP or RTMPS endpoint provided by the streaming platform.

The workflow typically includes:

RTMP handshake
Connection request
Stream creation
Publishing the live feed

RTMP uses commands such as connect, createStream, and publish to establish and manage the streaming session.

3. Transfer Media Through Messages and Chunks

RTMP transports different types of information through the same connection:

Video data
Audio data
Metadata
Timing information
Control messages

Large messages can be divided into smaller chunks, allowing different data types to be transmitted efficiently over a persistent connection.This design is one reason RTMP became widely adopted in broadcast workflows.

4. Process and Deliver the Stream

After receiving the RTMP stream, the media platform can:

Authenticate the publisher
Transcode into multiple qualities
Generate adaptive bitrate streams
Package content into HLS, DASH, or WebRTC
Apply access controls
Deliver content through a CDN

RTMP handles the upstream contribution workflow, while other technologies handle scalable delivery.

What Is RTMP Ingest?

RTMP ingest is the process of sending a live stream from an encoder to a media platform.

It is the connection point between content production and streaming infrastructure. A typical RTMP ingest workflow:
Encoder → RTMP Ingest Server → Media Processing → Streaming Distribution

RTMP ingest remains popular because of its broad compatibility with:

OBS and other software encoders
Hardware encoders
Broadcast systems
Enterprise streaming platforms

For many organizations, replacing existing RTMP workflows would require significant changes to production infrastructure.

RTMPS: Secure RTMP Streaming

RTMPS is RTMP transmitted over a TLS-encrypted connection.

Unlike standard RTMP, RTMPS protects data while it travels between the encoder and ingest server.

For production environments, RTMPS is generally preferred when supported.

However, transport encryption is only one part of streaming security. A complete security strategy should also include:

Stream key protection
Publisher authentication
Viewer authorization
Digital rights management
Access-control policies

RTMPS improves connection security but does not replace broader content protection strategies.

RTMP vs HLS vs SRT vs WebRTC

Different streaming protocols solve different problems.

Protocol	Primary Role	Typical Connection	Main Strength	Main Consideration
RTMP or RTMPS	Live ingest	Encoder to media server	Broad publishing compatibility	Plain RTMP is unencrypted
HLS	Viewer playback and distribution	Server to player	HTTP-based delivery at scale	Segmenting and buffering affect latency
SRT	Contribution and transport	Source to media infrastructure	Recovery across unpredictable networks	Both endpoints must support SRT
RTSP	Session setup and control	Client and media server	Controls media sessions	Commonly works with separate transport mechanisms
WebRTC	Interactive real-time communication	Browser, application, or peer communication	Real-time browser and application interaction	Scaling and architecture can be more complex

A common modern architecture is:
RTMP → Media Processing → HLS → Viewer

RTMP provides compatibility at ingest, while HLS provides scalable playback.

For interactive applications such as video conferencing or real-time collaboration, WebRTC may be a better choice.

Advantages and Limitations of RTMP

Advantages of RTMP

Mature Ecosystem
RTMP is supported by many existing encoders, production tools, and streaming platforms.

Simple Ingest Workflow
Many organizations already have established RTMP publishing workflows, monitoring systems, and operational processes.

Flexible Media Processing
Platforms can receive RTMP streams and convert them into multiple delivery formats.

Limitations of RTMP

No Encryption Without RTMPS
Standard RTMP does not encrypt traffic.

Not Suitable for Browser Playback
Modern browsers generally require protocols such as HLS, DASH, or WebRTC.

Latency Depends on the Entire Pipeline
RTMP itself does not determine final viewer latency.

Latency depends on:

Encoding configuration
Network conditions
Transcoding
Packaging
CDN delivery
Player buffering

How to Improve RTMP Streaming Reliability

Reliable RTMP streaming depends on the entire workflow, not only the protocol itself.

Key practices include:

Choose a suitable ingest endpoint: Evaluate network stability, routing quality, packet loss, and available upload capacity before production streaming.
Follow encoding requirements: Match the platform’s supported codec settings, bitrate, resolution, frame rate, and keyframe interval to avoid ingest instability.
Use RTMPS when available: Encrypted ingest helps protect media data and connection information during transmission.
Protect publishing credentials: Stream keys should be treated as sensitive credentials. Avoid public exposure, unnecessary sharing, and unused long-lived keys.
Prepare redundancy for critical events: Important broadcasts should consider backup encoders, network connections, power sources, or ingest endpoints.
Monitor the complete delivery pipeline: A successful encoder connection does not guarantee a good viewer experience. Monitor ingest health, processing status, CDN delivery, and playback quality.

How CDNetworks Supports RTMP Ingest and Live Streaming

RTMP remains a widely used ingest protocol because it integrates with established encoders and live streaming workflows.

CDNetworks Media Delivery services support RTMP ingest workflows by connecting RTMP-based publishing with distributed media delivery.

CDNetworks’ Enhanced RTMP/FLV support is designed to:

Maintain compatibility with popular streaming software such as OBS and VLC.
Support a broader range of media formats.
Reduce the need for additional protocol replacement or adaptation.
Support low-latency streaming experiences.
Help providers balance audience experience with streaming costs.

These capabilities allow organizations to continue using existing RTMP workflows while integrating with modern media delivery infrastructure.

Final Thoughts

RTMP is not the newest streaming protocol, but it remains an important part of modern live streaming workflows because of its compatibility and ecosystem maturity.

Modern streaming architectures are not built around one protocol. RTMP, HLS, SRT, and WebRTC each solve different problems across ingest, delivery, contribution, and interaction.

Understanding where RTMP fits is still essential for building reliable and scalable streaming systems.

Cybersecurity in 2026: The Trends Reshaping Modern Applications

Alvin — Fri, 24 Jul 2026 07:13:26 +0000

Cybersecurity in 2026 feels different.

It’s not simply because attacks are becoming more sophisticated or more frequent. What’s changing is where security problems begin. They’re no longer confined to isolated vulnerabilities or network boundaries—they’re increasingly emerging from the applications we build, the APIs we expose, the identities we manage, and the automated systems we rely on every day.

Modern applications have become highly distributed. AI is accelerating development cycles, APIs are powering nearly every digital experience, and machine identities are beginning to outnumber human users. At the same time, attackers are becoming faster, more automated, and increasingly capable of blending malicious behaviors into legitimate traffic patterns.

According to Statista, cybercrime cost businesses approximately $10.5 trillion in 2025 and is projected to reach $15.63 trillion by 2029. Ignoring these changes is becoming significantly more expensive than preparing for them.

Looking ahead to 2026, five cybersecurity trends stand out—not because they’re entirely new, but because they’re fundamentally changing how modern applications need to think about security.

AI Is Industrializing Cyberattacks

AI has become one of the most significant accelerators of cyberattacks. What makes AI particularly interesting isn’t simply its ability to automate existing attack techniques—it’s dramatically changing attacker economics by reducing both the cost and expertise required to launch sophisticated campaigns at scale.

The numbers are beginning to reflect this shift:

FBI IC3 recorded more than 22,000 AI-related complaints and over $893 million in adjusted losses during 2025.
The World Economic Forum reported that 87% of respondents identified AI-related vulnerabilities as the fastest-growing cyber risk throughout 2025.
Deepfakes contributed to nearly 10% of cyberattacks during 2024, with fraud losses ranging from $250,000 to $20 million per incident.

Technical Insight

We’re moving beyond scripted automation into adaptive attack operations. Large language models, agentic AI systems, browser automation frameworks, and proxy networks are enabling attackers to generate increasingly convincing phishing campaigns, automate vulnerability discovery, and launch context-aware social engineering attacks at unprecedented scale.

What’s changing isn’t simply attack volume—it’s attack velocity. AI is significantly shortening the time between discovering vulnerabilities and exploiting them while lowering the technical barriers required to execute sophisticated attacks.

Security Implications

Modern applications will increasingly need to prioritize:

Behavioral-based threat detection over static rule matching.
AI-assisted anomaly analysis and automated response capabilities.
Continuous authentication mechanisms across user and machine identities.
Adaptive security models capable of responding to evolving attack behaviors.

The question is no longer whether attackers will leverage AI—it’s how quickly defenders can adapt to AI-driven threats.

API Security Is Becoming Application Security

Modern applications are increasingly API-first, which also means they’re increasingly API-dependent.

Rapid AI adoption, microservices architectures, and multi-cloud deployments are continuously expanding the application attack surface. APIs that once existed only between internal services are increasingly exposed across partners, platforms, and AI integrations.

According to CybersecAsia, the speed of AI deployment is already exceeding the pace of API security adoption, creating growing concerns around shadow and unmanaged APIs.

According to API security observations published by CDNetworks throughout 2025, authentication bypass accounted for 18.8% of observed API attacks, while privilege escalation represented 12.5% of attack patterns. Low-frequency API attacks persisted for an average of 21.7 days, highlighting how difficult these attacks can be to detect using traditional security controls.

Technical Insight

What’s changing about API attacks is their behavior. Attackers aren’t necessarily generating massive traffic spikes or exploiting well-known vulnerabilities. Increasingly, they’re targeting authorization logic, session management mechanisms, and business workflows themselves.

Low-frequency attacks are particularly challenging because they often resemble legitimate user behaviors, allowing them to remain undetected for extended periods of time.

This is one of the reasons Web Application and API Protection (WAAP) is becoming increasingly strategic in 2026. Traditional WAF capabilities alone are no longer sufficient for protecting modern applications that depend heavily on APIs, automation, and distributed services.

Security Implications

API security is gradually becoming application security. Building secure applications increasingly means understanding:

Who is accessing an API.
Why they’re accessing it.
Whether their behavior aligns with expected business logic.
How APIs interact across distributed services and machine identities.

Continuous API discovery, behavioral baselining, and context-aware authorization will become increasingly important as API ecosystems continue expanding.

Availability Has Become an Architectural Concern

We often discuss cybersecurity through the lens of confidentiality and data protection. Increasingly, however, availability deserves equal attention.

Modern DDoS attacks aren’t necessarily becoming larger—they’re becoming more persistent.

According to technical traffic observations published by CDNetworks, more than 227.37 million network-layer DDoS attack requests were mitigated throughout 2025, with attack volumes remaining elevated for much of the year. CDNetworks also reported that 86% of terabit-scale DDoS incidents observed during 2024 lasted longer than ten minutes, highlighting the growing prevalence of sustained, high-capacity attacks.

Application-layer attacks continue presenting significant challenges as well. During 2025, 67.45% of Layer 7 DDoS attacks observed by CDNetworks were concentrated within the APAC region, reinforcing the importance of regional traffic visibility and application-layer protections.

At the same time, CDNetworks observed that 74% of bot traffic throughout 2025 originated from malicious bots, underscoring the growing need for adaptive bot management capabilities.

Technical Insight

What’s interesting here isn’t simply attack volume—it’s what the data suggests about attacker behavior. We’re increasingly seeing attackers optimize for sustained resource exhaustion rather than short-lived traffic bursts.

Modern attacks frequently combine automated bot traffic, application-layer abuse, and prolonged attack durations to maximize operational impact. Availability challenges are gradually moving beyond networking concerns and becoming application-level challenges.

Why This Matters

Building resilient applications in 2026 increasingly means assuming malicious traffic will coexist alongside legitimate users from day one.
Engineering teams should increasingly consider:
Multi-layer DDoS mitigation strategies.
Regional traffic visibility across globally distributed infrastructures.
Adaptive bot management capabilities.
Edge-based traffic filtering mechanisms.
Application-layer protections designed for modern workloads.

Availability is becoming an architectural concern rather than simply an operational one.

Content Is Becoming a Security Asset

AI crawlers represent one of the more interesting developments emerging across modern applications.

Unlike traditional malicious bots, AI crawlers exist within a much larger gray area. Some provide legitimate value through indexing and retrieval capabilities, while others create significant concerns around content ownership, licensing, attribution, and proprietary data reuse.

According to traffic intelligence published by CDNetworks throughout 2025, AI bot activity accounted for approximately 0.42% of total observed internet traffic, translating to roughly 1.64 million requests per day.
More significantly, 72.67% of observed AI bot activity was associated with content retrieval and data scraping operations.

CDNetworks also observed that OTT platforms accounted for 24% of application-layer DDoS attacks during 2025, followed by Broadcasting and Television at 23% and News and Publishing at 9%. Additionally, CDNetworks helped a licensed video and music content platform mitigate more than 10 million malicious crawler requests per day throughout 2025, highlighting how AI-driven scraping activities can directly affect copyrighted media assets.

Technical Insight

Applications can no longer assume that every visitor is either a human user or a malicious bot. Increasingly, they’ll need to distinguish between search crawlers, AI assistants, retrieval systems, legitimate automation, and malicious scraping activities.

The engineering challenge is no longer simply blocking malicious traffic—it’s making intelligent decisions about automated access.

Security Implications

Content protection is gradually becoming part of modern application security strategies.

Engineering teams should increasingly evaluate:

Bot identity and access intent.
Content sensitivity and business impact.
Usage patterns across automated traffic.
Granular access policies for AI crawlers and legitimate automation.

Modern applications will need to move beyond simple allow-or-block policies toward more intelligent approaches to automated access governance.

Identity Is Replacing the Traditional Perimeter

Perhaps the most significant shift happening across cybersecurity is the growing importance of identity security.

Traditional network perimeters are becoming increasingly difficult to define. Modern applications operate across cloud environments, remote workforces, APIs, and machine identities that extend far beyond conventional boundaries.

Identity is gradually replacing the perimeter itself.

According to Verizon’s 2025 findings, credential abuse accounted for approximately 22% of initial access vectors throughout the year. Meanwhile, APWG recorded 971,181 phishing attacks during Q1 2026, representing a 13.8% increase compared with Q4 2025, while the number of known Phishing-as-a-Service kits doubled throughout 2025.

Google has also highlighted the growing adoption of advanced MFA bypass techniques and increasingly sophisticated social engineering attacks, while deepfake technologies continue challenging traditional assumptions around identity verification.

Technical Insight

Attackers are no longer attempting only to compromise systems—they’re increasingly attempting to impersonate trust itself.

The implications extend far beyond user authentication. Machine identities are expanding rapidly across modern infrastructures, while compromised credentials can trigger automated actions across distributed environments with minimal friction.

Zero Trust Network Access (ZTNA) adoption is accelerating partly because of these changes. As legacy VPN technologies continue reaching end-of-life, organizations are increasingly shifting toward identity-aware access models that provide users with access only to the resources they require while limiting opportunities for lateral movement.

Security Implications

Identity protection in 2026 is becoming less about protecting credentials and more about continuously validating trust.

Modern security architectures should increasingly prioritize:

Zero Trust principles.
Adaptive authentication mechanisms.
Identity threat detection capabilities.
Machine identity governance.
Risk-based access controls across distributed environments.

Identity is becoming as strategic as cloud and network security in modern application architectures.

What Modern Applications Are Teaching Us

Looking across industries, several patterns are beginning to emerge.

E-commerce and retail platforms accounted for 24% of observed bot attacks during 2025, according to CDNetworks’ technical observations. API attacks represented 32% of attacks targeting the industry during 2024, while approximately 22% of major DDoS incidents in late 2025 targeted online retail infrastructures.
Gaming platforms remain particularly vulnerable to availability-related attacks. CDNetworks reported that gaming services experienced 57.38% of observed Layer 3 and Layer 4 attacks alongside 31.32% of Layer 7 attacks during 2024.
Healthcare organizations continue facing substantial ransomware risks, with approximately 40% anticipated to experience attacks during 2026. The average cost of healthcare data breaches is projected to reach $12.6 million.
Financial services remain heavily targeted by both API abuse and identity-related threats. According to CDNetworks, financial services accounted for 23.8% of observed API attacks throughout 2025, while Statista projects average breach costs within the sector will exceed $6.08 million during 2026. Deepfake attacks are accelerating as well, with Axios reporting that 55% of financial organizations experienced incidents during 2025, compared with 43% across other industries.

Although these industries face different challenges, they’re ultimately reinforcing similar lessons—security is moving closer to application architecture itself.

Final Thoughts

Cybersecurity in 2026 isn’t simply about defending against the next vulnerability.

Modern applications are changing faster than traditional security assumptions can keep pace. AI is reshaping attacker capabilities. APIs are continuously expanding application boundaries. Identity is replacing traditional perimeters, while availability and content protection are becoming architectural concerns rather than operational ones.

Perhaps the biggest change isn’t happening within cybersecurity itself—it’s happening within the applications we’re building.

Security is gradually moving closer to product architecture.

Building secure applications in 2026 increasingly means assuming that automation, malicious traffic, machine identities, and adaptive threats are part of the environment from day one. The question is no longer whether modern applications will face these challenges, but whether they’re designed to continuously adapt when they do.