DEV Community: ManageEngine Applications Manager

Container monitoring just got broader: Docker Swarm and Podman support is here

Priya Praburam — Thu, 26 Mar 2026 07:26:00 +0000

Container infrastructure has never been more diverse. Some teams rely on Docker Swarm to orchestrate services at scale. Others have moved to Podman because it doesn't require a root daemon, which matters in regulated or zero-trust environments. In practice, many organizations run both.

Until now, getting full observability across these environments meant stitching together multiple tools. We're closing that gap with native support for Docker Swarm and Podman monitoring in Applications Manager!

Docker Swarm monitoring: Visibility from cluster to container

Running a Swarm cluster at scale means managing services across many nodes simultaneously. In a cluster of any real size, a problem that goes unnoticed for even a few minutes can affect more services than expected.

Applications Manager's Docker Swarm monitor gives a multi-tier view of your entire cluster, from high-level node health down to per-container resource consumption, without requiring agents on your hosts. It connects via the Swarm REST API and is straightforward to configure.

Podman monitoring: Security-first observability

Podman's daemonless, rootless architecture is its defining strength and its main observability challenge. Traditional monitoring tools that depend on daemon access or privileged APIs don't fit the model. The Podman monitor in Applications Manager is built to work within Podman's security constraints rather than around them.

"Rootless containers in production deserve the same observability as anything else in your stack."

Applications Manager connects via the Podman REST API and collects metrics without requiring elevated permissions, keeping the security setup your team put in place intact.

Monitoring coverage that keeps up with how you build

Container infrastructure rarely follows a single path. Some teams standardize on Swarm for orchestration at scale. Others choose Podman because it doesn't require a persistent daemon, which matters in environments with strict security requirements. Many teams end up running both for different workloads within the same organization.

Applications Manager now monitors both natively, without needing separate tools for each. As container strategies evolve and architectural choices multiply, observability coverage can now keep pace.

How to get started

Docker Swarm and Podman monitoring are available in the latest version of Applications Manager. Upgrade your console to enable both, or download a 30-day, free trial to explore now!

PostgreSQL monitoring: Best practices and essential performance metrics

Priya Praburam — Mon, 02 Mar 2026 18:41:28 +0000

Ensuring the reliability, availability, and optimal performance of a database requires constant vigilance. For a healthy PostgreSQL database, this vigilance is achieved through comprehensive PostgreSQL monitoring. Organizations must track specific metrics and implement standardized maintenance routines to prevent downtime and resource exhaustion.

Essential metrics for PostgreSQL monitoring

To maintain a well-coordinated environment, several key areas of the PostgreSQL database require regular tracking. These metrics provide the data necessary to identify bottlenecks before they impact the end-user experience.

1. Transaction and query details

Tracking transaction details is vital because transactions directly impact database speed. Monitoring execution times and resource usage helps identify slow or long-running transactions that cause bottlenecks.

Transaction volume: Monitor commits and rollbacks per unit of time. A sudden spike in volume can indicate an overloaded system.
Rollback rates: An increase in rollbacks often points to errors, failed transactions, or logical flaws in application code.
Query performance: Analyze specific queries that contribute to slowdowns. If high wait times occur, examine locking behavior to see if transactions are waiting excessively for resources.

2. Database connection health

PostgreSQL has a limit on the number of simultaneous connections. Monitoring these connections ensures that the database can handle peak user activity.

Connection limits: Track the number of active vs. maximum allowed connections. If connections approach their limit, legitimate users may be blocked.
Connection leaks: If the total count increases steadily over time, it may indicate that the application code is failing to close connections properly.
Alerting strategies: Set thresholds for sudden spikes and when counts approach maximum capacity. Dynamic thresholds are effective as they adjust based on historical usage patterns.

3. Lock and buffer statistics

Locks maintain data consistency during concurrent operations, but excessive locking leads to database stalls. Monitoring lock tables provides insights into active locks and waiting processes.

Lock modes: Monitor strict modes like ACCESS EXCLUSIVE. High occurrences of these modes can risk query timeouts and limit data modifiability.
Buffer cache hit ratio: This cache stores frequently accessed data in memory to reduce slow disk access. A healthy buffer hit ratio should stay above 80%. If it drops lower, the cache may be undersized, or queries may be performing excessive disk reads.

4. Index and table scan details

Indexes enable rapid data retrieval. Monitoring index scans determines if queries are utilizing these structures effectively.

Sequential vs. index scans: A high rate of sequential scans suggests that indexes are missing on frequently accessed data.
Underutilized indexes: Dropping indexes that are never used can streamline storage management and improve write performance without sacrificing read speed.

5. Replication metrics

PostgreSQL uses Write-Ahead Logging (WAL) for replication. Monitoring this process ensures that standby servers stay synchronized with the primary server, which is critical for disaster recovery.

Replication delay: Track the lag between the primary and standby servers.
Consistency vs. performance: Streaming replication offers high availability with some potential lag, while synchronous replication guarantees consistency but can impact performance.

Proactive PostgreSQL monitoring with Applications Manager

Translating database metrics into actionable insights requires a robust tool. Applications Manager serves as a comprehensive solution for PostgreSQL monitoring, offering real-time visibility into health, resource utilization, and availability. By automating root-cause analysis and capacity planning, it ensures that your PostgreSQL environment remains stable and performant. Get started now by downloading a free, 30-day trial now!

Effective strategies for Oracle database performance monitoring

Priya Praburam — Thu, 26 Feb 2026 07:57:56 +0000

Large-scale enterprises rely on Oracle Database for its scalability and reliability. Maintaining this performance across a disparate IT infrastructure requires real-time visibility into resource utilization and system efficiency. Organizations often implement Oracle monitoring software to handle these complex environments, as managing individual components with native tools can be a time-consuming task for administrators.

The following article outlines the critical areas to focus on for effective Oracle Database performance management.

Track resource consumption and sessions

Oracle Database has unique KPIs that require constant surveillance to prevent unscheduled downtime. Key metrics include tablespace growth, disk I/O, and session activity.

Monitoring the growth of tablespaces ensures proper table allocation and prevents storage bottlenecks. When tablespaces reach capacity, applications can stall or fail to commit transactions. Additionally, tracking sessions provides a view of server load and wait times. Recording the status, duration, and failure count of scheduled jobs helps reveal performance gaps that might otherwise go unnoticed.

Memory management is another vital pillar. Monitoring PGA and SGA statistics allows you to see bytes and blocks allocated versus free space. This visibility ensures that no corner of the Oracle tablespace remains unattended, preventing memory fragmentation and ensuring the database has enough buffer cache to handle peak loads.

Identify slow queries

A common challenge for IT teams is determining whether a performance lag stems from the application code or the database query itself. When queries run slowly, it is often due to how data is retrieved from the disk or inefficient execution plans.

DevOps teams need visibility into individual SQL statements to identify which ones are causing high latency. Correlating application performance with database server metrics helps teams collaborate more effectively to reduce erroneous queries and maintain the speed of business-critical applications. By pinpointing the exact statement responsible for a slowdown, teams can optimize indexes or rewrite queries to improve throughput.

Resolve issues at the root cause

Pointing out a symptom is not enough. Resolving the root cause is what makes a system efficient in the long run. If Mean Time to Repair (MTTR) is increasing, it is critical to identify which specific element is to blame, whether it is a hardware bottleneck, a locking issue, or a network delay.

Using adaptive thresholds helps filter out noise while flagging genuine anomalies. These adjust in real time based on interdependent metrics. Identifying deviations from baseline values early allows administrators to resolve issues before they impact the end user. This proactive approach minimizes the risk of failures where one minor issue triggers a wider system outage.

Analyze trends for future planning

Monitoring is about more than just immediate fixes. Extracting data from past trends is essential for forecasting. Precise reports on resource usage help you make informed decisions regarding upgrades and budget planning.

By analyzing these trends, you can move from a reactive posture to a proactive one. Predictive analysis can suggest when current hardware will reach its limit based on historical growth. This ensures that infrastructure investments are backed by data.

ManageEngine Applications Manager: How it helps

ManageEngine Applications Manager provides visibility into Oracle Database performance. It automates the tracking of tablespaces, sessions, and memory stats while providing APM capabilities to trace slow SQL statements. With AI-powered adaptive thresholds and predictive analysis reports, it helps IT teams identify root causes quickly and plan for future resource needs. Beyond Oracle, it supports over 150 technologies across on-premises and cloud environments, offering a single pane for your entire infrastructure. Explore now by downloading a free, 30-day trial!

Beyond the dashboard: Decoding the APM, RUM, and DEM trinity

Priya Praburam — Tue, 27 Jan 2026 07:22:04 +0000

You check the dashboard and everything looks fine. The lights are green. The response times look normal. But then the support tickets start coming in. Users say the site is slow or the checkout button is not working.
This happens because most tools only watch one part of the system. Your servers might be fast, but your users are still struggling. To fix this, you need to see your service from three angles: the server, the user, and the full journey. This is where Application performance monitoring (APM), real user monitoring (RUM), and digital experience monitoring (DEM) come into play.

The restaurant analogy

Think about a restaurant to see how these three work together.

APM is the kitchen. It watches the chefs and the ovens. Is the food cooked on time? Is the fridge cold? If a meal is late, APM tells you if a stove broke or if a chef is moving too slow.
RUM is the customer at the table. It listens to the person eating the meal. Was the food cold when it reached them? Did they wait too long to be served? This is how you know if the customer is actually happy.
DEM is the entire experience. It looks at everything from the parking lot to the final bill. It checks if the customer will come back. It covers the parts of the visit that happen outside of the kitchen or the dining room.

1. APM: Watching the backend

Application Performance Monitoring (APM) is your view of the inside. It sits on your servers and watches your code.
What it does: It finds slow database queries or bugs in your code. If a service crashes, APM shows you exactly where the failure happened.
The limit: A server can be healthy, but a user can still have a bad experience. APM cannot see what happens once the data leaves your server. It does not know if a user has a slow phone or a bad internet connection.

2. RUM: The reality check

Real User Monitoring (RUM) picks up where APM stops. It follows your code to the user’s actual device.
What it does: It records how long a page takes to load for a real person. It sees if a button does not work or if the layout looks broken on a specific phone.
The limit: RUM tells you that a user is upset, but it might not tell you why. You often need APM to find the root cause in the backend code.

3. DEM: The full journey

Digital Experience Monitoring (DEM) is the widest view. It does not just look at your code or your user. It looks at every piece of technology between your business and your customer.
What it does: It tracks the path across web and mobile apps. It uses synthetic tests to check your site even when no one is using it. It also watches network paths and third party services like payment screens or chat bots.
Why it matters: It finds problems in the middle. Maybe a network provider is slow or a third party script is broken. These are things that APM and RUM often miss.

Why one view is not enough

If you only use one of these, you are only seeing a small part of the truth.
If you only use APM, you might think everything is fine while users are struggling.
If you only use RUM, you know users are unhappy but you do not know how to fix it.
If you only use DEM, you might see a problem but not the specific line of code causing it. When you use all three together, you stop guessing. You can see a problem, find the cause, and fix it before it hurts your sales.

From watching systems to fixing experiences

Uptime is not the only thing that matters anymore. Users do not care about server stats. They care about their own experience. Did the page load? Did the button work? Did the payment go through?
Using APM, RUM, and DEM together helps you move past simple dashboards. It helps you build a service that people can trust. When you see the whole picture, you can stop chasing alerts and start making your users happy.

Unifying the trinity: How Applications Manager closes the gap

Most teams struggle because their performance data is trapped in different silos. You might have one tool for servers and another for the frontend, but they don't talk to each other. ManageEngine Applications Manager changes that by bringing APM, RUM, and DEM into a single, unified conversation.
Instead of jumping between browser tabs to solve a mystery, you get a clear view of how everything connects:

Deep APM: Get visibility into your backend code, track database queries, and find the root cause of server-side errors quickly.
Real-time RUM: See exactly how your users experience your site. Track page load times, browser performance, and regional latency as it happens.
Complete DEM: Use synthetic monitoring to test your critical paths even when traffic is low. Monitor your network and third-party services to ensure the entire journey is smooth.

By using all three capabilities together, you can stop guessing where problems are and start fixing them. This helps you protect your revenue and keep your users happy.

Download a 30-day, free trial of Applications Manager to see your application from every angle.

Navigating the chaos: How to tame Kubernetes Monitoring challenges

Shallin Albert — Fri, 01 Aug 2025 09:18:06 +0000

Kubernetes has emerged as the backbone of modern, cloud-native application architecture powering everything from microservices to enterprise-scale container orchestration. Its dynamic, distributed nature offers unmatched scalability and agility. But with that power comes complexity, especially in how systems are monitored.

For DevOps teams, platform engineers, and SREs, Kubernetes monitoring isn't just about collecting metrics it’s about making sense of a moving target. From ephemeral workloads to multi-cloud sprawl, the challenges are real and they’re not going away unless you have the right observability strategy in place, one that’s built for dynamic infrastructure, not static assumptions..

So how do you cut through the noise and monitor Kubernetes effectively?
Let’s unpack the core challenges, and more importantly, explore how to overcome them with intelligent observability practices and platforms designed to bring clarity to the Kubernetes chaos. These challenges can be broken down into a few key areas as follows:

1. Distributed systems: A monitoring nightmare
Kubernetes environments are inherently complex with pods, nodes, containers, and microservices, all interacting in unpredictable ways. Gaining visibility across this web of components is a challenge in itself.

The fix: Full-stack visibility

Adopt tools that merge metrics collection (like Prometheus) with distributed tracing.
Consider service mesh integrations like Istio, or Linkerd for tracing service-to-service traffic.
Some observability platforms like Mange Engine's Applications Manager integrate metrics and traces to offer unified visibility across layers, reducing the guesswork in troubleshooting.

2. Ephemeral infrastructure and short-lived resources
Pods are born to die. Containers get recycled. Monitoring Kubernetes in a system where components are constantly shifting demands an adaptive approach.

The fix: embrace dynamism

Track resources using labels and tags instead of static identifiers.
Use tools like Fluentd, Loki, or ELK for log persistence.
Look for monitoring solutions that auto-discover services and adapt to dynamic environments without manual configuration.

3. The multi-cloud, multi-cluster maze
Many organizations now run Kubernetes across multiple clusters and clouds. Without a centralized monitoring view, you’re left piecing together siloed data.

The fix: Centralized control plane

To choose observability platforms like Applications Manager that support multi-cloud and hybrid environments natively.
Ideally, monitoring tools should offer a consistent interface across AWS, Azure, GCP, and on-prem, helping avoid blind spots in performance tracking.

4. Drowning in high-cardinality data
From pod names and container IDs to request paths and labels, Kubernetes generates massive volumes of data with high cardinality, often too much for traditional systems to handle efficiently.

The fix: Smart data management

Fine-tune metric retention and collection to avoid data overload.
Down-sample or aggregate less critical telemetry to save storage.
Consider platforms that offer adaptive sampling and efficient metric handling to balance performance and insight.

5. Digging into application performance
You can monitor CPU and memory all day, but if your login microservice is timing out, you need visibility into application behaviour, not just infrastructure stats.

The fix: Application Performance Monitoring (APM)

Use APM to track transactions, database calls, and service bottlenecks.
Correlate application health with infrastructure events.
Many observability tools like Applications Manager now combine Kubernetes monitoring with APM, enabling teams to troubleshoot end-to-end with better context.

6. Security, compliance, and peace of mind
Security risks like misconfigurations and exposed APIs pose a real threat to Kubernetes environments, and compliance adds another layer of responsibility.

The fix: Continuous security monitoring

Implement RBAC and enable audit logs.
Use policy enforcement tools and vulnerability scanners.
Some observability suites offer integrations with security layers, supporting audit trails and compliance-ready monitoring practices.

7. Alert fatigue is real
Getting bombarded by alerts, many of which don’t matter is more than annoying. It can be dangerous if critical issues get buried.

The fix: Smarter alerts, not more

Define severity-based alerting and reduce false positives with anomaly detection.
Use intelligent alerting platforms that learn normal behavior patterns to reduce noise.
Look for tools like Applications Manager with customizable thresholds and AI-assisted alerting workflows to cut through the clutter.

8. Standardization gaps across teams
Siloed tooling and inconsistent monitoring practices can cripple cross-team collaboration. Customizable dashboards help teams focus on what matters to them while still sharing a common view.

The fix: Centralized, vendor-neutral monitoring

Standardize observability frameworks across teams and clusters with tools like Applications Manager.
Opt for platforms that integrate with diverse tech stacks without enforcing ecosystem lock-in.
The goal: create a shared source of truth for all stakeholders, from DevOps to application owners.

Why is it essential to simplify Kubernetes Monitoring?
Kubernetes isn’t going to get simpler. But the right tools and strategies can make managing it more approachable. Whether you’re dealing with complex hybrid deployments, chasing down performance bugs, or fighting alert fatigue, your monitoring platform plays a central role. That's why experiencing it firsthand is valuable; give Applications Manager a try with a free 30-day trial.

Curious how it works in practice?
Explore a guided demo of Applications Manager to see how it can support your Kubernetes monitoring strategy without the overhead.

Essential best practices for real user monitoring (RUM)

Arshad — Fri, 01 Aug 2025 04:57:13 +0000

In today’s digital-first world, a brand’s reputation often hinges on the quality of its online experience. That’s why Real User Monitoring (RUM) has become a vital part of any strategy focused on tracking website and application performance. By observing how real users interact with your digital platforms, RUM uncovers performance bottlenecks and usability issues that can affect satisfaction and retention. Beyond simply collecting data, RUM empowers organizations to enhance user experience and drive sustainable business growth.

However, to unlock its full potential, you need a strategic approach. In this guide, we’ll outline practical best practices to help you get the most out of RUM—and keep your users delighted.

1. Establish concrete goals aligned with business objectives

Start by defining clear, measurable goals for your RUM strategy—such as reducing average page load times, increasing conversion rates, or lowering bounce rates. These objectives will guide which metrics matter most and how to interpret them. Crucially, ensure these business goals are linked to technical performance metrics. For instance, lowering bounce rates might involve optimizing rendering speed or streamlining resource loading. This alignment helps technical improvements translate directly into business value.

2. Focus on the metrics that matter

While RUM tools can track an array of metrics, only a select few are truly impactful. Concentrate on the KPIs most relevant to your users and business goals, such as:

Page load speed
Server response time
Error rates
Time to first byte(TTFB)

Prioritizing these essential metrics ensures that your monitoring efforts remain targeted and actionable, ultimately enhancing the user experience where it matters most.

3. Monitor critical user journeys

Identify the key interactions that users have on your platform—like logging in, searching for products, or completing checkout. By focusing your RUM analysis on these critical paths, you can address issues that have the biggest influence on user satisfaction and business outcomes.

4. Track performance across diverse platforms

User experiences can vary widely depending on browser, device, or operating system. That’s why it’s essential to analyze performance across all platforms.

This approach helps you pinpoint issues unique to specific device types or network conditions—for example, slow load times on mid-range smartphones in areas with limited connectivity.

5. Observe end-to-end user interactions

Rather than evaluating individual pages in isolation, monitor full user journeys—from entry to exit. This broader view allows you to identify points of friction and performance issues that page-level metrics may overlook. Pairing RUM with synthetic monitoring adds an extra layer: synthetic tests simulate user flows to detect problems before they impact real users, while RUM captures the live experience.

6. Integrate RUM with your observability ecosystem

Seamlessly incorporate RUM into your DevOps workflows to ensure consistent performance monitoring throughout the development lifecycle. Integrate RUM data with logs, distributed tracing, and other observability tools to gain a holistic view of system performance and quickly identify root causes. Also, connect RUM with incident response platforms such as ServiceNow, Slack, PagerDuty, or ServiceDesk Plus to automate alerts and accelerate resolution workflows.

7. Define baselines and service standards

Setting benchmarks and service level agreements (SLAs) is essential for tracking progress and measuring success. Use historical RUM data to establish meaningful baselines—for example, maintaining Largest Contentful Paint (LCP) below 2.5 seconds for 90% of visitors. Comparing real-time performance against these baselines helps teams stay aligned, measure improvements, and maintain business-focused accountability.

8. Turn insights into action

Collecting data is only the first step—what matters is how you act on it. Use RUM insights to prioritize optimizations, fix usability issues, and streamline user flows. Sharing dashboards and reports with product teams, designers, and key stakeholders helps everyone understand how performance affects both user behavior and business KPIs, fostering cross-functional collaboration.

9. Continuously refine your approach

Real user monitoring is not a set-it-and-forget-it solution—it requires ongoing iteration. Regularly review and refine your RUM strategy, update what you monitor, and analyze emerging user segments to keep your insights relevant. This proactive mindset ensures your digital platforms stay fast, responsive, and in sync with evolving user expectations.

Boost your RUM strategy with ease!

Take your website and web app performance to new heights by applying these RUM best practices. With ManageEngine Applications Manager, you gain comprehensive, real-time visibility into live user interactions across your infrastructure. Our robust real user monitoring solution offers deep insights into application behavior, infrastructure health, and cloud performance.

Quickly detect and resolve issues, harness automation to simplify operations, and ensure users enjoy seamless digital experiences.

Book a personalized demo today or explore our 30-day free trial to see the power of Applications Manager's RUM solution in action.

Solving container monitoring challenges with a smarter approach

Shallin Albert — Thu, 31 Jul 2025 12:24:41 +0000

Containers have become the backbone of modern application deployment, offering flexibility and efficiency. However, monitoring these dynamic environments presents unique challenges. Unlike traditional infrastructure, containers are short-lived, scale rapidly, and operate across diverse environments, making observability complex.

Consider an IT team managing a microservices-based e-commerce platform during a high-traffic sale event. Hundreds of new containers spin up in response to demand, but without proper container monitoring, tracking performance bottlenecks or failures in real time becomes a nightmare. Identifying and addressing issues in such scenarios requires a robust monitoring strategy.

1. Dealing with short-lived containers
One of the biggest hurdles in container monitoring is their transient nature, with some instances lasting only seconds, making real-time tracking essential for maintaining visibility into their health and performance.

How to address it:

Use real-time, Kubernetes-native monitoring tools (like Prometheus, cAdvisor, or ManageEngine Applications Manager) to instantly capture container and microservices performance. This ensures not missing out on critical data from containers that only lasts for few seconds.
Monitor Docker containers by collecting native Docker metrics and logs, especially in standalone or hybrid environments where Kubernetes isn’t fully adopted.
Use distributed tracing (such as Jaeger or OpenTelemetry) so that even short-lived container instances leave a trace for debugging and performance analysis.
Tailor observability for Kubernetes-dependent applications by tracking deployments, autoscaling behavior, and performance at the namespace or cluster level.

2. Managing scale without overwhelming your monitoring system
In large-scale deployments, traditional monitoring solutions struggle to keep up. Without automation, IT teams can quickly become overwhelmed by alerts and redundant logs.

Consider a media streaming service that auto-scales during peak hours. If thousands of containers are running simultaneously, manual tracking becomes impractical. Performance issues might go unnoticed until users report buffering problems.

How to address it:

Deploy auto-discovery mechanisms to dynamically track newly created containers.
Use AI-powered anomaly detection to reduce false positives and identify real issues.
Aggregate logs efficiently instead of drowning in unstructured data. Solutions like Fluentd or Loki can help.

3. Avoiding data overload in log and metric management
A single application running in containers generates thousands of logs per second. Without proper log management, IT teams may spend hours sifting through unnecessary data.

Take an example from a ride-hailing service: Each trip request generates logs related to user location, surge pricing, driver matching, and payment. If logs are not structured efficiently, detecting critical errors such as failed payments or driver assignment delays becomes a tedious process.

How to address it:

Define log retention policies to store only relevant data.
Use centralized log aggregation to streamline searchability and analysis.
Consider edge-based monitoring to process data locally before sending it to the cloud, reducing storage costs.

4. Ensuring visibility across multi-cloud and hybrid environments
Organizations are increasingly deploying containers across on-premises data centers, hybrid environments, and multiple cloud providers. However, monitoring becomes difficult when each platform has different standards and tools.

For example, a SaaS provider hosting applications in both AWS and Azure might struggle to correlate performance metrics between the two. When a latency issue arises, it's important to identify whether it’s an AWS network delay or an internal microservice failure requires a unified monitoring approach.

How to address it:

Adopt cloud-agnostic monitoring tools like Applications Manager that provide a single view across multiple environments.
Standardize logging and tracing frameworks across all deployments.
Implement service meshes like Istio to enhance visibility into inter-service communication.

5. Strengthening security without compromising performance
Security risks increase when organizations fail to monitor containerized environments effectively. Attackers often exploit misconfigured containers to gain access to sensitive data.

A real-world example is the Tesla Kubernetes breach, where attackers infiltrated a misconfigured Kubernetes console and ran cryptocurrency mining scripts. This type of vulnerability could have been prevented with proper security monitoring.

How to address it:

Implement real-time security monitoring to detect suspicious activity immediately.
Use container image scanning tools to prevent deploying vulnerable containers.
Enforce role-based access control (RBAC) to limit unauthorized access.

Comprehensive container monitoring with Applications Manager

For organizations looking for a robust solution to streamline container monitoring, Applications Manager provides end-to-end observability across Kubernetes, Docker, and OpenShift environments. It ensures optimal performance and availability through:

In-depth container monitoring for Docker, OpenShift, and Kubernetes, offering real-time visibility into container health and application performance.
Tracking of key performance indicators (KPIs) such as CPU, memory, disk, network usage, response times, and error rates, helping teams detect performance bottlenecks before they impact users.
Auto-discovery of new containers and services, ensuring seamless tracking of dynamic infrastructure across environments.
Kubernetes cluster monitoring, covering critical components like pods, nodes, and services, offers a holistic view of cluster health.
Granular Docker monitoring, analyzing CPU, memory, network I/O, and disk I/O at the container level to optimize resource utilization.
OpenShift performance tracking, providing insights into node, pod, and service health to prevent disruptions.
Root cause analysis and troubleshooting, utilizing ML-driven anomaly detection to identify and resolve issues before they impact end users.
Intelligent alerting and automation, notifying teams of critical events and enabling automated remediation when predefined thresholds are breached.
Advanced analytics and predictive insights, allowing organizations to analyze historical performance trends and optimize resource allocation.
Istio service mesh, allowing organizations to monitor latency, traffic routing, and service health for improved observability in service-to-service communications.

Conclusion
As container adoption grows, so do the complexities of monitoring them. By leveraging automation, AI-driven insights, and real-time observability, organizations can overcome these challenges and ensure seamless application performance.

For teams looking to streamline their monitoring strategy, Applications Manager provides an all-in-one solution to simplify observability across complex environments.

Explore how it works in your infrastructure. Schedule a free demo today.

Beyond the basics: A practical guide to JMX monitoring for Java applications

Arshad — Mon, 28 Jul 2025 04:21:33 +0000

As Java applications increasingly run across distributed, cloud-native environments, maintaining performance, scalability, and reliability is more challenging than ever. Performance issues can appear anywhere—from subtle memory leaks to thread contention—and detecting them early is essential. This is where JMX monitoring makes a difference. Rather than being just another tool, it’s a framework that turns JVM internals into actionable insights.

In this article, we’ll take a fresh look at what JMX monitoring does, why it’s important, the common obstacles teams encounter, and how to build a monitoring strategy that keeps your Java applications healthy and resilient.

How JMX monitoring gives you deeper visibility

At its core, Java Management Extensions (JMX) help open up the JVM, making it observable without needing to restart or disrupt the application. This is achieved through Managed Beans (MBeans) components designed to expose internal metrics and operational data.

MBeans communicate with the JVM’s internal MBean server, which acts as a central point that monitoring tools can query. This setup makes it possible to see real-time data on memory consumption, garbage collection behavior, active threads, and even application-specific metrics. By leveraging this live data, teams can pinpoint bottlenecks, fine-tune performance, and troubleshoot issues proactively.

Why JMX monitoring is more than just technical data

While JMX monitoring naturally starts with JVM metrics, it can also offer insights that bridge technical performance and business outcomes. Many teams create custom MBeans to capture data that directly reflects user experience and business health, such as cache efficiency, transaction rates, or queue depths.

This holistic view helps teams answer questions like:

How do peak loads affect response times?
Are growing queue sizes signaling a potential slowdown?
Do recent code changes increase memory usage?

By linking system-level data with business-critical metrics, JMX monitoring becomes an essential part of keeping applications not only technically sound but also aligned with organizational goals.

Typical challenges in JMX monitoring

Despite its flexibility, effective JMX monitoring can present a few common challenges:

Security risks: Leaving JMX endpoints exposed without proper encryption and authentication can allow unauthorized access to sensitive operations.
Information overload: The JVM can produce hundreds of metrics. Without clear priorities, dashboards can become cluttered and less useful.
Added resource consumption: Collecting too many metrics too frequently or using inefficient MBeans can increase CPU and memory overhead.
Complex integrations: Sending JMX data into platforms like Prometheus, Grafana, or cloud observability tools often requires additional setup.
Limited context: Metrics alone often show what happened, but without logs or traces, it’s difficult to see why an issue occurred.

KPIs to track in JMX monitoring

Rather than trying to track every possible metric, focus on those that reveal meaningful trends and help detect problems early:

Memory and garbage collection: Monitor heap and non-heap memory usage, garbage collection duration and frequency, and post-GC old generation usage to catch potential leaks.
Thread and concurrency metrics: Track active and peak threads, daemon threads, blocked or waiting threads, and JVM-reported deadlocks.
Class loading metrics: Keep an eye on the number of loaded classes and how these numbers change over time to identify unusual application behavior.
Custom business metrics: Use MBeans to track metrics closely tied to your application, such as transaction counts, active sessions, or queue sizes.
Connection pool statistics: Monitor active versus idle connections, wait times, and overall usage to maintain efficient interaction with databases and messaging systems.

Best practices for proactive JMX monitoring

To get the most out of JMX monitoring without introducing unnecessary complexity or overhead, consider these recommendations:

Focus on what matters: Start with metrics that directly impact user experience and application performance, and expand only as necessary.
Combine metrics with logs and traces: Use these together to get the context needed for faster, more accurate troubleshooting.
Secure your monitoring setup: Protect JMX endpoints with encryption, require authentication, and limit access to trusted networks.
Blend technical and business metrics: Track both JVM-level data and custom metrics that reflect user-facing performance.
Design effective dashboards and alerts: Build dashboards that clearly highlight trends, and set realistic alert thresholds to reduce false alarms.
Document your monitoring strategy: Keep clear records of what you monitor and why, so the strategy remains consistent and easier to update.
Optimize for low overhead: Tune polling intervals and use lightweight MBeans to avoid slowing down the application.
Regularly refine your approach: As applications evolve, adjust your monitoring strategy by adding new metrics and removing outdated ones.

Start your JMX monitoring journey with ease!

Modern Java applications require proactive monitoring to remain stable and responsive. ManageEngine Applications Manager's JMX monitoring simplifies this process by bringing together JVM metrics and custom application data in one platform for easy visualization and alerting. With Applications Manager, your team can detect and fix issues faster, see real-time business trends, and keep your Java applications performing reliably—even as workloads change and scale.

Ready to see how it works?

Schedule a personalized demo or explore a 30-day free trial today to discover how Applications Manager can help modernize and simplify your JMX monitoring techniques.

Boost website performance with real user monitoring

Arshad — Mon, 07 Jul 2025 12:33:02 +0000

In today’s fast-paced digital world, your website isn’t just your storefront—it is your product. A slow-loading page or clunky user experience could imply lost traffic, higher bounce rates, and fewer conversions.

That’s where real user monitoring comes in. Whether you're a webmaster, application developer, or site owner, RUM gives you a live, under-the-hood look at how real users are experiencing your website.

This article breaks down what RUM is, how it works, and why it’s a must-have for optimizing digital experiences.

What is real user monitoring?

Real user monitoring (RUM) is a method of passively capturing performance data from actual users visiting your website or app. Instead of synthetic tests that simulate behavior, RUM tells you exactly how your users experience your site—on different devices, browsers, networks, and locations. It tracks metrics like:

Page load times
Response times
Click paths
Errors and crashes
Transaction performance

This data helps identify and fix bottlenecks that hurt your site’s usability or performance.

Why should you care about RUM?

If you’ve ever said, “It works fine on my machine!”—RUM is for you. Here’s why RUM is crucial for you as a developer or webmaster:

Understand real-world performance: Get visibility into how users on slow networks, older browsers, or mobile devices are experiencing your site.
Identify performance issues quickly: Catch slow-loading pages, broken scripts, and failed transactions as they happen instead of waiting for angry support emails.
Optimize for conversion and retention: By seeing where users bounce or drop off, you can fine-tune your UX, navigation, and load speeds to improve engagement and revenue.
Track performance globally: If you have traffic from multiple geographies, RUM tells you exactly where performance lags so you can fix it fast.

Key features developers should look for in a RUM tool

Here are the must-have capabilities to look for in a RUM solution:

Real-time performance monitoring

Track web vitals (like LCP, FID, CLS), Apdex scores, and transaction response times as they occur—no guesswork.

Geo-specific insights

Visualize performance across different regions, helping you identify localized issues due to CDN, ISP, or infrastructure problems.

Slow transaction analysis

Zoom into individual transactions to understand what’s slowing things down—be it large payloads, JS execution, or third-party calls.

Session-level tracking

Replay user sessions or dig into session data to troubleshoot abandonment, navigation loops, or UI bugs.

Platform/browser/device analysis

Know how your site behaves on Chrome vs. Safari, or iOS vs. Android, and optimize accordingly.

JavaScript error reporting

Catch and debug script errors in real time, with details on the error type, frequency, affected pages, users, and devices.

How RUM works

RUM works by embedding a small JavaScript agent into your webpages. This script collects anonymized performance data from real user sessions and sends it to a central server for analysis. Some tools also integrate with server-side logs or APM data to give you a full-stack view. This helps you:

Combine frontend metrics with backend response times
Compare user-perceived performance with server-side metrics
Create data-driven performance budgets

Challenges in RUM

RUM is powerful, but it’s not without quirks:

Data overload: RUM tools can generate massive amounts of data. Make sure your tool offers filtering, tagging, or AI-assisted insights.
Lack of context: RUM shows what happened, but not always why. Consider pairing it with APM tools for backend correlation.
Privacy compliance: Be sure your solution respects GDPR, CCPA, and other data protection laws by anonymizing IPs and avoiding PII.
Device diversity: With so many device types and OS/browser combinations, consistent UX optimization can be tricky—but RUM gives you a fighting chance.

RUM in action: What you can do today

If you're a developer or webmaster, here are five immediate wins you can get with RUM:

Fix that one page your support team always gets complaints about.
Compare real vs. expected performance for your latest feature rollout.
Segment user experience by geography to detect CDN or routing issues.
Set up alerting when Apdex drops below a threshold.
Measure the performance delta before and after optimizations.

Why choose ManageEngine Applications Manager for RUM?

Here’s what makes ManageEngine Applications Manager a powerful, developer-friendly choice for real user monitoring:

Unified monitoring across frontend and backend

Applications Manager doesn’t just stop at the browser. It lets you correlate RUM data with application performance metrics, database response times, and infrastructure health—giving you full-stack visibility.

Session-level insights with drill-down

Dive into individual user sessions to analyze load times, interaction paths, errors, and delays—perfect for debugging specific issues or validating new features.

Geo-distributed performance heat maps

Get a visual view of your website’s global performance, pinpointing problem areas by country, state, or city. Ideal for websites with an international audience.

Multi-device and cross-browser support

Track how your site performs across desktop vs. mobile, or Chrome, Firefox, Safari, Edge, etc. Optimize for the platforms your visitors actually use.

JavaScript error detection with rich diagnostics

Detect, log, and analyze JS errors in real time—including frequency, affected users, impacted browsers/pages, and error stack traces.

Intuitive dashboards and custom reports

No more sifting through raw data. Applications Manager offers clean, customizable dashboards and automated reports to help teams stay aligned and make informed decisions.

Built-in alerting and integration

Set up smart alerts based on user satisfaction (Apdex scores), performance thresholds, or error rates. Integrate with tools like ServiceNow, Slack, or MS Teams to stay in the loop.

Real user experience is your most important performance metric. Don’t leave it to chance.

Start a 30-day free trial and see the difference RUM can make in optimizing your website’s performance and UX.

5 key MySQL metrics every DBA should track

Priya Praburam — Tue, 01 Jul 2025 07:13:20 +0000

MySQL is a widely used relational database that plays a central role in many enterprise and cloud-native applications. Whether supporting an e-commerce platform, a data-driven business process, or a custom internal tool, its performance has a direct impact on user experience and application responsiveness.

But ensuring consistent performance isn't just about tuning configurations once or scaling hardware. It requires ongoing observability. By monitoring the right set of metrics, teams can spot slowdowns early, resolve emerging bottlenecks, and optimize based on real-world workload behavior.
Here are five essential MySQL performance metrics every team should keep an eye on.

1. Query execution time

Query performance issues are one of the most common causes of slow applications. A single poorly optimized query can monopolize resources if it runs frequently or processes large volumes of data.
Tracking query execution time helps you identify which queries take the longest to complete and how often they are executed. When performance begins to vary significantly under load, it may point to missing indexes, inefficient joins, or sub queries that scale poorly as data grows.
Regularly monitoring these values allows you to tune queries based on actual usage patterns instead of assumptions. This insight also helps developers and DBAs prioritize which queries to optimize for the greatest performance gain.

2. Connection utilization

MySQL has a maximum connection limit. Once that limit is reached, new connection attempts are rejected, causing disruptions in applications that depend on the database.

Important metrics to watch include:

Threads_connected, which shows the number of current client connections
Threads_running, which reveals how many of those are actively executing queries
Aborted_connections, which helps identify failed connection attempts

These indicators provide early warnings about connection pool exhaustion, application-side connection leaks, or traffic surges. Monitoring connection usage over time helps teams adjust connection limits, optimize pooling strategies, and maintain database availability.

3. Replication lag

MySQL replication allows teams to maintain read scalability and fault tolerance. However, if replicas lag behind the primary server, they may serve stale data or fail to take over during a failover event.

To prevent these scenarios, monitor:

Seconds_behind_master, which shows how far behind the replica is
SQL and IO thread statuses, which indicate whether replication is running as expected
Replication errors or skipped events, which may signal configuration issues or performance bottlenecks

Consistent tracking of replication metrics ensures that secondary servers are ready to step in when needed and that applications relying on replicas do not encounter data consistency issues.

4. InnoDB buffer pool usage

MySQL's InnoDB storage engine relies heavily on memory to reduce disk I/O. The buffer pool stores frequently accessed data and indexes in memory, allowing faster query execution.

Key metrics to monitor include:

Buffer pool hit ratio, which reflects how often data is served from memory
Read and write IOPS, which shows how much disk activity is occurring
Pages read from disk vs. memory, which indicates memory efficiency

A low hit ratio or rising IOPS values may suggest that the buffer pool size is too small or that memory is not being used efficiently. Monitoring these indicators allows you to fine-tune memory allocation and improve performance for read-heavy workloads.

5. Lock and transaction metrics

MySQL uses locks to ensure data consistency, especially in environments with concurrent transactions. However, excessive or poorly managed locking can delay queries and reduce throughput.

Metrics to watch include:

Lock wait time, which measures how long transactions wait for resources
Active transactions, to understand how many transactions are in progress
Deadlock events, which point to transaction conflicts or poor query design

If lock contention is frequent or transaction durations grow unexpectedly, applications may slow down or fail under pressure. Tracking these values gives you visibility into potential concurrency issues before they become production incidents.

Turning metrics into action

These five metric categories give DBAs visibility into the most critical aspects of MySQL performance. But metrics alone are not enough. The ability to correlate trends, detect deviations, and receive timely alerts makes all the difference in keeping your database environment healthy and responsive.

That is where a monitoring solution comes into play.

ManageEngine Applications Manager provides end-to-end visibility into MySQL performance. It tracks query execution, replication lag, connection health, buffer pool usage, and transaction activity in real time. With customizable thresholds, behavior-based alerts, and intuitive dashboards, teams can troubleshoot faster and optimize more effectively.
Whether you are running a single MySQL instance or managing a fleet of production databases, Applications Manager's MySQL monitoring tool helps you shift from reactive problem-solving to proactive performance management.

Start your free, 30-day trial of Applications Manager now!

Challenges in website monitoring

Arshad — Fri, 30 May 2025 13:42:36 +0000

In today’s digital age, websites are essential tools for businesses, institutions, and individuals alike. They serve as gateways for communication, marketing, and online transactions—making it critical to monitor and manage them continuously. Website monitoring ensures optimal performance, availability, and a positive user experience by regularly tracking a site’s functionality and accessibility. However, website monitoring comes with its own set of challenges that can disrupt smooth operation and user satisfaction.
In this article, we’ll explore common challenges faced by businesses and website owners in monitoring their sites, along with practical ways to overcome them.

1. Downtime and outages

At times, a website may experience unavailability, rendering it inaccessible to its visitors and potentially resulting in a complete shutdown. This can occur due to a multitude of reasons, including server malfunctions, network complications, or technical malfunctions. The consequences of downtime and outages can be significant, as they not only disrupt the website's usability for users but can also result in financial losses and harm to the company's image.

Solution: Implementing a dependable website monitoring system that consistently monitors the accessibility of your site is the ultimate solution for combating downtime. With the ability to promptly notify the website owner or administrator of any downtime, swift action can be taken to mitigate its effects on users.

2. False positives and alert fatigue

Monitoring systems have the potential to produce an abundance of alerts, some of which may be inaccurate, causing teams to become inundated and potentially overlook critical issues. These false notifications arise when the monitoring system identifies an issue that is not truly problematic. There are numerous factors that can contribute to these false alarms, including network delays, server malfunctions, or incorrect setup of the monitoring software. For website owners, these false alarms can be a source of frustration and can result in avoidable periods of inactivity and disturbances.

Solution: It is crucial to consistently assess and improve the monitoring system to guarantee its effectiveness in identifying and communicating problems. Utilizing cutting-edge AI technology for anomaly detection and advanced filtering capabilities offered by tools such as Applications Manager can effectively minimize unnecessary alerts by prioritizing those that truly matter. Furthermore, establishing performance benchmarks and setting alerts for significant deviations is key to honing in on genuine issues.

3. Monitoring complex websites

Modern websites have evolved to include a plethora of third-party services, APIs, and dynamic content, posing a challenge for efficient monitoring. The emergence of online shopping, social media integration, and interactive elements has transformed websites from simple static pages to intricate platforms, making it difficult to pinpoint the source of any problems.

Solution: Having a monitoring system that can effectively manage the intricacies of contemporary websites and deliver precise and thorough information on their functionality is absolutely essential. Gaining a complete understanding of the entire infrastructure, applications, and third-party connections by consolidating metrics from servers, APIs, and front-end performance is key to expediting problem identification and resolution.

4. Lack of visibility and incomplete coverage

Many monitoring systems only measure a website's uptime and response time from the server's point of view, which may not accurately represent the user's true experience. This means that while a website may appear to be functioning properly, there could be underlying issues causing certain pages or features to load slowly or malfunction, resulting in a frustrating user experience. Furthermore, most monitoring setups only pay attention to the homepage, neglecting critical user paths like login screens, checkout processes, and dashboards, leaving potential failures unnoticed and potentially impacting revenue and customer satisfaction.

Solution: Utilizing a monitoring system that can mimic user actions and offer valuable insights into the functionality of a website from the user's point of view is crucial. By incorporating synthetic monitoring to replicate important user journeys (such as logging in or making a purchase) from various locations, along with real user monitoring to track genuine user interactions on all significant pages, you can guarantee comprehensive coverage and accurately depict the true user experience in real-time.

5. Monitoring from different locations

Websites are visited by people from all corners of the globe, and their browsing experience can differ greatly depending on where they are. With users accessing websites from various locations and devices, the resulting performance and experience can be difficult to keep tabs on. Additionally, monitoring from multiple locations can be quite a task, as it demands a considerable investment in resources and infrastructure.

Solution: Embracing a website monitoring solution that tracks a worldwide network of monitoring sites, granting a holistic perspective of the website's functionality across various regions. Create a distributed monitoring network utilizing both simulated and real user monitoring from a multitude of locations and devices, delivering multi-site response time charts and device-specific analysis to guarantee seamless global performance.

6. Performance and speed issues

In the fast-paced modern world today, website users have high expectations for speedy loading times and a flawless browsing experience. Unfortunately, performance hiccups such as sluggish loading speeds, broken links, and pesky errors can easily dampen their satisfaction and drive them away from the site. These pesky problems can stem from a variety of sources, such as overwhelming traffic, outdated technology, or subpar coding. Not only do slow load times and unresponsiveness hinder user experience, but they also negatively impact SEO rankings, yet they are often overlooked in monitoring efforts.

Solution: Gain in-depth understanding of load times, time to first byte, and core web vitals (LCP, FID, CLS) with comprehensive metrics. This includes detailed pagespeed insights to guide your website improvement strategy. By combining synthetic and real user monitoring, you can pinpoint bottlenecks and effortlessly enhance multimedia elements (such as image compression). Plus, consistent performance monitoring allows for early detection and resolution of any potential speed or functionality hindrances, guaranteeing a seamless and effective user journey.

7. Content management

Keeping websites current and relevant is a never-ending task, making website monitoring a daunting challenge. Content management requires meticulous attention to detail to ensure that all information is accurate, timely, and error-free. This can be a laborious and monotonous endeavor, especially for websites with a vast array of content.

Solution: By implementing a content management system (CMS), website monitoring becomes a breeze. With a CMS, website owners can effortlessly edit and publish content, while also enjoying features like version tracking and content scheduling. This not only frees up valuable time, but also guarantees that the website's content remains current and engaging.

8. Mobile responsiveness

As the use of mobile devices continues to rise, it has become crucial for websites to be optimized for mobile viewing. Yet, guaranteeing a website's mobile-responsiveness can prove to be a daunting task for website monitoring. While a website may appear flawless and operate seamlessly on a desktop, it may encounter difficulties when accessed on a mobile device.

Solution: Consistently checking a website's mobile adaptability is important to guarantee a flawless user journey on all gadgets. This can be accomplished using tools that mimic various screen dimensions and resolutions, enabling website owners to pinpoint and resolve any potential problems.

Overcome your website monitoring challenges now!

Uncover the full potential of ManageEngine Applications Manager, an all-inclusive website monitoring tool designed to effectively cater to your monitoring needs. With its advanced features, this software provides a comprehensive overview of your website's performance, whether through simulated or real-time monitoring.

In addition to proactive website monitoring, gain valuable insights into application performance, infrastructure health, and cloud performance, all within a single platform. Detect and resolve issues swiftly, automate tasks, and guarantee a seamless user experience. Request a personalized demo or take advantage of our 30-day free trial to fully harness the capabilities of our website monitoring solution and ensure utmost satisfaction and loyalty from your customers.

Azure database monitoring: Choosing the right tool in 2025

Sujitha Paduchuri — Fri, 23 May 2025 07:09:54 +0000

Azure databases play a major role in running cloud-native applications seamlessly by offering scalability, high availability, and easy management. But ensuring uninterrupted database operations needs real-time performance monitoring and code-deep insights.
Here’s what to consider when choosing an Azure database monitoring solution in 2025.

Why native monitoring doesn’t cut it:

Azure provides built-in tools like Azure Monitor, SQL Insights, and Log Analytics to monitor cloud services. But these native-cloud monitoring solutions come with certain limitations like:

Multiple interfaces: Admins will have to switch through different tools to monitor interconnected services.
Manual correlation: Troubleshooting requires manual performance analysis to map performance issues across interdependent services.
Complex setup: Some monitoring solutions might require additional integrations or third party deployments or KQL knowledge for full functionality.
Limited scope: Azure-native monitoring solutions cater to Azure-only environments, providing limited visibility into hybrid or multi-cloud environments.

This is why most organizations opt for dedicated cloud monitoring solutions that offer centralized visibility, smart root-cause analysis, and extensive cloud support.

What to look for in an Azure database monitoring tool?

Real-time monitoring:

Monitor uptime, memory usage, disk I/O, and network traffic in real time to identify potential issues before things go out of hand. Periodic performance analysis helps with trend analysis, capacity planning, and optimizing resource allocation.

Database-specific metric tracking:

Your Azure database monitoring solution should be able to monitor KPIs unique to each database engine; like SQL Server, PostgreSQL, MongoDB, MySQL, MariaDB, Cosmos DB, etc.

Key metrics include:

Replication lag: High replication lag can lead to stale reads, impacting application performance and availability.
Request rate and throughput: These metrics help assess database load and ensure it can handle user demand without bottlenecks.
Deadlocks and blocked sessions: Deadlocks occur when concurrent transactions compete for the same resources, leading to transaction failures or delays. Monitoring deadlocks and blocked sessions helps you optimize query performance and avoid app crashes.
Query execution and wait time: Monitoring query performance, status, and wait time is important for identifying slow queries and optimizing database performance.

Smart alerting and anomaly detection:

Make sure that your database monitoring solution offers modern and proactive monitoring features. This helps you stay ahead of performance issues and speed up issue resolution. You should look for:

Configurable severity-based alerts: Severity-based alerts classify incidents and prioritize critical issues. This reduces alert noise and helps teams understand the urgency of incident resolution.
Automated responses and ticket assignment: Automating escalations and triggering responsive actions saves time and improves mean time to resolution. This enhances quicker issue fixes and seamless database operations.
AI/ML-driven anomaly detection: Leveraging AI and ML to identify performance anomalies help you understand the peak load times, correlate KPIs across multiple cloud deployments and fix potential issues before they can lead to operational challenges in Azure cloud.

Backup and Recovery monitoring:

Ensure that the tool offers monitoring services to track the health of Azure backup and recovery services. Ensure backup readiness and avoid data loss during outages or failures by keeping an eye on RPO and RTO.

Support for hybrid and multi-cloud environments:

Check if your monitoring tool provides visibility across on-premises, Azure, AWS, Google, Oracle, and other cloud platforms that constitute your cloud environment. Centralized monitoring helps you correlate data across environments and streamline performance analysis efficiently.

Cost and scalability:

Choose a tool that can scale with your infrastructure and offers transparent pricing. Optimize cloud costs by avoiding renewal for licenses you don’t need.

ManageEngine Applications Manager is one such tool that offers complete visibility into your Azure databases. It provides monitoring support for Azure database services like Azure SQL, PostgreSQL, MySQL, MariaDB, and Cosmos DB. With extensive monitoring support for over 150 technologies, it centralizes infrastructure, cloud, and user experience monitoring. Download a 30-day free trial or book a demo to explore its full capabilities.

DEV Community: ManageEngine Applications Manager

Container monitoring just got broader: Docker Swarm and Podman support is here

Docker Swarm monitoring: Visibility from cluster to container

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Monitoring coverage that keeps up with how you build

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PostgreSQL monitoring: Best practices and essential performance metrics

Essential metrics for PostgreSQL monitoring

1. Transaction and query details

2. Database connection health

3. Lock and buffer statistics

4. Index and table scan details

5. Replication metrics

Top best practices for PostgreSQL monitoring

Proactive PostgreSQL monitoring with Applications Manager

Effective strategies for Oracle database performance monitoring

Track resource consumption and sessions

Identify slow queries

Resolve issues at the root cause

Analyze trends for future planning

ManageEngine Applications Manager: How it helps

Beyond the dashboard: Decoding the APM, RUM, and DEM trinity

The restaurant analogy

1. APM: Watching the backend

2. RUM: The reality check

3. DEM: The full journey

Why one view is not enough

From watching systems to fixing experiences

Unifying the trinity: How Applications Manager closes the gap

Navigating the chaos: How to tame Kubernetes Monitoring challenges

Essential best practices for real user monitoring (RUM)

1. Establish concrete goals aligned with business objectives

2. Focus on the metrics that matter

3. Monitor critical user journeys

4. Track performance across diverse platforms

5. Observe end-to-end user interactions

6. Integrate RUM with your observability ecosystem

7. Define baselines and service standards

8. Turn insights into action

9. Continuously refine your approach

Boost your RUM strategy with ease!

Solving container monitoring challenges with a smarter approach

Beyond the basics: A practical guide to JMX monitoring for Java applications

How JMX monitoring gives you deeper visibility

Why JMX monitoring is more than just technical data

Typical challenges in JMX monitoring

KPIs to track in JMX monitoring

Best practices for proactive JMX monitoring

Start your JMX monitoring journey with ease!

Ready to see how it works?

Boost website performance with real user monitoring

What is real user monitoring?

Why should you care about RUM?

Key features developers should look for in a RUM tool

Real-time performance monitoring

Geo-specific insights

Slow transaction analysis

Session-level tracking

Platform/browser/device analysis

JavaScript error reporting

How RUM works

Challenges in RUM

RUM in action: What you can do today

Why choose ManageEngine Applications Manager for RUM?

Unified monitoring across frontend and backend

Session-level insights with drill-down

Geo-distributed performance heat maps

Multi-device and cross-browser support

JavaScript error detection with rich diagnostics

Intuitive dashboards and custom reports

Built-in alerting and integration

5 key MySQL metrics every DBA should track

1. Query execution time

2. Connection utilization

3. Replication lag

4. InnoDB buffer pool usage

5. Lock and transaction metrics

Turning metrics into action

Challenges in website monitoring

1. Downtime and outages