DEV Community: Okereke Uneke Enyi

Definition of Terms

Okereke Uneke Enyi — Sun, 29 Sep 2024 22:58:49 +0000

What is Virtualization

Virtualization is the process of creating a virtual (rather than physical) version of something, such as an operating system, a server, a storage device, or network resources. It allows for the abstraction of computer resources, enabling multiple operating systems and applications to run on a single physical hardware system by creating isolated environments called virtual machines (VMs).

Key Types of Virtualization
Server Virtualization: Dividing a physical server into multiple virtual servers, each of which can run its own operating system and applications.
Desktop Virtualization: Hosting desktop environments on a centralized server and delivering them to end users on various devices.
Network Virtualization: Combining physical network resources to create multiple, isolated virtual networks.
Storage Virtualization: Pooling multiple physical storage devices into a single storage resource that can be managed from a central console.
Application Virtualization: Running applications in a virtual environment, isolated from the underlying OS.

What is Scalability
Scalability in cloud computing refers to the ability of a system to handle an increasing amount of work or its potential to accommodate growth by adding resources. It ensures that a cloud infrastructure can adjust its capacity to meet changing demand, either by increasing or decreasing computing resources like CPU, memory, storage, and bandwidth.

Types of Scalability:
Vertical Scalability (Scaling Up):

Involves adding more power (CPU, RAM) to an existing cloud server.
Example: Upgrading a VM from 4 GB to 16 GB of RAM.
Horizontal Scalability (Scaling Out):

Involves adding more servers or instances to distribute the workload.
Example: Increasing the number of servers handling an application to manage a growing number of users.
Auto-scaling:

Automatic adjustment of resources based on real-time demand.

What is Ajility
Agility in the context of cloud computing refers to the ability to quickly and efficiently respond to changes in demand, market conditions, or business requirements. It is the ease with which cloud services allow organizations to adapt to new challenges, launch new products, or scale infrastructure in response to evolving needs.

Key Aspects of Agility in Cloud Computing:
Rapid Deployment:

Cloud services allow businesses to deploy applications and services quickly, without the long setup times associated with traditional infrastructure.
On-Demand Resource Availability:

Businesses can access additional resources (compute, storage, etc.) immediately when needed, ensuring that IT systems keep up with changing workloads.
Innovation Enablement:

Cloud environments support innovation by providing developers with the tools, environments, and platforms to experiment, develop, and deploy solutions faster than traditional IT models.
Flexibility:

Cloud infrastructure allows companies to pivot, test new ideas, or scale back services with ease. This flexibility enables faster time-to-market for new applications or services.
Cost Efficiency:

The pay-as-you-go model ensures that organizations can quickly expand their capacity without long-term hardware investments, helping them stay agile without upfront costs.
Global Reach:

Cloud platforms often provide global data center coverage, allowing businesses to scale and deliver services to customers around the world with minimal latency or additional setup.

What is High Availability

High Availability (HA) in cloud computing refers to the design and implementation of systems that aim to ensure a high level of operational performance, typically by minimizing downtime and service interruptions. HA systems are designed to remain accessible and functional even in the event of hardware failures, network issues, or other disruptions, providing continuous service to users.

Key Components of High Availability:
**Redundancy:**

Multiple instances of critical system components (servers, databases, network connections) are maintained. If one fails, another immediately takes over, ensuring continuity.
Example: Having multiple copies of a server in different geographic regions.
Failover:

A backup system automatically takes over in case of failure of the primary system.
Example: If a server crashes, a standby server seamlessly takes over without user impact.
Load Balancing:

Distributes incoming traffic across multiple servers to avoid overloading any single resource and to ensure continuous service if one server fails.
Example: Cloud load balancers distribute requests among different virtual machines.
Data Replication:

Critical data is replicated across different servers or data centers to ensure data is always available, even if one location becomes unavailable.
Example: Replicating database instances across multiple cloud regions.
Monitoring and Self-Healing:

Continuous monitoring of system health allows early detection of issues, while self-healing mechanisms automatically correct certain issues.
Example: Auto-rebooting a virtual machine when a fault is detected.
Geographic Distribution:

Cloud systems often distribute resources across different geographic locations (availability zones or regions) to ensure uptime even in the case of localized failures (e.g., natural disasters or power outages).

What is Fault Tolerance
Fault Tolerance in cloud computing refers to the ability of a system to continue operating correctly even in the presence of hardware or software failures. A fault-tolerant system is designed to detect, manage, and recover from faults, ensuring minimal to no disruption in services or applications.

Key Concepts of Fault Tolerance:
Redundancy:

Critical components of the system (such as servers, networks, or databases) are duplicated or mirrored, so if one component fails, another can take over immediately without impacting the service.
Example: If one server in a cloud environment fails, another identical server takes over seamlessly.
Failover Mechanisms:

When a fault is detected, the system automatically switches to a redundant component, ensuring that the failure is transparent to users.
Example: In a multi-cloud setup, if one provider experiences downtime, traffic is redirected to another cloud provider.
Replication:

Data and processes are replicated across different machines, servers, or data centers. This ensures that if one instance fails, a copy of the data or process is still available elsewhere.
Example: Cloud databases like Amazon RDS often offer automatic replication across multiple availability zones for fault tolerance.
Error Detection and Correction:

The system can detect faults or errors and automatically correct them. This might involve restarting failed processes, fixing corrupted data, or rerouting tasks.
Example: Cloud platforms often monitor their services and perform self-healing actions like restarting instances or containers when errors occur.
Geographic Distribution:

Geographic Distribution:
Spreading systems across different geographical areas (multi-region setups) ensures that local disasters don’t disrupt the entire service.
Azure Availability Zones or AWS Availability Zones provide this capability.

Monitoring and Alerting:
Constant monitoring of the health of systems allows for quick responses to issues before they escalate.

Automated Backups and Recovery:
Regularly backing up data and systems, and ensuring there is a robust recovery plan in place.

What is Global Reach

Global Reach in cloud computing refers to the ability of cloud platforms to provide services and infrastructure that are accessible from virtually any location around the world. This concept is integral for businesses operating on a global scale, as it ensures that their services can serve users in different regions efficiently, with high availability and low latency.

*Key Features of Global Reach in the Cloud:*

Geographically Distributed Data Centers:

Major cloud providers, such as Microsoft Azure, Amazon Web Services (AWS), and Google Cloud, have data centers located across the globe, grouped into regions and availability zones. This allows businesses to deploy their applications closer to their users, reducing latency and improving performance.
Example: Azure has regions in the U.S., Europe, Asia-Pacific, Middle East, Africa, and more, providing coverage to almost any corner of the world.
Content Delivery Networks (CDN):

CDNs cache content in data centers across the globe, enabling fast delivery of data to users regardless of their physical location. They help distribute static and dynamic content with minimal delay.
Services like Azure CDN, Amazon CloudFront, and Google Cloud CDN ensure that global users experience quick access to web resources, improving application performance.
Multi-Region Deployments:

Global reach is enhanced when applications are deployed in multiple regions, making the system more resilient and reducing latency for end users in different geographical locations.
In AWS, for example, you can deploy an application across regions like the U.S. East, Europe, and Asia to ensure proximity to users.
Global Load Balancing:

Global load balancers distribute incoming traffic across various regions and data centers. This ensures that users are routed to the nearest, healthiest data center, optimizing performance and avoiding bottlenecks.
Azure Traffic Manager or AWS Route 53 are examples of global load balancers that allow businesses to manage global traffic efficiently.
Global Networking Solutions:

Cloud providers offer global virtual private networks (VPNs) or private connections like Azure ExpressRoute and AWS Direct Connect, enabling organizations to securely connect their on-premises infrastructure with cloud environments worldwide.
Disaster Recovery and Backup Across Regions:

Global reach ensures that cloud services can offer disaster recovery capabilities by replicating data across different regions. If one region experiences downtime due to natural disasters or other issues, another region can take over to provide seamless service continuity.
Azure Site Recovery, AWS Global Accelerator, and Google Cloud Interconnect are examples of services designed for cross-region disaster recovery and failover.
Global Databases and Data Replication:

Cloud platforms offer globally distributed databases that automatically replicate data across multiple regions. This ensures data consistency and availability, even in the event of region-level outages.
Examples include Azure Cosmos DB, Amazon DynamoDB Global Tables, and Google Cloud Spanner, all designed to provide fast, global access to data.
Multi-National Compliance:

Global reach also involves meeting different regulatory and compliance requirements across regions. Cloud providers often have certifications and compliance capabilities for specific countries or regions, allowing businesses to comply with local data privacy and security laws (e.g., GDPR in Europe).

What is the difference between Elasticity and Scalability

Elasticity and Scalability are both key concepts in cloud computing, often used to describe how a system handles changes in demand. However, they refer to different aspects of managing resources in a cloud environment.

Scalability
Scalability refers to the ability of a system to handle an increasing amount of workload by adding resources. It is generally planned for long-term growth. Scalability is about increasing the capacity of the infrastructure to accommodate larger loads, either by upgrading the existing resources or adding more resources.

Types of Scalability:
Vertical Scaling (Scaling Up):

Increases the capacity of a single resource, such as adding more CPU, RAM, or storage to a server or virtual machine.
Example: Upgrading from a smaller Azure VM instance to a larger one.
Horizontal Scaling (Scaling Out):

Adds more instances of resources (e.g., adding more servers or VMs) to distribute the workload across multiple machines.
Example: Adding more VMs to handle increased traffic in an Azure App Service.
Characteristics of Scalability:
Proactive: Typically involves adding resources in anticipation of increased demand.
Capacity Planning: Scalability is often related to planned growth, where you know that more resources will be needed as the user base or workload increases over time.
Example of Scalability:
A company starts with one virtual machine (VM) running its application. As the number of users increases, it adds more VMs to distribute the load across multiple machines (horizontal scaling).
Elasticity
Elasticity refers to the system's ability to automatically increase or decrease resources based on real-time demand, making it more dynamic. Elasticity is commonly associated with pay-as-you-go cloud services, where resources are adjusted in response to varying workloads, often on a minute-by-minute or hour-by-hour basis.

Characteristics of Elasticity:
Reactive: Resources are adjusted in real-time to match current demand.
Auto-Scaling: Resources are added or removed automatically without manual intervention.
Cost Efficiency: Only the resources needed at a given time are used, minimizing waste.
Example of Elasticity:
An e-commerce website experiences high traffic during Black Friday. The cloud infrastructure automatically spins up additional servers to handle the increased load, and when the traffic returns to normal, the extra servers are automatically shut down, reducing the cost.

Key Differences Between Elasticity and Scalability:

Creation of Resource Group in MS Azure

Okereke Uneke Enyi — Sun, 16 Jun 2024 22:24:54 +0000

Steps to Create a Resource Group on Azure

Login to MS Azure
Search for resource group

Then select resource group.

Click on + Create

The following create box comes up.

Type the name of your resource group and select your region, then click on review and create

Click on create to complete the creation of your resource group.

Click on Go to resource group to lunch your resource group.

Short notes on the following Concepts

Okereke Uneke Enyi — Sun, 16 Jun 2024 21:45:22 +0000

What is Virtualization?
Scalability
Agility
High Availability
Fault Tolerant
Global Reach
What is the difference between Elasticity and Scalability

1. What is virtualization?

This concept is related to creating or spooling virtualized systems with any of the following features: operating systems, servers, storage devices, or networks, rather than having these digital resources customized to physical hardware.

Virtualization technology enables multiple operating systems and applications to run simultaneously and independently on a single physical machine. This allows multiple virtual machines (VMs) to share the same CPU, memory, storage, and other resources while avoiding resource conflict.

Virtualization allows the creation of virtual environments to pool resources and reduce IT infrastructure costs whilst increasing access, manageability, and efficiency of resources and system resources to optimize service delivery and enhance performance. Hence, virtualization allows organizations to deploy and use multiple applications, system snapshots and efficiently optimize resource utilization, data storage and accessibility with less complexity, altogether improving scalability and more efficient data processing quicker.

Some of the potential benefits of virtualization include better resource management, cost savings on hardware, increased flexibility, virtual machine communication, isolation, easy moving apps, Load Balancing, less downtime offered by saved server occurrences.

2. What is scalability in cloud computing?

In cloud computing, scalability is the capacity of an infrastructure in the cloud to modify its resources in response to fluctuating demands. This implies that you will not need to wait for complicated hardware upgrades or complicated processes to expand or decrease resources like processor power, storage, or memory on the fly.

Below is a summary of the main elements of cloud scalability:

Dynamic Adjustment: You can scale your computing power to match your workload by adjusting cloud resources up or down as needed.
Cost-effectiveness: You do not have to spend money on extra hardware that sits around when demand is low because you only pay for the resources you utilize.
Flexibility: Cloud scalability makes it simple to adapt to unplanned growth, seasonal demands, or traffic spikes, ensuring that your applications can manage the strain.

Cloud scaling primarily comes in two flavors:

Increasing or decreasing a single server instance's resources, like RAM or CPU, is known as vertical scaling (scaling up/down).
Horizontal scaling, often known as scaling out, is the process of dividing the workload over several computers by adding or deleting complete server instances.

3. What is Agility in cloud computing?

In cloud computing, agility is the capacity of an enterprise to create, test, and implement applications in a cloud environment rapidly. It is basically the flexibility and nimbleness that come from using cloud resources.

Consider this: installing and managing IT infrastructure can be a laborious and slow procedure in a traditional on-premises environment. These obstacles are eliminated by cloud computing by providing:

On-Demand Resources: Cloud service providers provide an enormous pool of instantaneously provisionable and de-provisionable computer resources, such as memory, processing power, and storage. This removes the requirement for protracted cycles in hardware acquisition.
Automated Processes: A lot of cloud platforms come with capabilities for scaling, configuration management, and deployment automation. This allows IT personnel to concentrate on more advanced duties.
Elasticity: The ability to quickly scale up or down cloud resources in response to changing demand. This frees companies from worrying about infrastructure constraints so they may test new apps or handle spikes in demand.
The following are some advantages of cloud agility:

Faster Time to Market: Companies get a competitive edge by being able to provide new concepts and services to consumers more quickly.
Enhanced Innovation: A culture of experimentation and creativity is fostered by the cloud's ease of development and testing.
Lower Costs: Companies do not have to pay for hardware that is not being used because they only pay for the resources they use.

4. Explain High Availability

In cloud computing, high availability (HA) describes a system's capacity to continue functioning and being available for prolonged periods of time, even in the event of hardware or software problems. It is essential for applications that are mission-critical and cannot withstand downtime, since any disruption might result in major financial loss or disruptions to services.

An examination of high availability's operation is provided below:

Redundancy: Multiple servers, storage devices, and network connections are examples of redundant resources that are used by HA systems. There is less downtime when a component fails since another one takes over smoothly.
HA designs are built with automated failover in mind. This implies that, in the case of a failure, the system will identify the problem and, with the least amount of disturbance to continuing activities, will immediately transition to a backup resource.
Minimal Downtime: Achieving nearly constant uptime, sometimes expressed in "nines," is the aim of HA. For example, a system with three nines, or 99.99% uptime, would only have 53 minutes of outage a year.

To ensure high availability, cloud providers provide a range of tools and services, such as:

Virtual machines (VMs): You can set up and launch VMs on several hosts using cloud platforms. The program can be swiftly moved to another VM in case one fails.
By distributing incoming traffic among several servers, load balancing keeps any one server from getting overworked and possibly failing.
Disaster Recovery (DR): This extends beyond hardware malfunctions and entails data and application replication between geographically dispersed sites. This guarantees that your applications can be promptly restored in the event of a widespread outage or natural disaster.

High availability is a critical consideration for businesses that rely on continuous operation and minimal downtime. By implementing HA strategies in the cloud, you can ensure your applications are always up and running, fostering better customer experience and business continuity.

5. Fault Tolerance?

In cloud computing, fault tolerance is all about designing a system that can continue to function normally even in the event that certain components break or malfunction. Similar to having an infrastructure backup plan, it guarantees that your apps continue to function even in the event of technical difficulties.

The following describes how fault tolerance functions in a cloud environment:

Continuous Operation: The fundamental idea is to keep services running even in the event of software or hardware malfunctions. This is particularly crucial for vital applications since downtime can be expensive.
Redundancy is Crucial: Redundancy in cloud fault tolerance refers to the presence of backups for critical components. This can entail redundant network connections, additional servers with mirrored data, or extra storage devices.
Automatic Failover: Ideally, the system should automatically transition to a backup resource in the event of a fault. This reduces downtime and guarantees a seamless user transition.

To accomplish fault tolerance in the cloud, various methods are employed:

Replication is the process of making duplicates of your apps and data on different servers. Everything can continue to function even if one server dies because the other one can take over.
By distributing workloads among several servers, load balancing keeps any one server from getting overworked and possibly failing.
Self-Healing Mechanisms: A few cloud platforms have automated mechanisms that are able to identify and resolve issues without the need for human assistance. This strengthens the robustness of the system even further.

Fault tolerance has many advantages in cloud computing.

Reduced Downtime: Guards against interruptions and failures in service, guaranteeing that users can always access your apps.
Enhances the overall dependability of your cloud infrastructure by reducing the likelihood of failures.
Improved Business Continuity: Reduces possible losses by assisting companies in continuing to operate even in the face of unanticipated events.
You may create a more durable and resilient system and guarantee that your users can access and rely on your applications by implementing fault tolerance techniques into your cloud environment.

6. Global Reach

The ability of cloud providers to make their infrastructure and services available over a wide geographic area is referred to as "global reach" in the context of cloud computing.

Businesses can benefit from this in a number of ways.

Market Expansion: Cloud computing enables companies to effortlessly enter new international markets. Users may access data and apps with minimal latency, no matter where they are physically situated, thanks to data centers that are positioned strategically throughout multiple locations.
Global Scalability: Cloud resources are easily scalable, allowing them to adjust to changing demands in many locations. This eliminates the need for companies to develop and maintain physical infrastructure in each location, enabling them to respond to spikes in user base or traffic in particular areas.
Lower Costs: Companies save money by not having to build up and maintain many data centers, which would have required a large upfront investment and continuous upkeep. The infrastructure is handled by cloud providers, who provide a pay-as-you-go model that may be scaled to meet your demands.
Enhanced Compliance: Data centers that meet different local data privacy laws are provided by cloud providers. This makes it easier for companies to comply with local rules and regulations when storing and processing data, which is beneficial for worldwide operations.

Major cloud providers use their worldwide reach in the following ways:

Distributed Data Centers: A global network of data centers has been developed by cloud behemoths such as Google Cloud Platform (GCP), Microsoft Azure, and Amazon Web Services (AWS). This guarantees that users, wherever they may be, may access resources with minimal latency.
material Delivery Networks (CDNs): By distributing material among geographically separated servers, these networks allow users worldwide to load pages more quickly.
Regional Availability Zones: Cloud companies frequently provide many availability zones, or geographically separated data centers, within each region. In the event of an outage, this offers redundancy and fault tolerance.

For companies of all sizes, having a global presence is revolutionary. It gives companies the ability to take on global competition, attract new clients, and maximize the performance and financial efficiency of their cloud deployments.

7. What is the difference between Elasticity and Scalability

Cloud computing elasticity and scalability both cope with demand fluctuations, but they react differently and have different ideal conditions.

Below is a summary of the main distinctions:

Scalability

Focus: Scheduled resource modifications in response to projected increases or decreases in workload.
Action: Usually manual or based on pre-established limits. You can ask the cloud provider to release unused resources (scaling down) or request more resources (scaling up).
Timeline: Depending on the complexity and the procedure used by the cloud provider, scaling may take some time to implement.
Perfect for: Meeting demands for processing power, data storage, or a steady increase in the user base.
Example: A business expects the holidays to bring in a spike in internet sales. To manage the extra traffic, they might proactively scale up their server capacity in advance.

Elasticity

Focus: Real-time variations in demand are used to automatically adapt resources.
Action: Scaling automatically in accordance with preset criteria and triggers. The cloud system itself adjusts resource scaling up or down based on changes in workload.
Timeframe: Elasticity occurs in minutes or even seconds, far faster than deliberate scaling.
Perfect for: Managing sporadic variations in resource needs, workload surges, and erratic traffic spikes.
Example: A trending topic causes a rapid spike in visitors to a social networking app. Without the need for human intervention, elasticity automatically ramps up resources to maintain performance.

Here's a comparison:

Consider scalability like Lego construction. You have the freedom to design your structure and change the bricks (materials) as needed.
Similar to a stretched band is elasticity. Without the need to physically alter the band, it automatically adapts to varied tension (demand) levels.
To sum up, cloud computing offers both scalability and elasticity as beneficial advantages. Elasticity makes sure you can deal with unforeseen spikes in demand, while scalability helps you prepare for future expansion. To maximize both performance and cost-efficiency in your cloud environment, you should ideally combine the two.

Short notes on the following Concepts

Okereke Uneke Enyi — Sun, 16 Jun 2024 21:00:02 +0000

What is Virtualization?
Scalability
Agility
High Availability
Fault Tolerant
Global Reach
What is the difference between Elasticity and Scalability

1. What is virtualization?

2. What is scalability in cloud computing?

Below is a summary of the main elements of cloud scalability:

Cloud scaling primarily comes in two flavors:

3. What is Agility in cloud computing?

4. Explain High Availability

An examination of high availability's operation is provided below:

To ensure high availability, cloud providers provide a range of tools and services, such as:

5. Fault Tolerance?

The following describes how fault tolerance functions in a cloud environment:

To accomplish fault tolerance in the cloud, various methods are employed:

Fault tolerance has many advantages in cloud computing.

6. Global Reach

The ability of cloud providers to make their infrastructure and services available over a wide geographic area is referred to as "global reach" in the context of cloud computing.

Businesses can benefit from this in a number of ways.

Major cloud providers use their worldwide reach in the following ways:

7. What is the difference between Elasticity and Scalability

Cloud computing elasticity and scalability both cope with demand fluctuations, but they react differently and have different ideal conditions.

Below is a summary of the main distinctions:

Scalability

Elasticity

Here's a comparison:

Short notes on the following Concepts

Okereke Uneke Enyi — Sun, 16 Jun 2024 21:00:02 +0000

What is Virtualization?
Scalability
Agility
High Availability
Fault Tolerant
Global Reach
What is the difference between Elasticity and Scalability

1. What is virtualization?

2. What is scalability in cloud computing?

Below is a summary of the main elements of cloud scalability:

Cloud scaling primarily comes in two flavors:

3. What is Agility in cloud computing?

4. Explain High Availability

An examination of high availability's operation is provided below:

To ensure high availability, cloud providers provide a range of tools and services, such as:

5. Fault Tolerance?

The following describes how fault tolerance functions in a cloud environment:

To accomplish fault tolerance in the cloud, various methods are employed:

Fault tolerance has many advantages in cloud computing.

6. Global Reach

The ability of cloud providers to make their infrastructure and services available over a wide geographic area is referred to as "global reach" in the context of cloud computing.

Businesses can benefit from this in a number of ways.

Major cloud providers use their worldwide reach in the following ways:

7. What is the difference between Elasticity and Scalability

Cloud computing elasticity and scalability both cope with demand fluctuations, but they react differently and have different ideal conditions.

Below is a summary of the main distinctions:

Scalability

Elasticity

Here's a comparison:

Providing storage for the IT department testing and training

Okereke Uneke Enyi — Wed, 13 Dec 2023 06:21:37 +0000

What is Azure Storage?

Azure Storage provides highly accessible, massively scalable, secure, and long-lasting cloud storage for a wide range of data items. It is Microsoft's cloud storage solution for many data storage scenarios.

How to Create a resource group and a storage account

STEPS

1. Create and deploy a resource group to hold all your project resources.

In the Azure portal, search for and select Resource groups

Select + Create

Give your resource group a name. For example, storagerg

Select a region. Use this region throughout the project

Select Review and create to validate the resource group.

Select Create to deploy the resource group

The newly created resource group is highlighted

2. Create and deploy a storage account to support testing and training.

In the Azure portal, search for and select Storage accounts

Select + Create
On the Basics tab, select your Resource group

Provide a Storage account name. The storage account name must be unique in Azure.

Set the Performance to Standard.

Select Review, and then Create.

Wait for the storage account to deploy and then Go to resource

Configure simple settings in the storage account

STEPS

1. **The data in this storage account doesn’t require high availability or durability. A lowest cost storage solution is desired
**

In your storage account, in the Data management section, select the Redundancy blade

Select Locally-redundant storage (LRS) in the Redundancy drop-down

Be sure to Save your changes

Refresh the page and notice the content only exists in the primary location

2. **The storage account should only accept requests from secure connections**

In the Settings section, select the Configuration blade

Ensure Secure transfer required is Enabled

3. Developers would like the storage account to use at least TLS version 1.2

In the Settings section, select the Configuration blade
Ensure the Minimal TLS version is set to Version 1.2.

4. Until the storage is needed again, disable requests to the storage account

In the Settings section, select the Configuration blade
Ensure Allow storage account key access is Disabled

Be sure to Save your changes

5. Ensure the storage account allows public access from all networks

In the Security + networking section, select the **Networking **blade
Ensure Public network access is set to Enabled from all networks
Be sure to Save your changes

Summary
Thank you for taking the time to read! I hope these curated step-by-step procedures to create Azure resources, storage accounts, and configuration prove to be incredibly valuable on your development journey. If you have any suggestions or tips, either about the resources posted here or other tools you find helpful, please share them in the comments below.