Azure High Availability: Basic Concepts

on Azure Data Factory, Microsoft, Microsoft Azure • April 27th, 2022 • Write for Hevo

Azure High Availability Featured Image | Hevo

Microsoft Azure is one of the largest private and public Cloud platforms in the world. It offers over 600 services used by IT professionals to build, deploy, and manage the applications. As of 2021, Azure has a 20% market share, with Amazon Web Services (AWS) at 31%, and Google Cloud Platform (GCP) sitting at 9%. However, you need to define, plan, and deploy applications accordingly in order to have increased high availability. This article will help you check all the boxes required for Azure High Availability.

High availability is an important feature of every mission-critical computing infrastructure. High availability ensures that the computing infrastructure continues to work even when certain components of the system fail. Microsoft Azure’s global infrastructure is designed to deliver the highest levels of redundancy and resiliency to its customers. Azure High Availability provides a software and networking solution to protect against Data Center failures. Let’s get started.

Table of Contents

What is High Availability?

In simple terms, high availability is all about keeping your systems alive in case anything goes wrong. High availability is the quality of computing infrastructure that allows it to function even in the event of components failure. This is very critical for systems that cannot tolerate interruption in service, and any downtime can result in financial loss.

One of the important principles of high availability in Azure or anywhere else is to eliminate all single points of failure. For instance, if you had 1 Web Server and if that Web Server goes down, your whole website will be unavailable. So, to prevent that, you would need to have multiple Web Servers working together to ensure that the site stays up even if a Web Server goes down.

Highly available systems assure a certain percentage of uptime, let’s say, a system with 99.9% uptime will be down only 0.1% of the time.

Azure Availability Zones

Azure infrastructure constitutes geographies, regions, and availability zones, which limit the blast radius of a failure. This in turn helps to limit the potential impact of failure on customer applications and data. Availability zones are basically unique physical locations within an Azure region. Each zone comprises one or more Data Centers with independent power, networking, and cooling. 

Availability zones within a region are physically separated from each other to contain the impact of zone failures on customer data and applications. Zone failures include events such as large-scale flooding, major storms, and other events that could disrupt site access, extended utility uptime, and the availability of resources.

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Azure High Availability Zone Architecture

The architecture of availability zones is such that if 1 zone is compromised, the other availability zones in the region support the services, capacity, and availability. Availability zones can propagate a solution across multiple zones within a region. This allows an application to continue functioning even when 1 zone fails. With availability zones, Azure offers a 99.99% Virtual Machine (VM) uptime service-level agreement (SLA). So, here, the services are not dependent on zones, and they protect your services and data from single points of failure by replicating them across availability zones.

Azure High Availability: Azure availability zones | Hevo Data
Image Source: www.docs.microsoft.com

Elements and Tech Components for Azure High Availability

The following are the basic elements of an Azure High Availability system:

  • Redundancy: This ensures that critical elements have an additional, redundant component that can take over in the event of failure without affecting system operations.
  • Monitoring: Monitoring is nothing but collecting data from a running system and detecting component failures.
  • Failover: Failover is one of the important principles of high availability. This basically refers to a mechanism that can automatically switch from the currently active component to a redundant component if the active component fails.

The following systems are commonly used technical components in Azure High Availability systems:

  • Data Backup and Recovery: Data Backup systems automatically back up data to a secondary location and recover it back to the source location. This system can be used to set up redundancy and failover.
  • Load Balancing: A Load Balancing system manages traffic by routing it across more than one system that can serve that traffic. The Load Balancer can detect when a target system fails and it then redirects the traffic to another available system. This system can be used to implement monitoring and failover.
Azure High Availability: Load Balancer | Hevo Data
Image Source: www.cloud.netapp.com
  • Clustering: A cluster contains several nodes that serve a similar purpose. These clusters are typically viewed as one unit by the users. In the event of a failure, each node in the cluster is capable of failover to another node. Users can create redundancy between cluster nodes by setting up replication within the cluster.
Azure High Availability: Clustering | Hevo Data
Image Source: www.cloud.netapp.com

Checklist to Ensure Azure High Availability

This section will outline a 5-step Azure high availability checklist that can help you get your requirements and architecture in place.

Define Availability Requirements

This step requires you to identify and discover the high availability of Cloud workloads and their usage patterns. You can then identify and define your availability metrics. Below is a list of metrics that you can consider in order to define your target Service Level Agreement (SLA) for each application workload.

  • Percentage of Uptime
  • Mean Time between Failures (MTBR)
  • Mean Time to Recovery (MTTR)
  • Recovery Time Objective (RTO)
  • Recovery Point Objective (RPO)

However, you can also consider Microsoft’s defined SLAs based on the Azure services that you’re using. In cases where you may require a higher SLA than that guaranteed by Microsoft, you can always set up redundant components with failover.

Plan your High Availability Architecture

This step requires you to identify the root cause of failures, types of failures, their effects, and safety measures. Well, if you’re coming from a Mechanical background, you must be able to relate to this, right? Let’s discuss this in detail.

  • Failure Mode Analysis (FMA): Failure Mode Analysis (FMA) is a step-by-step process of identifying all possible types of failures in a design, a product, or service. It is a common tool for process analysis. As the name suggests, “failure modes” refer to the various ways or modes in which a product can fail. Failures could be any errors or flaws that affect the customer.
    Here, you basically need to identify the modes of failure (potential or actual), the consequences of each type of failure, and recovery strategies. FMA further helps you in identifying the degree of redundancy required for the components. You can eliminate single points of failure and use Load Balancer to distribute requests across redundant components.
  • Consider Costs: Well, everything comes at a cost. Each redundant layer effectively doubles your Cloud costs as it requires additional storage, networking, and bandwidth. Make sure you have mandatory licenses, enough resources, and a robust infrastructure to support the additional redundant instances.
  • Replicate Data: Data Replication is an important step here. You must ensure that the application data is replicated in such a way that it complements your redundancy strategy along with your RTO and RPO. Replicating fresh data to the redundant component prior to failure is essential if you wish to recover it.
  • Documentation: Documenting everything is a good practice. Document the steps required for failover and recovery in a short and precise manner. Instructions should be to the point and clear enough for emergency usage.

End-to-End Testing

Testing is an important part of any methodology. It is essential to test a product or system under realistic conditions in order to ensure reliability. You can use methods like Fault Injection to test failover and failback in different failure scenarios. Below mentioned is a list of additional testing measures that you can implement for Azure High Availability.

  • Disaster Recovery Exercises: This includes planned or unplanned experiments to test the readiness and credibility of the teams. Here, systems go down and your team must act and operate according to the disaster recovery plan.
  • Test Health Probes: The Azure Load Balancer is a great component to detect component failure. It uses health probes to ensure that the components respond correctly in an event of failure. 
  • Test Monitoring Systems: This includes checking data from Monitoring Systems for accuracy on a regular basis to detect a failure in time.

Deploy Applications Consistently

  • Change in Configurations: While provisioning Azure VMs you need to deploy new application code and hence the configuration needs to be changed. This change in configuration can lead to failure at times. Hence, there is a need of having an automated and consistent deployment process to reduce the chances of errors and failures.
  • Availability in Release Process: New releases require updates and updates require downtime of critical components. It becomes necessary to design your release process in such a way that the critical services and components are not disrupted. You can implement the blue-green strategy to have multiple versions of your production environment available for use.
  • Rollback Plan: It is necessary to have a rollback process in place that can help you restore systems automatically. Automatic deployment of applications saves you from manual configuration changes.

Monitor Application Health

Detecting failures in time is critical to Azure High Availability.

  • Declining Health Metrics: Declining health metrics is a good way to identify potential failures. An early warning system can assess key indicators of application performance and alert operators whenever any fallacy is detected.
  • Logging and Auditing: Azure comes with extensive logging and auditing capabilities that use semantic and asynchronous logging, measure remote call statistics, and separate application logs from audit logs.
  • Subscription Limits: Azure services come with subscription limits and going beyond the allowable limits will result in failure. Hence, it is necessary to be aware of the storage capacity, compute, throughput, and other limitations of the Azure service you’re using.

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Benefits and Use Cases of Azure High Availability

  • High Resiliency and high availability: Azure’s availability zones ensure high availability and resiliency as a part of your disaster recovery and business continuity strategy. Its high-performance architecture comes with a built-in strategy and is highly flexible.
  • Protection against Infrastructure Disruptions: Azure High Availability helps in eliminating any single point of failure across a regional network design. It connects at least 3 physically distinct Data Centres placed strategically in each region, considering more than 30 risk factors and viability criteria. 
  • Data Replication: Synchronous Data Replication further helps in containing the impact of Data Center failures by maintaining a latency perimeter of fewer than 2 milliseconds between Azure availability zones.
  • Easy Migration: Azure High Availability allows you to migrate and deploy an n-tier app from on-premises to the Cloud.

Conclusion

As of 2021, Microsoft Azure is one of the largest Cloud computing platforms offering over 600 services and serving millions of applications and customers. Azure High Availability ensures that the computing infrastructure continues to function even when certain components of the system fail.

This article introduced you to Microsoft Azure and took you through various aspects of Azure High Availability. However, it’s easy to become lost in a blend of data from multiple sources. Imagine trying to make heads or tails of such data. This is where Hevo comes in.

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Share your experience of understanding Azure High Availability in the comments section below.

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