Availability


Application design
  • Avoid any single point of failure. All components, services, resources, and compute instances should be deployed as multiple instances to prevent a single point of failure from affecting availability. This includes authentication mechanisms. Design the application to be configurable to use multiple instances, and to automatically detect failures and redirect requests to non-failed instances where the platform does not do this automatically.
  • Decompose workload per different service-level agreement. If a service is composed of critical and less-critical workloads, manage them differently and specify the service features and number of instances to meet their availability requirements.
  • Minimize and understand service dependencies. Minimize the number of different services used where possible, and ensure you understand all of the feature and service dependencies that exist in the system. This includes the nature of these dependencies, and the impact of failure or reduced performance in each one on the overall application. Microsoft guarantees at least 99.9 percent availability for most services, but this means that every additional service an application relies on potentially reduces the overall availability SLA of your system by 0.1 percent.
  • Design tasks and messages to be idempotent (safely repeatable) where possible, so that duplicated requests will not cause problems. For example, a service can act as a consumer that handles messages sent as requests by other parts of the system that act as producers. If the consumer fails after processing the message, but before acknowledging that it has been processed, a producer might submit a repeat request which could be handled by another instance of the consumer. For this reason, consumers and the operations they carry out should be idempotent so that repeating a previously executed operation does not render the results invalid. This may mean detecting duplicated messages, or ensuring consistency by using an optimistic approach to handling conflicts.
  • Use a message broker that implements high availability for critical transactions. Many scenarios for initiating tasks or accessing remote services use messaging to pass instructions between the application and the target service. For best performance, the application should be able to send the message and then return to process more requests, without needing to wait for a reply. To guarantee delivery of messages, the messaging system should provide high availability. Azure Service Bus message queues implementat least once semantics. This means that each message posted to a queue will not be lost, although duplicate copies may be delivered under certain circumstances. If message processing is idempotent (see the previous item), repeated delivery should not be a problem.
  • Design applications to gracefully degrade when reaching resource limits, and take appropriate action to minimize the impact for the user. In some cases, the load on the application may exceed the capacity of one or more parts, causing reduced availability and failed connections. Scaling can help to alleviate this, but it may reach a limit imposed by other factors, such as resource availability or cost. Design the application so that, in this situation, it can automatically degrade gracefully. For example, in an ecommerce system, if the order-processing subsystem is under strain (or has even failed completely), it can be temporarily disabled while allowing other functionality (such as browsing the product catalog) to continue. It might be appropriate to postpone requests to a failing subsystem, for example still enabling customers to submit orders but saving them for later processing, when the orders subsystem is available again.
  • Gracefully handle rapid burst events. Most applications need to handle varying workloads over time, such as peaks first thing in the morning in a business application or when a new product is released in an ecommerce site. Auto-scaling can help to handle the load, but it may take some time for additional instances to come online and handle requests. Prevent sudden and unexpected bursts of activity from overwhelming the application: design it to queue requests to the services it uses and degrade gracefully when queues are near to full capacity. Ensure that there is sufficient performance and capacity available under non-burst conditions to drain the queues and handle outstanding requests.
Deployment and maintenance
  • Deploy multiple instances of roles for each service. Microsoft makes availability guarantees for services that you create and deploy, but these guarantees are only valid if you deploy at least two instances of each role in the service. This enables one role to be unavailable while the other remains active. This is especially important if you need to deploy updates to a live system without interrupting clients’ activities; instances can be taken down and upgraded individually while the others continue online.
  • Host applications in multiple datacenters. Although extremely unlikely, it is possible for an entire datacenter to go offline through an event such as a natural disaster or Internet failure. Vital business applications should be hosted in more than one datacenter to provide maximum availability. This can also reduce latency for local users, and provide additional opportunities for flexibility when updating applications.
  • Automate and test deployment and maintenance tasks. Distributed applications consist of multiple parts that must work together. Deployment should therefore be automated, using tested and proven mechanisms such as scripts and deployment applications. These can update and validate configuration, and automate the deployment process. Automated techniques should also be used to perform updates of all or parts of applications. It is vital to test all of these processes fully to ensure that errors do not cause additional downtime. All deployment tools must have suitable security restrictions to protect the deployed application; define and enforce deployment policies carefully and minimize the need for human intervention.
  • Consider using staging and production features of the platform where these are available. For example, using Azure Cloud Services staging and production environments allows applications to be switched from one to another instantly through a virtual IP address swap (VIP Swap). However, if you prefer to stage on-premises, or deploy different versions of the application concurrently and gradually migrate users, you may not be able to use a VIP Swap operation.
  • Apply configuration changes without recycling the instance when possible. In many cases, the configuration settings for an Azure application or service can be changed without requiring the role to be restarted. Role expose events that can be handled to detect configuration changes and apply them to components within the application. However, some changes to the core platform settings do require a role to be restarted. When building components and services, maximize availability and minimize downtime by designing them to accept changes to configuration settings without requiring the application as a whole to be restarted.
  • Use upgrade domains for zero downtime during updates. Azure compute units such as web and worker roles are allocated to upgrade domains. Upgrade domains group role instances together so that, when a rolling update takes place, each role in the upgrade domain is stopped, updated, and restarted in turn. This minimizes the impact on application availability. You can specify how many upgrade domains should be created for a service when the service is deployed.
  • Configure availability sets for Azure virtual machines. Placing two or more virtual machines in the same availability set guarantees that these virtual machines will not be deployed to the same fault domain. To maximize availability, you should create multiple instances of each critical virtual machine used by your system and place these instances in the same availability set. If you are running multiple virtual machines that serve different purposes, create an availability set for each virtual machine. Add instances of each virtual machine to each availability set. For example, if you have created separate virtual machines to act as a web server and a reporting server, create an availability set for the web server and another availability set for the reporting server. Add instances of the web server virtual machine to the web server availability set, and add instances of the reporting server virtual machine to the reporting server availability set.