Design patterns and plan for developing high available azure applications

Design Patterns and Plan for developing High Available Azure

Applications

Himanshu SahuMindfire [email protected]

AvailabilityAvailability

Availability defines the proportion of time that the system is functional and working. It will be affected by system errors, infrastructure problems, malicious attacks, and system load. It is usually measured as a percentage of uptime. Cloud applications typically provide users with a service level agreement (SLA), which means that applications must be designed and implemented in a way that maximizes availability.

Why Design Patterns

Design patterns can help to solve a specific and commonly occurring problems that may be encountered when building applications that run in the cloud.

Problem Areas in the Cloud

Availability , Data management, Design and Implementation, Messaging, Management and Monitoring, Performance and Scalability, Resiliency, Security

Design Patterns and Plan for developing High Available Azure Applications

Different Patterns for High Availability 3.1 Health Endpoint Monitoring Pattern 3.2 Queue-based Load Leveling Pattern 3.2 Throttling Pattern 3.3 Retry Pattern 3.4 Multiple Datacenter Deployment Guidance

Health Endpoint Monitoring Pattern

Implement functional checks within an application that external tools can access through exposed endpoints at regular intervals. This pattern helps to verify that applications and services are performing correctly.

Many factors that affect cloud-hosted applications are network latency, the performance and availability of the underlying compute and storage systems, and the network bandwidth between them. The service may fail entirely or partially due to any of these factors. Therefore, you must verify at regular intervals that the service is performing correctly to ensure the required level of availability—which might be part of your Service Level Agreement (SLA).


SolutionsImplement health monitoring by sending requests to an endpoint on the application.A health monitoring check typically combines two factors: the checks (if any) performed by the application or service in response to the request to the health verification endpoint, and analysis of the result by the tool or framework that is performing the health verification check.



When to Use this PatternMonitoring websites and web applications to verify availability.Monitoring websites and web applications to check for correct operation.Monitoring middle-tier or shared services to detect and isolate a failure that could disrupt other applications.To complement existing instrumentation within the application, such as performance counters and error handlers. Health verification checking does not replace the requirement for logging and auditing in the application. Instrumentation can provide valuable information for an existing framework that monitors counters and error logs to detect failures or other issues. However, it cannot provide information if the application is unavailable.


How to do in AzureUse the built-in features of Microsoft Azure, such as the Management Services or Traffic Manager.

Use a third party service (NewRelic, and Statuscake)

Create a custom utility or a service that runs on your own or on a hosted server.

Queue-Based Load Leveling PatternUse a queue that acts as a buffer between a task and a service that it invokes in order to smooth intermittent heavy loads that may otherwise cause the service to fail or the task to time out. This pattern can help to minimize the impact of peaks in demand on availability and responsiveness for both the task and the service.

Temporal decoupling

Load leveling

Load balancing

Loose coupling

Queue-Based Load Leveling Pattern


When to Use this PatternThis pattern is ideally suited to any type of application that uses services that may be subject to overloading.This pattern might not be suitable if the application expects a response from the service with minimal latency.




How to do in AzureUsing Windows Azure Storage Queue or Windows Azure Service Bus

Throttling Pattern

Control the consumption of resources used by an instance of an application, an individual tenant, or an entire service.

This pattern can allow the system to continue to function and meet service level agreements, even when an increase in demand places an extreme load on resources.

Many factors that affect cloud-hosted applications are network latency, the performance and availability of the underlying compute and storage systems, and the network bandwidth between them. The service may fail entirely or partially due to any of these factors. Therefore, you must verify at regular intervals that the service is performing correctly to ensure the required level of availability—which might be part of your Service Level Agreement (SLA).

Throttling Pattern

SolutionsAuto Scaling

Queue-Based Load Leveling PatternPriority Queue Pattern

Rejecting requests from an individual user who has already accessed system APIs more than n times per second over a given period of time.

Disabling or degrading the functionality of selected nonessential services so that essential services can run unimpeded with sufficient resources.

Throttling Pattern

Throttling PatternWhen to Use this Pattern

To ensure that a system continues to meet service level agreements.

To prevent a single tenant from monopolizing the resources provided by an application.

To handle bursts in activity.

To help cost-optimize a system by limiting the maximum resource levels needed to keep it functioning.

Retry Pattern

Enable an application to handle anticipated, temporary failures when it attempts to connect to a service or network resource by transparently retrying an operation that has previously failed in the expectation that the cause of the failure is transient.

An application that communicates with elements running in the cloud must be sensitive to the transient faults (that means Faults which are self-correcting such as Network failure, temporarry serivice available or time-out error due to busy server ) that can occur in this environment.

Retry Pattern

Solutions

Implement retry logic when trying to connect any service in cloud.

Implement retry logic when trying to connect SQL AzureAzure Service BusAzure StorageAzure Caching Service

Retry PatternSolutionsThe Transient Fault Handling Application Block The Transient Fault Handling Application Block includes the following retry strategies FixedIntervalIncrementalExponentialBackoff

The FixedInterval retry strategy retries an operation a fixed number of times at fixed intervals.

Retry PatternSolutions

The Incremental retry strategy retries an operation a fixed number of times at intervals that increase by the same amount each time. For example, at two-second, four-second, six-second, and eight-second intervals.

The ExponentialBackoff retry strategy retries an operation a fixed number of times at intervals that increase by a greater number each time. For example, at two-second, four-second, eight-second, and sixteen-second intervals. This retry strategy also introduces a small amount of random variation into the intervals.

Retry PatternSolutions

Connection Resiliency / Retry Logic (EF6 onwards)

Connection Resiliency refers to the ability for EF to automatically retry any commands that fail due to connection throttling, or to instability in the network causing intermittent timeouts and other transient errors.

Multiple Datacenter Deployment Guidance

Growing capacity over time.

Providing global reach with minimum latency for users

Maintaining performance and availability

Providing additional instances for resiliency

Providing a facility for disaster recovery

Multiple Datacenter Deployment Guidance

Solutions

Manual Re-Routing On Application Failure

Automated Re-Routing On Application Failure Re-Routing with Azure Traffic Manager( Built-In Azure Service)

Resources

https://msdn.microsoft.com/en-us/library/dn600219.aspxhttps://msdn.microsoft.com/enus/library/hh680906(v=pandp.50).aspx

https://msdn.microsoft.com/en-us/library/dn589783.aspx

https://msdn.microsoft.com/en-us/library/dn589788.aspx

http://blogs.msdn.com/b/appfabric/archive/2011/05/17/an-introduction-to-service-bus-queues.aspx

Questions?

Thank you!

Engineering

Design patterns and plan for developing high available azure applications