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Microservices Availability: Microservices Architecture Resilient Against Failures

May 29, 2020

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One of the biggest concerns with distributed systems is fault tolerance. A lot of development as well as testing time is spent over exception handling and regression. Microservices Architecture is essential for failure handling in the times when application complexity is on rage. So, how exactly does microservices based systems handle failure? What are the principles that guide it? Most importantly, what measure do the organizations need to take so that these principles are practically met for a  scaling customer base.  Let us have a look.

 

A Resilient Architecture

Resilience is a key governing principle of the microservice architecture. In general terms, it states that the microservice, at any time, should be available for function even if there’s a failure. Practically, this is achieved by restarting the replica of the failed microservices on another machine, hence maintaining the availability undisturbed. Furthermore, the state of the failed microservice is saved to be retrieved later. Therefore, resiliency and availability ensure data consistency and fail-fast mechanism. However, with the increasing complexity of the applications, the availability of microservices might face some challenges like the applications upgrade, for instance. Here the dilemma for the deploying microservices is whether to upgrade to a newer version or roll back to an older one. There need to be enough machines for the app to run uninterrupted during the update. Additionally, a constant monitoring of microservices health is required to make timely decisions in this regard. 

Here are some tips to maintain the resilience and availability of microservices for a fail-proof architecture:

 

    • Proactive Diagnostics: The frontline fighters have to microservices themselves. Regular health insights sent by them can help with proactive diagnosis. A standardized logging format can help teams to understand the behavioral patterns of the microservices and take decisions over allocating the resources to deal with possible failure. Consistency in this approach can minimize the failure risks for the application.

 

  • Regular Monitoring: While proactive diagnosis is helpful to understand the functional patterns of the microservices, a regular monitoring of the current state is also necessary. This will help the teams to immediately take actions, should the proactive diagnosis fail to predict the current state of the microservices..  Health is different from diagnostics.Moreover, regular monitoring also ensures better availability of microservices especially during the times of app upgrades. Libraries can be included to streamline the monitoring and reporting process. These libraries automatically keep tabs on whether the microservices is alive and ready to function.

 

 

  • Managing the health data: Each microservices is meant to deal with a specific domain of the application. This means that, the more complex your application is, the more essential it is to properly manage the diagnostic data and monitoring reports. A microservices architecture is meant to deal with the complexity of the application. However, the complexity of the architecture itself might need some handling of its own. The multiple instances of a microservice that are needed for resilience and availability during unforeseen failures need to be consistently monitored. It is necessary for the team working on specific domains to properly manage the health and diagnosis data to ensure the stability of the overall system.

Conclusion

The robustness of the microservices architecture is also a result of its resilience and availability. As the customers scale for the organizations, mere multiplication of microservice instances won’t work. There need to be provisions in place to deal with the unpredicted failures. A little proactiveness and experience on the part of the organization can help their applications to fully enjoy the benefits of this architecture while also avoiding certain pitfalls.


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