There are a number of ways through which a business can ensure that its microservices architecture is efficiently integrated with resilience and that when a single component gets subjected to failure, it does not cause the entire microservices chain to collapse. When it comes to a monolithic application, the whole application can potentially be brought down with only a small and single error. Microservices architecture can avoid such a mishap as it consists of small units that are deployed independently and, in separation, do not affect the whole system.
However, this does not mean that all microservices architectures are highly resilient. When organizations convert their monolith into microservices, failures can still occur, and issues do not get automatically resolved. As a matter of fact, various other challenges can also arise when a business works with a system that is distributed. Therefore, it is crucial to assume high volumes of failure-occurrence while designing cloud applications that are distributed so that you architect them for resilience.
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A Microservices Architecture Without Resilience
A microservices architecture consists of several moving components and therefore has a number of different points of potential failure. There are a lot of reasons why failures can happen in a non-resilient microservices architecture, such as
- Dependent services
- Communication over a network that is not reliable
- Lack or absence of unit tests
- Poor architecture
- Failure of data center
- Hardware failures
- Bad deployments
- Release of new code
- Exceptions and errors in code
How to Design Resilience Into Microservices Architecture
Here are different ways that allow you to integrate a microservices architecture with resilience:
Identification of Failure Scenarios
Organizations need to make sure they have tested their microservices in an adequate and proper manner before they release them to production. A business needs to be prepared for the worst-case scenario and be ready to recover from different kinds of failures in a quick time and graceful manner. What planning and staying ready do is that they provide the system with the ability to minimize the impact of a failure and equip it with confidence.
A useful way of achieving resilience is by allowing your microservices architecture to fail and then practicing recovery. You can practice with different types of failures and gain an understanding of how the system behaves with each type. This is also called Chaos Testing. Some of the scenarios you can test include:
- Injection of delays or faults into the services
- Server is not responding or down
- Inaccessibility of the database
- Inability of your application to create a connection to the file system
- Inability of service A to make communication with service B
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Avoiding Cascading Failures
When the architecture of a business consists of dependencies among its different services, it needs to make sure that a ripple effect is not caused by a single service failure across the entire chain. Doing this not only allows the service in which the issue resides to recover but enables you to leverage threads in an optimal manner as well. What is more, is that it will allow you to save network resources. Organizations need to make sure they allow a failed service some time to recover instead of hammering it with additional requests.
Avoiding Single Points of Failure
It is highly recommended that a business, during the designing stages of its microservices, thinks about how it will act in the case of specific components being down. This process results in a discussion that is healthier as well as helps build a service that is fault-tolerant and equipped with resilience. However, organizations need to avoid designing their microservices in a manner that they are highly dependent on a particular component. An application that gives you single points of failure negatively impacts your ability to handle requests at all times. You need to ensure availability throughout the microservices architecture.
Allowing Fast Degradation and Handling Failures Gracefully
The designing process of microservices is where you need to incorporate resilience into it. The service should be able to take on an exception or error in a graceful manner by providing a default value or an error message.
Different Design Patterns For Resilience of Microservices Architecture
There are a number of design patterns that are commonly used and offer service capabilities of self-healing. Let us take a look at each of them:
Circuit Breaker Pattern
If you identify failures in a microservices architecture, make sure no additional calls reach the service that is failing by opening the circuit and failing fast. The circuit breaker pattern regularly checks the ecosystem for failures and closes the circuit when things get back to usual.
Retry Design Pattern
If a connection fails due to an exception, you can retry it automatically with the use of the retry design pattern. If there is a temporary issue with a service of yours, this comes in quite handy. A simple retry fixes the problem more often than not.
Timeout Design Pattern
The pattern throws an exception instead of making you wait for too long for a service to respond. This is useful for mitigating the chances of you being stuck in a limbo state. The thread gets freed as soon as the timeout period gets met.
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Our Final Thoughts for How to Design Resilience Into Microservices Architecture
The vast and extensive pool of benefits that microservices offer is benefiting organizations in tremendous ways. Any business that has not yet switched from a monolithic application to a microservices architecture is at risk of losing its competitiveness in the market. The reason you need to make your microservices architecture resilient is that applications that are distributed communicate over a network, which can be highly unreliable at times. To make sure your microservices have adequate resilience and to reap the optimal benefits that a microservices architecture has to offer, get in touch with Cloud Computing Technologies today.
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