The idea of organisational agility is so tempting for modern businesses that it makes them actively engage in building microservices-based infrastructures. However, early adopters have quickly realised that structures with many asynchronously functioning elements make software testing much more nuanced than monolithic architectures.
First of all, quality assurance (QA) experts have to constantly deal with the availability issues, as microservices are usually managed by different teams, which makes it difficult to request separate instances for testing in isolation or request them all to see how they work in sync. Secondly, microservices testing requires dedicated knowledge to fully understand how each service behaves and how to write effective tests.
As a result, companies set about developing new QA strategies in order to keep control over their microservices-centric projects. According to the experts from a1qa, a software testing company, many businesses now want to secure their project with a workable testing strategy enforced with the right tools and frameworks.
So, what’s an optimal testing approach for multiple distributed elements that interact with one another in various, sometimes unpredictable ways?
What makes up the microservices testing strategy?
A successful QA strategy should involve testing of objects in isolation as well as validation of how hundreds of distributed microservices interact as a synergetic formation. Although there’s no testing strategy fit specifically for microservices and common software testing methods still present some challenges in this regard, acknowledging these potential issues helps design a more tailored approach.
It is highly efficient, relatively cheap to run, and not too complex to perform. That’s why it takes up the largest share of the regular microservices testing cycle.
Unit testing allows looking at each microservice at a granular level by breaking it into smaller testable functional parts. Unit tests allow specialists to observe changes in the object’s state as well as analyze interactions between the object and its dependencies.
Unit tests ensure a greater software quality as they let QA experts fix issues in the smallest chunks of code. These checks can also help document the project as they define and explain the microservices under the test.
On the downside, this testing method is rather time-consuming, as the QA team has to test the entire solution in the smallest elements. Plus, testing standalone objects in isolation doesn’t guarantee successful post-deployment performance of the solution.
While unit testing focuses on checking the functionality and interactions within a microservice, component testing is directed at assessing how a microservice operates as a whole. It uses mocking techniques to replace objects that interact with this integrated module, thus eliminating undesirable reactions between different systems during testing and providing more options for accessing compatibility.
Similar to unit tests, component tests are performed at an early development stage in an isolated environment with mocks and stubs. This, however, can lead to a certain amount of incompatibility issues when the service interacts with other objects in real life.
Contract testing simulates interaction scenarios between consumers and microservices API providers. It helps ensure that the contract between the consumer and the data provider is observed by verifying the format of transferred data and detecting possible malfunctions. This testing type is also directed at debugging consumer workflows and eliminating configuration errors.
Contract tests don’t check the microservice’s performance. They help make it consumer-centric as they give developers an idea of how a particular microservice or introduced changes impact the software’s consumers.
By means of integration testing, QA specialists review how well microservices connect, communicate, and interact as a whole system. They also verify that the integrated modules meet performance and reliability expectations.
Though important for checking performance of user-facing features, integration testing of microservices requires a lot of effort that makes the procedure expensive in terms of person-hours. The number of such tests is usually soaring as it involves checking not only a particular microservice’s code but also code combinations of the microservices it communicates with. To facilitate this process, QA teams can try varying integration tests by their granularity.
Integration tests designed for microservices are also highly error-prone. If the test algorithm contains even the smallest discrepancy, it should be entirely re-written. For this reason, when integration tests are critical to the software product, companies need to consider investing in test automation within the continuous testing framework.
It evaluates the microservice’s operation under various levels of load. Performance testing is directed at monitoring real-time responsiveness, identifying load-balancing bottlenecks, and improving the system’s fault-tolerance.
In the conditions of continuous integration and continuous development, it should be completed as quickly as possible. To speed up the process and make it fail-proof, it’s a good idea to apply the following practices:
- Create mocks for all dependencies and access all microservice endpoints directly to assess its performance in isolation.
- Add gateway factors to check the performance of all requests going through a gateway to the microservice.
- In case of a hybrid architecture, it’s necessary to test each server as well as to measure performance of data replication between cloud and legacy servers.
The modular, flexible, and independent nature of the microservices-based architecture requires adopting security testing, which takes into account each integrated modules’s specific logic and doesn’t interfere with continuous integration. For this reason, it’s necessary to apply a unique set of checks to each microservice, using such methods as vulnerability scanning, penetration testing, risk assessment, API gateway safety review as well as automated vulnerability and security scans.
Summing it up
The microservices-based architecture has fundamentally changed the approach to app design and development as well as to the way software engineering and QA teams work together. As microservices are not going anywhere and will continue to evolve, QA specialists have to master new skills to understand how these new systems behave. They also need to stay informed of new tools and frameworks to augment their competence and design optimal testing strategies based on the best QA practices in order to ensure the seamless operation of microservices-related systems.
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