As more and more applications become cloud-native keeping up with the digital transformation goals it becomes important to meticulously plan a test strategy. Cloud-native applications reduce downtime, improves resilience, and offers scalability leveraging complex microservices based architecture.
The need of cloud-native testing
Cloud-native applications follow microservices based architecture. Each microservices takes care of one service of the application. Testing in isolation is not ideal for such architecture as it is also important to check if the services are perfectly interacting with each other. While end-to-end testing during staging, pre-production, creating synthetic environments may be an option, the cost incurred is very high.
Container orchestration systems like Kubernetes supports testing in production environments. While testing in production environments has several advantages it is also prone to glitches. Appropriate testing strategy and cloud-native testing tools are crucial for wholesome validation of cloud-native applications.
Features of cloud-native testing tools
Cloud-native testing tools are built for cloud-native environments. They facilitate deployment of tests in clusters, offer high scalability in test execution, and can make tests independent to any CI/CD framework.
Cloud-native testing tools support various platforms like Windows, Mac, and Linux so that the difference in target machine configuration, cluster size doesn’t impact the test strategy.
Setting the cloud-native test strategy
While setting up the test plan for a cloud-native application a lot of unique factors come into play due to the dynamic nature of cloud.
Test scope and coverage
Cloud-native applications are usually microservices based and consist of a wide number of small, independent services. It is important to decide the test scope depending on the critical and high-risk areas. Appropriate cloud platforms and services should be chosen to meet the test requirements.
Infrastructure
Cloud-native applications are typically deployed to dynamic cloud environments, which means that the underlying infrastructure can change at any time. This makes it important to design test cases that are resilient to change.
Load
Cloud-native applications often need to be able to handle high levels of traffic and concurrency. This means that performance testing is essential for cloud-native applications. The test plan should also check for scalability and load tolerance.
Approach to testing cloud-native application
Testing is an integral part for all the phases of software development lifecycle. Cloud-native testing provides quality assurance for reliable software. Depending on the architecture, load, environment various types of testing methods are implemented.
Unit test
Unit testing is required to test microservices at a granular level. Unit test ascertains that the microservices are working perfectly fine or not. The test also helps developers to understand change of state, relation to dependencies, and provides a quick feedback of changes and glitches arising for a code change.
Integration testing
Integration tests are automated as a part of DevOps practices and triggered by the CI server whenever a change takes place. They explore the communication path between various individual microservices and also between microservices and external services, systems, or datastore.
Contract testing
Contract testing is a way to ensure that the different microservices in an application can communicate and interact with each other as expected. This is done by creating contracts that define the inputs and outputs of each interaction between microservices. The contracts can then be used to generate test cases that are used to verify that the interactions are working as expected.
Contract testing is particularly important for microservices-based applications because each microservice is typically developed and maintained by a different team. This can make it difficult to coordinate the testing of the interactions between microservices. Contract testing provides a way to automate the testing of these interactions and to ensure that they are working as expected, even when the microservices are developed and maintained by different teams.
Non-functional testing
Functional tests ensure that the application meets the business needs. However, non-functional tests are important to ensure that the applications behave in a desired manner in production, and is resilient to sudden server crash or a service component unavailability. Non-functional tests measures product performance against various factors such as latency, load balancing, usability, and static and dynamic security.
Failure mode testing
For microservices there are several number of modes to fail. Chaos engineering is an interesting way to introduce controlled failures to detect what can possibly go wrong. Identifying failures in production helps to build confidence in applications resilience to sudden disruption.
Conclusion
The goal of a robust test strategy for cloud-native applications is to ensure that maximum quality check has been performed and the risk of unexpected failures is reduced. The complex nature of cloud-native applications wouldn’t allow for exhaustive testing so the teams need to take a risk-based approach towards testing and be aware of high vulnerable areas.
