As more and more applications become cloud-native to keep up with digital transformation goals, it is essential to meticulously plan a testing strategy. Cloud-native applications, built on microservices architecture, reduce downtime, improve resilience, and offer scalability, but they also require specialized testing strategies to ensure they perform optimally.
The need of cloud-native testing
Cloud-native applications typically follow a microservices-based architecture, where each microservice handles a specific service of the application. Testing these applications in isolation is not ideal since it’s crucial to test how microservices interact with one another. While end-to-end testing in staging or creating synthetic environments may seem like an option, it comes with a high cost.
Container orchestration systems like Kubernetes, enable testing in production environments, which can be very useful but also carries some risks. Hence, a solid testing strategy combined with the right cloud-native testing tools is vital for proper validation of cloud-native applications.
Features of cloud-native testing tools
Cloud-native testing tools are designed specifically for cloud-native environments. They allow for scalable test execution, deployment across clusters, and can function independently of CI/CD framework.
These tools are cross-platform, supporting environments like Windows, Mac, and Linux, ensuring that test strategies are not impacted by differences in target machine configurations or cluster sizes.
Setting the cloud-native test strategy
A cloud-native test strategy must account for several unique factors due to the dynamic nature of cloud environments.
Test scope and coverage
Since cloud-native applications often consist of numerous small, independent microservices, it’s crucial to focus on high-risk areas when defining the test scope. Selecting appropriate cloud platforms and services for testing is also critical.
Infrastructure
Cloud-native applications are deployed in dynamic environments, meaning the infrastructure can change at any time. Test cases should be resilient to these changes, ensuring they still run effectively as the underlying infrastructure evolves.
Load Testing
Cloud-native applications need to handle high levels of traffic and concurrency, which means performance testing is a must. A solid test plan should check for scalability, load tolerance, and stress points within the system.
Approach to testing cloud-native application
Testing is a key part of the software development lifecycle, and it ensures that cloud-native applications remain reliable and functional. Different testing methods must be applied depending on the application’s architecture, environment, and load.
Unit test
Unit tests are essential to ensure each microservice functions correctly. They help developers identify issues early by providing feedback on code changes, dependency relations, and states.
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
Non-functional testing evaluates the resilience of applications in production. These tests measure performance factors like latency, load balancing, security, and usability, ensuring that the system behaves well under different conditions.
Failure mode testing
Chaos engineering introduces controlled failures in production to test how systems respond to unexpected disruptions. This helps build confidence in the system’s resilience and ability to recover from failures.
Conclusion
A comprehensive test strategy for cloud-native applications aims to maximize quality and reduce the risks of failures. Given the complexity of cloud-native applications, exhaustive testing isn’t feasible, so teams should focus on a risk-based approach, emphasizing high-vulnerability areas while leveraging automation tools and frameworks designed for cloud-native testing.
