Microservices enable developers to work with greater autonomy, allowing for the development and deployment of individual services independently. This is often viewed as a critical component of a successful microservice strategy, providing flexibility to teams. However, this autonomy comes at the cost of increased uncertainty.
Autonomous execution=Independent deployments
The freedom to make changes to one service can result in breaking changes to other dependent services. This rapid pace of change can introduce new failures at an accelerated rate, making multi-repo systems more susceptible to unintended errors.
Given the inherent rapid development associated with microservices, teams must thoroughly test each service separately and in conjunction with others to evaluate the overall stability and quality of these distributed systems.
Where E2E Testing Approach Lacks?
End-to-end tests are positioned at the top of the testing pyramid, a concept introduced by Martin Fowler. Their primary purpose is to verify the functionality of all services operating together as a cohesive system in a production-like environment. Despite their potential benefits, e2e tests have several limitations and drawbacks.
One major concern is their tendency to be unreliable and prone to unexpected failures. Factors such as environmental changes or third-party integrations can impact their execution, leading to false positives. Additionally, given their broad scope, end-to-end tests can uncover a range of issues, including:
One of the most significant issues is creating simulations and shadow environments that accurately reflect the production environment. This can be both expensive and resource-intensive, especially for systems with multiple microservices.
Furthermore, all the services involved in a system need to be kept up and running, increasing the complexity and time required to maintain the tests.
In addition, testing every aspect of a system may not always be feasible, and end-to-end testing may not provide insight into the root cause of a problem, making it difficult to isolate and resolve issues.
Another challenge with e2e testing is that it may not detect errors or problems that occur at the component level, particularly when components are tested in isolation. This can result in compatibility and integration issues when the components are combined.
When contrasted with other test varieties, these tests undeniably exhibit the slowest performance. Developers can anticipate a substantial waiting period before receiving feedback regarding the status of their modifications.
The broader the scope of a test, the more challenging it becomes to create, run, and maintain it. Agile teams worship speed and don't want their release velocity to be slowed down by their testing approach. So, clearly, end-to-end testing is out of the question when it comes to microservices; they will only cause your system to fail.
What’s the right approach, then?
In the context of microservices, a consumer-provider model is utilized, where one microservice depends on another to complete specific tasks or provide data. Communication between these microservices is facilitated via a well-defined API over a network.
The integration and communication between various services are the backbone of the entire system, and ensuring that this integration remains functional and up-to-date can effectively address the challenge of testing microservices.
A specialized approach is required that concentrates on verifying the interaction points between different services, which is precisely the opposite of what E2E (end-to-end) tests aim to accomplish.
Contract Testing to the Rescue
Contract testing is a testing technique that focuses on the interactions between two or more services in a microservices architecture. Contract testing focuses on the interactions between services rather than the entire system. This type of testing helps to reduce the complexity and dependencies of E2E testing, leading to faster feedback loops and more cost-effective testing.
The goal of contract testing is to ensure that each service meets the contract requirements specified by the other services it interacts with. This helps to identify issues that may arise due to changes in the behavior of the service without having to perform end-to-end testing.
Contract testing is one of the most frequently used testing techniques in microservices architectures, according to a survey by the Continuous Delivery Foundation. As per the survey, 36% of respondents reported utilizing contract testing.
Contract testing is considered the most effective and efficient way to test interservice integration, eliminating the need for expensive end-to-end (E2E) tests and the hassle of maintaining all services.
These tests help identify and prevent issues and bugs that can arise when multiple components are integrated together, speeding up the development process and providing fast feedback loops to developers.
Contract testing also reduces infrastructure costs by reducing the number of tests required to be run in a deployed environment.
It supports the scalability of microservices by accelerating the testing process, making it easier to develop at scale.
Additionally, contract testing empowers developers to take ownership of their code by ensuring comprehensive and detailed contracts.
How can HyperTest help your microservices?
In the world of microservices, the hardest thing about testing them is having the ability to test the different communication between these services. Our suggested approach to counteracting this issue is to use unit testing with smart mocks.
HyperTest sits right on top of each of your microservice, recording and monitoring every little interaction that your services have with each other.
Once it is done recording, it will create mocks of the communication that takes place between two services. So that, the next time, the test will run against the mocks and the need to keep the dependent services vanishes.
If you make any changes in any of the services, all the dependent services will be notified via Slack about the change. Once you approve of the change, all the mocks will be updated automatically without you having to write the tests manually.
HyperTest will run the auto-generated unit tests for each of your services, so that the mocks will never become out-of-sync and are always updated whenever you make changes.
Coming up next, we'll delve into the intricacies of unit testing by demonstrating the clever utilization of updated mocks, accompanied by a comprehensive overview of all the cutting-edge tools at your disposal. Stay tuned!
Meanwhile, be sure to peruse our all-encompassing white paper devoted entirely to scrutinizing microservices integration. Discover the obstacles that the ride-hailing titan, Uber, encountered with their microservices infrastructure, and explore the effective measures they implemented to overcome them.
What is Contract Testing?
Contract testing is a quality assurance technique used in microservices architecture. It verifies that communication between microservices adheres to predefined contracts, ensuring compatibility and preventing integration issues when services change.
What is Contract Testing for Microservices?
Contract testing for microservices is a method of verifying that communication between individual microservices complies with predefined contracts or specifications. It ensures that the services understand and interact with each other correctly. By validating contracts, contract testing helps prevent integration issues and maintains compatibility as services evolve independently, supporting the robustness and reliability of a microservices-based system.
What is contract Testing vs unit testing?
Contract testing verifies interactions between different software components, like microservices, to ensure they conform to predefined contracts. Unit testing, on the other hand, tests individual units or functions in isolation to validate their correctness. While unit testing focuses on isolated components, contract testing emphasizes the integration and collaboration between components, especially in distributed systems like microservices.