Microservices Testing Approach
Microservices strategy is an approach of developing an application by splitting it into smaller services, where each module runs in its own process and communicating with each other in a lightweight mechanism. These services are independently deployed and fully automated.
Microservice Testing is a new term introduced which changed the architecture of the software development, moreover, it changes the working culture of the teams the way teams work together.
What is the Microservices Testing Strategy?
Microservices architecture divides the complex application into smaller modules. This provides a number of benefits over the monolithic architecture.
Microservices architecture deploys independently of the other modules. Microservices take this approach to independent services. With microservices, we will easily be able to adopt technology more quickly and understand how new advancements may help us.
In short, the Microservices architectural style is an approach to developing a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms, often an HTTP resource API.
These services are built around business capabilities and independently deployable by fully automated deployment machinery. There is a bare minimum of centralized management of these services, which may be written in different programming languages and use different data storage technologies.
Image Source – ThoughtWorks
Multiple services work together to form whole application, Services like service A, service B and service C work independently, and they collaborate and form the whole application. These services collaborate for the functioning of the application. These chunks of services are called Microservices.
How to Adopt Automated Testing for Microservices?
There are five strategies used to approach testing Microservices successfully.
The documentation-first strategy
Follow a documentation first approach, the majority of documentation is markdown in Git. API documents stay open source, so it’s all public. At that point, before anybody writes any API changes or either different API, refresh the documentation first, have that change investigated to ensure that it adjusts with API conventions and standards which are altogether documented, and ensure that there’s no breaking change present. Ensure it accommodates with naming conventions and so forth as well.
The full stack in-a-box strategy
The entire stack in-a-box strategy entails replicating a Cloud environment locally and testing everything all in one vagrant instance (“$ vagrant up”).
The AWS testing strategy
This third method involves turning up an Amazon Web Services (AWS) framework to deploy and run tests on. This is a more adaptable approach to the full stack in-a-box strategy. A few people called this a personal deployment [strategy], where everybody have their AWS account. Push the code that’s on workstation up into AWS in around ten minutes and just run it in like a real system.
The shared testing instances strategy
The fourth strategy is a cross breed between full stack in-a-box and AWS testing. That’s because it involves working from own local station while utilizing a different, shared instance of a Microservice to point local environment at during testing. Some run a different instance of a Microservice just to be utilized for testing local builds. However, the local builder would point to a test image parser that’s running in the Google infrastructure.
The stubbed services strategy
The marks or ‘stubs’ of Microservices behave like the right service and advertise in service discovery as real service, but are a dummy imitation. For example, a testing service may require that the service becomes aware that a user carries out a set of tasks. With stubbed services, imagine that user tasks have occurred without the typical complexities that come with that. This approach is much more lightweight compared to running services in their totality.
Benefits of enabling Automated Testing for Microservices
The benefits of microservices are many and varied. Many of these benefits can be laid at the door of any distributed system. Microservices, however, tend to achieve these benefits to a greater degree primarily due to how far they take the concepts behind distributed systems and service-oriented architecture.
There are following benefits of enabling Automated Testing for Microservices –
- Incentive better isolation between services and the design of better systems.
- It applies a certain design pressure on programmers to structure the API in a way that’s easy to consume.
- Tests act as fantastic documentation for the API exposed by an application.
- Test each service individually.
- Test the different functional pieces of the application.
- Monitor to assess the impact of the change.
- Monitor the ongoing performance of your application.
The most important benefit of the microservices is that it deployed independently of the other modules. In case if there is need to make changes to the module other modules remain unaffected. If one module stopped working then the application as a whole will not be affected only that one module will be affected.
The application which was broken down into smaller modules will be developed parallel to different developer work on different module and development of all the modules in parallel.
Need for Microservices Testing and Test Automation
It is very important to test the microservices as to be very confident about the assumptions made for each service that it will do what it says to do. Testing of microservices is the first step in making the service reliable for the user. For the internal functional dependency of the microservices, the testing is more important for the service to stay strong.
How Automated Testing for Works?
Test each service individually
Test automation is a tool for testing discrete Microservices. It is easy to create a simple test harness that repeatedly calls the service and compares a known set of inputs against an expected output. In any case, all by itself, it wouldn’t get unusually far with testing. It will free up test team to concentrate on more complex testing.
Test the different functional pieces of the application
Having recognized the key functional elements in the application should seek to test these in much the manner would traditionally do Integration Testing. Here the advantage of test automation is clear. Rapidly build test scripts run each time one of the Microservices refreshes. Compares the outputs of the new code with previous outputs, quickly establish if anything has changed.
Don’t test in a small setup
There’s an ability among some managers to keep the testing group of resources. But with Microservices-based applications this is counterproductive. As opposed to attempting to make small local staging environments to test code in, should look to leverage Cloud-Based testing. Here dynamically allocate resources as tests need them, freeing them up when tests have completed. As such, test automation won’t directly help here.
Try to test across different setups
Advised to use multiple environments to test code, similar to cross-browser testing for web applications. The idea is to expose code to any minor variations in things like library versions, underlying hardware, etc. that may affect it while deploying to production. One approach to do this may be to make staging environments on the fly. Utilizing Kubernetes, it’s conceivable to create a test environment, populate it with data from a known source, load code and then run tests. The excellence is that the environment is recreated each time automatically exposed to any differences that might exist. Of course, the flip side is that it becomes harder to diagnose the underlying cause of any bugs.
Use Canary testing as much as possible
Canary testing is a methodology where a small set of users presented to changes in the code and contrast their experience with the experiences of those users still running the old code. This methodology is particularly useful for testing Microservices. It uses monitoring to survey the effect of the change.It views error rates, service load, responsiveness, and similar metrics can tell whether the new code has a negative impact by adopting a strategy where one service instance at a time update, can quickly and automatically do Canary Testing.
Canary testing is a methodology where a little arrangement of clients present to changes in the code, and contrast experience and the encounters of those clients as yet running the old code. This methodology is especially helpful for testing Microservices. It utilizes checking to survey the effect of the change. It views blunder rates, benefit load, responsiveness, and comparative measurements to disclose whether the new code has an adverse effect. By embracing a procedure when one administration case at once is refreshing, get without much of a stretch and consequently do Canary Testing.
AI or Artificial Intelligence utilized to automate Canary Testing of the Microservices application completely. AI methodologies such as Deep Learning recognize changes and issues activated by the new code. Few users moved over to the new framework, and the AI compares the experience with that of the existing users. Since this is possible automatically, it replaces the human in the loop.
Writing debuggable code includes the capacity to make inquiries later on, which in turn involves –
Correct Code Instrumentation.
Knowing the Observability arrangement of choice (be it metrics or logs or unique case trackers or traces or a mix of these) and its pros and cons.
Capacity to pick the best observability to arrange given the requirements of the given service, operational quirks of the dependencies and good engineering intuition.
Microservices Testing Approach
It is essential that a microservice application is built with an awareness of how it can be tested. Having good test coverage gives you more confidence in your code and results in a better continuous delivery pipeline.
As this is a new architectural approach so require a new approach of doing automated testing and quality assurance. New approach divides the specific layer of tests. There is five layers of tests that are performed over microservices –
What is Unit Testing?
Tests a single class or a set of closely coupled classes. These unit tests can either be run using the actual objects that the unit interacts with or by employing the use of test doubles or mocks.
In Unit testing, the smallest piece of testable software is tested in the application to determine whether it behaves as expected or not. Tests are typically run at the class level or around a small group of related classes. In unit testing, an important distinction is seen based on whether or not the unit under test is isolated from its collaborators.
Unit tests are usually written by the programmers using their regular tools – the only difference being the use of the same sort of unit testing framework.
There is further two types of testing in Unit Testing
- Sociable Unit Testing
- Solitary Unit Testing
Sociable Unit Testing
It focuses on testing the behavior of modules by observing changes in their state. This treats the unit under test as a black box tested entirely through its interface.
Solitary Unit Testing
It looks at the interactions and collaborations between an object and its dependencies, which are replaced by test doubles.
Imagine you’re testing an order class’s price method. The price method needs to invoke some functions on the product and customer classes. If you like your unit tests to be solitary, you don’t want to use the real product or customer classes here, because a fault in the customer class would cause the order class’s tests to fail. Instead, you use Test doubles for the collaborators.
Unit testing alone does not provide a guarantee about the behavior of the system. Unit testing covers the core testing of each module, however, there is no coverage of the test when these modules collaborate to work together to interact with the remote dependencies.
To be sure about each module work correctly with remote dependencies finer coarse-grained testing is required.
What is Integration Testing?
Integration tests are used to test communication between services. These tests are designed to test basic success and error paths over a network boundary.
Different components interact with each other for their functional dependency, while communicating with each other integration test verifies the communication paths between the components and detect the interface defects.
Here, all test modules are integrated together and tested as a subsystem. It checks that the communication paths between the subsystem work correctly while interacting with its peers. In microservice architecture, they are typically used to verify interactions between layers of integration code and the external components to which they are integrating.
When the automated tests are written for the modules which are interacting with an external component, the basic goal is to verify the modules are interacting sufficiently with the external component.
It is very difficult to trigger abnormal behavior such as a timeout or slow responses from the external component. Special tests are written to ensure that test respond as expected in the unexpected circumstances
Persistence integration tests provide assurances that the schema assumed by the code matches that is available in the data store.
With unit testing and integration testing, we can have confidence in the correctness of the logic contained in the individual modules that make up the microservice, but we cannot be sure that the microservices work together as a whole to satisfy business requirements.
What is Component Testing?
Tests the full function of a single microservice. During this type of testing, any calls to external services are mocked in some way.
A component is any well-encapsulated, coherent and independently replaceable part of a larger system. In a microservice architecture, the components are the services themselves.
A component’s complex behavior is avoided by isolating it from its peers, also isolation help in controlling the test environment for the component.
What is Contract Testing?
Test the agreed contract for APIs and other resources that are provided by the microservice.
At the boundary of the external service, an Integrated contract test is done to verify the contract that is expected by the consuming service. This test verifies that the component meets a contract.
A test suite is written to verify only those aspects of the producing service that is in use. The behavior of the service is not deeply tested, response latency and throughput should be within acceptable limits when input and output of the service call contain required attributes.
This test is written by each test consuming team and then packaged. The main aim of this test is to know the impact of the changes made by the maintainers on the consumers.
What is the End-to-End Testing?
End-to-End Testing, Tests a complete flow through the application or microservice. Usually used to test a golden path or to verify that the application meets external requirements.
End-to-End testing tests the whole system from end to end. It verifies that the entire system meets the external requirements and eventually achieve its goal. Without bothering about the internal architecture of the application business goal should be achieved by the End to End testing.
The system is fully deployed and is treated as a black box and the test is exercised. With Public interference through GUIs and API, the system is manipulated. End to End Tests is more business facing.
This test verifies that the firewall, proxies, and load balancers are correctly configured.
In microservice architecture, for one behavior, there are many microservices which interact to respond to that behavior, an end to end testing provides value by adding coverage of gaps between the system.
Challenges in Implementing Microservices Testing Strategy
Microservices architecture includes numerous tiny independently services which integrate with each other to form the whole application. These microservices interact with each other in the production environment for the functionality of the application, although these small microservices are very simple while communicating with each other there arise many complexities. As the granularity of the application increases.
Summary of Microservices Architecture
Microservices architecture is a distributed approach designed to overcome the limitations of traditional monolithic architectures. It helps to scale applications and organizations while improving cycle times, however, they also come with a couple of challenges that may cause additional architectural complexity and operational burden.
One of the benefits of microservice architectures is agility. Because each individual service has a focused scope and an independent lifecycle, it takes less time to implement a new feature as a microservice, test it, and deploy it into production.
How Can XenonStack Help You?
XenonStack offers Automation Testing in Microservices along with Microservices Performance Testing. Microservices Approach for Enterprises and Startups –
Application Modernization services enable the migration of monolithic applications to new Microservices architecture with Native Cloud Support including the integration of new functionality to create new value from an existing application.
Microservices With Docker & Kubernetes
Build your Microservices in a new and easy way with Docker & Kubernetes Containers. Run each service inside a container and combine all those containers to form a complex Microservices Application.
Continuous Integration & Continuous Deployment
Setup your Continuous Integration Pipeline to build and deploy your Microservices Application on Docker & Kubernetes. Drive the application from testing, staging, and into production without having to tweak any code.
Test-Driven Development Approach For Microservices
XenonStack follows the Test Driven Development Approach in the development of Enterprise-level Applications following Agile Scrum Methodology. TDD for Microservices improves not only the code quality but also increases the productivity and overall development of software/program. TDD also leads to more modularized, flexible and extensible code.