How to Test Microservices: Strategy, Types & Tools

Microservices is a distinctive software development approach that focuses on building single-function modules that work collectively to execute similar tasks. Instead of following a traditional monolithic architecture (single application with multiple functions), developers use the microservice approach to create independent modules for each function.

They isolate each software component with the help of service boundaries, so it’s easier to deploy and operate each service separately. Since each software component is independent of each other, adding new functionalities or scaling services is a lot easier compared to the monolithic architecture.

Nevertheless, the microservice architecture can also make an application more complex, especially if we add multiple functionalities. Likewise, testing the collective functionality of multiple services is a lot more difficult due to the distributed nature of the application.

Since microservices follow a different architecture, we also need a unique strategy for load testing microservices. In this article, we will explore different approaches, tools, and tips for load testing microservice applications.

Table of Contents

1. Microservice Architectures: Idea and Benefits
2. Tips for Testing
3. Load Testing for Microservices
4. Load Testing Tools for Microservices
5. Microservices Testing in PFLB

Microservice Architectures: Idea and Benefits

Microservices have created more adaptable and flexible IT infrastructures. It allows you to modify only one service, without altering the rest of the infrastructure. In other words, you can deploy and modify each service without affecting the functional aspects of other services or the application. Following are some of the major benefits of a Microservice Architecture:

Faster Delivery

Through distributed development, microservices empower teams to develop multiple microservices simultaneously. Due to the reduction of development cycles, a microservice architecture allows implementation and updates to be carried out more quickly. As a result, software teams have more time to market their product.

Greater Scalability

As the demand for certain services grows, it is possible to carry out implementations on different servers and infrastructures to meet your needs.

Resilience

The microservice architecture promotes independent development, deployment, and operation of service. Therefore, if an application follows a similar approach, any failure in an individual service will not affect other services in the application. The service boundaries of each microservice protect prevent failure of the entire application.

Ease of Implementation

Microservice applications follow a modular approach and each service is smaller than a traditional monolithic application. As a result, implementing a single service is a lot easier.

Defined Architecture

Since larger applications are broken down into smaller parts, developers can more easily understand, update and improve those parts; in this way, faster development cycles are obtained.

Tips for Testing

The traditional testing approach follows testing each bit of code individually through unit tests. After we join these units together, we test them collectively with the help of integration tests.

Once all these tests are passed, we create a release candidate, which is then subjected to a series of other tests, including performance tests, load tests, system tests, regression tests, and user acceptance tests. While this approach works well for a monolithic architecture, it simply doesn’t work for systems built on microservices.

One obvious reason behind this is the scale of services involved in microservices testing. A number of apps built as microservices use dozens of services simultaneously. Therefore, it’s possible that all these services not in the same form in a staging environment compared to the production environment.

Furthermore, since these services scale dynamically and have to share the collective demand, we need to use a distinct testing approach for microservices. This is necessary because using a traditional testing approach in such situations is much more complex.

Lastly, in a microservice architecture, the orchestration of all services in the application (the way services are assembled) responds to load dynamically. To learn how to test microservices, you can follow the tips below:

Treat Individual Services as Software Modules

You should try conducting unit tests on each individual service as you would traditionally for any new piece of code. Each service in a microservice architecture needs to be treated as a black box. Therefore, you should test each service in a similar manner in a microservices testing framework.

Identify and Test Essential Links in Architecture

During testing, you should try to identify essential links in the microservice architecture and then test those links separately. For instance, if there is a strong link between user login service, you need to both the database that stores these user login details as well as the front-end that displays those details.

Avoid Assembling the Microservice Environment in a Small Testing Setup

Trying to assemble the entire microservice environment in a small testing setup will be an unnecessary waste of time and resources.

Testing across Different Setups

As an experienced tester will tell you, you will witness a greater proportion of bugs if you attempt diversifying your setup. This happens more often, where there are extremely complex virtual environments. In such environments, even tiny differences between libraries and underlying hardware can result in unwarranted changes in functionality, even if you add a virtualization layer. Therefore, it’s best for these components in detail.

Leverage Canary Testing for New Code

Canary testing is an approach for introducing code changes to end-users. However, in this approach, the developers don’t introduce these changes ton users who have volunteered for testing. Therefore, developers have to test new code changes directly to real-time users. Leveraging canary testing for microservices ensures that code changes are transparent and ready for the real-world environment.

Load Testing for Microservices

Applications designed according to the microservices architecture are extremely complex in the way functionality flows through the different services. The service paths within an application can vary depending on the functionality a user consumes. In some systems, it is extremely rare for the application to use the exact same service path.

At the same time, there are countless variables that influence the operations of a microservice application. Every user request for a service needs to traverse through the entire network. Therefore, the response time and latency of the service can vary depending on the ongoing traffic on the network.

This is something that is uniquely distinct between monolithic and microservice applications. In traditional monolithic applications, we can execute functionality calls within the same binary. Therefore, we only have to add one more function call to the execution stack to make it work.

On the contrary, in a microservices environment, the application might depend on supporting resources or services. These services might operate slower or faster depending upon the state of available resources and the total traffic on the network.

For this reason, it’s best to consider microservices as a dynamic environment that needs to cope with constant changes. At the same time, we must understand that simple functionality testing does not work in a microservice environment.

This is why load testing microservices are mandatory for observing how the application responds to a high number of service requests. Likewise, load testing helps us understand the behavior of an application when a large amount of data is being transferred between single services. In such cases, the network often causes bottlenecks in the application.

Load testing microservice applications help us expose components of the application that are not optimized for scalability. As a result, we can prevent application crashes caused by large user loads in the production environment.

Here are some tips you can follow to load test microservices:

Prioritize High-Risk Services Instead of Going for 100% Testing

Long-running load tests can quickly become a bottleneck in microservices if you try to implement it too early in the development cycle. In other words, testing too many things in the early stage slows down the development process.

This is why we need to prioritize the testing of high-risk services so as to avoid excessive testing. By relegating the testing of less-risky services to later stages we can expedite the development process.

Leverage Service Virtualization Instead of Waiting for Fully Functional Dependencies

Dependencies can a significant obstacle during software development. Often we see teams completing one component of the code, but being delayed because other teams haven’t delivered a dependency yet.

However, you can address these types of delays with the help of service virtualization. Service virtualization is a lot similar to the process of mocking a service. This means that you only need to create a microservice that contains the URLs you need.

Don’t Rely on a Single Runtime Environment

It’s quite common for microservice load testing to take too long. This happens usually when there is some issue with the resources being used in a run-time environment. Therefore, if you rely on a single run-time environment, you are always at risk of delaying the load testing procedure. Having multiple run-time environments can help you avoid bottlenecks during load testing of microservices.

Go Beyond the Request/Response Ratio as a Metric for Performance

Although it’s extremely important to load test the performance of requests and responses in a microservice, there are various other things you need to consider. This is why you need to put mechanisms in place to monitor the behavior of all critical components in a microservice.

Configure Service Level Agreements through Testing

Although testing for service level agreements is something obvious, many companies have an organizational structure that stops them from doing this. For instance, many organizations have different teams for product management and microservice load testing, and some of these teams never interact with each other.

This creates significant problems for both these teams. Testing teams have to rely on guesswork and go through endless cycles of testing while product managers have to hear the complaints of stakeholders when requirements are not met. Merging both teams is a useful technique for creating accurate service level agreements for your microservices.

An even better approach would be to rely on an experienced testing service for load testing microservice. Such a team would not only identify bottlenecks more accurately but will also deliver metrics of service level agreements in a more comprehensive manner.

Load Testing Tools for Microservices

Instead of implementing a few random tests on your microservice application, you should use sophisticated load-testing solutions to avoid your unexpected meltdowns. There are various load testing tools that generate virtual traffic accurately to test microservices against overwhelming user loads. Here are some of the best microservices load testing tools in the market:

JMeter for Microservices

Apache JMeter is easily one of the most used performance testing tools for developers. It is available in an open-source format, which makes it highly accessible to software businesses of all sizes.

The performance testing tool supports a 100% Java scripted desktop application. At the same time, it allows developers to load test functional behavior of microservices and measure the performance of microservices under varying user loads.

influxDB for Microservices

InfluxDB is an open-source application written in the Go language. It serves as a fast, reliable, and highly available database optimized for retrieving time series data. Using this tool for load testing microservices can help you identify bottlenecks.

Grafana for Microservices

Grafana It is an open-source metric visualization and analytics suite. You can use it for visualizing time series data to see how your microservices behaves under real-time traffic.

CloudWatch for Microservices

Amazon CloudWatch is a monitoring service that evaluates resource usage for applications or microservices deployed on AWS. Therefore, it can be a useful tool if you want to perform load testing for microservices.

Microservices Testing in PFLB

Choosing the right microservice testing service can help you ensure the best quality of software and deliver a product that wins the market. PFLB is a software testing service that has experience of serving over 500 companies across all domains, from finance and healthcare to retail and technology.

Due to their vast experience, they can ensure that your mobile application excels and performs better than the competitions’.

Besides Performance Testing, the company has expertise in other core software testing services, such as Manual Testing, Usability Testing, Integration Testing, Test Automation, and much more. To learn more about the company feel free to visit their website at PFLB.