Microservices Testing Tutorial: How to Test Microservices?

OVERVIEW

Microservices testing combines QA activities to ensure each microservice's functionality and performance are stable, its failure does not affect the entire software, and all microservices work seamlessly together.

Microservices minimize server outage risks and make it feasible for developers to make corrections to small code components without impacting the front end. Software product development with microservice architecture has been a standard for over a decade.

Even though it solves a plethora of problems arising from conventional software development, adopting a microservice architecture has also posed challenges in some areas. One of them is microservice application testing. Microservices applications require testing strategies that consider their isolated nature and dependencies. It often tests each microservice independently before integrating them.

A microservice architecture refers to a structure where an application sits as a collection or an arrangement of different autonomous or loosely coupled services surrounding a specific business domain.

In other words, it is a group or collection of several distributed programs communicating over networks. They also occasionally interface with databases and some third-party services. Since microservices are networked by nature, there are a large number of points of failure. To address this issue, the approach to software testing has to broaden.

In a microservice architecture, processing functions of applications happen by considering them a loosely coupled separate service with its database and logic. Deployment, updates, scaling, and testing processes occur inside one single module.

On the other hand, even the tiniest of changes have the power to impact the entire app. Moreover, it takes a lot of time to check and debug them, leading to less frequent updates and increasingly high changes being brought into production at once.

A monolithic architecture lacks insulation due to its single-tier nature. The data access code and user interface combine into one program from one platform. But even though it's independent and self-contained, a single bug or even the slightest issue in one module has the capability to break down the entire infrastructure of an application.

Having a microservice architecture offers several advantages over its monolithic counterparts. They include:

• Faster deployment with less code.
• Small amounts of code make it easier for programmers to decipher what works and how it works.
• Greater manageability and stability as individual service failure doesn't negatively impact the entire workflow.
• More independence and autonomy.
• Ability to leverage the power of various platforms and technologies.

In 2005, Peter Rodgers first used the term 'micro web services.’ He successfully deduced what a well-structured microservices platform looked like while attempting to create a more service-oriented and flexible software architecture.

In 2007, Juval Löwy, the famous software architect, explained the granularity of services, leading to many case studies that gave positive outcomes. This moved microservices architecture from just being a buzzword to embodying the present and future of pragmatic development and maintenance of software development.

To be precise, microservices architecture describes a modular approach to building software. Applications have different suites comprising various independently managed and deployed microservices. We can define these services as processes communicating over a network with the help of technology-agnostic protocols. Due to their small size and decentralized nature, microservices offer flexibility with software, environment, hardware, and programming languages.

In this section of the microservices testing tutorial, we will discuss different components of the microservices architecture.

Microservices

Starting with microservices themselves, they make up the core foundation of the architecture. As discussed earlier, microservices are applications broken down into self-contained services communicating over protocols.

It's up to different teams to decide the appropriate microservice size, keeping in mind that two segmented or overly granular services contribute to high management and overhead needs. But when you decouple these services, it minimizes independencies and promotes autonomy.

Clients

The client handles calls to endpoints in case of directly performed consumption. Also, the client needs more than a single microservice for consuming functionality.

Identity Providers

Identity providers are lightweight and fine-grained services offering identity data with server-to-server and user-driven access.

Messaging Formats

Messaging formats are formats via which microservices communicate through. Asynchronized and synchronized messages are the two forms of communication all microservices use to interact with each other.

Static Content

Static content refers to the content microservices deployed to a cloud storage service that directly delivers to the clients through content delivery networks.

Management

Management is a capability that facilitates business users and operations to carry out service configuration during runtime.

Service Mesh

Service mesh is a dynamic layer of messaging that facilitates communication. In other words, a service mesh eliminates the need for developers to perform coding for enterprise communications during creation.

Containers

Containers are software units responsible for packaging services along with their dependencies. They maintain consistency in the unit throughout development, testing, and production. Containers are also accountable for enhancing and accelerating applications' deployment time and efficiency more than many other deployment processes in a microservices architecture.

API Gateway

API gateways are an essential component to facilitate smooth communication. When it comes to a distributed architecture, it handles both administrative roles and communication occurring within one of the many applications. As a result, microservices remain lightweight as API gateways create the core abstraction layer between outside clients and microservices.

An API gateway is also responsible for authenticating, caching, and managing requests, balancing the necessary load, and monitoring the messaging. It also standardizes messaging protocol translation and frees the service and the client from requesting translations in unfamiliar formats. As a result, the communication between clients and microservices fastens.

Service Discovery

Microservices during deployment can quickly fluctuate because of changes in workloads, failure, mitigations, updates, etc. This makes it difficult to track many services in distributed networks all over the app architecture. That's where service discovery comes into the big picture. It helps adapt service instances with changeable deployment and facilitates load distribution among microservices.

The service discovery contains three components and two discovery patterns.

• Service consumer: It instantly retrieves the service location from the registry and facilitates communication with that particular instance.
• Service provider: Responsible for originating service instances.
• Service registry: Stores service instance location and plays the role of a database.
• Server-side discovery pattern: In this particular discovery pattern, the router finds an applicable service by searching the entire service registry and accordingly forwards requests.
• Client-side discovery pattern: This pattern is responsible for locating a service provider by searching the service registry and using a load-balancing algorithm to choose an available service instance, followed by making a request.

Besides being independent, microservices are also interdependent, full-stack, stateless, and small applications that can be individually functioning and implemented. Following are some core microservices design principles that ensure successful microservice design.

• Single point of contact
• Distinct microservice boundaries
• Transportable microservice
• Data-storage mechanism
• Implicitly ephemeral

Single point of contact

Establishing a single point of contact makes the microservice easier to manage and scale. For example, if the microservice is meant to provide authentication, it should perform authentication. This means that its interface should only reveal access points related to authentication.

Distinct microservice boundaries

A microservice should have distinct boundaries segregating it from its environment. It means that all logic and data of a single contact of a microservice must be contained in a single deployment unit. A discrete microservice is hosted in its source control repository and has its own CI/CD (continuous integration/continuous delivery) workflow.

After deployment, the microservice becomes a component of a large application. However, each microservice is separated from all other microservices from development to testing to release. When a microservice is isolated, it becomes easily transportable.

Transportable microservice

A transportable microservice can be easily relocated from one runtime environment to another. This makes microservices easier to use in an automated or declarative deployment workflow.

Data-storage mechanism

Each microservice should have its data-storage mechanism isolated from other microservices. Microservices can only share data through their public interfaces with other microservices. The key benefit of microservices carrying their data is enforcing all the other principles. In particular, this is crucial when it comes to the final principle.

Implicitly ephemeral

Having an ephemeral microservice can be created, destroyed, and replenished quickly without any impact. There is a standard operating expectation that microservices will come and go frequently, sometimes due to system failures or scaling requirements.

It might seem intimidating to switch from your conventional software architecture to a microservices one. So, to eliminate the jitters, here are some pointers to keep in mind before you start. Let's take a look.

Continuous monitoring

All portions of a large broken-down application produce numerous logs that require an in-depth analysis. This makes it crucial to have a crystal clear monitoring plan in place. As far as the individual microservices are concerned, you can use service error and response time notifications along with dashboards to conduct an overview and facilitate continuous monitoring.

Getting all teams on par with each other

All the teams involved need to be on the same page before you transition to a microservices architecture. Even though the teams can be independent, it's important to note that shifting to a microservices architecture will also create a monumental shift in the company mentality and overall culture.

Some key essentials to prepare beforehand include logging formats, documentation of shared API, and communication standards.

Define target architecture

Lack of proper designing and management of a microservices architecture can create chaos instead of sticking to its purpose, reducing the software landscape's complexities. Therefore, always define the target architecture and ensure consistency across all microservice data. You might want to consider frequent network upgrades to avoid in-service traffic.

The major challenge in a distributed environment is the vast number of moving components within the systems and subsystems. The components are constantly changing, and several services interact with one another at the same time.

Let's consider you manage different teams continually working on various areas of your systems and subsystems, deploying several times a day. If you were unaware of the changes made by your team members, you might notice some negative impacts if thorough testing is not performed.

This becomes highly complex, and the rollbacks are typically quite severe in the event of an error. Due to the dependency tree, eliminating one of those microservices from the system can be challenging, as doing so frequently requires reverting other deployments that are dependent on it. Therefore, it becomes crucial to perform microservices testing.

Following are the three strategies that will make your microservices testing even more effective.

• Identify high-risk microservices: Automation testing is part of the continuous integration and continuous delivery (CI/CD) process. Load testing is crucial for large-scale microservices, as other sorts of testing can be complicated and time-consuming, such as integration testing and microservices security testing. These types of testing can take time and often slow down the CI/CD pipeline.

To mitigate risks later, you can check for high-risk microservices and thoroughly test them early in the cycle. This can take more time, but it will be effective by reducing issues later in the process.

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• Implement service virtualization: Service virtualization is a technique for simulating the behavior of various services and components within the software. First, you need to create a microservice with the required URLs. Following that, the URLs can accept data and respond in accordance with the microservice specification.
• Create a service level agreement (SLA): Testers, developers, and key stakeholders should be on the same page to optimize productivity throughout the development process. For this, they can create a service-level agreement to ensure that all stakeholders are in sync. Ideally, developers and testers should coordinate to create the SLA document.

The test pyramid for microservices testing explains what types of tests are covered while performing microservices testing, how they cover different areas of your software, and how they interact.

Unit tests are at the bottom of the pyramid because they are cheap, fast, and easy to develop. As we move upward, the tests become more complex. They are also more expensive and slower to build and maintain.

Functional tests usually have more code lines than other tests, but they are easier to group. Finally, there are integration tests, which interact with other entities. You can use end-to-end (E2E) tests to test your entire system or subsystem, which requires a lot of configuration.

Numerous tests are available, but the key is determining how to evaluate specific functionalities. Sometimes testing at the unit level is enough, but it is not possible in a few instances since the feature is too complex or unreliable to test at lower levels.

Testing strategies for microservices should aim to provide coverage to all layers and those in between. At the same time, they should also aim to stay lightweight. Let us now take a detailed look at the most crucial types of microservices testing.

Unit Testing

The core purpose of unit testing is to test each function or unit. Testers have to determine whether every single piece of code is working as expected. Usually, automation, testers, and developers create unit tests.

While unit testing, a good rule is to write tests as soon as you make a new addition to an existing program. This way, it won't be necessary to turn over the entire code if it grows. Implementing CI/CD would prevent the deployment of new builds until the test passes.

A solitary unit test would work with collaborators and gateways without touching the network. It will also work with repositories if you don't have to perform integration tests. But if you're working with domain logic, it is advisable to conduct a sociable unit test. After all, isolating is not a possibility here due to state-based objects.

Besides finding bugs and testing business logic, unit tests help identify design issues. It's not new to testers that leaving the code uncovered will lead to architectural problems later on. But when you run unit tests with microservices, you can refactor them since it reveals issues in the early stages of testing.

If you don't write unit tests, not only will you increase the possibility of making a blunder with changes, the architecture will become more confusing and complicated. However, even though unit testing assures the correct working for individual portions of the code, testers need to determine whether the code works well. That's where integration testing comes into the picture.

Integration Testing

If you're looking for a methodology that guarantees the successful interaction of a software product with different systems by helping you simulate user actions, integration testing is the way to go. As a result, the costs of correcting defects lower drastically. Integration testing also reduces the human factor impact and prevents critical errors from occurring during operation.

Checking a particular service against laid-out business requirements is one of the main ways we can use integration tests. Instead of trying to test the business logic through business cases, reproduce the main ones for a particular service. This way, you can easily ensure that the service works according to the requirements.

• Persistence integration testing: It helps testers ensure that the schema the code assumes matches the one the data store has readily available. Most data stores face network failures and timeouts due to their existence across network partitions. Persistence integration tests help verify the handling ability of integration modules for such shortcomings.
• Gateway integration testing: Gateway integration tests eliminate mismatches in requests and responses, faulty SSL handling, missing HTTP headers, and other errors at the protocol level with one of the finest granularities feasible.

Component Testing

Component testing refers to a subset of acceptance testing that examines the behavior of a single or a set of microservices in isolation. Testers substitute services with mocking or simulated resources.

In-process component testing involves the test runner exiting in the same process or thread as the microservice under test. You can even run the test without a network, thanks to the offline test mode that mocks all dependencies. This type of testing works only on a single microservice component.

Out-of-process component testing involves the unaltered deployment of a component in an environment with stubbed-out or mocked external dependencies. This type of testing works on any component size, including a single microservice component or one made up of different microservices.

End-To-End Testing

End-to-end testing is responsible for testing the entire system’s behavior. The granularity of the interaction of end-to-end tests is the most coarse. It gives the confidence of an entire system working without hassles that don't come from only separately checking the services. The idea is to step into users' shoes and ensure that the software product fulfills their expectations.

In a nutshell, end-to-end tests use business logic like integration tests, but the latter does it in isolation, whereas the former conducts it across a system-wide range. All in all, end-to-end tests determine whether the application satisfies each request the end user makes.

Performance Testing

No matter what exchange protocol you're using, the information exchange speed among applications will eventually decline. This makes load testing a crucial part of microservices testing. Performance testing, in this case, means determining the system's reference behavior. This involves testing reliability or stability by identifying factors affecting loads, such as server restarts and memory leaks for long-term use.

Another part of performance testing for microservices includes stress testing that checks an application’s or a website’s tipping point under a high load over a time span. It also plays a crucial role in determining the reliability of APIs, applications, websites, and other web resources. Testers also assign an enormous job to the system to test and monitor its endurance. Sometimes, they may assign empty tasks to check a system's behavior in a scenario with zero loads.

Before beginning performance testing, thorough planning and research are mandatory. Testers need to collect data such as peak-hour traffic, session duration, and information from analytic tools.

Contract Testing

Contract testing is one of the most undeniable forms of testing that goes hand-in-hand with microservices. It is a technique that involves checking all apps separately to test an integration point in a distributed environment. It communicates a message that should adhere to a well-documented set of rules in a contract. The integration points are supposed to follow an agreement or a standard contract.

With contract testing, any microservice system can’t escape modular testing. It makes up for numerous integration testing loopholes and ensures that a system works just fine as a single unit. End-to-end integrated tests are relatively slow, thanks to a data preparation setup, and testers have to run them serially.

To ensure effective microservices testing, you need to make additional efforts from the start, such as managing numerous repositories, each with its database. However, while performing microservices testing, the following challenges may arise.

• To develop effective integration test cases, a quality assurance engineer should be well-versed in all software services. Analyzing logs from several microservices can be cumbersome.
• It can be difficult for a software architect to redesign an application in line with microservices, especially for a large organization with complex systems.
• The complexity of a software product is directly proportional to the number of microservices delivered or added by the product.
• Microservices allow developers to rely less on a single programming language, improving flexibility. However, you will have to deal with the hassle of maintaining several libraries and database versions.
• With many microservices available, it is essential to prioritize these services in resource allocation. You cannot manage to launch an excess amount of resources in a microservice team that is responsible for basic functionality.

In this section of the microservices testing guide, we list down a few best practices for testing microservices.

• Specify and execute the appropriate level of tests, such as static code tests, unit tests, integration tests, component tests, and so on.
• Check the proper security of the services.
• Evaluate the system's performance.
• Test how the complete system reacts when one of the services fails.
• Check if your system is automatically identified when it starts up.

The buzz around microservices doesn't come as a surprise. As we already know, software applications have been becoming more complex. In a world where people wake up to applications and see them the last thing before sleeping, it's no wonder they are becoming challenging to manage, maintain, and update. The microservices architecture addresses this issue with a brand-new development approach.

Not only is testing microservices more crucial than ever, adjusting our testing techniques according to the current development model is also the need of the hour. For that, you need a robust testing tool that has proven to offer excellent results in the past and has an impeccable global trust rating.