Azure DevOps is a modern-day tool used for version control and trouble-free team management. An individual can manage his entire team with a minimum of a browser as a requirement. The team can easily be part of different countries and manage their activities without any delay. The development team can be in one country, and the testing team can be working in another country. Even If the management has trust issues, the Azure Audit does an audit of each activity that the team is doing, and the management must only worry about cross-country chatting and financial management.

The following types of testing are mission-critical for ensuring the success and reliability of your software:

1. Unit Testing with Azure DevOps
2. Integration Testing with Azure DevOps
3. System Testing with Azure DevOps
4. Functional Testing with Azure DevOps
5. Acceptance Testing with Azure DevOps
6. Smoke Testing with Azure DevOps
7. Regression Testing with Azure DevOps
8. Performance Testing with Azure DevOps
9. Security Testing with Azure DevOps
10. User Acceptance Testing with Azure DevOps

1. Unit Testing with Azure DevOps

Unit testing is breaking the code into its parts and testing each separate code one by one. This testing technique should never be confused with any other testing technique. This is because unit testing is like laying a brick. Brick by brick, the developer will lay code and test each code unit; this is what unit testing is all about. Azure DevOps creates version-controlled parts of the project; they can be assigned, and the automation tests can be tested using a version-controlled build. It also provides the user with the ability to have a view based on recent pipeline activities and control access to various stakeholders.

Fig 1. Pipelines in Azure DevOps

2. Integration Testing with Azure DevOps

Integration testing establishes testing techniques for when the individual bricks of code are laid together to test the data movement and failure points when separate developers merge their code together. Since each developer is separate, they can make fatal flaws in how the code blends together. Terraform is a recommended tool from the Azure team for such chaotic activity. The tool allows the user to create their own customised configuration files and allows the developer or tester to test the ability of their code to work with these config files, along with an additional static code analysis feature. For more information regarding Terraform, visit their website, Terraform by HashiCorp. Another cool thing about Terraform is that it is Datadog-ready.

Fig 2. Integration Testing flow using Terraform

3. System Testing with Azure DevOps

System testing tests all the modules together and is closely related to integration testing in the sense that all modules are integrated together to do a full system QA. Azure DevOps allows integration with various service providers. The workings of this are already mentioned in integration testing. Another nuance of system testing is that the testers may not have the necessary understanding of how the code works. It is divided into functional and non-functional testing.

Also Read: Testing Assistive Technologies in a Product

4. Functional Testing with Azure DevOps

Testers like to fondly call functional testing feature testing because it’s exactly that. The tester tests all the features of the individual module and sees that the features that you intended to have in the software are there in the product. A few years of experience will tell you that Azure DevOps is a lifesaver in terms of linking manual test cases with bugs, PBIs, and feature requests. The Azure DevOps and its rich UI provide a very good mapping of individual features of the product, which allows newbies to join the team to understand the pros and cons of the product within a 60-day period for the development or testing team. Some of these details can be used again by automation to conduct regression testing.

5. Acceptance Testing with Azure DevOps

Code must be accepted in the context of business, user requirements, regulation, the vision of the developers, and feedback from the testers. Just like the Azure DevOps functional test. Azure DevOps is good at keeping track of users’ use cases, scenarios, and even edge cases. Every idea from every individual on the team can be tracked and used at any phase of the project to get a customer-centric product. Standardised tests in the context of regulations that will be applied to the product can also be added to plans in Azure DevOps when they need to be conducted.

6. Smoke Testing with Azure DevOps

This is simply to check or test whether the build is stable enough or worthy enough to do a sanity or regression test. The plan will mostly come from years of experience from previous releases or simply from a list of critical functionalities that should be working, based on the consensus made by the management on what should be working.

7. Regression Testing

Smoke tests and sanity lead to regression with regular intervals to submit a bug. The entire code is under scrutiny. Azure DevOps can help in creating manual tests in a flash based on queries from in-sprint QA and years of experience in testing the product. Azure DevOps helps in creating the test plan and managing it at the time of execution with the help of filters and neat charts that provide feedback to management and the tester about their progress. What shift managers fail to manage in factories, Azure DevOps does in a flash: employee engagement when the work is in progress.

8. Performance Testing

Performance testing is a test to know whether software performs at scale, on a good foundation for speed, and to remove bottlenecks whenever developers and testers identify bottlenecks. The example provided below is based on a tool of preference based on popularity. Ex: JMeter and test engines connected to the virtual machine and various other tools and app services to conduct performance testing using a dashboard from Azure DevOps Performance testing is simple with Azure DevOps.

Fig 3. Load testing flow in Azure DevOps

9. Security Testing

Test the HTML and JavaScript code; for other cases, it’s different, for vulnerability to threats, security loopholes, risks, and emulating an actual hack or attack. Pen testing is one example of security testing. Security testing involves adding common CVE-identifying tools to a Kali Linux machine, adding them to Azure DevOps using Azure agents, running security tests, and providing feedback using Azure charts using data available to Azure DevOps.

10. User Acceptance Testing

Code must be accepted in the context of business and user requirements, as well as based on regulations, by the end users. Support engineers love it because it integrates well with the sales force. Continuous cooperation among support engineers, in-sprint engineers, and regression of manual and automation can constantly happen. They can quickly interact with urgent changes and ensure that the code is stable after testing.

Conclusion

Based on the above description, Azure DevOps is a tool that allows a wide range of integration with tools of maximum importance in the development and testing of a new product. Along with it, it has control over the process of development and testing with neat features like version control based on Git and Team Foundation. Everything is audited. The dev team, management, and product owners can all be in sync with the latest features and details. Since Microsoft owns almost everything related to IDEs, Git, and cloud infrastructure, it is going to be the future of everything in development, at least for the foreseeable future.

The post Empowering Testing Excellence: Exploring the Synergy between Azure DevOps and Diverse Testing Techniques appeared first on Indium.

In a microservices architecture, an entire codebase doesn’t have to be rewritten to add or modify an application feature. Organizations thus reduce time-to-market for their applications and products. Debugging and testing applications are simpler too, and it helps organizations significantly improve their rate of delivering error-free applications.

However, with microservices, testing is not straightforward.

For starters, each independent service is communicating with other services in multiple and often unexpected ways. Dependency is one of the challenges: while each microservice must function on its own, it’s not uncommon for one part of the system to access data managed by another (known as data sharing). New dependencies emerge as new features are added. A microservices architecture must be able to handle potential issues (database errors, network congestion and latency, service unavailability, to name a few) with increase in the number of services.

To test microservices, software testing companies must be aware of not only an isolated service but also its dependencies and build their test strategy accordingly.

Test Automation of Microservices

AI-enabled test automation of microservices helps create reliable tests, thereby reducing the time for test creation, analysis and maintenance. The tests help check inter-service communication, test communication pathways and more.

The following strategies could be employed to test microservices:

• Handle each service as a software module
• Identify the important links in the architecture and prioritize testing them
• Do not assemble the microservice architecture in a small-scale test environment
• Test different setups
• Make the most of canary testing for new code

Approaches to Microservices Test Automation

An effective test automation process requires automating at three levels namely unit, service and user interface (UI).

However, with microservices, testers must not only be cognizant of the service they test but also its dependencies. Also, due to the granular nature of microservices, boundaries at different levels must be tested, too: unit, component and integration.

Unit Testing

It helps validate the code of application components to ensure they comply with the business logic.

This is usually the stage where the largest number of individual test units are processed and is especially vital in microservices testing.

For effective and accurate microservices testing, it’s essential to limit to small test units. Large units could result in randomly complex tests as the services maximize resource consumption with time.

Open-source xUnit testing frameworks or VCR recording code functionality could be utilized to perform unit testing.

Integration Testing

For microservices architectures, integration testing is conducted to verify the communication between subsystems that interact with external components such as data stores and other services.

Since microservices communicate and execute together to complete a business goal, tests must examine requests flowing through the services to ensure communication channels function as intended.

Test automation suites such as Katalon Studio or open-source Selenium could be used to run integration tests.

Component Testing

As the name suggests, this type of testing is employed to test a component or the services of an application. The test checks microservices by forming mock services that resemble the deployed services.

It helps validate the communication between distributed services and their dependencies such as a database and third-party components.

Component testing can be performed with the help of Hoverfly and similar API simulators.

Contract Testing

It’s a test strategy that helps validate if two separate systems (two microservices, in this case) are compatible with each other.

The interactions between the services are stored in a contract which is verified to ensure both parties comply with it.

RAML, OpenAPI and API Blueprint are some of the tools that automatically create documentation when an API is defined against a recognized standard.

End-to-end testing

End-to-end testing of microservices helps validate the entire system’s ability to meet business goals irrespective of the component architecture that’s in use. Testers use this type of testing to verify the accuracy of the message moving between the services.

The following strategies could be employed when writing an end-to-end test suit:

• Create as few end-to-end tests as possible
• Prioritize personas and customer journeys
• Ensure test data is independent

Martin Fowler, an international public speaker on software development, says: “End-to-end test may also have to account for asynchrony in the system whether in the GUI (Graphical User Interface) or due to asynchronous backend process between the services.”

Java’s JBehave and similar frameworks could be deployed to automate functional testing by using user stories to verify if the system behaves as intended.

Summary

Abovementioned are the tests (unit, integration, component, contract and end-to-end) conducted on microservices to ensure the entire system functions as it’s meant to. Test automation of microservices may not remove issues associated with software testing but it certainly helps expedite the software testing process while making it efficient and smarter too.

The post Approaches to Automating Microservices Testing appeared first on Indium.

At a basic level, microservices make up applications. They’re small and compact files that provide a multitude of services.

They’re programmed to ensure decentralized management (especially for data storage). And they’re designed for quick access too.

We use them in our daily lives, and for a variety of functions. They can be anything from productivity applications, to small games, or special professional programs.

Testing a Microservice

A bundle of microservices make up an application. And it’s important to test each microservice separately and in conjunction with each other.

That’s one of the pros of a microservice. They launch separate of others within an application. And this lets you deploy and test each without problems.

From there on, we’ll need to plan our approach for testing. Specifically, we’ll need to…

• Understand different testing types.
• Understand different testing strategies.

We’ll explore both below. We’ll mention the 5 testing types and the best strategies for each.

1. Unit Testing

While contract testing checks for communication, unit testing checks for coding. It ensures that a microservice does what it’s supposed to do with each test.

And here, a unit represents the smallest possible portion of a microservice that can be tested.

With unit testing, it’s key to test each unit in isolation. After that, units can be tested together (integration testing). And this ensures that microservices collaborate well in an application.

Important Note

This tends to be the first type of microservice testing that’s performed. It’s usually performed during the development process (instead of before deployment).

This makes it a cost-effective form of testing. It aids developers in finding errors early in design, without the need for prolonged testing afterwards.

Plus, the changes can be done quickly – which saves more money.

Testing Strategy

Unit testing is straightforward. It involves taking a microservice, creating a mock object (as a replacement for codes yet to be designed). From there, the unit is tested for proper coding.

There is a multitude of unit testing tools (and for different programming languages). They include,

• Junit (a free tool for Java).
• JMockit (an open-source tool with verification syntax and API).
• NUnit (a framework that works with .net languages).

2. Functionality Testing

This is the beta stage of most apps and software. Here, microservices are tested from a user perspective.

This form of testing can be jammed anywhere in the design stage. Functions can be tested with each microservice. Or, they can be done at the end, testing the functionality of the entire system.

Important Note

What makes functionality testing different from unit testing is the focus. Unit testing focuses on how codes are executed.

It tries to find errors beforehand per microservice.

With functionality testing, the program is handled from an “end-user” perspective. It’s used as if the consumer was using it. The results are then noted down before any adjustments are made.

Testing Strategy

Functionality testing should be done after unit testing for smaller apps. For larger ones, we recommend delaying the process to the end.

It can, however, be executed for larger apps through the design process – by testing the functions of unrelated components separately.

3. Integration Testing

What happens after a unit is tested? What happens after functionality is checked?

Several units are banded up together and tested. This is called integration testing, and it checks as to how each unit communicates with each other.

The focus here differs from unit testing. While unit testing checks for functionality, integration testing looks for defects when multiple microservices interact.

Strategy for Integration Testing

One is called the “Big Bang”strategy. It involves testing all microservices together after development is complete.

This strategy saves time, ensuring that integration testing isn’t done frequently. But it comes with the drawback of pinpointing errors.

When an error message (or an undesired result) is presented, it’s hard to tell which microservice is at fault. It’s also difficult to tell which coding line is responsible.

Thus, this strategy works for small applications only (ones with a minor amount of microservices – and little upgrades).

As for larger applications, we recommend an “incremental strategy.” Here, microservices are categorized (as to how they logically relate to each other).

Then, they’re tested for proper functionality. While this strategy isn’t as comprehensive as the previous – it works well for large applications that require frequent updates.

4. Contract Testing

A microservice communicates between a client and an API provider. And with a contract test, a developer can tell if any communication issues exist.

Contract testing focuses on setting an endpoint through testing. Tests are done until the desired response is found after multiple tries.

Coding lines are changed in accordance with the results of each trial.

Contract testing looks at the program from an end-user perspective (like functionality testing).

It ensures that a user operates each microservice smoothly and without issues. And if any disruptions happen through the experience, then they’re fixed.

Why They’re Necessary

They’re vital for documenting the final product. Contract testing is what defines the advertised “specs” of a program.

It sets the system requirements, speed, and effectiveness of the app.

As a result, this form of testing is always done after an app is completed. It’s done to ensure that the final product hits the specification goals set by a business.

The Right Strategy

Contract testing should only be done to optimize microservices “per business specifications.” Not every microservice should be tweaked for maximum performance. This should be left to the business to define.

5. End to End Testing

This is similar to integration testing. In fact, it’s a combination of contract and integration testing, only on a large scale.

Here, the focus is on the system as a whole. This, it includes backend systems and interfaces too. And what’s being tested is the entire system before deployment.

The goal is to ensure that the entire system works as specified (irrespective of individual microservices).

How This Affects Microservices

Microservices can be tweaked as a result of end-to-end testing. This form of testing ensures that the right code branches are used in a program.

And if there are any missing functions, then the tests check for microservices that can fill in the blanks.

Strategy

This tends to be the longest form of testing in any application’s design.

A good strategy is to create test cases. They should be executed, with the results being compared against the desired outcomes.

This form of testing should be done manually. It’s difficult to automate since the entire system’s components work at the same time.

Its amount of times should be limited. Being an exhaustive form of testing, it can cost a business too much when designing an application.

Creating a Comprehensive Testing Strategy

One of the problems with the microservice design is how you plan to test. You can mix and match the forms of testing you do.

You can also schedule different tests for different times (throughout the design cycle).

Basically, what works for one app may not work for another. Thus, we recommend consulting previous projects when designing a test strategy.

That way, you can fully test your codes with minimal time and financial investment!

The post Testing Microservices? Here’s a Guide on Designing a Strategy! appeared first on Indium.