What is Continuous Testing?
Customers currently demand high-quality software for their enterprises and personal use. Software businesses are implementing Continuous Testing procedures to meet this need, ensuring that the software they deliver to the market can outperform the competition. Continuous Testing in DevOps is a procedure of testing early, testing regularly, test everywhere, and automating. Continuous Testing means undisrupted testing done on a continuous basis. In a Continuous DevOps process, a software change continuously moves from Development to Testing to Deployment. This process helps us to find the risk, address them and improve the quality of the product.
functional testingData preparation involves the process of identifying, cleansing and transforming raw data into meaningful sets of data. Source: Preparing Integration Data
What are its various types?
Unit tests are low-level tests performed close to the application's source code. Individual methods and functions of your software's classes, components, and modules are tested. Automating unit tests is often inexpensive, and a continuous integration server can execute them quickly.
Integration tests ensure that your application's various components and services are compatible. It could be as simple as verifying the database's interaction or ensuring that microservices interact as planned. Because they require various application portions to be up and running, these tests are more expensive to conduct.
API Testing is a type of software test that demonstrates Application Programming Interfaces. API testing ensures that programming endpoints are functional, dependable, fast, and secure. API Testing, as opposed to traditional user inputs and outputs, employs software to make API calls, obtain information, and record the response of a system. API tests differ from GUI tests in that they do not focus on the look and feel of a program. It focuses more on the organization logic layer of software architecture.
System testing validates the entire and fully integrated software product. A system test is used to examine the end-to-end system specifications. Typically, the software is just one component of a more extensive computer-based system. Finally, the software is linked to other software/hardware systems. System testing is a collection of various tests whose single objective is to put the entire computer-based system through its paces.
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What are the best Continuous Testing Tools?
Selenium is an open-source software testing tool. It supports all the leading browsers like Firefox, Chrome, IE, and Safari. Selenium WebDriver is used to automate web application testing.
Appium is a mobile testing framework similar to Selenium. It's a well-known mobile testing framework that many teams have used.
Kobiton makes it and Mobile/IoT DevOps a reality. Prevent bugs before pushing code to test, perfect your mobile app or website with Functional, Performance, and Visual test automation, resolve issues before releasing to production, and rapidly deploy and kick off tests with seamless CI/CD integrations.
The qualities of the best tools
- A planning tool: Wekan board and similar planning tools provide the functionality to track user stories, epics, and tasks.
- A version control system: Version control systems, like GitLab, allows development teams to track, collaborate and communicate on versions of the source code.
- A build tool: Gitlab and similar tools to build and run Unit and Functional automation tests from the source code.
- A testing tool: Tools like Robot framework, and Selenium insert the tester into this Continuous Delivery pipeline providing test validation against Wekan board issues and connect into source code repositories to streamline manual to automated test scripts.
The Imaportance of Continuous Testing
It improves the initial authorization of software faults and problems. As defects are identified early, the company's costs are lowered. A good testing strategy at the start of the manufacturing process allows for speedier recovery of unanticipated errors or bugs in the product. Continuous delivery necessitates it, which can only be accomplished through test automation. The use of automation technologies reduces the amount of time spent on Testing. Automation tools help the testing team and the whole product development focus on Continuous Development.
- Early Defects, Less Cost: It helps in the initial authorization & determination of software defects/bugs. As early bugs will fix; the cost to the company gets reduced. A suitable testing process in an initial stage of production allows faster recovery in case of unexpected defects /bugs in the product.
- Easy Automation: A Continuous delivery model requires it, possible only through test automation. It coordinates Quality Assurance efforts to balance the speed of DevOps, assisting developers to deliver unique software features quicker.
- Reduce Testing Efforts: Automation tools reduce the testing efforts. With the focus on Continuous Development, automation tools serve the testing team and overall product development.
How is Continuous Testing and agility related?
It is the technique of running automated tests as part of the software delivery pipeline to quickly get feedback on the business risks associated with a software release candidate. It improves and expands test automation to keep up with the complexity and speed of current application development and delivery. All software providers should use Agile as their delivery model. True agility refers to an organization's ability to quickly shift emphasis and respond to consumer input or market developments. It also allows teams to experiment with new ideas and solutions. It facilitates this agility by promoting a shift-left approach that emphasizes the usage of test automation early in the development cycle. Shifting to the left creates a continual feedback loop, allowing teams to respond to issues and improve team communication.
Check the quality of the software as a part of the continuous delivery process, with early and often testing. Click to explore about our, Role of Continuous Testing in Continuous Delivery
How does Continuous Testing work?
Developers write the code and commit, it goes to version control/SCM. It is the first stage in DevOps. It manages the code written by developers. Next phase is Continuous Integration. Continuous means rather than waiting for all the developers to commit code and then build and test it, in Continuous Integration approach, the code is merged into the main branch. Then use Jenkins/Git to create an build, and after that, test code in a virtualized environment. It saves a lot of time in moving the code from Dev environment to Test environment without waiting for all the developers to commit.
Performing Continuous Integration is of no use, if not testing continuously. So the next stage is it, where QA automates test by writing scripts like Selenium, Robot Framework and run it through Jenkins/Git in a virtualized environment. If the test fails then stops here and sends back the issues to the developers. If the test passes, move ahead for the Continuous Deployment.
What are the Stages of Continuous Deployment?Continuous deployment stage we have two parts -
- Configuration management
Consider there are five servers are up and running having same libraries, tools on them. Many of them are from an older background having shell scripts to do this job. Now to have exact configuration on 100 of servers, using shell scripts, it will be pretty much complicated. Therefore, require a tool to automate the job. Puppet is the most popular tool for Configuration Management. The second part of Continuous Deployment is Containerization, in this stage as create a test environment to run application and test. It’s used for testing purpose; provides virtualized environment to run script like Selenium scripts to test application. 90% of organizations use Containerization only in the testing stage, only 10% of the organization use on production.
In 2015 Docker 1.9 came stable to run on production as well. For example, to run some application on production for the shorter duration, quickly create a container on prod and run those applications in that container, and when don’t need those applications anymore, destroy the container. Deploy application; monitor to see whether the application is performing as desired and the environment stable. Continuous Monitoring determines when a service is unavailable, understands the underlying causes, and reports the issues to the developers. Nagios is one of the most popular tools used in Continuous Monitoring. So this is how all stages are connected.
A process that continuously searches the web applications and the IT infrastructure for possible vulnerability and security risks. Click to explore about our, What is Continuous Security Testing?
What is the Continuous testing framework?
It refers to a collection of development tasks, methods, and technologies. It is impossible to create a one-size-fits-all its architecture for any technical organization. However, you may identify the essential components of any framework and then determine how they relate to your specific situation.
CI stands for continuous integration, a software development method in which developers submit code to a shared repository daily or multiple-times-a-day basis. On the other hand, automated build testing is essential to continuous integration since DevOps-minded teams need to detect problems and bugs in code before it goes into production.
Individual units of source code, sets of one or more computer program modules, associated control data, and actions are checked to determine suitability for unit testing. Unit test is designed to perform the test on each unit of the software code. Save money and time in the early stages of the development lifecycle can be done by Unit testing.
Performance testing is carried out and provides information to clients about their application's efficiency, reliability, and scalability. It's typically used to track a product's or feature's speed, dependability, and total uptime. On the other hand, software performance testing is critical because it's one of the best ways to figure out how your customers will react to your service. Furthermore, performance testing is frequently carried out in staging and production settings, allowing you to spot earlier issues.
Integration and Functional Testing
In the sense that you are testing individual components of a system, integration testing is comparable to unit testing. On the other hand, integration testing merges these separate pieces into a group that can be tested together. This type of Testing will identify potential failure points and weaknesses amongst integrated pieces, ideally before they are put into production. This is frequently associated with functional Testing, in which pieces of a system are verified against the system's requirements, expectations, and specifications. Businesses need functional Testing because they need to know precisely how a system should behave and whether it responds correctly and consistently, especially in production.
Software engineers may frequently do end-to-end tests to verify that data or workflows travel through an application or service. End-to-end Testing is critical for a product's overall reliability. On the other hand, End-to-end Testing will rarely benefit you in determining the precise source of a mistake or incident; instead, it will simply inform you that something is wrong.
Acceptance testing will be the last test you perform before releasing a feature or service to production. The core purpose of this Testing is to check the business requirements and system's functionality, whether it is correct for delivery or not.
Smoke testing plays a vital role in software development, in which the DevOps organization has to figure out the critical elements of a system and then start testing them. Customers will benefit from a high level of reliability if the most crucial processes and operations inside an application or service are continuously tested.
"Chaos testing is all about", Creating a state of chaos in your staging and production settings to see how a system reacts to unknown circumstances and stress. Chaos testing regularly might help you identify issues in your infrastructure and apps that you may not be aware of. Conducting stress tests in advance and incorporating chaotic engineering as a regular practice can also better-prepared engineers for real-world issues in your production environments.
It involves automating any or all of the tests outlined above. Otherwise, you'll spend all of your time recruiting new QA engineers, who will spend their time manually testing the overall system rather than developing new functionality for customers. It's important to remember that automated it must be beneficial to everyone involved with your products — your consumers and your employees.
It requires consistent delivery. We will deploy to production more frequently and with fewer defects, if you know that code works as quickly as it's continually integrated into a shared repository. You may start delivering value to clients daily with more automated Testing and a commitment to continuous manual Testing throughout the software development and release lifecycle.
CI/CD is a collection of practices that enable application development teams to deliver changes more reliably and regularly. Source: Continuous Integration and Continuous Delivery
Benefits of Continuous Testing in DevOpsThe benefits of continuous testing are below:
Reduces Application-bound RisksFaster turnaround time is a crucial benefit expected from it, but ensuring a risk-free output is similarly essential. At whatever point the code changes, there is a right amount of scope for errors. It prompts to a severe effect on the application or software and increases costs while rectifying towards the finish of the development process.
Helps to bring ConsistencyIt is made viable with Test Automation, in keeping consistency with the testing procedure. It helps to keep each system and subsystem on a consistent stream with Continuous Integration. It helps in giving a configured environment that is robust and sustains the required configuration for comparative tests.
Enable Faster ReleasesContinuous Integration executed to allow quicker and frequent releases. When tests are automated, code is tested thoroughly and always, enabling the development teams to convey assured results even at speed. With it, teams release cleaner code on a reliable basis, at speed.
Improves Test CoverageDo you require test coverage for code? It accomplishes more test coverage, as the tests automated and executed right from the earliest of the development process. It guarantees to cover every potential failure, and evaluates all the features. Maximum Test Coverage is a great relief for the testing and development folks.
Enables more TransparencyConsidering that testing is continually done and right from the earliest starting point; it empowers greater visibility for the testers and the developers. It enhances value to the overall software/application development process. Moreover, the test automation tool enables accurate reporting across the dashboard, increases the straightforwardness of the process. In the end, the team is kept informed on every error, success, and failure of the tests.
Cuts downtime took for Code ReviewIt empowers quick feedback and encourages coordination between the testing and development teams. This way, Continuous Integration, and Version Control System cooperate and decide when to start a merge request. The system estimates when the tests pass successfully and related requirements are met. It drastically decreases the time taken for Code Review.
How to adopt it?Embed quality in applications; teams add more modern testing practices in the form of small quality checks performed throughout the application pipeline. It enables small sections of code tested continuously. Test automation not always the first thing to be tackled. The reason is that even after API tests and GUI tests automated and integrated into a Continuous Integration agent, those tests have dependencies — test data, interfaces, and environments — that have to be satisfied before executed.
Virtualized EnvironmentsIt means testing more frequently. That means hitting multiple environments more frequently. And that represents a problem, a bottleneck if those environments are not available all the time. How to coordinate testing through multiple environment owners that may not always keep their environments up and running for you to test against? Virtualizing those environments allows to test code without having to worry with areas are not changing (i.e., other systems and environments).
Test Data ManagementHave the right data and the appropriate diversity of data for positive and negative scenarios. Diversity in production is difficult— that is critical. Therefore, synthetic data generation is the way to go to achieve it with the highest levels of confidence having no personally identifiable information is at risk in the data. Also, cannot bring data from production, condition it and provision it at the speed, application pipeline requires.
Test AutomationIn an entire application pipeline, today’s scripts fail due to things not related to the application code, no one trusts the results. Need reliable test automation to adopt it.
Pipeline OrchestrationThe backbone, everything tied to it, integrated with automation suite. Understand how it works, how to interpret results and how to make it scalable. It sets up it in a manner to integrate it attributes within a pipeline. Make sure it’s transparent, and everyone has full visibility into what’s run through the pipeline. It’s an automated workflow tool which runs all of automated tests and fully integrates with code deployment activities as it moves through the pipeline. As part of any DevOps adoption initiative, it is unrealistic to expect to get to it without the reliability and speed of a standardized and automated pipeline.
API TestingIt enables the alignment of the testing pyramid. Organizations strive to test as much as the unit and API levels as possible and minimizes reliance on UI testing. To adopt it, embrace the concept of the testing pyramid properly, strengthen Unit and API testing, and reduce reliance on UI testing, especially for business logic testing.
Performance/Load TestingEven when applications functionally useful, must radically change the way think about Performance Testing. As shift testing to the left, testing earlier in the life cycle, with less application and infrastructure components, means the tests are smaller by nature. But they are also much higher in volume. Make that capability accessible to everyone across all Agile teams. That means all developers and testers alike create a performance test and run it by themselves, without having to send any requests to anyone.
Continuous Load testing is a risk management activity to transpose more significant business risks. Source: Continuous Load Testing
Security TestingDevelopers need to be clear on the expectations around the code's state to be allowed or denied to be released. They must receive proper training and tooling to measure how secure their code is. Education of developers must be ongoing, as the application security area is always evolving. The application pipeline must be set up to run the static analysis automatically, dynamic analysis, and software composition analysis, so that any security issues are caught and highlighted, then those must be used as an opportunity to make developers better. Security testing needs to happen at every step of the life cycle.
Acceptance of TDD And BDDTake the acceptance criteria for each user story and create the tests to ensure those are met. This keeps testing focused within the sprints and ensures developers develop what the business expects. Over time, teams will define much more detailed acceptance criteria, which requires tests to be more comprehensive.
Automated Test GenerationThe activity of manually designing and writing manual tests or automated test scripts is a bottleneck. Automatically generate the new acceptance-level tests for manual and Automated Testing at the beginning of the sprint; developers start checking in and merging the first working pieces of their code, and start running tests in an automated fashion. This gives the ability for developers to get immediate feedback on the quality of their code as they check it into source control.
Requirements EngineeringInclude all SDLC stakeholders into the Continuous Testing journey. Find a better way to communicate and collaborate on the requirements. Include requirements engineering into it initiative, the smoother the journey will be, because team members work with the same understanding from the beginning.
Feedback LoopsThese are critical to successful it. Dashboards in Real-Time, must be automatic and entire team must have access. Feedback loops across the entire SDLC, not just production, as a compass to navigate its transformation.
Continuous Testing always viable to perform all the tests every time, so for its strategy to serve. Source: Continuous Testing for Data Integration
What are the best practices of Continuous Testing in DevOps?
Here is the list of best practices of it. Each one is discussed in length below
- Treat Test Code as Code
- Employ a Risk-based Test Automation Strategy
- Provide Fast Feedback
- Generate and Maintain Test Data
- Ensure Access to a steady Lab and Test Environment 24/7
- Improve the relationship between tester and each developer
- Make automation a priority
- Get small Design
- Keep track of everything
- Get the right continuous testing tools
- Develop a system to display results
Treat Test Code as CodeDevelop test code the correct way from the start, mean the difference between a high-value test suite and a time-consuming, flaky and wasteful one. To empower it, treat test code the same as production code.
Employ a Risk-based Test Automation StrategyIncorporate a methodology into it procedure to identify, evaluate and mitigate the causes and consequences of terrible user experience. Consider time, value, affect, history – and don’t ignore developers’ gut instincts.
Provide Fast FeedbackIt creates vast amounts of data that give testers and developers new insight into explicit issues and provide managers with dashboard-level perspectives for “go, no-go”essential leadership.
Generate and Maintain Test DataBanks, insurance companies, healthcare suppliers and anyone with a mission-basic application need to test against real-world conditions. Provide QA testers and developers with high-esteem test data and guarantee that it evolves with the applications.
Ensure Access to a steady Lab and Test Environment 24/7A steady lab implies that all platforms associated with it, together with supporting test environments, 3rd party tools, and APIs, working every minute of every day with close to zero downtime.
Improve the relationship between tester and each developerKeep the teams small, encourage inter-team collaboration, and make reports easy to access and share online.
Make automation a priorityDo not remove all manual testing tasks, but adopt an “automated first” mindset. Focus that on areas that will be run repeatedly. In essence, set up the plumbing first to let the water flow later without any worry or concern about leaks. Map out SDLC and identify automation opportunities.
Get small DesignBreak work down into smaller increments that are easier to test after coding and design. This makes easier to automate the tests, and much more readily deployable.
Keep track of everythingUse metrics and set pass-fail criteria. It immediately identifies if things are working or not.
Get the right toolsTo develop, test and analyze continuously. Pick the best-of-breed tools that work together in a way that incorporates easily into the working environment. Choose tools that have community-based support where everyone shares challenges, solutions and exciting use cases.
Develop a system to display resultsDo deep dives into results, to know if code is working and where the gaps are. Define KPIs and acceptance criteria and make them quantifiable. Create dashboards to track the KPIs, including a baseline and subsequent changes.
Continuous Testing is the procedure of executing automated tests as part of the software delivery pipeline to acquire immediate feedback on the business risks associated with a software release candidate as quickly as possible. It involves executing the right set of tests at the right stage of the delivery pipeline—without creating a bottleneck.