It takes time for developers to accommodate changes in line-of-business requirements, which continually causes...
frustration among the businesses that software applications support.
The traditional approach to software is to have periodic releases and to assign changes to a specific release on a future date. This helps developers organize changes to applications in a controllable, efficient way. It also introduces delays. In an internet-driven, commercial model, line department frustration in software delays is at such a peak that software development techniques have evolved to speed up application modernization. Continuous deployment is the processes and tools that guide software dev and ops teams to make changes in production applications without losing software integrity. In the broadest sense, continuous development is an integration problem, because component-level changes stream in constantly.
Rapid development or rapid deployment tools help development organizations think of software enhancements, much like an assembly line process where changes simply integrate into a continuous flow.
In theory, software is more responsive to business needs. However, continuous deployment can lead to catastrophic software errors or outright failures. How do you test software in a continuous development and deployment world? Continuous integration (CI) begets continuous deployment, with testing at the heart of its success.
Start with continuous testing
Continuous testing isn't just a tool; it's a model. Continuous testing requires three things. First, match the changes that associate with specific applications/components to enable targeted testing. This isn't simple: Modern applications are highly integrated, and updates can flow from one application to another. Second, establish a test pipeline for the collection of changes that affect common components for the whole development-to-production progression. Organize changes so that you don't make a change to components already updated from prior modifications. Third, the procedures and data used for testing must enable a complete assessment of the change, not a partial understanding of it. Also, regression test the impacted components to ensure that one update will not break another. The first and second of these testing points upstream of continuous deployment are part of continuous integration, and the third is automated testing.
Because CI introduces changes into functioning applications dynamically rather than by periodic release, it is the foundation of successful continuous deployment. The test process qualifies new software to advance toward the final step of production. The tests are built on use cases that describe functional modifications in terms of specific I/O relationships. The line department develops the use cases from the proposed changes, with the aid of either enterprise or software architects who understand the business-to-software connection of the application.
Use cases are a convenient place to frame individual changes that facilitate tests. Rather than attempt to automate a testing process wherein multiple changes to the same components proceed independently, rely on triggers. Component changes trigger the inclusion of use cases that drive testing. Update use cases to reflect all the changes to the point when a trigger initiates a transition into test data development and, finally, testing.
Successful CI depends on the team generating specific use cases that drive specific changes made via continuous development, leading to continuous deployment. Industry trends in development favor use case-driven models. Numerous enterprise software development management tools and frameworks are available, including the Rational products from IBM and Oracle Unified Method, that include use case and testing elements.
Use a broad suite or a test creation tool to convert use cases to test generation. The core activity in testing for continuous deployment is the creation and scheduling of the actual tests not as discrete components, but as integrated applications. A package with the proper scope and features will make CI and continuous deployment work. One popular tool is the Jenkins open source project automation tool, which includes the Blue Ocean CI element. Travis CI and TeamCity are also used for CI pipelines.
For comprehensive continuous deployment, rely on tools that include the ability to generate test data from Unified Modeling Language or use cases and to generate the tests, meaning the tool injects the data into the application under realistic conditions. There are tools focused specifically on the automated testing portion of CI functionality.
Move to automation
Automated testing tools vary in terms of the extent to which they can mimic the applications' actual use, in activity levels and in the location of the users. For example, load testing is sometimes called performance testing, but the user must check the specific features of the automated testing package to determine whether it can actually generate the workloads for true performance testing and reflect the various points of data injection from the real world. The latter is especially important for applications with geographically distributed components, as with cloud-native designs.
Not all automated testing tools check the results of tests either. That's particularly true in cases where the test outcome involves database updates rather than, or in addition to, visible onscreen responses. Applications that have event-driven or message-driven inputs may be hard to test if the message formats are difficult to interpret in an automated package. If you need test result analysis, do a pilot test to validate the tool's ability to decipher responses and validate test results without manual review.
Every business wants software that's responsive to business needs. Continuous deployment practices can only meet that goal if software quality isn't compromised. You can safeguard business operations and security and compliance goals with proper testing tools integrated with modern rapid development practices. To ensure business goals are met, integrate new components to code and test the resulting versions efficiently and thoroughly.