DevOps And Test Automation

• Admin
• 13 Sep 19

To achieve such speed and legerity, it’s vital to automatize all the testing processes and assemble them to run automatically once the preparation is completed within the QA atmosphere.

Specialized automation testing tools and continuous integration tools are accustomed to attaining this integration.This conjointly necessitates the building of a mature automation testing framework through that one will quickly script new test cases.

DevOps Testing Strategy: Tips for DevOps Success

The test cases that are needed to be executed for a specific build ought to be known.
The test execution should essentially be lean.

The QA and dev ought to sit along and establish the areas affected due to a specific build and execute those connected test cases and a saneness test pass.

You also ought to set up specialized code analysis and coverage tools to create certainty and achieve close to100 pc code coverage.

The thought of executing all regression test cases for a test pass is shortly changing into obsolete.

Strategy around testing new options ought to be formalized and the interim builds will be equipped to QA who would, in turn, produce test scripts and run these automation tests
on the interim builds until the code becomes stable enough to be deployed onto the production atmosphere.

All the environments needed for testing ought to be standardized and therefore the deployments need to be automated. Using varied automation techniques, QA ought to be ready to fire automation testing runs across varied cross-platform.

Parallel execution of tests helps in reducing time-to-live, that successively is the crux of a winning DevOps implementation.

Exit criteria ought to be set for every run so once the results of the tests are fed back to the chain, a go/no-go call to Production is taken.

Blocker or essential bugs found ought to be reported and passed through identical chain of events before the code is deployed within the Production atmosphere.

Application Monitoring

QA should also be ready to discover issues early and report them proactively.
To achieve this, they must line up monitoring on the production atmosphere to be ready to expose bugs before they cause a failure.

Setting up specialized counters like response times, memory utilization, etc. can give a great deal of insight into the end-user expertise.

For example, if the typical latency for login is step by step increasing over the varied builds, QA ought to proactively report this issue for optimizing the login code, else future builds
might cause end-user frustration because of high response times.

QA may also use a little subset of existing high priority test cases to be executed sporadically on production, to actively monitor the atmosphere. Bugs like, “This bug seems sometimes” or “Cannot Reproduce” will be caught through this strategy which, in the end, makes the appliance more stable and conjointly gets a lot of glad end-users.

Again, these monitors ought to be designed to run automatically with wealthy reportage (like logs & screenshots of failures, etc.).

Conclusion

Waterfall gave way to V-Model that successively was replaced by Agile because the most popular selection for software system development.