A staging environment (stage) is a nearly exact replica of a production environment for software testing. Staging environments are made to test codes, builds, and updates to ensure quality under a production-like environment before application deployment. The staging environment requires a copy of the same configurations of hardware, servers, databases, and caches. Everything in a staging environment should be as close a copy to the production environment as possible to ensure the software works correctly.
The significance of staging environments
Steps to deploy software include development, integration, testing and QA, staging, and production. At a time when users have little patience for poorly performing apps, finding bugs and software errors is vital for performance. Staging environments test on a near-production level in a non-production environment and can lead to further confidence in the software when in production.Content Continues Below
Staging environments conduct tests that prevent problems in production and thwart poor performance for the end user. As the application gets deployed to the production environment, fewer fixes are necessary.
Tests in staging
Smoke tests and user acceptance testing (UAT) can be performed in a staging environment. Smoke tests check for essential service functionalities, and UAT tests are performed from the perspective of an end user. For example, if a new build undergoes development and integration, a smoke test can confirm the main functions still work properly, and a UAT test can ensure quality from the user's perspective. Tests are performed on the staging environment because if there is a major flaw and the system breaks, the production environment doesn't have to shut down.
Additionally, chaos engineering tests can be implemented in staging environments. Chaos engineering reinforces confidence in the system by constantly trying to break the code. Chaos engineering normally gets implemented in production; however, it is possible to start chaos engineering in a staging environment as practice before testing in production. Chaos engineering can help to earlier identify potential issues software may have in a production system.
Staging environments can be easily created in cloud computing which get deployed into production environments. This can help automate continuous delivery.
Staging environments limitations
Although staging environments provide an additional layer of confidence in a system, staging still has limitations. No matter how well a staging environment replicates the production environment, there remain scenarios that can't be imitated. For example, it can be extremely difficult or impractical to replicate high volumes of traffic to test the application under stress.
If a staging environment is built incorrectly or is poorly utilized, then more problems may occur. If the configurations of both staging and production environments don't match, the data gathered from the replicated tests isn't accurate. Defects could potentially get released to the production environment. For example, code should be stored in the same way in the staging environment as it is in the production environment. If that doesn’t happen the latency test results may differ.
Testing in staging environments in a limited time capacity may create other issues. Data corruption or memory leaks take a longer period of time to show up. To avoid this problem, staging environments should be able to run as long as production environments run.
Alternatives to staging
Some companies choose to skip staging altogether. A large amount of data can be pulled from a production environment, including information that could not be obtained through staging, such as amounts of traffic. If you use data from the production environment to create and maintain changes, it can save time compared to copying, managing, and gathering data from a staging environment. Working within a production environment is faster. There is more upkeep with a staging environment, since new builds and fixes are prepared frequently and would have to be implemented in staging and then in production. However, the choice to skip staging is done at the risk of less confidence in the system, and the possibility of introducing major problems to the production environment.