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In this Blog Post we are going to discuss performance testing in production. Now before you think we have gone mad and lost our minds completely this is not as crazy as it sounds. Production is an environment that: All the things you spend a significant amount of time getting right in your performance testing environment and that can be difficult to achieve. Therefore, it seems like the perfect environment to performance test in.

The growth of a code base is unpredictable. To account for this uncertainty, we call on everything we've learnt in the last x years about how to scale an application effectively: adopting naming conventions, creating file and folder structures, using the latest patterns, and producing sensible abstractions. These actions add up over time. Eventually, you'll mentally high-five your past self for having taken the time to do them ✋.

Plenty of development life cycles are involved in a software project, so selecting the correct one becomes difficult. Software Development Models should be selected wisely by looking at the budget, team size, project criticality, and criticality of the product. Choosing the suitable model will improve the efficiency of your IT projects and manage risks associated with the software development lifecycle.

We’ve all heard about the significant WhatsApp breakdowns that have happened in the recent past, during which the app was unavailable for the public for an hour. However, from a technical standpoint, WhatsApp returned in less than an hour. What would have enabled the engineers at WhatsApp to quickly restore the services? Technically speaking, the team experienced an extremely stressful production failure because of this.