They say that procrastination is the thief of time. In the world of software development, there are some additional “time thieves” that prevent our teams from developing new features or slow them down as they attempt to fix issues. As software engineers or R&D managers, we take it for granted that our teams spend a lot of their time waiting for compiling, testing, and deploying.

Develop fast, release, learn, repeat. That’s essentially the (not-so-secret) innovation formula, right? Most of us spend our time enhancing the products we have already released. We want to be innovative, releasing new features with the velocity of an unencumbered startup. Yet, we also have customers with quality expectations we need to meet. Guidance on shortening release cycles often centers on adopting agile (or similar) development methodologies. But most companies are already there.

Over the recent years, software development organizations have seen a major shift in where they build and run their applications. Teams have transitioned from building applications that run exclusively on-prem to microservices applications that are built to run natively in the cloud. This shift gives businesses more flexibility as well as quick and easy access to enterprise services without the need to host costly applications and infrastructure.

As new advances in software development have allowed developers to increase their velocity and push out new software at ever increasing speeds, one less measured metric is software understandability. Although it probably seems obvious, when building new software the goal should always be to build software that is as simple and easy to understand as possible.

As most developers will agree, writing code is oftentimes, if not always, easier than debugging. As a simple definition, debugging is the process of understanding what is going on in your code. When speaking in terms of Python, it is a relatively simple process. Every developer has their own personal debugging method or tool they swear by. When it comes to Python, most developers use one (or more) of the following: print statements, traditional logging, a pdb debugger, or an IDE debugger.

Hans Ulrich Obrist once said that “everything I do is somehow connected to velocity”. We couldn’t agree more. As is in most companies, there’s always something affecting your team’s velocity, whether that’s a new work from home routine, a change in budget, or a variety of other reasons. So many influences are out of your control- how do you make sure that your devs are working at optimal velocity?

As they say in the sports world, “instinctively knowing when to run forward, when to ease back, and when to let someone else take over...these are the marks of a great team and a great team player”. Here, in the tech world, we couldn’t agree more.

The modern age of web development that includes modularized, encapsulated web components, has brought us a plethora of tools, technologies, frameworks, and libraries of all varieties. With every such tool that is created to simplify our lives as developers in the long run, there's also a catch we sometimes neglect to consider: the cost of maintenance and performance.