For the last several years, GitLab has run a major survey about the trends facing the DevSecOps community. This year over 4,000 people responded to the survey, 40% who identified as a Software Developer / Software Engineer. Also about half the survey participants are based in Asia, a major region for Software Developers. One of the biggest trends you will find throughout the survey is how much developers value speed and efficiency.

Here at Ably, we deal with hard engineering problems all the time and pushing at the edges often results in us running up against all sorts of interesting gotchas. We recently made some AWS NLBs fall over, and had a hazardous encounter with Cassandra counter columns. In our day-to-day, we use gRPC for fast and efficient data exchange with mutual client/server state synchronization.

While Kubernetes is a very powerful and comprehensive application, it can also be very complicated and confusing to new users. Thankfully, the community is great at pulling together to try to tame the Kubernetes beasts, and as more users join the platform, more handy tools to help you manage your cluster are developed. Kubernetes Resources range from everyday helper tools to development tools to troubleshooting tools, and in this article we’ll discuss fifteen of the best ones.

APIs are the backbone of digital transformation. Via APIs, you can securely share data and functionality with developers both inside and outside of your organizational boundaries, letting you build applications faster, seamlessly connect and interact with partners, and drive new business revenue. Because APIs encompass business-critical information, any downtime or performance degradation can lead to significant loss in revenue, customers, and brand value.

The Atlanta Startup Podcast is the briefing room for the innovation ecosystem, featuring the investors, founders and activators creating the fastest emerging venture capital ecosystem in the country. Ken Ahrens, founder and CEO of Speedscale sits down with Valor Investor, William Leonard in this episode.

DevOps and cloud-based computing have existed in our life for some time now. These both can be regarded as the latest techs in the arsenal of information technology. Thinking back on how SDLC started and what it is today, the only reasons for its success can be accounted to efficiency, speed and most importantly automation – DevOps and cloud-based solutions can be considered major contributors here (after all DevOps is 41% less time-consuming than traditional ops).

Speedscale was built primarily to provide engineering teams with better insight into their applications over time, replaying single transactions for root cause analysis that give developers and SREs confidence that tomorrow’s application code will work just as well in production as it did yesterday.

Testing in production simply means testing new code changes in production, with live traffic, in order to test the system’s reliability, resiliency, and stability. It helps teams solve bugs and other issues faster, as well as effectively analyze the performance of newly released changes. Its overall purpose is to expose problems that can’t be identified in non-production environments for reasons that may include not being able to mimic the concurrency, load, or user behavior.

At Speedscale, we’re always trying to find ways to iterate faster and reduce developer toil. In line with that mission, we slant our engineering decisions towards using cutting edge tech because we usually move faster and it also allows us to help our customers later on when they upgrade their own tech stack. Recently, we had the opportunity to upgrade the communication channel between our api-gateway and react front end. This journey provided some unexpected benefits.

Large portions of software development budgets are dedicated for testing code. A new component may take weeks to thoroughly test, and even then mistakes happen. If you consider software defects as security issues then the concern goes well beyond an application temporarily crashing. Although even minor bugs can cost companies a lot of time to locate the bug, resolve it, retest it in lower environments, then deploy it back to production.