Kubecon 2023 was more than just another conference to check off my list. It marked my first chance to work in the booth with my incredible Kentik colleagues. It let me dive deep into the code, community, and culture of Kubernetes. It was a moment when members of an underrepresented group met face-to-face and experienced an event previously not an option.
Here at AlertBot, we know that our customers don’t want to get bogged down with mountains of raw information about their websites and related processes. Instead, they want clear, organized, and reliable intelligence that tells them: what happened recently, what’s happening now, what’s likely to happen in the near future — and what they can do about it. That’s where email reports enter the story.
JSON files have become part of our daily lives. We use JSON files for all sorts of tasks like settings, defining database schemas, and much more. The other day I found out that invalid JSON files had been pushed to one of our repositories. So, I decided to include JSON file validation as part of our build on Azure DevOps. In this post, I'll share the solution. I'm sure you can think of a scenario where invalid JSON files either do not parse as valid syntax or don't conform to the intended format.
Data teams are adopting more processes and tools that align with software engineering, and from talks at the dbt Coalesce conference in 2023, there’s clearly a big push towards adopting software engineering practices at enterprise scale companies. At the moment, there are a lot of tools in the data space for identifying errors in data pipelines, but no tools for responding to these errors, such as coordinating fixes. This is exactly where an incident management platform makes sense to implement.
The software engineering world has become a place where compute, storage, and availability have become the cornerstones of scale. As an industry and as individuals, we should stop to take a closer look at scaling the most important of all resources… our people. In this post I’ve modeled a team with 6 engineers, 2 Sr, 3 Mid, and 1 Jr. This team is getting 450 “units” of work done ( where a unit is just some measure of throughput ) per interval (2 months).
In this livestream, I talked to Ryan Saunders – Manager of Security Operations at SpyCloud, about how he used the Cribl Reference Architecture to build a scalable deployment. He explained how this approach enabled SpyCloud to grow alongside its evolving needs without requiring significant rework. The reference architecture also facilitated a repeatable data-onboarding process, reducing administrative time and allowing the team to focus on critical security and data analysis tasks.