Operations | Monitoring | ITSM | DevOps | Cloud

Generative AI has the world thinking about automation now more than ever before. The Information Technology Infrastructure Library (ITIL) has prioritized it from the start. ITIL has advocated for automation as a transformative tool for organizations to deliver business value, accelerate change, and reinvent service configuration management. By handling mundane tasks, automation can empower people to do more innovative and effective work.

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.

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).

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.

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.