Operations | Monitoring | ITSM | DevOps | Cloud

Integrating monitoring and logging into your application stack is crucial for maintaining performance, enhancing security, and streamlining troubleshooting. Grafana Cloud offers a robust solution for monitoring your applications by collecting metrics and logs using an agent, such as Grafana Agent, but there are many environments where this isn’t feasible.

Today, we are excited to announce that we have partnered with Boomi to provide its customers with unparalleled observability capabilities on its integration platform.

In the rapidly changing world of technology, effective monitoring is critical for maintaining your infrastructure and ensuring it performs effectively. While traditional monitoring methods are effective, they can fall short as systems scale and become more dynamic and complex. This article aims to bridge the gap by introducing software engineers to the power of machine learning (ML) in infrastructure monitoring, outlining not just the ‘how’ but the ‘why’ of its application.

Sentry knows a lot about the inner workings of an application’s codebase. So we got to thinking, how can we use this rich dataset to make debugging with Sentry even faster? Many generative AI (GenAI) tools (e.g. GitHub Copilot) improve developer productivity in their dev environment, though few have the contextual data Sentry has to help fix errors in production.

We’ve been exploring new approaches to make Sentry issues more actionable. Read on to learn how we’re using machine learning to improve issue creation (i.e. grouping) and alerts, with as little configuration as possible, so you can focus on fixing the most important issues.