Operations | Monitoring | ITSM | DevOps | Cloud

The availability and performance of a website is critical to achieving success for the business behind it. That’s why website owners must deeply concentrate on monitoring and sweetening their website’s Key Performance Indicators (KPIs). In our post today, we aim to get to know the top 11 availability and performance KPIs website owner should be aware of. We will categorize these indicators into three segments: availability KPIs, performance KPIs, and user engagement analytics.

With many SASE vendors prioritizing security over performance, businesses are left with a gap in their network management strategies. Before implementations, SASE vendors make promises about the performance of their SASE services, but, how can customers ensure they’re getting what they paid for? And how can they avoid slow or sluggish networks leading to frustrated users, decreased productivity, and even financial losses?

In the first article of our series, we explored the importance of trace headers and the complexities involved in their propagation. Now, we shift from theory to practice. This second installment will take you through a hands-on baseline scenario and our initial strategy of propagating the OpenTelemetry trace context in AWS Kinesis by using the PartitionKey parameter.

AIOps is a game changer for MSPs. But how do you implement AIOps to ensure you get those game-changing benefits? Chances are, you’re not interested in spending the resources and time required to build it yourself with all of the development, testing, maintenance, etc. that entails. Instead, AIOps as a service provides you with the capabilities to better manage the IT infrastructure and operations of multiple clients.

The more data you have, the harder it becomes to read through it, let alone identify trends or crucial patterns. Couple that with a shortage of time, and the ability not only to visualize but also to communicate with your data becomes paramount.

We are consistently releasing helpful updates and fun features in Grafana Cloud, our fully managed observability platform powered by the open source Grafana LGTM Stack (Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics). In case you missed it, here’s a roundup of the latest and greatest upgrades for Grafana Cloud this month. If you’re not a Grafana Cloud user, what are we waiting for?

Slow code is everywhere—or maybe "anywhere. "Slowness" is a spectrum. Sometimes, you triumphantly move performance bottlenecks so that the bar for "slow" always gets lower. In our experience, though, things often trend in the other direction.

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.