Operations | Monitoring | ITSM | DevOps | Cloud

Tracing is a widely adopted solution to provide performance insights into distributed applications. It is a valuable resource for developers to view the service call graph and track service latency at a granular level. It’s also a handy tool for on-call engineers to drill down and debug a problematic service during an outage. There are a number of open source distributed tracing frameworks out in the wild, including Jaeger, Zipkin, and OpenTelemetry.

Since Petr Slavotinek created the Carpet plot plugin in 2017, it’s been one of the most popular community plugins for Grafana. Unfortunately, even though the Carpet plot plugin continues to be useful to many users, it’s no longer being maintained. Grafana 7.0 introduced a brand new React-based platform, along with a set of improved APIs for building plugins.

At Grafana Labs, we’re all big fans of the Prometheus and Grafana combination. To an extent, we just won’t shut up about it. We strongly believe in simplicity and think you shouldn’t need any extra effort to understand the metrics of your service(s) holistically. Yet we’ve all been in that situation where it is challenging to fully grasp what the metrics of our service(s) are and what they do. While naming conventions exist, at times they are not followed or enforced.

Among the many new features introduced in Grafana 7.0, one of the most exciting ones is transformations. The concept of data transformation is not new to Grafana, but prior to Grafana 7, it was fairly rigid and available only in the Table panel.

The just-released Prometheus v2.19.0 introduces the new feature of memory-mapping full chunks of the head (in-memory) block from disk, which reduces memory usage and also makes restarts faster. I will be talking about this feature in this blog post.

Running your software on dynamic infrastructure means that your monitoring platform needs to change dynamically. Variables let you reuse a single dashboard for all your services. Select the service you want to inspect from a drop-down menu, and watch panels update to only show you metrics from that service. Grafana lets you create dynamic dashboards using template variables. Any variables in your queries interpolate the current value of the variable before the query is sent to the database.

When we graduated Loki into a GA release last year, there were more than 137 contributors who already made more than 1,000 contributions to the project. We also added hosted Loki to the lineup of Grafana Cloud offerings after it proved to be stable internally for our ops cluster, storing 40TB and half a trillion log lines each month. There was, however, one persistent problem that kept surfacing, especially for developers who were writing applications in Go: The regex package was slow.

Last year, when a company that works with several of the world’s top carriers, OEMs, and enterprises to provide caller identity and spam blocking services for more than 120 million users needed to make changes to their monitoring service, Grafana Labs got the call. Hiya was founded in 2016, and from the start was a container-centric Kubernetes shop.

Today we are releasing Grafana 6.7.4 and 7.0.2. These patch releases include an important security fix for an issue that affects all Grafana versions from 3.0.1 to 7.0.1.

GrafanaCONline wrapped up last Friday, and we were thrilled to have so many of you join the sessions over the past three weeks. Thank you for tuning in, asking questions, chatting on Slack, and generally making our reimagined conference a success.