Over the past four days, Grafana Labs' ObservabilityCON 2020 brought together the Grafana community for talks dedicated to observability. We hope you enjoyed all of the sessions, which are available on demand now. (Link to them from the schedule on the event page). The conference wrapped up with predictions and advice from observability experts, lessons in failure, and Grafana Labs team members showcasing ways Grafana and other tools fit into an observability workflow.

Today is the last day of ObservabilityCON 2020! We hope you’ve had the chance to catch the talks so far, and will tune in live for today’s sessions. View the full schedule on the event page, and for additional information on viewing, participate in Q&As, and more, check out our quick guide to getting the most out of ObservabilityCON. If you aren’t up-to-date on the presentations so far, here’s a recap of day three of the conference.

Grafana v7.3 has been released! With Grafana 7.0, we rounded out our observability story by making tracing a first-class citizen in Grafana alongside metrics and logs. That release included integrations with Jaeger and Zipkin, and earlier this month, we announced our integration with AWS X-Ray. At ObservabilityCON on Monday, we announced Grafana Tempo, our new open source distributed tracing system. Tempo is massively scalable, cost-effective, and easy to operate.

ObservabilityCON 2020 is live! This week Grafana Labs is bringing together the Grafana community for talks dedicated to observability. We hope you’re able to catch the great sessions we have planned. You can find the full schedule on the event page, and for additional information on viewing, participating in Q&As, and more, check out our quick guide to getting the most out of ObservabilityCON. Day 2 was dedicated to all things Prometheus — featuring new solutions and in-depth case studies.

ObservabilityCON 2020 is live! Over the next few days, Grafana Labs is bringing together the Grafana community for talks dedicated to observability. Day 1 was filled with several new announcements about exciting projects and feature enhancements we’ve been working on for our customers and community. And there will be a lot more to learn about this week, like the session on Loki 2.0 on Wednesday.

Grafana Labs is proud to announce an easy-to-operate, high-scale, and cost-effective distributed tracing system: Tempo. Tempo is designed to be a robust trace id lookup store whose only dependency is object storage (GCS/S3). Join us in the Grafana Slack #tempo channel or the tempo-users google group to get involved today!

Snowflake offers a cloud-based data storage and analytics service, generally termed “data warehouse-as-a-service.” The main benefit of Snowflake is that you pay for compute and storage that you “actually use,” so it’s not “just another database.” Snowflake has become very popular over the last few years, culminating in a huge IPO just a couple of weeks ago, by allowing enterprise users to affordably store and analyze data using cloud-based hardware and software

AWS is announcing the AWS Distro for OpenTelemetry today. This is a distribution of OpenTelemetry, itself a CNCF sandbox project. This is part of a wider push towards Open Source, cloud native technologies, and modern observability, all based on Open Standards. This push can be observed across the whole technology sector, but with increasing velocity from within AWS. As they are the largest public cloud provider by far, this is noteworthy in and of itself.

Most of us have learned the hard way that it’s usually cheaper to fix something before it breaks and needs an expensive emergency repair. Because of that, I like to keep track of what’s happening in my house so I know as early as possible if something is wrong. As part of that effort, I have a temperature sensor in my attic attached to a Raspberry Pi, which Prometheus scrapes every 15 seconds so I can view the data in Grafana.

If you’ve been following the blog updates on the development of Cortex – the long-term distributed storage for Prometheus – you surely noticed the recent release of Cortex 1.4, which focuses on making support for “blocks engine” production-ready. Marco Pracucci has already written about the blocks support in Cortex, how it reduces operational complexity for running Prometheus at massive scale, and why Grafana Labs has invested in all of that work.

A few months ago, I blogged about memory-mapping of full chunks of the head block from disk. The feature, which was introduced in Prometheus v2.19.0, brings down memory usage and restart time. Additionally, there’s another Prometheus feature in progress that snapshots in-memory data during shutdown for faster restarts; it’s expected to cut down the restart times by a big factor.

As you add more panels to your dashboard, more requests are being made, potentially leading to your dashboard taking longer to load. While you can limit the data requested in each query, one of the best ways to reduce the loading time is to reduce the number of requests being made to the data source. Grafana makes a data source query for each panel in your dashboard, even if those queries are identical.

Helm charts are great. They combine high quality, ready-made runtime configurations for a huge number of applications with an incredible getting-started experience. There is literally no faster way to install a production-ready Grafana or Loki on Kubernetes than using helm install. Unfortunately, Helm charts can also be incredibly inflexible.

We’ve just launched Cortex 1.4.0, one of the most significant releases of 2020. The big headline: The new blocks storage engine has exited the experimental phase and is now marked as Generally Available. Blocks storage aims to reduce the operational complexity and costs of running a Cortex cluster at scale. In particular, it removes the dependency from a NoSQL database to store series indexes.

In early 2020, the Wavefront team was merged into the newly formed “Tanzu” portfolio under VMware’s Modern Applications business unit.

Often there’s a focus on how a service is running from the perspective of the organization. But what does service health monitoring look like from the perspective of a user? Today, understanding your end users’ experience is a key component of ensuring your website or application is functioning correctly. Having a website that is performing well regardless of location, load, or connection type is no longer a nice-to-have, but rather a requirement.

In collaboration with the AWS team, we have just launched another AWS integration, the X-ray data source. Combined with the CloudWatch and Timestream integrations, the AWS X-Ray data source simplifies monitoring and triaging with one Grafana console. The addition of the AWS X-ray data source reflects Grafana’s commitment to becoming a full observability platform that supports distributed tracing as well as metrics and logs.

Greetings! This is Eldin reporting from the Solutions Engineering team at Grafana Labs. In previous posts, you might have read about announcing ObservabilityCON or our release of Grafana 7.2. In this week’s post, I am introducing Dave Frankel, who will be covering our updated ServiceNow plugin. – Eldin In a previous post we announced the release of our Enterprise ServiceNow plugin. Our first release was focused around incident and change management based on the feedback we received.