Grafana Labs announced two new open source projects: Grafana Phlare, a horizontally scalable continuous profiling database, and Grafana Faro, a web SDK that enables frontend application observability.
Grafana Phlare – which brings Grafana Labs’ horizontally scalable, object-storage-based database design to profiling data – joins Mimir, Loki, and Tempo in the Grafana open source observability stack. Phlare natively integrates with Grafana, allowing you to visualize your profiling data alongside your metrics, logs, and traces as well as data from any of the hundreds of disparate data sources that can be visualized in Grafana.
Grafana Faro is an open source project that enables you to collect data about the health of the frontend of your web applications. A highly configurable web SDK instruments web applications to capture observability signals.This frontend telemetry can then be correlated with backend and infrastructure data in the LGTM stack for a seamless, full-stack, open source observability solution.
Feature highlights include:
- Setup in seconds with just two lines of code
- Automatic instrumentation that captures errors, logs, and performance metrics
- Pre-configured tracing system based on OpenTelemetry with automatic instrumentations
- Easy-to-use API for manual instrumentation
The easiest way to get started observing your application frontend with Grafana Faro is with the fully managed Grafana Cloud observability offering. The new Frontend Application Observability service, now in private beta, will be available for all Grafana Cloud users.
Grafana Labs also announced the latest developments across the LGTM Stack, which has surpassed 1 million instances, including OSS and Grafana Cloud:
- A backend for all metrics formats: Grafana Mimir, which was launched in March 2022 with native support for Prometheus metrics, now also supports ingestion of Influx, Datadog, Graphite, and OpenTelemetry metrics. With this development, Grafana Labs leans into the “big tent” philosophy by providing a data format-agnostic backend that allows organizations to ingest data from as many sources as possible while leveraging a single query language, PromQL. Just as Grafana is the one tool that enables you to visualize all your data, no matter where it lives, Mimir is being built to enable you to store all your metrics, no matter the format.
- A new index in Loki 2.7: Loki’s index has been redesigned, replacing a bespoke format with a design based on Prometheus’s TSDB. This new format, which will be GA in the upcoming 2.7 release, takes up 75 percent less space on disk, can be accessed more efficiently, and enables further parallelized query execution. Loki can now scan log lines at up to 400GB/second at peak (4x faster than before).
- Export logs from Grafana Cloud: Some Grafana Cloud users need to keep logs for years after they’re generated, often for compliance reasons. This feature in Grafana Cloud allows you to ship your logs to an object storage bucket you own in AWS, Azure, or GCP for long-term storage, and query it using LogCLI or by running your own Loki, with no additional cost to re-ingest the data to Grafana Cloud. This feature is now in private beta.
- k6 x Tempo: An industry first, this integration brings together observability and performance testing, allowing you to troubleshoot k6 test runs with server-side tracing data from Tempo. Metrics are generated in real time by aggregating your internal tracing data and correlated with k6’s test run data. You can then query these metrics with Prometheus APIs and PromQL or use the attached exemplars to quickly spot if your database was struggling, if the cache hit rate decreased, or if an internal service was taking too much time to respond at some point of the test run. This integration is now in private beta.
- Introducing TraceQL: Originally, Grafana Tempo could only look up traces by ID; metrics or logs were required to surface the right trace ID. Then search was introduced, allowing you to find traces by fields like service name. And now, coming soon to Tempo 2.0 is TraceQL, a language designed from the ground up for querying trace data, modeled on PromQL and LogQL to make it easier to learn if you’re already familiar with those languages. With TraceQL, you’ll have a more powerful, flexible way to pinpoint the traces you need to answer questions about your system.
“These days, companies really care that they are able to be online, that their applications are performing fast, that their users aren’t getting annoyed and switching to a competitor. The experience and the quality of that online experience is of paramount importance to everybody. So making sure all the software and infrastructure is running, and running properly, is top of mind for every company,” said co-founder and CEO at Grafana Labs, Raj Dutt. “To support these organizations, we’re launching two brand new open source projects and numerous updates to our Grafana LGTM stack. The team has been innovating a lot the last few quarters, and we’re really looking forward to sharing these latest projects and updates with our community.”
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