Cortex 2020 year in review

Published: 23 Dec 2020

2020 is coming to an end, and we can definitely say it was an amazing year for Cortex. Dare I say, it has been the best year so far!

It was a year filled with huge milestones for the project. We released the first major version 1.0.0 back in April, along with introducing some versioning rules to avoid breaking changes to our users. Six more releases followed for a total of nine Cortex versions released this year at a regular cadence of six weeks, with countless features, improvements, optimizations and fresh documentation.

Back in August, Cortex advanced from sandbox to incubation within the Cloud Native Computing Foundation after a vote from CNCF’s Technical Oversight Committee (TOC). The TOC’s decision was a signal that Cortex has stepped up in maturity, attracting not just innovators but also early adopters within enterprises.

2020 has also been the year of the Cortex blocks storage, a new long-term storage engine for Cortex which requires only an object store and reduces Cortex operational costs by 4x. The new blocks storage has been a huge effort that involved several people both from the Cortex and Thanos community, and it’s now taking over the previous storage engine (chunks).

We’ve also seen a growing interest around Cortex and an increasing number of contributions, from features and bug fixes to documentation and support. According to CNCF statistics, Cortex doubled its contributions. If someone told us that would happen at the end of 2019, we wouldn’t have believed it!

This year Cortex formed a stronger relationship with our sibling project Thanos. The new Cortex blocks storage is based on some Thanos components, and this gave us the opportunity to contribute improvements and features to Thanos. At PromCon 2020, Bartek Plotka and I also had the opportunity to tell the story behind the collaboration between these two projects.

But all of these successes wouldn’t be the same without the fantastic people behind and around the project. We’ve seen an increasing demand for an easy-to-operate, scalable, blazing fast solution to store and query millions of metrics, and the recent progress in Cortex contributed to boosting awareness and increasing adoption.

We worked closely with a few new adopters to learn more behind-the-scenes details about their journey towards Cortex, and we published some case studies from Buoyant (creator of Linkerd), REWE Digital, and Gojek

To end the year with a bang, AWS announced its new Amazon Managed Service for Prometheus, built on the Cortex project for running Prometheus at scale. This service can complement the Amazon Managed Service for Grafana, a scalable managed offering that provides AWS customers a native way to run Grafana directly within AWS alongside all their other AWS services.

All in all, 2020 has been a fantastic year for Cortex. We are very grateful for all the love shown by the community, and we promise to continue to work on Cortex and make it the most scalable and cost-effective solution to store and query massive amounts of Prometheus metrics.

Looking forward to an even better 2021! Stay tuned!

CORTEX RESOURCES

TALKS & WEBINARS

KubeCon + CloudNativeCon EU recap: Getting some Thanos into Cortex while scaling Prometheus

PromCon Online: “Sharing is Caring: Leveraging Open Source to Improve Cortex & Thanos” 

BLOG POSTS

How the Cortex and Thanos projects collaborate to make scaling Prometheus better for all

How blocks storage in Cortex reduces operational complexity for running Prometheus at massive scale

Scaling Prometheus: How we’re pushing Cortex blocks storage to its limit and beyond

Now GA: Cortex blocks storage for running Prometheus at scale with reduced operational complexity

How to switch Cortex from chunks to blocks storage (and why you won’t look back)

Cortex, the scalable Prometheus project, has advanced to incubation within CNCF

Cortex v1.1 released with improved reliability and performance

Cortex v1.0 released: The highly scalable, fast Prometheus implementation is generally available for production use

How we’re using gossip to improve Cortex and Loki availability

The Future of Cortex: Into the Next Decade