Memory for ingestion is just one part of the resources Prometheus uses, let’s look at disk blocks. Every 2 hours Prometheus compacts the data that has been buffered up in memory onto blocks on disk. This will include the chunks, indexes, tombstones, and various metadata. The main part of this should usually be the chunks […]
Prometheus 2.x has a very different ingestion system to 1.x, with many performance improvements. This time I’m also going to take into account the cost of cardinality in the head block. To start with I took a profile of a Prometheus 2.9.2 ingesting from a single target with 100k unique time series: This gives a […]
With 4,000 proprietary microservices and a growing number of open source systems that needed to be monitored, by late 2014 Uber was outgrowing its usage of Graphite and Nagios for metrics. They evaluated several technologies, including Atlas and OpenTSDB, but the fact that a growing number of open source systems were adding native support for […]
There have been some reportsthat compaction was causing larger memory spikes than was desirable. I dug into this and improved it for Prometheus 2.6.0, so let’s see how. Firstly I wrote a test setup that created some samples for 100k time series, in a way that would require compaction. It would be nice to get […]
Our industry has long been relying on microservice-based architecture to deliver software faster and safer. The advent and ubiquity of microservices naturally paved the way for container technology, empowering us to rethink how we build and deploy our applications. Docker exploded onto the scene in 2013, and, for companies focusing on modernizing their infrastructure and […]
Uber, like most large technology companies, relies extensively on metrics to effectively monitor its entire stack. From low-level system metrics, such as memory utilization of a host, to high-level business metrics, including the number of Uber Eats orders in a particular city, they allow our engineers to gain insight into how our services are operating […]