Modern StatsD Monitoring
Improve the ease, accuracy, and scale of your StatsD monitoring. Seamlessly replace Graphite while keeping your Grafana dashboards.
Legacy StatsD pipelines are not equipped to handle the volume of data emitted by today’s applications, causing inaccuracies and limitations when monitoring StatsD metrics. That’s why more organizations are leveraging Circonus to modernize their StatsD monitoring and replace solutions like Graphite. Circonus’ powerful IRONdb time-series database and patented log linear OpenHistograms ingest an unlimited volume of highly granular data and efficiently store it at low cost for years using large scale data compression. As a result, users can replace pre-calculated aggregations required by legacy solutions with arbitrary on-demand analysis, enable Metrics 2.0 tagging, simplify their StatsD metrics pipelines to reduce resources, and scale indefinitely without sacrificing performance.
Easily correlate, graph, and analyze StatsD metrics on-demand
- Replace pre-calculated aggregations such as P50, P95, P99, Min, Max with on-demand analytics through the Circonus Analytics Query Language (CAQL). Pre-calculated aggregations congest telemetry ingestion, require excessive storage, and make metrics hard to find.
- Enable Metrics 2.0 tagging of StatsD telemetry to make it easier to search, analyze, and slice and dice data.
- Use CAQL to create customized queries against your StatsD metric data and to power your Grafana dashboards, which natively support CAQL.
Empower SRE and software development teams to dynamically create SLOs
- Simplify defining and measuring SLOs by dynamically computing aggregations from raw data on-demand, after ingestion, using Circonus’ OpenHistograms, which can collect and efficiently store all source data.
- Enable various teams to set their own SLOs rather than be forced to share the same pre-calculated aggregations that only a subset of the team can use.
- Calculate more advanced aggregates such as arbitrary quantiles, percentiles, inverse quantiles and inverse percentiles — all without needing to manage and store additional metrics.
Redfin uses Circonus to overcome the challenges of StatsD monitoring and replace Graphite.
Ensure data scale, accuracy, and safety without sacrificing performance
- Eliminate the need for StatsD sampling associated with high-volume, real-time telemetry emitted by modern applications. This sampling was historically performed to conserve computing or networking resources, but no tradeoff is needed with Circonus.
- Ingest, aggregate, and store an unlimited volume of StatsD metrics at extremely high granularity (trillions of measurements per second) to ensure accurate real-time and historical analysis of StatsD metrics.
- Circonus operates with data replicated across multiple availability zones, stores multiple copies of data in a cluster of nodes, and ensures data retention in cases of network instability with its store and forward technology.
Simplify StatsD metric pipelines to reduce costs and resources
- Reduce or eliminate overhead associated with running legacy, outdated, and unsupported StatsD and Graphite ecosystem components.
- Reduce overall metric ingestion and storage by a factor of 10-20x with Circonus’ log linear OpenHistograms, which support large scale data compression so you can store all data for years at very low cost.
- Circonus’ agents remove the need for a StatsD server, eliminating the overhead of maintaining a complex infrastructure to perform StatsD aggregations.
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