Interesting - I had not heard of Fnordmetrics before. There are not many monitoring systems that implement dimensionality for metrics tagging. It looks like Fnordmetrics goes about it slightly differently, but it seems to achieve the same end goal of arbitrary grouping by like characteristics.
In the Atlas eco-system, Servo and Atlas client eliminate the need for StatsD. The combination of these products allow for code-level instrumentation and delivery of metrics. The Prana sidecar is available for non-Java applications to deliver metrics to the Atlas backend as formatted JSON objects.
Atlas supports multiple backend storage systems, although this is not easily pluggable just yet. Earlier iterations of Atlas had support for MongoDB and Cassandra as storage backends, but there were issues obtaining enough IOPS to satisfy the read and write performance requirements at scale, so storage was switched to in-memory.
Atlas can return data in JSON format (?format=json) which is suitable for JS or SVG based rendering systems such as Highcharts. There is also a streaming API that trades response time for increased data payloads.
It takes some time to learn the Atlas Stack Language, but the fact that it is URL-based means that the browser is the interactive query editor. Using tools like Chrome's Edit URL to help handle long strings, you can make small changes to queries iteratively and see the results in less than 2 seconds in many cases. Average PNG render time is typically less than 10 seconds; slow rendering can take around 30 seconds.
In the Atlas eco-system, Servo and Atlas client eliminate the need for StatsD. The combination of these products allow for code-level instrumentation and delivery of metrics. The Prana sidecar is available for non-Java applications to deliver metrics to the Atlas backend as formatted JSON objects.
Atlas supports multiple backend storage systems, although this is not easily pluggable just yet. Earlier iterations of Atlas had support for MongoDB and Cassandra as storage backends, but there were issues obtaining enough IOPS to satisfy the read and write performance requirements at scale, so storage was switched to in-memory.
Atlas can return data in JSON format (?format=json) which is suitable for JS or SVG based rendering systems such as Highcharts. There is also a streaming API that trades response time for increased data payloads.
It takes some time to learn the Atlas Stack Language, but the fact that it is URL-based means that the browser is the interactive query editor. Using tools like Chrome's Edit URL to help handle long strings, you can make small changes to queries iteratively and see the results in less than 2 seconds in many cases. Average PNG render time is typically less than 10 seconds; slow rendering can take around 30 seconds.