GitHub - stripe/veneur: A distributed, fault-tolerant pipeline for observability data
Once you cross a threshold into dozens, hundreds or (gasp!) thousands of machines emitting metric data for an application, you've moved into that world where data about individual hosts is uninteresting except in aggregate form. Instead of paying to store tons of data points and then aggregating them later at read-time, Veneur can calculate global aggregates, like percentiles and forward those alo
statsd-vis - Standalone StatsD Server with Built-in Visualization
statsd-vis - Standalone StatsD Server with Built-in Visualizationstatsd-vis is a standalone, zero-dependency single-binary StatsD server with built-in web UI with which you can visualize graphs. It holds time series data for a configurable time in-memory, and does not persist or forward it. This is how it looks: Ad OpsDash - Server, Database & App Metric Monitoring & Alerting. Zero-dependency Go-
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Etsy Engineering | Introducing statsd-jvm-profiler: A JVM Profiler for Hadoop
At Etsy we run thousands of Hadoop jobs over hundreds of terabytes of data every day.  When operating at this scale optimizing jobs is vital: we need to make sure that users get the results they need quickly, while also ensuring we use our cluster’s resources efficiently.  Actually doing that optimizing is the hard part, however.  To make accurate decisions you need measurements, and so we have cr
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etsy/logster - GitHub - Parse log files, generate metrics for Graphite and Ganglia
Logster is a utility for reading log files and generating metrics to configurable outputs. It is ideal for visualizing trends of events that are occurring in your application/system/error logs. For example, you might use logster to graph the number of occurrences of HTTP response code that appears in your web server logs. Logster maintains a cursor, via a tailer, on each log file that it reads so
Statsite by armon - A C implementation of statsd
Statsite is a metrics aggregation server. Statsite is based heavily on Etsy's StatsD https://github.com/etsy/statsd, and is wire compatible. Features Multiple metric types Key / Value Gauges Counters Timers Sets Efficient summary metrics for timer data: Mean Min/Max Standard deviation Median, Percentile 95, Percentile 99 Histograms Dynamic set implementation: Exactly counts for small sets HyperLog
Open Source Monitoring Tools
This document summarizes and compares several open source monitoring tools: Nagios, Graphite, StatsD, Logstash, and Sensu. Nagios is introduced as a commonly used tool that some love and some find frustrating. Graphite is described as a tool for storing and graphing time-series data. StatsD aggregates counters and timers and sends them to backend services like Graphite. Logstash is an tool for man
Why use statsd when graphite's Carbon aggregator can do the same job?
tldr: you will probably want statsd (or carbon-c-relay) if you ever want to look at the server-specific sums or averages. carbon aggregator is designed to aggregate values from multiple metrics together into a single output metric, typically to increase graph rendering performance. statsd is designed to aggregate multiple data points in a single metric, because otherwise graphite only stores the l
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GitHub - danni-m/redis-info-statsd: redis module to update your statsd server
GitHub - slackhq/go-rsyslog-pstats: Parses and forwards rsyslog process stats to a local statsite, statsd, or wire protocol compatible service.
GitHub - mozilla-services/heka: DEPRECATED: Data collection and processing made easy.
ezotrank/logsend · GitHub - Logsend is high-performance tool for processing logs
GitHub - spotify/ffwd: a flexible metric forwarding agent
Collecting Metrics with Graphite and StatsD
etsy/statsd-jvm-profiler · GitHub - Simple JVM Profiler Using StatsD
eleme/node-bell · GitHub - Realtime anomalies detection based on statsd, for periodic time series.
Developers Summit 2014 Summer　ã€B-4】LMQã§ãŠæ‰‹è»½åˆ†æ•£ã‚·ã‚¹ãƒ†ãƒ 開発
http://dev.nuclearrooster.com/2011/05/11/sending-metrics-to-statsd-from-bash/
StatsD: Measure Anything / Measure Everything
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