Graphite
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Graphite is a highly scalable tool for collecting and storing metrics to analyze system performance and optimize costs. It provides a powerful UI for pulling, correlating, and manipulating collected data. Graphite is easy to scale through techniques like increasing storage, using multiple instances, and deduplicating data. It has no central configuration, allowing metrics to be collected from any source. Supporting tools like Collectd, Statsd, and various dashboards make Graphite a full-stack solution for monitoring system and application metrics.
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Hadoop has been widely embraced for its ability to economically store and analyze large data sets. Using parallel computing techniques like MapReduce, Hadoop can reduce long computation times to hours or minutes. This works well for mining large volumes of historical data stored on disk, but it is not suitable for gaining real-time insights from live operational data. Still, the idea of using Hadoop for real-time data analytics on live data is appealing because it leverages existing programming skills and infrastructure – and the parallel architecture of Hadoop itself. This presentation will describe how real-time analytics using Hadoop can be performed by combining an in-memory data grid (IMDG) with an integrated, stand-alone Hadoop MapReduce execution engine. This new technology delivers fast results for live data and also accelerates the analysis of large, static data sets.
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Graphite
- 2. Why collect data? - Problem Determination - Root Cause Analysis - Performance Optimization - Cost optimization - Reporting - Forecasting
- 3. Why Graphite? - Powerful UI - Highly scalable - No central configuration - Lots of Supporting tools - Collectd - Statsd - Dashboards
- 4. Powerful UI - Pulling data - Correlating data - Aggregating data - Manipulating Data
- 5. Highly Scalable - Metrics are queued - I/O nice - 40,000+ metrics/minute on 1CPU 3G VM
- 6. How to scale? - Big $$$ storage - Mount multiple independent RAID partitions - Multiple Graphite instances - Deduplication
- 7. No Central Configuration - Push metrics from anywhere - Clients available for many programming languages - Write data to socket in standard format <Metric.name> <value> <timestamp>
- 8. Supporting tools Collectd - Metric collection daemon - Plugin based - Support for… - Apache - JMX - Load - Memory - Disk I/O and usage - Etc.
- 9. Supporting tools Statsd - Metrics are submitted to buckets - Buckets flush on a regular interval - Aggregated metrics are written to graphite - Useful for application metrics - Support for… - Counters - Timers - Guages - Sets
- 10. Supporting tools Dashboards - Graphite - Descartes - Cubism - Tasseo
- 11. Glenn Poston - Twitter: gposton - Github: gposton - Blog: www.glennposton.com