Search Results for "ckjm java metrics"
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Showing 6 open source projects for "ckjm java metrics"
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Apache HBase
Get random, realtime read/write access to your Big Data
Use Apache HBase™ when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables, billions of rows X millions of columns, atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable. A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, Apache... -
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JAMon API
Monitor Java applications - SQL, HTTP, Methods, Exceptions and more.
JAMon API is a free, simple, high performance, thread safe, Java API that allows developers to easily monitor the performance and scalability of production applications. JAMon tracks hits, execution times (total, avg, min, max, std dev), and more. * JAMon Users Manual: For more on the JAMon, including installing, configuring, and using it, see http://jamonapi.sourceforge.net/. * Support: If you have any questions about usage please post a question on the forum at ... -
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OpenTSDB
A scalable, distributed time series database
OpenTSDB is a distributed, scalable Time Series Database (TSDB) written on top of HBase. OpenTSDB was written to address a common need: store, index and serve metrics collected from computer systems (network gear, operating systems, applications) at a large scale, and make this data easily accessible and graphable. Store and serve massive amounts of time series data without losing granularity. Generate graphs from the GUI, pull from the HTTP API, choose an open source front-end. OpenTSDB... -
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Heroic
The Heroic Time Series Database
Heroic is a scalable time-series database developed by Spotify, designed for real-time analytics and monitoring of large-scale systems. -
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HBase - Hannibal
Monitor and maintain HBase configured for manual splitting
Hannibal is a tool to help monitor and maintain HBase-Clusters that are configured for manual splitting. While HBase provides metrics to monitor overall cluster health via JMX or Ganglia, it lacks the ability to monitor single regions in an easy way. This information is essential when your cluster is configured for manual splits, especially when the data growth is not uniform. This tool tries to fill that gap by answering the following questions: How well are regions balanced over... -
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Reporting solution that collects data from multiple MySQL databases and presents important metrics and reports related to performance and usage.
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