InfluxDB & Grafana
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InfluxDB is an open source time series database written in Go that stores metric data and performs real-time analytics. It has no external dependencies. InfluxDB stores data as time series with measurements, tags, and fields. Data is written using a line protocol and can be visualized using Grafana, an open source metrics dashboard.
![• data written using line protocol
• [key] [point] [timestamp]
• key = <measurement>,<tag set>
• temperature,machine=unit42,type=assembly
• point = <field set>
• internal=32,external=100
• timestamp
• 1434055562000000035
• there can only be one point for a series and timestamp
• you define precision of point (s, ms, μs, ns)
• you define how long data is kept : retention policy (replication, duration)](https://image.slidesharecdn.com/20150909influxdb-150909002334-lva1-app6891/85/InfluxDB-Grafana-8-320.jpg)
InfluxDB & Grafana
- 1. InfluxDB & Grafana @ OC Tanner by Pedro Salgado
- 2. 1-slide intro to InfluxDB • “InfluxDB is a time series, metrics, and analytics database. • It’s written in Go and has no external dependencies. • That means once you install it there’s nothing else to manage (such as Redis, ZooKeeper, Cassandra, HBase, or anything else). • InfluxDB is targeted at use cases for DevOps, metrics, sensor data, and real-time analytics. • It arose from our need for a database like this on more than a few previous products we’ve built.” • source: influxdb.com
- 3. – Mark Twain “Get your facts first, then you can distort them as you please.”
- 4. Time-series • “A time series is a sequence of data points, typically consisting of successive measurements made over a time interval. • Examples of time series are ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. • Time series are very frequently plotted via line charts.” • source: wikipedia
- 5. Data point • “In statistics, a data point or observation is a set of one or more measurements on a single member of a statistical population.“ • source: wikipedia
- 6. Measurement • “Measurement is the assignment of a number to a characteristic of an object or event, which can be compared with other objects or events. • The scope and application of a measurement is dependent on the context and discipline. • source: wikipedia
- 7. Example in InfluxDB terms • time series • internal and external temperature for machine X type Y in time interval • measurement : temperature • tag set : machine, type • field set : internal_temperature, external_temperature • temperature,machine=unit42,type=assembly internal=32,external=100 1434055562000000035 • filtering done on tags • computation / analysis done on fields • fields aren’t indexed
- 8. • data written using line protocol • [key] [point] [timestamp] • key = <measurement>,<tag set> • temperature,machine=unit42,type=assembly • point = <field set> • internal=32,external=100 • timestamp • 1434055562000000035 • there can only be one point for a series and timestamp • you define precision of point (s, ms, μs, ns) • you define how long data is kept : retention policy (replication, duration)
- 9. Other interesting features • continuous queries • clustering (alpha)
- 10. Grafana • “An open source, feature rich metrics dashboard and graph editor for Graphite, InfluxDB & OpenTSDB” • source: grafana.org
- 11. “A picture is worth a thousand words.”
- 12. • https://en.wikipedia.org/wiki/Time_series • https://en.wikipedia.org/wiki/Data_point • https://en.wikipedia.org/wiki/Measurement • https://influxdb.com/docs/v0.9/introduction/ overview.html • https://influxdb.com/docs/v0.9/concepts/glossary.html • http://grafana.org/ • https://github.com/steenzout/
- 13. – Dr Seuss “Don't cry because it's over, smile because it happened.”