Download as PDF, PPTX
CÜ
Uploaded byCaner Ünal
PDF, PPTX713 views
InfluxDB and Grafana: An Introduction to Time-Based Data Storage and Visualization
The document discusses InfluxDB, a time-based, schemaless database supporting real-time analytics and custom monitoring, particularly suited for IoT and sensor data. It highlights key features like its HTTP API, InfluxQL query language, and the importance of managing cardinality through tags and fields. Additionally, it mentions Grafana's capabilities for querying and visualizing time series data, including compatibility with various data sources.
More Related Content
Viewers also liked
Similar to InfluxDB and Grafana: An Introduction to Time-Based Data Storage and Visualization
Recently uploaded
InfluxDB and Grafana: An Introduction to Time-Based Data Storage and Visualization
- 1.
- 2. InfluxDB ● Time-based database ●Schemaless design ● HTTP API support ● InfluxQL - Similiar to SQL ● Storage part of the TICK stack ❖ Telegraf ❖ InfluxDB ❖ Chronograf ❖ Kapacitor
- 3. Time-Series Data ● Real-TimeAnalytics ● Custom Monitoring ● IoT and Sensor Data ● Openstack, Docker and Virtualization
- 4. Key Concepts Line Protocol DatabaseMeasurement Tag Field Timestamp
- 5. Data Import ● InfluxDBweb interface + command line ● HTTP API Command or text files. ● HTTP API Client Libraries We use an Asp.Net library.
- 6. measurement, tkey=tvalue, tkey2=tvalue2...fkey=fvalue Write Syntax
- 7. Performance ● Decide avariable whether tag or field is important. Series Cardinality : The number of unique measurement and tag set combinations in an instance. When tag values are dependent they don't increase cardinality at all ● Retention Policy and Continuous Queries Continuous Query: An InfluxQL query that runs automatically and periodically within a database.
- 8.
- 9. Grafana ● Querying andVisualizing time series and metrics ● Supports InfluxDB, Elasticsearch, Cloudwatch, Prometheus, Graphite ● Plugins can be installed