A collection of prepackaged InfluxDB configurations for quickly collecting and analyzing time series data from various sources.
InfluxDB Community Templates is a collection of prepackaged configuration manifests for InfluxDB 2.0. It provides ready-to-use setups for collecting, monitoring, and visualizing time series data from a wide variety of sources like cloud platforms, databases, applications, and IoT devices. The project solves the problem of manually configuring InfluxDB for common use cases, significantly reducing setup time and complexity.
DevOps engineers, SREs, and developers who use InfluxDB for monitoring and observability, and need quick, reliable configurations for data collection from diverse systems.
It offers a community-curated library of battle-tested templates, enabling users to deploy production-ready monitoring in minutes rather than hours. The open-source, collaborative model ensures continuous improvement and a wide range of supported data sources.
InfluxDB Community Templates: Quickly collect & analyze time series data from a range of sources: Kubernetes, MySQL, Postgres, AWS, Nginx, Jenkins, and more.
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Templates bundle dashboards, Telegraf configs, and alerts into a single manifest file, enabling users to set up monitoring in minutes, as highlighted in the README.
Includes templates for AWS, Kubernetes, databases like MySQL, and niche sources like ADS-B receivers, covering a wide range of common use cases from the provided list.
Open for submissions and improvements, fostering knowledge sharing and continuous enhancement, as emphasized in the project's philosophy of reducing setup time.
Templates can be easily shared, backed up, and reused across deployments, making them ideal for team standardization and quick replication of setups.
InfluxData does not test or guarantee the quality or safety of contributed templates, leaving support entirely to community authors, which poses risks for production environments.
Templates only work with InfluxDB 2.0, creating vendor lock-in and excluding users on older versions or other time-series databases.
Community contributions lead to inconsistencies in documentation, maintenance, and reliability across templates, as noted in the support section.