hyperdxio/hyperdx
HyperDX is an open source observability platform powered by Clickhouse and OpenTelemetry that centralizes and correlates logs, metrics, traces, errors, and session replays to help engineers quickly resolve production issues.
Awesome ClickHouse › Metrics and Monitoring
go-graphite/graphite-clickhouse
The project 'graphite-clickhouse' is a backend solution designed to integrate Graphite clusters with ClickHouse, a fast open-source column-oriented database management system. It serves as a bridge allowing Graphite, a popular monitoring tool for storing and graphing time-series data, to leverage ClickHouse's high-performance analytical capabilities. The repository provides a preconfigured Docker Compose setup for easy deployment and includes Docker images for straightforward installation and use. The project supports compatibility with various versions of graphite-web (1.1.0, 0.9.15, 1.0.0) and related tools like carbonapi and carbonzipper, ensuring it can fit into existing Graphite ecosystems. It requires Go language version 1.18 or higher for building from source. The installation process involves setting up Yandex ClickHouse and carbon-clickhouse, followed by configuring graphite-clickhouse and adding its host and port to graphite-web's cluster servers configuration. Special HTTP headers are handled by the service to support integrations with Grafana dashboards and debugging features. These headers allow logging of dashboard and panel IDs, enable debug output for external data tables, and facilitate checking of binary data integrity. Response headers provide request IDs and cache hit flags to assist in monitoring and troubleshooting. The project documentation includes configuration details and instructions for running graphite-clickhouse alongside older versions of graphite-web on the same host. This flexibility allows users to upgrade or integrate new components without disrupting existing setups. Overall, graphite-clickhouse enhances Graphite's scalability and query performance by utilizing ClickHouse's efficient data storage and retrieval mechanisms, making it suitable for large-scale monitoring environments requiring fast and reliable time-series data processing.
https://github.com/go-graphite/graphite-clickhouse
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