GreptimeTeam

Guide for creating GreptimeDB flow tasks — continuous aggregation that updates a sink table on the fly as data is ingested. Use when the user asks to build a materialized view, continuous aggregation, downsampling job, or rollup. Triggers on phrases like "create flow", "continuous aggregation", "连续聚合", "物化视图", "materialized view", "downsampling", "time window aggregation". Note that Flow's original streaming mode is deprecated; batching mode is active for aggregation workloads.

Entry-point guide for agents to use GreptimeDB end-to-end — when it fits, how to deploy (Docker / binary / Kubernetes / GreptimeCloud), how to configure the server (storage backend, TTL, auth, listen addresses), which write protocol to choose by data type (metrics / logs / traces / events), how to query via SQL or PromQL, and how to discover deeper docs via llms.txt. Use this when the user wants to evaluate, deploy, configure, ingest into, or query GreptimeDB, or when a project needs a time-series / observability backend. Triggers on phrases like "use GreptimeDB", "deploy GreptimeDB", "install GreptimeDB", "configure GreptimeDB", "store metrics", "store logs", "store traces", "OTLP backend", "replace Prometheus", "replace Loki", "replace Elasticsearch", "时序数据库", "可观测性存储", "GreptimeDB 怎么用", "GreptimeDB 配置", "ingest observability data".

Locate GreptimeDB self-monitoring incident windows and safely export complete logs, with optional related metrics, for engineering investigation.

Guide for creating a GreptimeDB Pipeline — a processing layer between ingestion and storage that parses, transforms, indexes, and optionally routes log data. Use when the user asks to create a pipeline, parse logs, transform fields, write a pipeline YAML, dryrun a pipeline, or fan out logs to multiple tables. Triggers on phrases like "create pipeline", "解析日志", "log parsing", "transform fields", "GreptimeDB pipeline yaml", "dryrun pipeline", "dispatcher 分流", "VRL processor".

[Enterprise only] Guide for creating GreptimeDB Triggers — periodic evaluation rules (SQL or TQL/PromQL via TQL EVAL) that fire Alertmanager-compatible webhooks when conditions are met. Use as an alternative to Prometheus alerting rules, or to host existing PromQL alerts on GreptimeDB. Triggers on phrases like "create trigger", "alerting rule", "告警规则", "trigger webhook", "alertmanager 对接", "migrate prometheus alerts", "promql alert".

Investigate a failed GreptimeDB fuzz CI target link by downloading GitHub Actions job logs plus fuzz artifacts such as kind logs, monitor dumps, and CSV dumps, then correlate the failure with local GreptimeDB source code. Use when the user provides a failed fuzz CI target/job URL or asks to diagnose GreptimeDB fuzz CI failures.

Generate a GreptimeDB release changelog with git cliff (correct range, subtract already-released patch PRs, rebuild contributors, add human-curated highlights), output to a file, and prepare the docs-repo blog PR. Use when asked to write/generate a GreptimeDB release note or changelog.

Runbook for publishing a new GreptimeDB version (tag + GitHub release + docs release-note PR) on the upstream GreptimeTeam/greptimedb repo. Use when asked to "release" / "publish" a GreptimeDB version (e.g. v1.1.0, v1.0.3).

Generate Perses dashboards or single panels for GreptimeDB. Use when the user asks to create, generate, or scaffold a Perses dashboard or panel from table names, SQL/PromQL queries, natural-language prompts, or JSON paste into the Perses editor. Dashboard output is compatible with GET/POST /v1/dashboards; panel output is a paste-ready Panel object with kind Panel. Datasources are limited to promql-default (Prometheus) and sql-default (GreptimeDB) only. Reference GET /v1/dashboards for live metrics (SQL/PromQL), logs, and traces formats.