Local timeseries tooling

Quick Start

docker compose up -d
./import-csv.sh < (curl https://gist.githubusercontent.com/tbg/98d9814f624629833e6cfb7d25cb8258/raw/70a96d50032361f864b240dbd9f1c36c385b7515/sample.csv)
# User/Pass admin/x
open http://127.0.0.1:3000

Usage:

Step 1: procure a metrics dump

The source of this could be a debug zip (pending #50432), or

./cockroach debug tsdump --format=csv --host=... > dump.csv.

Step 2: docker compose up -d

Not much more to be said. Unsurprisingly, this needs Docker to work. Omit the -d if you want to see what's going on behind the scenes. It may take a moment for the next step to work.

Step 3: ./import-csv.sh < dump.csv

This loads the CSV data into your local Postgres instance. Note that it will truncate any existing data you have imported, so you're not accidentally mixing metrics from various sources.

If you legitimately want to import multiple csvs at once, use cat *.csv | ./import-csv instead.

Step 3: open Grafana

Log in as user admin, password x. You should be able to find a reference to the CockroachDB dashboard on the landing page.

Step 4: Play

You can edit the provided panel or add panels to plot interesting metrics. A good starting point for learning how to do that is the Grafana blog.

Replace ./grafana/dashboards/home.json if you want the changes to persist.

TODO(tbg): auto-generate a better home.json from pkg/ts/catalog.

Step 5: docker compose stop

To avoid hogging resources on your machine. The postgres database is on your local file system, so it will remain. If you want to nuke everything, use down instead of stop and then git clean -f ..