Used to be in the README, but I want to break the content into an actionable ticket...
ELK - ElasticSearch, LogStash, Kibana
The ELK stack is a long-standing solution for logs and metrics.
LogStash has a well-established history of being deployed as an ETL pipeline.
LGTM/P - Loki, Grafana, Tempo, Mimir / Prometheus
The full Grafana stack requires a lot of operational experience. It effectively requires learning three new "databases"
for data that is largely the same. Loki is effectively a database for logs. Tempo, a database for traces. And finally,
Mimir / Prometheus, a database for metrics. Each of these systems have their own resource usage and scaling requirements.
In addition, this is a partial solution as it does not cover the business intelligence side of the world. An additional
database can be added to support your business analytics, but doing so will only add to the complexity.
XOG - ?, OpenTelemetry, Grafana
Because OpenTelemetry is so flexible, why not pick one of the many other databases?
For a starter or simplified deployment, this is a great option. Leveraging an existing database technology may simplify
complexity today, it will pose some interesting technical challenges later on. Importing data from an existing database
technology into a solution like Clickhouse will be relatively easy.
Used to be in the README, but I want to break the content into an actionable ticket...