openstack-helm/doc/source/devref/fluent-logging.rst
Vladimir Kozhukalov 81e1a8f71d Remove sphinxcontrib-blockdiag doc dependency
This is because Pillow upgrade to version 10.x
(from OpenStack upper constraints) breaks its usage.

Change-Id: Iec6567df69a5e1468151f1162600ca254a649c23
2024-11-18 22:46:24 -06:00

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Logging Mechanism

Logging Requirements

OpenStack-Helm defines a centralized logging mechanism to provide insight into the state of the OpenStack services and infrastructure components as well as underlying Kubernetes platform. Among the requirements for a logging platform, where log data can come from and where log data need to be delivered are very variable. To support various logging scenarios, OpenStack-Helm should provide a flexible mechanism to meet with certain operation needs.

EFK (Elasticsearch, Fluent-bit & Fluentd, Kibana) based Logging Mechanism

OpenStack-Helm provides fast and lightweight log forwarder and full featured log aggregator complementing each other providing a flexible and reliable solution. Especially, Fluent-bit is used as a log forwarder and Fluentd is used as a main log aggregator and processor.

Fluent-bit, Fluentd meet OpenStack-Helm's logging requirements for gathering, aggregating, and delivering of logged events. Fluent-bit runs as a daemonset on each node and mounts the /var/lib/docker/containers directory. The Docker container runtime engine directs events posted to stdout and stderr to this directory on the host. Fluent-bit then forward the contents of that directory to Fluentd. Fluentd runs as deployment at the designated nodes and expose service for Fluent-bit to forward logs. Fluentd should then apply the Logstash format to the logs. Fluentd can also write kubernetes and OpenStack metadata to the logs. Fluentd will then forward the results to Elasticsearch and to optionally Kafka. Elasticsearch indexes the logs in a logstash-* index by default. Kafka stores the logs in a logs topic by default. Any external tool can then consume the logs topic.

The resulting logs can then be queried directly through Elasticsearch, or they can be viewed via Kibana. Kibana offers a dashboard that can create custom views on logged events, and Kibana integrates well with Elasticsearch by default.