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Enable sphinx-lint via pre-commit and fix up the existing issues. The most common one was single backtick vs double backtick. In ReStructured Text you must use a double backtick while Markdown uses the single backtick for a fixed-width font. The other issue was a tabs vs spaces change in a file. Change-Id: I28e91272d67d13db0fefaa7165e0ba887086eae9 Signed-off-by: Doug Goldstein <cardoe@cardoe.com>
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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.