106 lines
4.2 KiB
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106 lines
4.2 KiB
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======================
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Compute server logging
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======================
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The logs on the compute nodes, or any server running nova-compute (for example
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in a hyperconverged architecture), are the primary points for troubleshooting
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issues with the hypervisor and compute services. Additionally, operating system
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logs can also provide useful information.
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As the cloud environment grows, the amount of log data increases exponentially.
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Enabling debugging on either the OpenStack services or the operating system
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further compounds the data issues.
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Logging is described in more detail in the `Operations Guide
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<https://docs.openstack.org/ops-guide/ops-logging-monitoring.html>`_. However,
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it is an important design consideration to take into account before commencing
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operations of your cloud.
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OpenStack produces a great deal of useful logging information, but for
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the information to be useful for operations purposes, you should consider
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having a central logging server to send logs to, and a log parsing/analysis
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system such as Elastic Stack [formerly known as ELK].
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Elastic Stack consists of mainly three components: Elasticsearch (log search
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and analysis), Logstash (log intake, processing and output) and Kibana (log
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dashboard service).
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.. figure:: ../figures/ELKbasicArch.png
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:align: center
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:alt: Elastic Search Basic Architecture
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Due to the amount of logs being sent from servers in the OpenStack environment,
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an optional in-memory data structure store can be used. Common examples are
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Redis and Memcached. In newer versions of Elastic Stack, a file buffer called
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`Filebeat <https://www.elastic.co/products/beats/filebeat>`_ is used for a
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similar purpose but adds a "backpressure-sensitive" protocol when sending data
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to Logstash or Elasticsearch.
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Log analysis often requires disparate logs of differing formats. Elastic
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Stack (namely Logstash) was created to take many different log inputs and
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transform them into a consistent format that Elasticsearch can catalog and
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analyze. As seen in the image above, the process of ingestion starts on the
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servers by Logstash, is forwarded to the Elasticsearch server for storage and
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searching, and then displayed through Kibana for visual analysis and
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interaction.
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For instructions on installing Logstash, Elasticsearch and Kibana, see the
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`Elasticsearch reference
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<https://www.elastic.co/guide/en/elasticsearch/reference/current/getting-started.html>`_.
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There are some specific configuration parameters that are needed to
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configure Logstash for OpenStack. For example, in order to get Logstash to
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collect, parse, and send the correct portions of log files to the Elasticsearch
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server, you need to format the configuration file properly. There
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are input, output and filter configurations. Input configurations tell Logstash
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where to receive data from (log files/forwarders/filebeats/StdIn/Eventlog),
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output configurations specify where to put the data, and filter configurations
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define the input contents to forward to the output.
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The Logstash filter performs intermediary processing on each event. Conditional
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filters are applied based on the characteristics of the input and the event.
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Some examples of filtering are:
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* grok
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* date
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* csv
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* json
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There are also output filters available that send event data to many different
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destinations. Some examples are:
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* csv
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* redis
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* elasticsearch
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* file
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* jira
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* nagios
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* pagerduty
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* stdout
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Additionally there are several codecs that can be used to change the data
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representation of events such as:
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* collectd
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* graphite
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* json
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* plan
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* rubydebug
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These input, output and filter configurations are typically stored in
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:file:`/etc/logstash/conf.d` but may vary by linux distribution. Separate
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configuration files should be created for different logging systems such as
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syslog, Apache, and OpenStack.
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General examples and configuration guides can be found on the Elastic `Logstash
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Configuration page
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<https://www.elastic.co/guide/en/logstash/current/configuration-file-structure.html>`_.
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OpenStack input, output and filter examples can be found at
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`sorantis/elkstack
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<https://github.com/sorantis/elkstack/tree/master/elk/logstash>`_.
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Once a configuration is complete, Kibana can be used as a visualization tool
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for OpenStack and system logging. This will allow operators to configure custom
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dashboards for performance, monitoring and security.
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