f12e72440a
In some scenarios it may be useful to apply custom filters to logs before forwarding them. This may be useful to add additional tags to the messages or to modify the tags to conform to a log format that differs from the one defined by kolla-ansible. Configuration of custom fluentd filters is possible by placing filter configuration files in ``/etc/kolla/config/fluentd/filter/*.conf`` on the ansible control host. Change-Id: I29a20efb0df4bf3564ef009616c786e928aa26d9 Implements: blueprint fluentd-custom-filters
179 lines
7.0 KiB
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179 lines
7.0 KiB
ReStructuredText
.. _central-logging-guide:
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========================
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Central Logging in Kolla
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========================
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An OpenStack deployment generates vast amounts of log data. In order to
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successfully monitor this and use it to diagnose problems, the standard "ssh
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and grep" solution quickly becomes unmanageable.
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Preparation and deployment
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==========================
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Modify the configuration file ``/etc/kolla/globals.yml`` and change
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the following:
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::
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enable_central_logging: "yes"
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Elasticsearch
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=============
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Kolla deploys Elasticsearch as part of the E*K stack to store, organize
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and make logs easily accessible.
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By default Elasticsearch is deployed on port ``9200``.
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.. note::
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Elasticsearch stores a lot of logs, so if you are running centralized logging,
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remember to give ``/var/lib/docker`` an adequate space.
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Kibana
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======
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Kolla deploys Kibana as part of the E*K stack in order to allow operators to
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search and visualise logs in a centralised manner.
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After successful deployment, Kibana can be accessed using a browser on
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``<kolla_external_vip_address>:5601``.
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The default username is ``kibana``, the password can be located under
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``<kibana_password>`` in ``/etc/kolla/passwords.yml``.
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Search logs - Discover tab
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--------------------------
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Operators can create and store searches based on various fields from logs, for
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example, "show all logs marked with ERROR on nova-compute".
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To do this, click the ``Discover`` tab. Fields from the logs can be filtered by
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hovering over entries from the left hand side, and clicking ``add`` or
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``remove``. Add the following fields:
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* Hostname
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* Payload
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* severity_label
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* programname
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This yields an easy to read list of all log events from each node in the
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deployment within the last 15 minutes. A "tail like" functionality can be
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achieved by clicking the clock icon in the top right hand corner of the screen,
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and selecting ``Auto-refresh``.
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Logs can also be filtered down further. To use the above example, type
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``programname:nova-compute`` in the search bar. Click the drop-down arrow from
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one of the results, then the small magnifying glass icon from beside the
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programname field. This should now show a list of all events from nova-compute
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services across the cluster.
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The current search can also be saved by clicking the ``Save Search`` icon
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available from the menu on the right hand side.
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Example: using Kibana to diagnose a common failure
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--------------------------------------------------
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The following example demonstrates how Kibana can be used to diagnose a common
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OpenStack problem, where an instance fails to launch with the error 'No valid
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host was found'.
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First, re-run the server creation with ``--debug``:
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::
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openstack --debug server create --image cirros --flavor m1.tiny \
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--key-name mykey --nic net-id=00af016f-dffe-4e3c-a9b8-ec52ccd8ea65 \
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demo1
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In this output, look for the key ``X-Compute-Request-Id``. This is a unique
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identifier that can be used to track the request through the system. An
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example ID looks like this:
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::
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X-Compute-Request-Id: req-c076b50a-6a22-48bf-8810-b9f41176a6d5
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Taking the value of ``X-Compute-Request-Id``, enter the value into the Kibana
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search bar, minus the leading ``req-``. Assuming some basic filters have been
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added as shown in the previous section, Kibana should now show the path this
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request made through the OpenStack deployment, starting at a ``nova-api`` on
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a control node, through the ``nova-scheduler``, ``nova-conductor``, and finally
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``nova-compute``. Inspecting the ``Payload`` of the entries marked ``ERROR``
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should quickly lead to the source of the problem.
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While some knowledge is still required of how Nova works in this instance, it
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can still be seen how Kibana helps in tracing this data, particularly in a
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large scale deployment scenario.
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Visualize data - Visualize tab
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------------------------------
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In the visualization tab a wide range of charts is available. If any
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visualization has not been saved yet, after choosing this tab *Create a new
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visualization* panel is opened. If a visualization has already been saved,
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after choosing this tab, lately modified visualization is opened. In this
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case, one can create a new visualization by choosing *add visualization*
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option in the menu on the right. In order to create new visualization, one
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of the available options has to be chosen (pie chart, area chart). Each
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visualization can be created from a saved or a new search. After choosing
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any kind of search, a design panel is opened. In this panel, a chart can be
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generated and previewed. In the menu on the left, metrics for a chart can
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be chosen. The chart can be generated by pressing a green arrow on the top
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of the left-side menu.
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.. note:: After creating a visualization, it can be saved by choosing *save
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visualization* option in the menu on the right. If it is not saved, it
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will be lost after leaving a page or creating another visualization.
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Organize visualizations and searches - Dashboard tab
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----------------------------------------------------
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In the Dashboard tab all of saved visualizations and searches can be
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organized in one Dashboard. To add visualization or search, one can choose
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*add visualization* option in the menu on the right and then choose an item
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from all saved ones. The order and size of elements can be changed directly
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in this place by moving them or resizing. The color of charts can also be
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changed by checking a colorful dots on the legend near each visualization.
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.. note:: After creating a dashboard, it can be saved by choosing *save dashboard*
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option in the menu on the right. If it is not saved, it will be lost after
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leaving a page or creating another dashboard.
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If a Dashboard has already been saved, it can be opened by choosing *open
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dashboard* option in the menu on the right.
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Exporting and importing created items - Settings tab
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----------------------------------------------------
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Once visualizations, searches or dashboards are created, they can be exported
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to a JSON format by choosing Settings tab and then Objects tab. Each of the
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item can be exported separately by selecting it in the menu. All of the items
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can also be exported at once by choosing *export everything* option.
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In the same tab (Settings - Objects) one can also import saved items by
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choosing *import* option.
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Custom log filtering
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====================
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In some scenarios it may be useful to apply custom filters to logs before
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forwarding them. This may be useful to add additional tags to the messages
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or to modify the tags to conform to a log format that differs from the one
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defined by kolla-ansible.
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Configuration of custom fluentd filters is possible by placing filter
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configuration files in ``/etc/kolla/config/fluentd/filter/*.conf`` on the
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control host.
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Custom log forwarding
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=====================
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In some scenarios it may be useful to forward logs to a logging service other
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than elasticsearch. This can be done by configuring custom fluentd outputs.
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Configuration of custom fluentd outputs is possible by placing output
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configuration files in ``/etc/kolla/config/fluentd/output/*.conf`` on the
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control host.
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