fb4651461b
In some scenarios it may be useful to configure custom fluentd outputs to forward logs to a logging service other than elasticsearch. This change supports configuration of fluentd outputs by placing output configuration files in /etc/kolla/config/fluentd/output/*.conf. Change-Id: I3c0b271d88dbb307ba3a23546e29c72e8baeca55 Implements: blueprint fluentd-custom-outputs
167 lines
6.5 KiB
ReStructuredText
167 lines
6.5 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 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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