kolla-ansible/doc/source/reference/logging-and-monitoring/central-logging-guide.rst

Central Logging

An OpenStack deployment generates vast amounts of log data. In order to successfully monitor this and use it to diagnose problems, the standard "ssh and grep" solution quickly becomes unmanageable.

Preparation and deployment

Modify the configuration file /etc/kolla/globals.yml and change the following:

enable_central_logging: "yes"

Elasticsearch

Kolla deploys Elasticsearch as part of the E*K stack to store, organize and make logs easily accessible.

By default Elasticsearch is deployed on port 9200.

Note

Elasticsearch stores a lot of logs, so if you are running centralized logging, remember to give /var/lib/docker adequate space.

Alternatively it is possible to use a local directory instead of the volume elasticsearch to store the data of Elasticsearch. The path can be set via the variable elasticsearch_datadir_volume.

Curator

To stop your disks filling up, retention policies can be set. These are enforced by Elasticsearch Curator which can be enabled by setting the following in /etc/kolla/globals.yml:

enable_elasticsearch_curator: "yes"

Elasticsearch Curator is configured via an actions file. The format of the actions file is described in the Elasticsearch Curator documentation. A default actions file is provided which closes indices and then deletes them some time later. The periods for these operations, as well as the prefix for determining which indicies should be managed are defined in the Elasticsearch role defaults and can be overridden in /etc/kolla/globals.yml if required.

If the default actions file is not malleable enough, a custom actions file can be placed in the Kolla custom config directory, for example: /etc/kolla/config/elasticsearch/elasticsearch-curator-actions.yml.

When testing the actions file you may wish to perform a dry run to be certain of what Curator will actually do. A dry run can be enabled by setting the following in /etc/kolla/globals.yml:

elasticsearch_curator_dry_run: "yes"

The actions which would be taken if a dry run were to be disabled are then logged in the Elasticsearch Kolla logs folder under /var/log/kolla/elasticsearch/elasticsearch-curator.log.

Kibana

Kolla deploys Kibana as part of the E*K stack in order to allow operators to search and visualise logs in a centralised manner.

After successful deployment, Kibana can be accessed using a browser on <kolla_external_vip_address>:5601.

The default username is kibana, the password can be located under <kibana_password> in /etc/kolla/passwords.yml.

First Login

When Kibana is opened for the first time, it requires creating a default index pattern. To view, analyse and search logs, at least one index pattern has to be created. To match indices stored in ElasticSearch, we suggest using the following configuration:

1. Index pattern - flog-*
2. Time Filter field name - @timestamp
3. Expand index pattern when searching [DEPRECATED] - not checked
4. Use event times to create index names [DEPRECATED] - not checked

After setting parameters, one can create an index with the Create button.

Search logs - Discover tab

Operators can create and store searches based on various fields from logs, for example, "show all logs marked with ERROR on nova-compute".

To do this, click the Discover tab. Fields from the logs can be filtered by hovering over entries from the left hand side, and clicking add or remove. Add the following fields:

• Hostname
• Payload
• severity_label
• programname

This yields an easy to read list of all log events from each node in the deployment within the last 15 minutes. A "tail like" functionality can be achieved by clicking the clock icon in the top right hand corner of the screen, and selecting Auto-refresh.

Logs can also be filtered down further. To use the above example, type programname:nova-compute in the search bar. Click the drop-down arrow from one of the results, then the small magnifying glass icon from beside the programname field. This should now show a list of all events from nova-compute services across the cluster.

The current search can also be saved by clicking the Save Search icon available from the menu on the right hand side.

Example: using Kibana to diagnose a common failure

The following example demonstrates how Kibana can be used to diagnose a common OpenStack problem, where an instance fails to launch with the error 'No valid host was found'.

First, re-run the server creation with --debug:

openstack --debug server create --image cirros --flavor m1.tiny \
--key-name mykey --nic net-id=00af016f-dffe-4e3c-a9b8-ec52ccd8ea65 \
demo1

In this output, look for the key X-Compute-Request-Id. This is a unique identifier that can be used to track the request through the system. An example ID looks like this:

X-Compute-Request-Id: req-c076b50a-6a22-48bf-8810-b9f41176a6d5

Taking the value of X-Compute-Request-Id, enter the value into the Kibana search bar, minus the leading req-. Assuming some basic filters have been added as shown in the previous section, Kibana should now show the path this request made through the OpenStack deployment, starting at a nova-api on a control node, through the nova-scheduler, nova-conductor, and finally nova-compute. Inspecting the Payload of the entries marked ERROR should quickly lead to the source of the problem.

While some knowledge is still required of how Nova works in this instance, it can still be seen how Kibana helps in tracing this data, particularly in a large scale deployment scenario.

Visualize data - Visualize tab

In the visualization tab a wide range of charts is available. If any visualization has not been saved yet, after choosing this tab Create a new visualization panel is opened. If a visualization has already been saved, after choosing this tab, lately modified visualization is opened. In this case, one can create a new visualization by choosing add visualization option in the menu on the right. In order to create new visualization, one of the available options has to be chosen (pie chart, area chart). Each visualization can be created from a saved or a new search. After choosing any kind of search, a design panel is opened. In this panel, a chart can be generated and previewed. In the menu on the left, metrics for a chart can be chosen. The chart can be generated by pressing a green arrow on the top of the left-side menu.

Note

After creating a visualization, it can be saved by choosing save visualization option in the menu on the right. If it is not saved, it will be lost after leaving a page or creating another visualization.

Organize visualizations and searches - Dashboard tab

In the Dashboard tab all of saved visualizations and searches can be organized in one Dashboard. To add visualization or search, one can choose add visualization option in the menu on the right and then choose an item from all saved ones. The order and size of elements can be changed directly in this place by moving them or resizing. The color of charts can also be changed by checking a colorful dots on the legend near each visualization.

Note

After creating a dashboard, it can be saved by choosing save dashboard option in the menu on the right. If it is not saved, it will be lost after leaving a page or creating another dashboard.

If a Dashboard has already been saved, it can be opened by choosing open dashboard option in the menu on the right.

Exporting and importing created items - Settings tab

Once visualizations, searches or dashboards are created, they can be exported to a JSON format by choosing Settings tab and then Objects tab. Each of the item can be exported separately by selecting it in the menu. All of the items can also be exported at once by choosing export everything option. In the same tab (Settings - Objects) one can also import saved items by choosing import option.

Custom log rules

Kolla Ansible automatically deploys Fluentd for forwarding OpenStack logs from across the control plane to a central logging repository. The Fluentd configuration is split into four parts: Input, forwarding, filtering and formatting. The following can be customised:

Custom log filtering

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 control host.

Custom log formatting

In some scenarios it may be useful to perform custom formatting of logs before forwarding them. For example, the JSON formatter plugin can be used to convert an event to JSON.

Configuration of custom fluentd formatting is possible by placing filter configuration files in /etc/kolla/config/fluentd/format/*.conf on the control host.

Custom log forwarding

In some scenarios it may be useful to forward logs to a logging service other than elasticsearch. This can be done by configuring custom fluentd outputs.

Configuration of custom fluentd outputs is possible by placing output configuration files in /etc/kolla/config/fluentd/output/*.conf on the control host.

Custom log inputs

In some scenarios it may be useful to input logs from other services, e.g. network equipment. This can be done by configuring custom fluentd inputs.

Configuration of custom fluentd inputs is possible by placing input configuration files in /etc/kolla/config/fluentd/input/*.conf on the control host.