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Central Logging

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Warning

Elasticsearch indexes created in version 6 or below are not supported by OpenSearch 2.x. Please reindex those before upgrading to Zed. Official Elasticsearch reindex documentation.

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:

OpenSearch #

Kolla deploys OpenSearch to store, organize and make logs easily accessible.

By default OpenSearch is deployed on port 9200.

Note

OpenSearch 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 opensearch to store the data of OpenSearch. The path can be set via the variable opensearch_datadir_volume.

Applying log retention policies #

To stop your disks filling up, the Index State Management plugin for OpenSearch can be used to define log retention policies. A default retention policy is applied to all indicies which match the opensearch_log_index_prefix. This policy first closes old indicies, and then eventually deletes them. It can be customised via the following variables:

  • opensearch_apply_log_retention_policy
  • opensearch_soft_retention_period_days
  • opensearch_hard_retention_period_days

By default the soft and hard retention periods are 30 and 60 days respectively. If you are upgrading from ElasticSearch, and have previously configured elasticsearch_curator_soft_retention_period_days or elasticsearch_curator_hard_retention_period_days, those variables will be used instead of the defaults. You should migrate your configuration to use the new variable names before the Caracal release.

Advanced users may wish to customise the retention policy, which is possible by overriding opensearch_retention_policy with a valid policy. See the Index Management plugin documentation for further details.

Updating log retention policies #

By design, Kolla Ansible will NOT update an existing retention policy in OpenSearch. This is to prevent policy changes that may have been made via the OpenSearch Dashboards UI, or external tooling, from being wiped out.

There are three options for modifying an existing policy:

1. Via the OpenSearch Dashboards UI. See the Index Management plugin documentation for further details.

  1. Via the OpenSearch API using external tooling.
  2. By manually removing the existing policy via the OpenSearch Dashboards UI (or API), before re-applying the updated policy with Kolla Ansible.

OpenSearch Dashboards #

Kolla deploys OpenSearch dashboards to allow operators to search and visualise logs in a centralised manner.

After a successful deployment, OpenSearch Dashboards can be accessed using a browser on <kolla_internal_fqdn>:5601 or <kolla_external_fqdn>:5601.

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

If you want to prevent OpenSearch Dashboards being exposed on the external VIP, you can set enable_opensearch_dashboards_external to false in /etc/kolla/globals.yml.

First Login #

When OpenSearch Dashboards 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 OpenSearch, 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 OpenSearch Dashboards to diagnose a common failure #

The following example demonstrates how OpenSearch 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 OpenSearch Dashboards search bar, minus the leading req-. Assuming some basic filters have been added as shown in the previous section, OpenSearch Dashboards 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 OpenSearch Dashboards 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.

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