Monitoring Tools Configuration Guide
A guide to OpenStack logging and monitoring tools
OpenStack Documentation Team
rhos-docs@redhat.com
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Chapter 1. Introduction to Red Hat OpenStack Platform monitoring tools
Monitoring tools are an optional suite of tools designed to help operators maintain an OpenStack environment. The tools perform the following functions:
- Centralized logging: Gather logs from all components in the OpenStack environment in one central location. You can identify problems across all nodes and services, and optionally, export the log data to Red Hat for assistance in diagnosing problems.
- Availability monitoring: Monitor all components in the OpenStack environment and determine if any components are currently experiencing outages or are otherwise not functional. You can also configure the system to alert you when problems are identified.
1.1. Support status of monitoring components
Use this table to view the support status of monitoring components in Red Hat OpenStack Platform (RHOSP).
Table 1.1. Support status
Component | Fully supported since | Deprecated in | Removed since | Note |
---|---|---|---|---|
Aodh | RHOSP 9 | RHOSP 15 | Supported for the autoscaling use case. | |
Ceilometer | RHOSP 4 | Supported for collection of metrics and events for RHOSP in the autoscaling and Service Telemetry Framework (STF) use cases. | ||
Collectd | RHOSP 11 | RHOSP 17.1 | Supported for collection of infrastructure metrics for STF. | |
Gnocchi | RHOSP 9 | RHOSP 15 | Supported for storage of metrics for the autoscaling use case. | |
Panko | RHOSP 11 | RHOSP 12, not installed by default since RHOSP 14 | RHOSP 17.0 | |
QDR | RHOSP 13 | RHOSP 17.1 | Supported for transmission of metrics and events data from RHOSP to STF. |
Chapter 2. Monitoring architecture
Monitoring tools use a client-server model with the client deployed onto the Red Hat OpenStack Platform overcloud nodes. The Rsyslog service provides client-side centralized logging (CL) and the collectd with enabled sensubility plugin provides client-side availability monitoring (AM).
2.1. Centralized logging
In your Red Hat OpenStack environment, collecting the logs from all services in one central location simplifies debugging and administration. These logs come from the operating system, such as syslog and audit log files, infrastructure components such as RabbitMQ and MariaDB, and OpenStack services such as Identity, Compute, and others.
The centralized logging toolchain consists of the following components:
- Log Collection Agent (Rsyslog)
- Data Store (Elasticsearch)
- API/Presentation Layer (Kibana)
Red Hat OpenStack Platform director does not deploy the server-side components for centralized logging. Red Hat does not support the server-side components, including the Elasticsearch database and Kibana.
2.2. Availability monitoring
With availability monitoring, you have one central place to monitor the high-level functionality of all components across your entire OpenStack environment.
The availability monitoring toolchain consists of several components:
- Monitoring Agent (collectd with enabled sensubility plugin)
- Monitoring Relay/Proxy (RabbitMQ)
- Monitoring Controller/Server (Sensu server)
- API/Presentation Layer (Uchiwa)
Red Hat OpenStack Platform director does not deploy the server-side components for availability monitoring. Red Hat does not support the server-side components, including Uchiwa, Sensu Server, the Sensu API plus RabbitMQ, and a Redis instance running on a monitoring node.
The availability monitoring components and their interactions are laid out in the following diagrams:
Items shown in blue denote Red Hat-supported components.
Figure 2.1. Availability monitoring architecture at a high level
Figure 2.2. Single-node deployment for Red Hat OpenStack Platform
Figure 2.3. HA deployment for Red Hat OpenStack Platform
Chapter 3. Installing the client-side tools
Before you deploy the overcloud, you need to determine the configuration settings to apply to each client. Copy the example environment files from the heat template collection and modify the files to suit your environment.
3.1. Setting centralized logging client parameters
For more information, see Enabling centralized logging with Elasticsearch in the Logging, Monitoring, and Troubleshooting guide.
3.2. Setting monitoring client parameters
The monitoring solution collects system information periodically and provides a mechanism to store and monitor the values in a variety of ways using a data collecting agent. Red Hat supports collectd as a collection agent. Collectd-sensubility is an extention of collectd and communicates with Sensu server side through RabbitMQ. You can use Service Telemetry Framework (STF) to store the data, and in turn, monitor systems, find performance bottlenecks, and predict future system load. For more information about Service Telemetry Framework, see the Service Telemetry Framework 1.3 guide.
To configure collectd and collectd-sensubility, complete the following steps:
Create
config.yaml
in your home directory, for example,/home/templates/custom
, and configure theMetricsQdrConnectors
parameter to point to STF server side:MetricsQdrConnectors: - host: qdr-normal-sa-telemetry.apps.remote.tld port: 443 role: inter-router sslProfile: sslProfile verifyHostname: false MetricsQdrSSLProfiles: - name: sslProfile
In the
config.yaml
file, list the plugins you want to use underCollectdExtraPlugins
. You can also provide parameters in theExtraConfig
section. By default, collectd comes with thecpu
,df
,disk
,hugepages
,interface
,load
,memory
,processes
,tcpconns
,unixsock
, anduptime
plugins. You can add additional plugins using theCollectdExtraPlugins
parameter. You can also provide additional configuration information for theCollectdExtraPlugins
using theExtraConfig
option. For example, to enable thevirt
plugin, and configure the connection string and the hostname format, use the following syntax:parameter_defaults: CollectdExtraPlugins: - disk - df - virt ExtraConfig: collectd::plugin::virt::connection: "qemu:///system" collectd::plugin::virt::hostname_format: "hostname uuid"
NoteDo not remove the
unixsock
plugin. Removal results in the permanent marking of the collectd container as unhealthy.Optional: To collect metric and event data through AMQ Interconnect, add the line
MetricsQdrExternalEndpoint: true
to theconfig.yaml
file:parameter_defaults: MetricsQdrExternalEndpoint: true
To enable collectd-sensubility, add the following environment configuration to the
config.yaml
file:parameter_defaults: CollectdEnableSensubility: true # Use this if there is restricted access for your checks by using the sudo command. # The rule will be created in /etc/sudoers.d for sensubility to enable it calling restricted commands via sensubility executor. CollectdSensubilityExecSudoRule: "collectd ALL = NOPASSWD: <some command or ALL for all commands>" # Connection URL to Sensu server side for reporting check results. CollectdSensubilityConnection: "amqp://sensu:sensu@<sensu server side IP>:5672//sensu" # Interval in seconds for sending keepalive messages to Sensu server side. CollectdSensubilityKeepaliveInterval: 20 # Path to temporary directory where the check scripts are created. CollectdSensubilityTmpDir: /var/tmp/collectd-sensubility-checks # Path to shell used for executing check scripts. CollectdSensubilityShellPath: /usr/bin/sh # To improve check execution rate use this parameter and value to change the number of goroutines spawned for executing check scripts. CollectdSensubilityWorkerCount: 2 # JSON-formatted definition of standalone checks to be scheduled on client side. If you need to schedule checks # on overcloud nodes instead of Sensu server, use this parameter. Configuration is compatible with Sensu check definition. # For more information, see https://docs.sensu.io/sensu-core/1.7/reference/checks/#check-definition-specification # There are some configuration options which sensubility ignores such as: extension, publish, cron, stdin, hooks. CollectdSensubilityChecks: example: command: "ping -c1 -W1 8.8.8.8" interval: 30 # The following parameters are used to modify standard, standalone checks for monitoring container health on overcloud nodes. # Do not modify these parameters. # CollectdEnableContainerHealthCheck: true # CollectdContainerHealthCheckCommand: <snip> # CollectdContainerHealthCheckInterval: 10 # The Sensu server side event handler to use for events created by the container health check. # CollectdContainerHealthCheckHandlers: # - handle-container-health-check # CollectdContainerHealthCheckOccurrences: 3 # CollectdContainerHealthCheckRefresh: 90
Deploy the overcloud. Include
config.yaml
,collectd-write-qdr.yaml
, and one of theqdr-*.yaml
files in your overcloud deploy command:$ openstack overcloud deploy -e /home/templates/custom/config.yaml -e tripleo-heat-templates/environments/metrics/collectd-write-qdr.yaml -e tripleo-heat-templates/environments/metrics/qdr-form-controller-mesh.yaml
-
Optional: To enable overcloud RabbitMQ monitoring, include the
collectd-read-rabbitmq.yaml
file in theovercloud deploy
command.
Additional resources
- For more information about the YAML files, see Section 3.5, “YAML files”.
- For more information about collectd plugins, see Section 3.4, “Collectd plugin configurations”.
- For more information about Service Telemetry Framework, see the Service Telemetry Framework 1.3 guide.
3.3. Collecting data through AMQ Interconnect
To subscribe to the available AMQ Interconnect addresses for metric and event data consumption, create an environment file to expose AMQ Interconnect for client connections, and deploy the overcloud.
The Service Telemetry Operator simplifies the deployment of all data ingestion and data storage components for single cloud deployments. To share the data storage domain with multiple clouds, see Configuring multiple clouds in the Service Telemetry Framework 1.3 guide.
It is not possible to switch between QDR mesh mode and QDR edge mode, as used by the Service Telemetry Framework (STF). Additionally, it is not possible to use QDR mesh mode if you enable data collection for STF.
Procedure
-
Log on to the Red Hat OpenStack Platform undercloud as the
stack
user. -
Create a configuration file called
data-collection.yaml
in the/home/stack
directory. To enable external endpoints, add the
MetricsQdrExternalEndpoint: true
parameter to thedata-collection.yaml
file:parameter_defaults: MetricsQdrExternalEndpoint: true
To enable collectd and AMQ Interconnect, add the following files to your Red Hat OpenStack Platform director deployment:
-
the
data-collection.yaml
environment file the
qdr-form-controller-mesh.yaml
file that enables the client side AMQ Interconnect to connect to the external endpointsopenstack overcloud deploy <other arguments> --templates /usr/share/openstack-tripleo-heat-templates \ --environment-file <...other-environment-files...> \ --environment-file /usr/share/openstack-tripleo-heat-templates/environments/metrics/qdr-form-controller-mesh.yaml \ --environment-file /home/stack/data-collection.yaml
-
the
-
Optional: To collect Ceilometer and collectd events, include
ceilometer-write-qdr.yaml
andcollectd-write-qdr.yaml
file in yourovercloud deploy
command. - Deploy the overcloud.
Additional resources
- For more information about the YAML files, see Section 3.5, “YAML files”.
3.4. Collectd plugin configurations
There are many configuration possibilities of Red Hat OpenStack Platform director. You can configure multiple collectd plugins to suit your environment. Each documented plugin has a description and example configuration. Some plugins have a table of metrics that you can query for from Grafana or Prometheus, and a list of options that you can configure, if available.
Additional resources
- To view a complete list of collectd plugin options, see collectd plugins in the Service Telemetry Framework guide.
3.5. YAML files
You can include the following YAML files in your overcloud deploy
command when you configure collectd:
-
collectd-read-rabbitmq.yaml
: Enables and configurespython-collect-rabbitmq
to monitor the overcloud RabbitMQ instance. -
collectd-write-qdr.yaml
: Enables collectd to send telemetry and notification data through AMQ Interconnect. -
qdr-edge-only.yaml
: Enables deployment of AMQ Interconnect. Each overcloud node has one local qdrouterd service running and operating in edge mode. For example, sending received data straight to definedMetricsQdrConnectors
. -
qdr-form-controller-mesh.yaml
: Enables deployment of AMQ Interconnect. Each overcloud node has one local qdrouterd service forming a mesh topology. For example, AMQ Interconnect routers on controllers operate in interior router mode, with connections to definedMetricsQdrConnectors
, and AMQ Interconnect routers on other node types connect in edge mode to the interior routers running on the controllers.
Additional resources
For more information about configuring collectd, see Section 3.2, “Setting monitoring client parameters”.