Monitoring Che

This chapter describes how to configure Che to expose metrics and how to build an example monitoring stack with external tools to process data exposed as metrics by Che.

Enabling and exposing Che metrics

This section describes how to enable and expose Che metrics.

Procedure

Set the CHE_METRICS_ENABLED=true environment variable, which will expose the 8087 port as a service on the che-master host.

When Eclipse Che is installed from the OperatorHub, the environment variable is set automatically if the default CheCluster CR is used:

spec:
  metrics:
    enable: true

Collecting Che metrics with Prometheus

This section describes how to use the Prometheus monitoring system to collect, store, and query metrics about Che.

Prerequisites

Che is exposing metrics on port 8087. See Enabling and exposing Che metrics.
Prometheus 2.9.1 or later is running. The Prometheus console is running on port 9090 with a corresponding service and route. See First steps with Prometheus.

Procedure

Configure Prometheus to scrape metrics from the 8087 port:

Example 1. Prometheus configuration example

apiVersion: v1
kind: ConfigMap
metadata:
  name: prometheus-config
data:
  prometheus.yml: |-
      global:
        scrape_interval:     5s             (1)
        evaluation_interval: 5s             (2)
      scrape_configs:                       (3)
        - job_name: 'che'
          static_configs:
            - targets: ['[che-host]:8087']  (4)

1	Rate, at which a target is scraped.
2	Rate, at which recording and alerting rules are re-checked (not used in the system at the moment).
3	Resources Prometheus monitors. In the default configuration, a single job called `che`, scrapes the time series data exposed by the Che server.
4	Scrape metrics from the `8087` port.

Verification steps

Use the Prometheus console to query and view metrics.

Metrics are available at: http://<che-server-url>:9090/metrics.

For more information, see Using the expression browser.

Additional resources

Viewing Che metrics on Grafana dashboards

This section describes how to view Che metrics on Grafana dashboards.

Prerequisites

Prometheus is collecting metrics on the Che cluster. See Collecting Che metrics with Prometheus.
Grafana 6.0 or above is running on port 3000 with a corresponding service and route. See Installing Grafana.

Procedure

Deploy Che-specific dashboards on Grafana using the che-monitoring.yaml configuration file.

Three ConfigMaps are used to configure Grafana:
- grafana-datasources — configuration for Grafana data source, a Prometheus endpoint
- grafana-dashboards — configuration of Grafana dashboards and panels
- grafana-dashboard-provider — configuration of the Grafana dashboard provider API object, which tells Grafana where to look in the file system for pre-provisioned dashboards

Verification steps

Use the Grafana console to view Che metrics.

Additional resources

Installing Grafana.

Grafana dashboards for Che

This section describes the Grafana dashboards that are displaying metrics collected from Che.

monitoring che che server dashboard general panel

Figure 1. The General panel

The General panel contains basic information, such as the total number of users and workspaces in the Che database.

Figure 2. The Workspaces panel

Workspace start rate — the ratio between successful and failed started workspaces
Workspace stop rate — the ratio between successful and failed stopped workspaces
Workspace Failures — the number of workspace failures shown on the graph
Starting Workspaces — the gauge that shows the number of currently starting workspaces
Average Workspace Start Time — 1-hour average of workspace starts or fails
Average Workspace Stop Time — 1-hour average of workspace stops
Running Workspaces — the gauge that shows the number of currently running workspaces
Stopping Workspaces — the gauge that shows the number of currently stopping workspaces
Workspaces started under 60 seconds — the percentage of workspaces started under 60 seconds
Number of Workspaces — the number of workspaces created over time
Workspace start attempts — the number of attempts to start a workspace comparing regular attempts with start-debug mode

Figure 3. The Users panel

Number of Users — the number of users known to Che over time

Figure 4. The Tomcat panel

Max number of active sessions — the max number of active sessions that have been active at the same time
Number of current active sessions — the number of currently active sessions
Total sessions — the total number of sessions
Expired sessions — the number of sessions that have expired
Rejected sessions — the number of sessions that were not created because the maximum number of active sessions was reached
Longest time of an expired session — the longest time (in seconds) that an expired session had been alive

Figure 5. The Request panel

The Requests panel displays HTTP requests in a graph that shows the average number of requests per minute.

Figure 6. The Executors panel, part 1

Threads running - the number of threads that are not terminated aka alive. May include threads that are in a waiting or blocked state.
Threads terminated - the number of threads that was finished its execution.
Threads created - number of threads created by thread factory for given executor service.
Created thread per minute - Speed of thread creating for the given executor service.

Figure 7. The Executors panel, part 2

Executor threads active - number of threads that actively execute tasks.
Executor pool size - number of threads that actively execute tasks.
Queued task - the approximate number of tasks that are queued for execution
Queued occupancy - the percent of the queue used by the tasks that are waiting for execution.

Figure 8. The Executors panel, part 3

Rejected task - the number of tasks that were rejected from execution.
Rejected task per minute - the speed of task rejections
Completed tasks - the number of completed tasks
Completed tasks per minute - the speed of task execution

Figure 9. The Executors panel, part 4

Task execution seconds max - 5min moving maximum of task execution
Tasks execution seconds avg - 1h moving average of task execution
Executor idle seconds max - 5min moving maximum of executor idle state.
Executor idle seconds avg - 1h moving average of executor idle state.

Figure 10. The Traces panel, part 1

Workspace start Max - maximum workspace start time
Workspace start Avg - 1h moving average of the workspace start time components
Workspace stop Max - maximum of workspace stop time
Workspace stop Avg - 1h moving average of the workspace stop time components

Figure 11. The Traces panel, part 2

OpenShiftInternalRuntime#start Max - maximum time of OpenShiftInternalRuntime#start operation
OpenShiftInternalRuntime#start Avg - 1h moving average time of OpenShiftInternalRuntime#start operation

Plugin Brokering Execution Max - maximum time of PluginBrokerManager#getTooling operation
Plugin Brokering Execution Avg - 1h moving average of PluginBrokerManager#getTooling operation

Figure 12. The Traces panel, part 3

OpenShiftEnvironmentProvisioner#provision Max - maximum time of OpenShiftEnvironmentProvisioner#provision operation
OpenShiftEnvironmentProvisioner#provision Avg -1h moving average of OpenShiftEnvironmentProvisioner#provision operation

Plugin Brokering Execution Max - maximum time of PluginBrokerManager#getTooling components execution time
Plugin Brokering Execution Avg - 1h moving average of time of PluginBrokerManager#getTooling components execution time

Figure 13. The Traces panel, part 4

WaitMachinesStart Max - maximum time of WaitMachinesStart operations
WaitMachinesStart Avg - 1h moving average time of WaitMachinesStart operations
OpenShiftInternalRuntime#startMachines Max - maximum time of OpenShiftInternalRuntime#startMachines operations
OpenShiftInternalRuntime#startMachines Avg - 1h moving average of the time of OpenShiftInternalRuntime#startMachines operations

Figure 14. The Workspace detailed panel, part 1

The Workspace Detailed panel contains heat maps, which illustrate the average time of workspace starts or fails. The row shows some period of time.

Figure 15. The Workspace detailed panel, part 2

Messages sent to runtime log - Number of messages sent to the workspace startup log.
Bytes sent to runtime log - Number of bytes of the messages sent to the workspace startup log.
Current Log Watchers - Number of currently watched containers logs

Che server JVM dashboard

Use case: JVM metrics of the Che server, such as JVM memory or class loading.

Figure 16. Che server JVM dashboard

Figure 17. Quick Facts

Figure 18. JVM Memory

Figure 19. JVM Misc

Figure 20. JVM Memory Pools (heap)

Figure 21. JVM Memory Pools (Non-Heap)

Figure 22. Garbage Collection

Figure 23. Class loading

Figure 24. Buffer Pools

Developing Grafana dashboards

Grafana offers the possibility to add custom panels.

Procedure

To add a custom panel, use the New dashboard view.

In the first section, define Queries to. Use the Prometheus Query Language to construct a specific metric, as well as to modify it with various aggregation operators.

Figure 25. New Grafana dashboard: Queries to
In the Visualisation section, choose a metric to be shown in the following visual in the form of a graph, gauge, heatmap, or others.

Figure 26. New Grafana dashboard: Visualization
Save changes to the dashboard using the Save button, and copy and paste the JSON code to the deployment.
Load changes in the configuration of a running Grafana deployment. First remove the deployment:
```
$ oc process -f che-monitoring.yaml | oc delete -f -
```
Then redeploy your Grafana with the new configuration:
```
$ oc process -f che-monitoring.yaml | oc apply -f - | oc rollout latest grafana
```