Apache Flink

The Apache Flink integration collects client, jobmanager and taskmanager logs and parses them into a JSON payload. The result includes fields for logger, level, and message.

For more information about Flink, see the Apache Flink documentation.

Prerequisites

To collect Flink telemetry, you must install the Ops Agent:

  • For logs, install version 2.17.0 or higher.
  • For metrics, install version 2.18.1 or higher.

This integration supports Flink versions 1.12.5, 1.13.6 and 1.14.4.

Configure the Ops Agent for Flink

Following the guide for Configuring the Ops Agent, add the required elements to collect telemetry from Flink instances, and restart the agent.

Example configuration

The following command creates the configuration to collect and ingest telemetry for Flink and restarts the Ops Agent.

# Configures Ops Agent to collect telemetry from the app and restart Ops Agent.

set -e

# Create a back up of the existing file so existing configurations are not lost.
sudo cp /etc/google-cloud-ops-agent/config.yaml /etc/google-cloud-ops-agent/config.yaml.bak

# Configure the Ops Agent.
sudo tee /etc/google-cloud-ops-agent/config.yaml > /dev/null << EOF
metrics:
  receivers:
    flink:
      type: flink
  service:
    pipelines:
      flink:
        receivers:
          - flink
logging:
  receivers:
    flink:
      type: flink
  service:
    pipelines:
      flink:
        receivers:
          - flink
EOF

sudo service google-cloud-ops-agent restart
sleep 30

To ingest logs from Flink, you must create receivers for the logs that Flink produces and then create a pipeline for the new receivers.

To configure a receiver for your flink logs, specify the following fields:

Field Default Description
exclude_paths A list of filesystem path patterns to exclude from the set matched by include_paths.
include_paths [/opt/flink/log/flink-*-standalonesession-*.log, /opt/flink/log/flink-*-taskexecutor-*.log, /opt/flink/log/flink-*-client-*.log] A list of filesystem paths to read by tailing each file. A wild card (*) can be used in the paths.
record_log_file_path false If set to true, then the path to the specific file from which the log record was obtained appears in the output log entry as the value of the agent.googleapis.com/log_file_path label. When using a wildcard, only the path of the file from which the record was obtained is recorded.
type The value must be flink.
wildcard_refresh_interval 60s The interval at which wildcard file paths in include_paths are refreshed. Given as a time duration, for example 30s or 2m. This property might be useful under high logging throughputs where log files are rotated faster than the default interval.

What is logged

The logName is derived from the receiver IDs specified in the configuration. Detailed fields inside the LogEntry are as follows.

The flink logs contain the following fields in the LogEntry:

Field Type Description
jsonPayload.level string Log entry level
jsonPayload.message string Log message, including detailed stacktrace where provided.
jsonPayload.source string The source Java class of the log entry.
severity string (LogSeverity) Log entry level (translated).

To ingest metrics from Flink, you must create a receiver for the metrics that Flink produces and then create a pipeline for the new receiver.

This receiver does not support the use of multiple instances in the configuration, for example, to monitor multiple endpoints. All such instances write to the same time series, and Cloud Monitoring has no way to distinguish among them.

To configure a receiver for your flink metrics, specify the following fields:

Field Default Description
collection_interval 60s A time.Duration value, such as 30s or 5m.
endpoint http://localhost:8081 The URL exposed by Flink.
type The value must be flink.

What is monitored

The following table provides the list of metrics that the Ops Agent collects from the Flink instance.

Metric type 
Kind, Type
Monitored resources		 Labels
workload.googleapis.com/flink.job.checkpoint.count
CUMULATIVE, INT64
gce_instance 		host_name
job_name
checkpoint
workload.googleapis.com/flink.job.checkpoint.in_progress
GAUGE, INT64
gce_instance 		host_name
job_name
workload.googleapis.com/flink.job.last_checkpoint.size
GAUGE, INT64
gce_instance 		host_name
job_name
workload.googleapis.com/flink.job.last_checkpoint.time
GAUGE, INT64
gce_instance 		host_name
job_name
workload.googleapis.com/flink.job.restart.count
CUMULATIVE, INT64
gce_instance 		host_name
job_name
workload.googleapis.com/flink.jvm.class_loader.classes_loaded
CUMULATIVE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.cpu.load
GAUGE, DOUBLE
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.cpu.time
CUMULATIVE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.gc.collections.count
CUMULATIVE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
garbage_collector_name
workload.googleapis.com/flink.jvm.gc.collections.time
CUMULATIVE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
garbage_collector_name
workload.googleapis.com/flink.jvm.memory.direct.total_capacity
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.direct.used
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.heap.committed
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.heap.max
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.heap.used
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.mapped.total_capacity
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.mapped.used
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.metaspace.committed
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.metaspace.max
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.metaspace.used
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.nonheap.committed
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.nonheap.max
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.memory.nonheap.used
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.jvm.threads.count
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.memory.managed.total
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.memory.managed.used
GAUGE, INT64
gce_instance 		host_name
resource_type
taskmanager_id
workload.googleapis.com/flink.operator.record.count
CUMULATIVE, INT64
gce_instance 		host_name
taskmanager_id
job_name
operator_name
task_name
subtask_index
record
workload.googleapis.com/flink.operator.watermark.output
GAUGE, INT64
gce_instance 		host_name
job_name
operator_name
subtask_index
task_name
taskmanager_id
workload.googleapis.com/flink.task.record.count
CUMULATIVE, INT64
gce_instance 		host_name
taskmanager_id
job_name
task_name
subtask_index
record

Verify the configuration

This section describes how to verify that you correctly configured the Flink receiver. It might take one or two minutes for the Ops Agent to begin collecting telemetry.

To verify that Flink logs are being sent to Cloud Logging, do the following:

  1. In the Google Cloud console, select Logging, and then select Logs Explorer, or click the following button:

    Go to the Logs Explorer

  2. Enter the following query in the editor, and then click Run query: 
    resource.type="gce_instance"
log_id("flink")

To verify that Flink metrics are being sent to Cloud Monitoring, do the following:

  1. In the Google Cloud console, select Monitoring, and then select  Metrics Explorer, or click the following button:

    Go to Metrics Explorer

  2. In the toolbar of the Select a metric pane, select the button whose name starts with Code.
  3. Select MQL in the Language toggle. The language toggle is in the same toolbar that lets you format your query.
  4. Enter the following query in the editor, and then click Run query: 
    fetch gce_instance
| metric 'workload.googleapis.com/flink.jvm.memory.heap.used'
| every 1m

View dashboard

To view your Flink metrics, you must have a chart or dashboard configured. The Flink integration includes one or more dashboards for you. Any dashboards are automatically installed after you configure the integration and the Ops Agent has begun collecting metric data.

You can also view static previews of dashboards without installing the integration.

To view an installed dashboard, do the following:

  1. In the Google Cloud console, select Monitoring, and then select  Dashboards, or click the following button:

    Go to Dashboards

  2. Select the Dashboard List tab, and then choose the Integrations category.
  3. Click the name of the dashboard you want to view.

If you have configured an integration but the dashboard has not been installed, then check that the Ops Agent is running. When there is no metric data for a chart in the dashboard, installation of the dashboard fails. After the Ops Agent begins collecting metrics, the dashboard is installed for you.

To view a static preview of the dashboard, do the following:

  1. In the Google Cloud console, select Monitoring, and then select  Integrations, or click the following button:

    Go to Integrations

  2. Click the Compute Engine deployment-platform filter.
  3. Locate the entry for Flink and click View Details.
  4. Select the Dashboards tab to see a static preview. If the dashboard is installed, then you can navigate to it by clicking View dashboard.

For more information about dashboards in Cloud Monitoring, see Dashboards and charts.

For more information about using the Integrations page, see Manage integrations.

Install alerting policies

Alerting policies instruct Cloud Monitoring to notify you when specified conditions occur. The Flink integration includes one or more alerting policies for you to use. You can view and install these alerting policies from the Integrations page in Monitoring.

To view the descriptions of available alerting policies and install them, do the following:

  1. In the Google Cloud console, select Monitoring, and then select  Integrations, or click the following button:

    Go to Integrations

  2. Locate the entry for Flink and click View Details.
  3. Select the Alerts tab. This tab provides descriptions of available alerting policies and provides an interface for installing them.
  4. Install alerting policies. Alerting policies need to know where to send notifications that the alert has been triggered, so they require information from you for installation. To install alerting policies, do the following:
    1. From the list of available alerting policies, select those that you want to install.

    2. In the Configure notifications section, select one or more notification channels. You have the option to disable the use of notification channels, but if you do, then your alerting policies fire silently. You can check their status in Monitoring, but you receive no notifications.

      For more information about notification channels, see Manage notification channels.

    3. Click Create Policies.

For more information about alerting policies in Cloud Monitoring, see Introduction to alerting.

For more information about using the Integrations page, see Manage integrations.

What's next

For a walkthrough on how to use Ansible to install the Ops Agent, configure a third-party application, and install a sample dashboard, see the Install the Ops Agent to troubleshoot third-party applications video.