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Google Cloud Dataflow monitoring integration

New Relic integrations with the Google Cloud Platform (GCP) include one that reports Google Cloud Dataflow data to New Relic. This document explains how to activate the GCP Cloud Dataflow integration and describes the data it reports.

Features

Cloud Dataflow is Google Cloud's fully managed streaming and batch data-processing service based on Apache Beam. New Relic Dataflow integration collects worker resource, throughput, lag, and job-state metrics for each Dataflow job.

Activate integration

To enable the integration, follow standard procedures to connect your GCP service to New Relic:

Polling frequency

New Relic integrations query your GCP services according to a polling interval that varies by integration. The polling frequency for Google Cloud Dataflow is 5 minutes. The resolution is 1 data point every minute.

Important

Cloud Dataflow supports 1-minute polling intervals for WIF integrations in limited preview. To request access, contact New Relic support.

Workload Identity Federation

Find and use data

After you enable the integration, your Dataflow resources appear as entities in the New Relic entity explorer. To see dashboards and manage services, go to one.newrelic.com > All capabilities > Infrastructure > GCP.

All Dataflow metrics available in GCP Cloud Monitoring are collected as dimensional metrics in the Metric event type. Additional metrics beyond this table are collected automatically. See Google's Dataflow metrics documentation for the complete list.

Entities

Metric data

Key metrics — Job

Metric name

Unit

Description

gcp.dataflow.job.current_num_vcpus

Count

Number of vCPUs currently allocated to the Dataflow job.

gcp.dataflow.job.total_vcpu_time

Seconds

Total vCPU-seconds consumed by the Dataflow job.

gcp.dataflow.job.elements_produced_count

Count

Number of elements produced by the Dataflow job, faceted by transform.

gcp.dataflow.job.system_lag

Seconds

Maximum time an element has been waiting in the Dataflow pipeline.

gcp.dataflow.job.data_watermark_age

Seconds

Age of the data watermark for the Dataflow job.

gcp.dataflow.job.per_stage_system_lag

Seconds

System lag observed at each stage of the Dataflow job.

gcp.dataflow.job.user_counter

Count

User-defined counters emitted by the Dataflow job, faceted by counter name.

For the complete list of Dataflow metrics, see Google's Dataflow metrics documentation.

Service account or user account

Find and use data

To find your integration data, go to one.newrelic.com > All capabilities > Infrastructure > GCP and select an integration.

Data is attached to the following event type:

Entity

Event Type

Provider

Job

GcpDataflowJobSample

GcpDataflowJob

For more on how to use your data, see Understand and use integration data.

Metric data

This integration collects GCP Dataflow data for Job.

Dataflow Job data

Metric

Unit

Description

job.BillableShuffleDataProcessed

Bytes

The billable bytes of shuffle data processed by this Dataflow job.

job.CurrentNumVcpus

Count

The number of vCPUs currently being used by this Dataflow job. This is the current number of workers times the number of vCPUs per worker.

job.CurrentShuffleSlots

Count

The current shuffle slots used by this Dataflow job.

job.DataWatermarkAge

Seconds

The age (time since event timestamp) up to which all data has been processed by the pipeline.

job.ElapsedTime

Seconds

Duration that the current run of this pipeline has been in the Running state so far, in seconds. When a run completes, this stays at the duration of that run until the next run starts.

job.Elements

Count

Number of elements added to the pcollection so far.

job.EstimatedBytes

Bytes

An estimated number of bytes added to the pcollection so far. Dataflow calculates the average encoded size of elements in a pcollection and mutiplies it by the number of elements.

job.IsFailed

Count

Has this job failed.

job.PerStageDataWatermarkAge

Seconds

The age (time since event timestamp) up to which all data has been processed by this stage of the pipeline.

job.PerStageSystemLag

Seconds

The current maximum duration that an item of data has been processing or awaiting processing in seconds, per pipeline stage.

job.SystemLag

Seconds

The current maximum duration that an item of data has been processing or awaiting processing, in seconds.

job.TotalMemoryUsageTime

Other

The total GB seconds of memory allocated to this Dataflow job.

job.TotalPdUsageTime

Other

The total GB seconds for all persistent disk used by all workers associated with this Dataflow job.

job.TotalShuffleDataProcessed

Bytes

The total bytes of shuffle data processed by this Dataflow job.

job.TotalStreamingDataProcessed

Bytes

The total bytes of streaming data processed by this Dataflow job.

job.TotalVcpuTime

Seconds

The total vCPU seconds used by this Dataflow job.

job.UserCounter

Count

A user-defined counter metric.

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