Databricks Workspace

Databricks Workspace

Remotely monitor your Databricks Workspaces!

Extension

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Product information
Release notes

Overview

With Dynatrace, you can remotely monitor your Databricks Workspaces. This extension works in harmony with the OneAgent based Databricks extension but, is also ideal for workspaces and clusters where the OneAgent cannot be installed such as Databricks Serverless compute.

Use cases

Gather Databricks Job Run metrics including success rate and job duration
For Databricks Jobs running on All-purpose and Job Compute Clusters understand cost of these jobs (currently Azure Databricks is supported)
Ingest Job and Task run information as traces allowing for further analysis
Gather health metrics and detailed usage information from your Databricks model serving endpoints
Ingest billing data from Databricks to understand usage across workspaces, SKU & product category, jobs, and more

Get started

For more information on the installation and configuration, please see Databricks Workspace extension in the Dynatrace Documentation.

Details

Compatibility information

Databricks API version 2.2 is used for the APIs below:

API version 2.1 is used for the following:

Get cluster info

API version 2.0 is used for the following:

The following system tables are queried when ingesting model serving endpoint data:

And billing & cost data:

To query any of the above system table data, the workspace must also have:

Unity Catalog enabled.
A SQL warehouse set up.

For the databricks.job.cost metric, currently only Azure Databricks workspaces are supported.

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Feature sets

Below is a complete list of the feature sets provided in this version. To ensure a good fit for your needs, individual feature sets can be activated and deactivated by your administrator during configuration.

Feature setsNumber of metrics included

Metric name	Metric key	Description	Unit
Job Run Duration	databricks.job.duration.run	-	MilliSecond
Job Success Rate	databricks.job.success_rate	-	Percent

Metric name	Metric key	Description	Unit
Job Setup Duration	databricks.job.duration.setup	-	MilliSecond
Job Execution Duration	databricks.job.duration.execution	-	MilliSecond
Job Cleanup Duration	databricks.job.duration.cleanup	-	MilliSecond
Job Queue Duration	databricks.job.duration.queue	-	MilliSecond

Metric name	Metric key	Description	Unit
Job Cost (Approx)	databricks.job.cost	-	Unspecified

Metric name	Metric key	Description	Unit
Model Serving Endpoint Memory Usage Percentage	databricks.model_endpoint.mem_usage_percentage	-	Percent
Model Serving Endpoint CPU Usage Percentage	databricks.model_endpoint.cpu_usage_percentage	-	Percent
Model Serving Endpoint Request Count Total	databricks.model_endpoint.request_count_total	-	Count
Model Serving Endpoint Request 5xx Count Total	databricks.model_endpoint.request_5xx_count_total	-	Count
Model Serving Endpoint Provisioned Concurrent Requests Total	databricks.model_endpoint.provisioned_concurrent_requests_total	-	Count
Model Serving Endpoint Request 4xx Count Total	databricks.model_endpoint.request_4xx_count_total	-	Count
Model Serving Endpoint GPU Usage Percentage	databricks.model_endpoint.gpu_usage_percentage	-	Percent
Model Serving Endpoint GPU Memory Usage Percentage	databricks.model_endpoint.gpu_memory_usage_percentage	-	Percent
Model Serving Endpoint Average Request Latency	databricks.model_endpoint.request_latency_ms_avg	-	MilliSecond
Model Serving Endpoint P99 Request Latency	databricks.model_endpoint.request_latency_ms_p99	-	MilliSecond
Model Serving Endpoint P95 Request Latency	databricks.model_endpoint.request_latency_ms_p95	-	MilliSecond

Related to Databricks Workspace

Databricks

Monitor your Databricks Clusters via its multiple APIs!

Full version history

To have more information on how to install the downloaded package, please follow the instructions on this page.

ReleaseDate

Full version history

⚠️Breaking change

Upgrading existing monitoring configurations from previous versions to this version will not be possible and will require recreating those monitoring configurations. New monitoring configurations will not be affected.

✨New in this version:

Monitor model serving endpoint usage and billing data from your workspaces with new Gen3 dashboards provided for analysis. See documentation for how to get started collecting this data.
Added the option to report running/active jobs as logs.
Added the option to report job tags as metric dimensions and trace attributes.
Support added for OAuth when querying Databricks APIs and system tables.
Credential Vault support added for all secrets provided in the configuration.
Updated Jobs API from v2.1 to v2.2.
Db.job.* attributes now added to all task spans.
Updated all Gen3 dashboard links to point to new entity pages in the Infrastructure and Operations app.
Databricks workspace name added to trace service name.

Full version history

v1.3.11

Vulnerability fix for protobuf:6.33.4 (CVE-2026-0994)

Full version history

1.3.9

DXS-3787
- Update classic entity screen to remove optional dimension preventing data from being shown

Full version history

1.3.4

DXS-3317
- Add Platform Dashboard
- Add new Workspace Entity
- Add Platform Screen
- Add dt.security_context attribute
Updated how auto-detection of trace endpoint URL is done
Updated activation schema to allow for custom trace endpoint URL
- Added custom Root CA path as an optional field
Fixes for job status metric and reporting for traces

Full version history

v1.0.2

DXS-3253
- Update Library Versions

Full version history

V1.0.1

Initial version with updated Platform Dashboard link

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