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Delta Operational Metrics Store (DeltaOMS)

Delta Operational Metrics Store (DeltaOMS) is a solution that helps to build a centralized repository of operational metrics/statistics for your Lakehouse built on Delta Lake

Project Overview

DeltaOMS provides a solution for automatically collecting operational metrics/statistics from Delta Lakehouse tables into a separate centralized database. This will enable you to gain centralized access to the operational metrics for your data in near real-time. This centralized data can be utilized to gain helpful operational insights, setting up monitoring/alerting and observability for your Delta Lakehouse ETL Pipelines. It could also help you to identify trends based on data characteristics, improve ETL pipeline performance, provide capabilities for auditing and traceability of your Delta Lake data etc.

Few examples of how you could use the centralized operational metrics/statistics collated by DeltaOMS :

  • What are the most frequent WRITE operations across my data lakehouse ?
  • How many WRITE operations were run on my Data Lakehouse in the last hour ?
  • Which are the top WRITE heavy databases in my data lakehouse ?
  • Track File I/O ( bytes written, number of writes etc.) across my entire data lakehouse
  • Tracking growth of data size, commit frequency etc. over time for tables/databases
  • Did the delete operations for GDPR compliance go through and what changes it made to the filesystem ?

How does DeltaOMS work

DeltaOMS subscribes to the delta logs of the configured databases/tables and pulls all the operational metrics written out during Delta table writes. These metrics are enriched with additional information ( like path, file name, commit timestamp etc.), processed to build snapshots over time and persisted into different tables as actions and commit information. Refer to the Delta Transaction Log Protocol for more details on Actions and CommitInfo.

High-Level Process Flow:

DeltaOMS High-Level Process Flow

How is the DeltaOMS executed

DeltaOMS provides a jar and sample notebooks to help you setup , configure and create the required databases, tables and Databricks Jobs.These notebooks and jobs run on your environment to create a centralized operational metrics database, capture metrics and make it available for analytics.

How much does it cost ?

DeltaOMS does not have any direct cost associated with it other than the cost to run the jobs on your environment.The overall cost will be determined primarily by the number of Delta Lakehouse objects tracked and frequency of the OMS data refresh. We have found that the additional insights gained from DeltaOMS helps reduce the total cost of ownership through better management and optimization of your data pipelines while providing much improved view on the operational metrics and statistics for the Delta Lakehouse.

More questions

Refer to the FAQ and Developer Guide

Getting Started

Refer to the Getting Started guide

Deploying / Installing / Using the Project

The DeltaOMS solution is available through Maven central. You can get the jar using the following maven co-ordinates :

  • Snapshot release :"com.databricks.labs" % "delta-oms_2.12" % "0.x.0-SNAPSHOT"
  • Regular release :"com.databricks.labs" % "delta-oms_2.12" % "0.x.0"

Please follow the Getting Started guide for instructions on using DeltaOMS on Databricks environment.

DEMO

The following Databricks notebooks also provides an end to end demonstration of DeltaOMS execution and analysis:

These three notebooks can be put in the same folder and executed on a Databricks cluster.

Releasing the Project

DeltaOMS is released as a jar (through Maven) and notebooks (through Github Repo) for setting up Databricks jobs. It also provides few sample notebooks for typical analysis. Refer to the Getting Started guide for more details.

Project Support

Please note that all projects in the databrickslabs github account are provided for your exploration only, and are not formally supported by Databricks with Service Level Agreements (SLAs). They are provided AS-IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects.

Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.

Contributing

See our CONTRIBUTING for more details.