How We Modernized Databricks Release by Utilizing GitLab CI/CD?
Our client is a leading rent-to-own service provider based out of the US that offers leasing services for commodities like furniture, appliances, and...
At a Glance
Our client is a leading rent-to-own service provider based out of the US that offers leasing services for commodities like furniture, appliances, and electronics. They provide services through an online storefront and around 2000+ offline storefront locations across the country.
Challenge
Manual deployment of Databricks patches & upgrades
The client faced challenges with their Databricks management, such as frequent patches, upgrades, performance tuning, and other time-consuming DBA activities. The manual deployment of SQL scripts in their multi-stage Databricks environment was mundane, time-consuming, and inefficient.
They were in need of streamlined data operations, to eliminate manual interventions.
Solution
Transforming SQL scripts deployment model to automated DataOps pipelines
Our DevOps experts conducted detailed analysis and proposed an effective solution for deploying SQL scripts in different Databricks environments. We recommended leveraging GitLab as a streamlined version control and CI/CD solution for deploying SQL scripts.
A standard branching strategy in GitLab was adopted, and the SQL scripts were stored as Notebook files. This enables the in-house team to automate the build, test, and deployment processes through a CI/CD pipeline. We established a specialized GitLab CI/CD pipeline for the client's multi-stage Databricks environment. This pipeline ensured efficient and automated deployments, eliminating manual intervention and reducing the risk of errors.
To improve the deployment process, best practices were implemented, such as configuring pre-deployment approval for preferred user groups and notifying them of the success or failure of the deployment process.
The client achieved a modernized and automated deployment pipeline for their Databricks environment by implementing these comprehensive DataOps.
Benefits
Streamlined Databricks deployment and enhanced productivity
Our client experienced a remarkable 65% reduction in Databricks deployment efforts. By effortlessly approving patches, they can easily push changes in SQL scripts to higher environments. This smooth-running process freed up their development teams to focus on enhancements, patches, and upgrades, instead of being entangled in deployment complexities.
With our best practice recommendations, the client gained the ability to roll back changes in their data warehouse environment. These best practices ensured complete business continuity, seamless data streaming, improved productivity, and smooth operations.
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