Over 2 years, the client deployed and maintained 5 critical solutions using the framework.
Meet our client
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Client’s Challenge
The client needed to quickly bring complex solutions developed by the DS team into production while avoiding delays caused by dependency on the Cloud Ops team. Data persistence in production environments (e.g., BigQuery) was essential, but time constraints and formal complications deanded a streamlined, independent process.
Our Solution
We introduced a pipeline deployment template that incorporated code quality enforcement, CI/CD, Infrastructure as Code (IaC), and versioning to ensure robust workflows. The solution featured semi-automated deployment with job scheduling, automated documentation, and IaC for easy setup. Integration with Jupyter notebooks streamlined maintenance and issue analysis.
Client’s Benefits
This framework enabled rapid time-to-market, accelerating idea delivery for business stakeholders. Over 2 years, the client deployed and maintained 5 critical solutions using the framework.
