Coforge's Data Cosmos BricksOps

BricksOps is a Coforge Data Cosmos accelerator (under the Pulsar suite) that transforms Databricks operations on Azure with governance analysis, and platform observability into a unified and scalable workflow. It enables platform, engineering, and governance teams to collect workspace inventory, correlate source code and CI/CD activity with Databricks job execution timelines, detect governance signals, and generate cluster optimization recommendations — all from a single control plane. Part of Coforge Data Cosmos™ — the innovation backbone combining platforms, agentic accelerators, and services for end-to-end data engineering, BI, governance, and analytics.

Why BricksOps Exists: Many organizations manage Databricks operations through disconnected workflows and manual processes leading to time-consuming metadata extraction, slow root-cause analysis, reactive cluster optimization, and high effort for governance reviews and audits.

Core Capabilities: • Automated Databricks Inventory Collection – section-based workspace scans with async execution, status tracking, and snapshot storage • Code Repository, CI/CD & Databricks Timeline Correlation – commit tracking, PR/workflow monitoring, and job lifecycle correlation with provenance • Governance and Audit Analysis – unified job timelines, change traceability, and audit-ready evidence generation • Cluster Advisory & Optimization Planning – config analysis, recommendation generation, and rollback-aware adoption planning • Multi-View Operations Portal – executive dashboards, KPI/health summaries, inventory exploration, and governance traceability

Internal Roles Architecture: Collector (workspace inventory), Correlator (repo/CI-CD to job mapping), Advisor (optimization recommendations), and Planner (adoption and rollout strategies). Key Value: accelerated insights (hours to minutes), improved governance and audit readiness, reduced operational effort, and cluster cost optimization.

Key Use Cases: • Banking – audit-ready governance and incident investigation across Databricks jobs for regulatory reviews • Insurance – post-release validation and change traceability across claims and actuarial workloads • Travel – FinOps and cluster cost optimization for peak-season Databricks workloads • Healthcare – governance traceability and audit evidence for HIPAA-regulated Databricks pipelines

The 8-week implementation engagement covers: discovery and workspace inventory setup, platform deployment on Azure, repository/CI-CD correlation configuration, governance and audit analysis enablement, cluster advisory setup, operations portal configuration, and knowledge transfer.

Target Audience: Databricks Platform & Operations Teams, Data Engineering & Platform Teams, FinOps & Cost Optimization Teams, Governance & Audit Teams, and Data Architects.