https://store-images.s-microsoft.com/image/apps.42955.f1f4ec03-9473-4e5b-ac7a-c7bed72a7813.120a8fec-062c-4990-bf77-b509937fb3a9.ed075036-b8df-4800-bc61-888f8a4e1726

Azure Databricks Optimization & Cost Savings Assessment

WinWire Technologies

Preços $30,000

Assess and optimize your Azure Databricks workloads to reduce costs by up to 40% and improve performance across data, AI, and analytics.

Business Challenge

Azure Databricks is the preferred platform for AI, ML, and advanced analytics, but enterprises often face challenges:

  • Oversized or idle clusters driving unnecessary DBU and Azure VM spend
  • Inefficient Spark jobs consuming excessive compute across Azure Databricks pipelines
  • Data growth in Azure Data Lake Storage (ADLS) leading to storage inefficiencies
  • Limited monitoring through Azure Cost Management & Azure Monitor

    • Weak governance and policy enforcement without Azure Policy and cluster policies

    What WinWire Offers

    A structured Azure Databricks Optimization & Cost Savings Assessment (DOCSA) that leverages WinWire’s proven Cloud Cost Optimization (WinCCO) methodology, focused on the Databricks ecosystem on Azure. This identifies performance bottlenecks and provides actionable recommendations to reduce costs by up to 40%, while improving workload efficiency. Key activities:

  • Assess: Review consumption patterns across Azure Databricks clusters, pipelines and ADLS storage. Collect telemetry via Azure Monitor, Log Analytics, and Cost Management.
  • Analyze: Identify underutilized Azure VMs, inefficient jobs, suboptimal Delta table storage, and workload scheduling inefficiencies.
  • Recommend: 1) Right-size Azure Databricks clusters (VM types, driver/worker). 2) Enable autoscaling and auto-termination using Azure-native policies. 3) Optimize data pipelines across Azure Databricks. 4) Tier data within ADLS for cost efficiency. 5) Optimize ML/AI workloads (MLflow, GPU utilization) and streaming pipelines for performance and cost efficiency.
  • Implement & Govern: Configure Azure Policy & tagging, enable chargeback/showback reporting for FinOps alignment, deploy monitoring dashboards via Power BI, and enforce cluster usage policies.

    • Key Deliverables

  • Implement & Govern: Configure Azure Policy & tagging, enable chargeback/showback reporting for FinOps alignment, deploy monitoring dashboards via Power BI, and enforce cluster usage policies.
  • Modeled Cost Savings Report ($/DBU + Azure VM/Storage impact)
  • Cluster Right-Sizing & Governance Policy Recommendations
  • Delta Lake & ADLS Optimization Plan.
  • Ongoing Cost Monitoring Dashboards (Power BI, Azure Monitor)
  • All deliverables aligned with Azure best practices for cost optimization and governance
  • FinOps-ready chargeback/showback reporting and DBU cost forecasting

    • Business Benefits

  • Achieve 30–40% cost savings on Azure Databricks workloads
  • Improve pipeline & Spark job performance with optimized VM usage
  • Reduce ADLS storage costs through tiering & compaction
  • Strengthen compliance with Azure Policy-driven governance
  • Provide FinOps-ready transparency with dashboards

    • Engagement Timeline

    This assessment is designed for organizations leveraging Azure Databricks and integrates with key Azure services to deliver actionable cost savings, governance, and performance improvements:

  • Week 1: Discovery & Azure Monitor/Cost Management setup
  • Week 2–3: Analysis across Azure Databricks, ADLS
  • Week 4: Recommendations, Roadmap, & Executive Review

    • Visão geral

    https://store-images.s-microsoft.com/image/apps.57405.f1f4ec03-9473-4e5b-ac7a-c7bed72a7813.120a8fec-062c-4990-bf77-b509937fb3a9.6386883b-cf38-4763-9eee-5b6a6c88e538