How Codincity Helped Optimize Azure Spend for Automotive Leader
Client Overview
Client: Automotive Leader
Industry: Heavy Vehicles
Geography: Japan & India
Solution Focus: Cloud Architecture & Service Evaluation, Infrastructure Optimization
The Business Challenge
The client had an annual Azure infrastructure spend of approximately USD 4 million. Their objective was to rapidly optimize cloud costs without disrupting business continuity or operational performance.
Codincity’s Solution
Backed by the strength of our dedicated internal FinOps practice and proven experience delivering FinOps consulting and implementation engagements for global customers, Codincity planned and executed a targeted Azure Cost Optimization initiative. Leveraging FinOps principles, the focus was to achieve maximum cost impact in the shortest time possible without disrupting business operations. The initiative was delivered in an Agile model, executed over six focused sprints to enable rapid discovery, implementation, and validation.
Business Impact
Analysed Azure resource utilization (VMs, storage, PaaS workloads) against application needs and performance baselines; proposed and implemented rightsizing across compute tiers.
Identified and decommissioned idle or underutilized resources, including legacy test environments, unattached disks, orphaned NICs, and redundant backups.
Implemented Reserved Instances (RIs) selectively based on workload classification (steady state vs. burst), application lifecycle stage, and environment (production, UAT, dev).
Introduced Auto-shutdown and Scaling Policies for non-production workloads and infrequently used services.
Applied Azure Hybrid Benefit (AHB) where applicable to leverage existing licensing investments.
Enabled Azure Cost Management & Budgets, configuring budgets, cost alerts, and tagging policies for improved cost governance.
Established tagging standards and naming conventions to align cloud cost reporting with business units, projects, and owners.
Embedded the FinOps framework with regular cadence for review, variance analysis, chargeback/showback models, and KPI-driven decision-making.
Business Outcome
A total of 28% in cost optimization opportunities were identified, categorized into short-, medium-, and long-term initiatives.
20% of savings were successfully implemented within the scope of this engagement.
Annualized savings of USD 768K were realized, with USD 510K achieved within the first six weeks of execution.
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