46% Reduction in Azure Spend Through an Automation-First FinOps Engine
A leading global transportation services provider
“When cloud infrastructure grows without clear ownership, governance, or automation, cost overruns become inevitable. The answer is not more manual oversight; it is an intelligent FinOps engine that continuously governs, optimizes, and automates cloud consumption.”
—– An enterprise technology leader seeking greater control over cloud costs, security, and resource utilization
When Beacon Mobility set out to regain control of its rapidly expanding Azure environment, an automation-first FinOps approach delivered measurable improvements:
46%
Reduction in monthly Azure spend
$30K
Monthly savings achieved against peak Azure spend
85%
Of VMs and databases identified as overprovisioned
Zero
Manual effort required to operate the automated shutdown schedule
Business Problem
Beacon Mobility’s Azure footprint had grown beyond its original operating model. What was expected to be a ~$30,000/month cloud environment had increased to more than $65,000/month, while cloud operations remained outsourced to a third-party IT provider.
The environment lacked a consistent tagging strategy, clear ownership boundaries, and systematic resource governance. More than eight accounts held Global Admin access, while infrastructure was frequently provisioned reactively with limited decommissioning discipline.
The lack of visibility made it difficult for engineering leadership to determine what resources were running, who owned them, why they existed, and whether the capacity being paid for was actually being used.
Beacon Mobility needed a way to move from reactive cloud management to automated, policy-driven FinOps without adding another layer of manual operational overhead.
Customer Challenge
Beacon Mobility faced multiple challenges across its Azure environment, including data analytics pipelines, a data warehouse, an internal security tool, and BI dashboards.
85% of the VMs and databases analyzed were overprovisioned, with more than 60% of provisioned VMs using only 15% of average vCPU and 65% of peak vCPU over the measured 45-day period. Similarly, 75% of databases had used less than 15% of their provisioned IOPS.
The absence of tagging made it difficult to programmatically distinguish development, staging, and production workloads. Shutdown and scaling activities were handled manually, creating recurring opportunities for idle resources to remain active overnight.
At the same time, excessive administrative access introduced security risk, while the absence of a monitoring feedback loop allowed cost anomalies to accumulate unnoticed.
Azure-native tools addressed individual aspects of the problem, but no single solution provided the required combination of tag-driven automation, scheduled shutdown, PaaS coverage, rightsizing, governance, and continuous optimization.
Movate Solution
Movate designed an automation-first FinOps engine to strengthen governance, automate cloud operations, and continuously optimize Azure consumption. The solution introduced mandatory tagging for Environment, Owner, CostCenter, and Criticality, enforced through Azure Policy, while reducing global admin access through least-privilege roles.
At its core, a serverless Azure Functions engine automatically identified tagged VMs and PaaS databases and shut them down outside business hours, bringing them back online before the next business day.
The solution also included:
- Time-zone-aware scheduling with Daylight-Saving handling
- Tag-driven resource targeting
- Least-privilege execution
- Failure alerts
- Continuous rightsizing based on utilization
- Spot and on-demand purchasing based on workload needs
This created a closed-loop FinOps model combining governance, automation, optimization, and cost visibility.
Movate Applied AI Differentiator
Movate transformed Beacon Mobility’s cloud cost-management model from manual, reactive oversight to automated, policy-driven optimization.
The tag-driven automation engine now automatically stops non-critical workloads for approximately 12 hours per night, six nights a week, eliminating the need for teams to remember or manually execute shutdown schedules. The resulting operating model requires zero manual effort to run the schedule.
The impact was significant: monthly Azure spend fell from $65,000 to $35,000—a 46% reduction from peak spend. At the same time, Beacon Mobility gained full tag-based resource visibility and moved away from its previous vendor-managed, untagged environment.
Beyond immediate savings, the solution established a sustainable foundation for continued optimization. The $35,000 run rate became a visible, measurable baseline, enabling Beacon Mobility to identify further opportunities across PaaS rightsizing and reserved-capacity optimization rather than operating without a clear understanding of where cloud spend was going.
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