The Situation

Acquisitions created cloud chaos

A Fortune 500 professional services firm had grown rapidly through acquisitions. Different divisions used different clouds: AWS was the core, but Azure came in with M365 integrations, and GCP arrived with a machine learning-focused company they bought two years ago. No single governance, no unified cost controls, high spend, massive licensing overlap.

The hidden cost of accidental multi-cloud

With 50,000 employees and global operations across 30 countries, the organization had become genuinely multi-cloud not by strategy but by accident. Teams duplicated tools. Contracts overlapped. No one knew total cloud spend.

  • Cost blindness. AWS and Azure bills went to different cost centers. GCP was owned by a division with its own budget. No consolidated view.
  • Duplicate licensing. Monitoring tools, CI/CD systems, databases licensed on multiple clouds, often underutilized on each.
  • Fragmented identity. Different identity providers per cloud. No single sign-on. Compliance audits required separate reviews per cloud.
  • Network mess. No hub-and-spoke architecture. Egress costs high. No inter-cloud networking. Data transfer between clouds charged at retail rates.
  • Team sprawl. Different teams owned each cloud with no knowledge sharing. AWS skills did not transfer to Azure.
How We Unified Them

Workload-appropriate placement + single governance

01
Multi-Cloud Inventory & Cost Attribution
Unified billing across all three clouds into a single cost data warehouse. Assigned workloads to business units using chargeback tags. Identified duplicate tools, unused resources, and overlapping licenses. Built cost baseline by division and cloud.
Month 1-2Discovery
02
Workload Placement Framework
Evaluated all workloads against criteria: compute model (traditional vs serverless), data gravity, cost, ecosystem lock-in, and team expertise. AWS for core compute and data, Azure for identity and M365 integration, GCP for ML and analytics. No unnecessary cross-cloud migration.
Month 2-3Strategy
03
Unified Networking & Identity
Built Azure Arc to manage on-premises and edge infrastructure alongside Azure. Deployed Anthos for Kubernetes workloads across clouds. Unified identity: Azure AD as single sign-on with AWS IAM federation and GCP Workforce Identity.
Month 3-5Architecture
04
FinOps Platform & Governance Council
Deployed Apptio Cloudability for multi-cloud cost management, optimization recommendations, and allocation. Established cloud governance council with reps from each cloud team. Monthly optimization meetings reduced waste.
Month 5-7Governance
05
License Consolidation & Renegotiation
Consolidated duplicate tool licensing: Terraform Cloud for all IaC, DataDog for monitoring across clouds, HashiCorp Vault for secrets. Renegotiated enterprise agreements with cloud providers. Decommissioned 60+ redundant tools.
Month 6-8Optimization
06
Training & Knowledge Transfer
Multi-cloud certification program for engineers. AWS-to-Azure knowledge sharing sessions. Documented best practices per cloud and created shared runbooks. Reduced context switching for teams.
Month 7-9Operations
What We Delivered

Strategy wins in three numbers

$7M
Annual savings from optimization
Identified through cost analysis, duplicate tool elimination, and license renegotiation. Payoff on the engagement in under 2 months. Savings reinvested in infrastructure modernization.
35%
Cost reduction from baseline
While maintaining performance and capability, across all three clouds. Conservative estimate with room for further optimization in Year 2.
60%
Reduction in duplicate licensing
Single tools deployed across clouds instead of separate instances. Consolidation of monitoring, CI/CD, secrets management, and infrastructure tools.
Why It Worked

Accept reality, then optimize

We did not argue for cloud consolidation to a single provider. Instead, we accepted that this company had three clouds and made that an advantage: AWS for what it does best, Azure for identity, GCP for ML. Then we unified the control plane.

Governance from the cost data, not mandates

Instead of "move everything to AWS," we showed each division exactly what they spent, where, and why. Teams saw the duplicate costs and asked for consolidation. The governance council did not force optimization, it enabled it.

  • Visibility first. Monthly cost dashboards per division, per cloud, per workload. Impossible to hide inefficiency.
  • Chargeback model. Costs attributed directly to business units and application owners. Accountability creates discipline.
  • Workload ownership. Each workload assigned an owner responsible for cost and performance. Owner can move workload to different cloud if cost case exists.
  • Quarterly business reviews. Cloud governance council reviewed optimization progress, approved cost targets, and reported to CFO.
  • Unified roadmap. All three clouds have a 3-year modernization plan tied to cost reduction targets and capability improvements.
Technology Stack

Three clouds, unified operations

AWS
Primary for compute, data lakes, analytics, and high-scale workloads. EC2, RDS, S3, SageMaker for core services.
Azure Arc + Anthos
Unified management across on-premises, edge, and multi-cloud infrastructure. Consistent Kubernetes experience (Anthos) for application deployment.
Apptio Cloudability
Multi-cloud FinOps platform for cost allocation, optimization, and reporting across AWS, Azure, and GCP in a single pane.
Terraform + Vault
Infrastructure as code and secrets management deployed consistently across all three clouds. GitOps workflow for change management.
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