Choosing the right cloud provider in 2025 is no longer a simple “AWS vs GCP vs Azure” debate. For engineering teams, the real question is: Which cloud matches your workloads, cost constraints, and SLOs?
Why Benchmarking Matters
On paper, all three cloud providers look similar. But once you start deploying:
- AWS offers strong multi-AZ reliability, but network egress costs can quickly surprise you.
- GCP is highly cost-efficient and shines in data/ML workloads.
- Azure provides seamless integration with Microsoft stack—a big plus for enterprises already in that ecosystem.
Without proper benchmarking, teams often run into unexpected latency issues, escalating TCO, or unnecessary complexity in architecture.
What We Learned from Running Benchmarks
- AWS → Best for enterprises that prioritize high availability and global scale.
- GCP → Great for startups/SMEs thanks to predictable pricing and strong data/ML offerings.
- Azure → Works smoothly for organizations tied to Microsoft tools (AD, Office, Dynamics).
A Practical Cloud Selection Roadmap (6 Steps)
This framework helps avoid vendor lock-in and ensures your cloud decision is backed by measurable performance and cost data.
Key Takeaways:
- There’s no one-size-fits-all cloud. The “best” provider depends on your workload and scale.
- Benchmark before you commit—POC results often differ from vendor marketing claims.
- Always consider both SLOs and TCO when making long-term decisions.
I’ve published a detailed benchmark report with a free Cloud TCO & SLO Calculator.
If you want to see the full comparison and apply the methodology to your own projects, check it out!
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