Choosing an IaaS provider isn’t just about picking a logo. You’re deciding how your workloads will behave for years how much they’ll cost, how they’ll scale, and how safely they’ll run.
If you’re a CTO, DevOps lead, or IT manager, you’ve probably lived through a cloud that looked great at kickoff, then bit back with jitter, noisy neighbors, or surprise bills.
Let’s keep this practical. We’ll start from the workloads you run, translate that into hard requirements, and finish with a scoring model you can take to your board.
1. Start With a Clear Workload Map
You can’t pick a provider without understanding what you run and how it behaves under load.
Classify workloads by profile.
Group them as steady (long-running), bursty (batch), latency-sensitive (APIs), or data-heavy (analytics). Note CPU/GPU ratios, memory, and I/O patterns.
Translate SLOs into hard requirements.
Write down RTO/RPO, uptime targets, latency ceilings, and region constraints. If you need 50 ms p99 latency in-country, say it up front.
Map tenancy and identity needs.
Decide if each product, environment, or team gets its own account. Define key ownership, network change approval, and audit trail requirements early.
2. Align on Baseline Definitions
Make sure everyone’s talking about the same thing.
Use a neutral IaaS reference.
Define where infrastructure ends and managed services begin. Align on compute, storage, and network scope so later comparisons stay clean.
3. Security and Compliance: Beyond the Checkbox
Certificates are table stakes. You need verifiable controls that match your threat model.
Use a control framework as your spine.
Map your policies to a standard like CSA CCM or ISO 27001. Focus on tenant isolation, key management, encryption, and admin access logging.
Ask for the right evidence.
Get docs on key lifecycle management, network isolation tests, and incident response communication. If they won’t show you, that’s a flag.
Clarify shared responsibility.
Spell out who patches what, who monitors which logs, and how incident response hand-offs work.
Suggested read: Check this guide for more details about IaaS Architecture and Components - Best Practices
4. SLA Decoding: What “Four Nines” Really Means
SLA math is easy to read, easy to misunderstand, and rarely covers business loss.
Read the fine print.
Is uptime per-region, per-instance, or per-service? Are maintenance windows excluded? Small details change everything.
Credits ≠ compensation.
Most SLAs pay in credits. They’re capped, non-cash, and often expire. If that’s not good enough, negotiate for stronger remedies.
Design to the SLA.
Multi-AZ placement, health checks, and graceful degradation should be part of your architecture — not an afterthought.
5. Cost Model That Won’t Burn You in Month Three
List prices are the tip of the iceberg. The real spend lives in patterns.
Use commitments and spot wisely.
Commit for steady workloads; use spot/preemptible for stateless or batch jobs with checkpoints. Know where interruptions are safe.
Find the hidden lines.
Egress, inter-AZ traffic, NAT, public IPs, IOPS tiers, snapshots — these add up fast. Model them per workload.
Add guardrails.
Tag everything. Set budgets and anomaly alerts from day one. Have kill switches for runaway jobs — and test them.
6. Network and Data Gravity: Where Lock-In Hides
Lock-in isn’t magic — it’s bandwidth bills and control-plane drift.
Understand egress and locality.
Model data flows both ways, across regions and providers. Check for residency rules and sovereign zones before you deploy.
Test portability.
Can you export and boot VM images elsewhere? Does your Terraform apply cleanly across providers? Run an exit test now, not later.
7. Performance and Scaling: Test Before You Trust
A one-week POC tells you more than any sales deck.
Target tail pain.
Run cold-start, noisy-neighbor, and cross-AZ throughput tests. Track p95/p99 latency, retries, and backoff behavior.
Check quotas and supply.
Open tickets. See how fast you can get capacity. Note GPU and high-memory shape availability.
Validate observability.
Confirm that logs, metrics, and traces export cleanly to your stack. Make sure audit logs are tamper-evident.
8. Org Model and IAM Fit: Who Can Break Prod?
If IAM doesn’t fit your org structure, you’ll fight it daily.
Review hierarchy.
Understand how accounts, projects, or resource groups inherit policies. Decide if you centralize networking or delegate per team.
Enforce least privilege.
Use managed roles, custom roles, and permission boundaries. Build a two-person “break glass” path that’s auditable.
9. Vendor Health and Roadmap
You need a provider that’ll still ship capacity and features next year.
Check market signals.
Look at regional expansion, hardware roadmaps, and AI/GPU availability. Growth pace matters more than press releases.
Know your support path.
Who’s your TAM? What are severity-1 response SLAs? How do you escalate after hours?
Lock in contract levers.
Push for price protection, flexible committed spend, and clear offboarding support.
10. Build a Scoring Model You Can Defend
Keep the decision objective and explainable.
|
Criteria |
Weight |
Example Evidence |
|
Security & compliance |
25 |
Control mappings, audit results |
|
Cost predictability |
20 |
12-month forecast incl. egress |
|
Performance & scaling |
20 |
POC latency & failover metrics |
|
Operational fit |
15 |
IAM design, quota process |
|
Portability |
10 |
Exit test proof |
|
Support & roadmap |
10 |
SLA & TAM details |
Color-code each workload/provider as green (meets), yellow (workaround), or red (risk).
Review reds in a short risk meeting, not a long argument.
TL;DR: Fast Selection Checklist
Must-haves
- Region and data residency fit
- Customer-managed keys with HSM option
- Multi-AZ SLA aligned with architecture
- Cost guardrails and budget alerts
- Proven exit path (image export tested)
Nice-to-haves
- Sovereign regions
- BYO IP space
- Private backbone routing
- Live-migration during maintenance
One-Week POC Plan (Copy-Paste Ready)
Day 1: Set up accounts, IAM, and logging. Deploy canary service.
Day 2: Run cold-start and auto-scale tests.
Day 3: Test storage tail latency under noisy neighbors.
Day 4: Measure cross-AZ throughput and inter-AZ cost.
Day 5: Run failure drills; validate alerts and dashboards.
Day 6: File quota and support tickets; record response times.
Day 7: Roll up costs, color-code results, and estimate 12-month TCO.
Final Notes from the Field
Pick the provider that fits your workloads, not the one with the flashiest service catalog.
If IAM, networking, or billing visibility feels painful in week one, it’ll be worse at scale.
Tight scope. Honest tests. A clear scoring model. That’s how you actually evaluate IaaS providers for enterprise workloads without getting burned later.
Top comments (0)