Aws To Azure Services Comparison

AWS to Azure: Migration Tactics for Core Infrastructure Without Sacrificing Performance or Security

Cloud teams tasked with cross-cloud migration run into an immediate reality: “equivalent service” rarely means “identical behavior.” Even minor mismatches—VM instance types, storage APIs, load balancer semantics—can introduce subtle instability, security drift, or cost overruns when moving production workloads. Below: direct mapping, caveats (the ones vendor docs bury in footnotes), and pragmatic migration strategies from AWS to Azure.

AWS ↔ Azure: Service Alignment Table

Direct mapping is a fallacy. Start with the table, but dig for edge-case differences that will matter post-cutover.

Proven Migration Workflow: AWS to Azure

Forget “lift-and-shift” as a silver bullet. To avoid degraded UX and hidden security exposure, tighten each phase:

1. Inventory: Catalog AWS Resources Precisely

Automatic is better:

• Use aws configservice, aws ec2 describe-instances, and aws s3api list-buckets.
• Generate architectural diagrams—CloudMapper can help, though expect inaccuracies with complex orgs.

Document:

• Instance types and AMIs (e.g., c5.large with Amazon Linux 2, kernel ver. 4.14)
• Custom security group rules—parse with scripts, don’t trust the console summary.
• All IAM roles, trust relationships, and explicit policy JSONs.
• RDS engine versions (postgresql 13.7 often isn’t supported on Azure’s Basic SKU).

2. Map Constructs: Plan for Parity — and Gaps

Paste the current state into a mapping table. Flag things that won’t translate:

Note: Azure cost estimation calculators routinely underestimate storage IO; test with synthetic loads using fio or an application-level workload replay.

3. Azure Network & Security: Recreate, Don’t Copy

• VNet layout: Redraw subnet diagrams. Don’t use default address spaces; align with RFC1918 scope and real org CIDR plans.
• NSGs: Automate rule import (Azure PowerShell or Bicep). Layer NSGs at both subnet and NIC for more granular control than AWS Security Groups.
• Key Vault: KMS keys can’t be exported. You’ll need to roll new keys in Key Vault and re-encrypt assets client-side.

# Sample: Importing Security Group to NSG
aws ec2 describe-security-groups --group-id sg-abc123 > sg.json
# (transform with jq, then convert to az network nsg rule create commands)

Gotcha: Azure Private Endpoints behave differently from AWS PrivateLink. DNS integration, specifically, is less transparent—expect to update internal resolution.

4. Data and Compute Migration: Orchestrate for Low Downtime

VM/Compute:

• Azure Migrate works, but for large ops, wrap calls in scripts and monitor migration logs at /var/log/waaagent.log.
• Check for ephemeral disk loss: by default, Azure wipes the temporary drive on redeploy.

Data Layer:

• Databases: Use Azure Database Migration Service with continuous sync, or pg_dump/pg_restore for PostgreSQL—but ensure extensions (pg_crypto, postgis) are supported.
• Object storage: AzCopy with /S flag for recursive, or third-party tools like Flexify for high concurrency (note Azure throttling at scale).

5. Identity & Permissions: Major Rework Required

Porting AWS IAM policies directly isn’t viable.

• Rebuild RBAC: Use role assignments (az role assignment create) at the resource group and object levels.
• Azure AD integration: Plan for hybrid identity if you’re federating with on-prem AD or AWS SSO.

Side effect: Application/service principal creation—automation accounts sometimes hit RSA key size limitations on initial app registration (see [AzureAD error AADSTS700016]).

6. End-to-End Validation: Repeatable, Not One-Off

• Test application performance with wrk or k6 against the new Azure endpoint—track latency and failure rate especially for cross-region traffic.
• Run vulnerability scans (az security assessment), and validate storage/server-side encryption.
• Monitor Azure diagnostic logs (az monitor activity-log list --resource-group ...).

Example: Media Streaming Platform Migration

Scenario:
Live transcoding backend:

• EC2 g4dn.xlarge nodes (NVIDIA T4), auto-scaled.
• S3 for media chunks; Glacier for cold storage.
• RDS PostgreSQL, Multi-AZ.
• ELB with HTTPS listener, SNI routing.

On Azure:

• VMs: NV series (e.g., Standard_NV6_Promo), check tensor core support with driver v.511+.
• Blob storage: hot and cool tiers, lifecycle policies for archive. Blob versioning replaces S3 versioning, not enabled by default.
• PostgreSQL: Flexible Server with active geo-replication, but note maintenance windows differ (UTC only).
• App Gateway: TLS offloading with custom WAF rules (SendRequestBodyToLog: true). Azure CDN for low-latency global delivery.
• Security: Azure AD B2C for user auth, Key Vault for media encryption keys.

Note: S3 event notifications to Lambda must be re-implemented, typically via Azure Event Grid + Azure Functions. Failure to do so may miss object-created triggers—silent data lag.

Non-Obvious Pitfall: Feature Drift Over Time

Equivalent deployments on Day 1 may diverge after 12+ months. Managed services evolve at different cadences.
Watch for:

• Breaking changes with Azure Functions runtime upgrades (v4.x+ introduces cold start changes).
• Retiring instance types or storage SKUs (classic VMs, GRS in some regions).

Build for change: use IaC (Terraform, Bicep) for all infra, and schedule quarterly drift-checks.

Final practice tip:

• Run A/B tests between AWS and Azure endpoints pre-cutover (not just smoke tests). Log user-facing error rates, latency >p95 and >p99. Unexpected: Azure storage accounts throttle differently than S3 at high concurrency.

Cloud-agnostic architecture only works if you treat migration as a recurring process, not a one-time event. Document exceptions, automate regression tests, and budget for recurrent feature review.

Questions—or need a region-specific service equivalency matrix? Reach out.