Selecting a cloud platform for production systems is one of the most consequential technical decisions you’ll make. The choice affects costs, architectural possibilities, operational complexity, and how easily you can change direction later. Unlike development environments where you can experiment freely, production systems demand stability, performance, and predictable costs at scale.
The three major platforms are AWS, Google Cloud Platform, and Azure. Each has matured to the point where you can build almost anything on any of them. The differences lie in pricing structures, regional availability, specific service capabilities, and operational philosophies.
Compute Service Comparison
How you run your code fundamentally shapes operational complexity and cost structure. Each platform offers multiple compute paradigms with different tradeoffs.
Virtual Machines and Bare Metal
AWS EC2 provides the most mature VM offering with the widest instance type selection. Reserved instances and savings plans offer significant discounts for committed usage. Spot instances provide steep discounts for interruptible workloads. Pricing varies by region, instance type, and commitment level.
GCP Compute Engine offers fewer instance types but with more flexible custom machine configurations. You specify exactly how many vCPUs and memory you need rather than choosing from predefined combinations. Sustained use discounts apply automatically without commitment.
Azure Virtual Machines integrates tightly with Microsoft’s ecosystem, making it the natural choice if you’re already invested in Windows Server or Active Directory. Pricing and instance variety falls between AWS and GCP.
Container Orchestration
Kubernetes runs on all three platforms with varying degrees of operational overhead. GKE pioneered managed Kubernetes and remains the most polished implementation. Autopilot mode handles node management entirely, letting you focus purely on workload configuration.
EKS provides managed Kubernetes control planes but requires more operational work around node management and networking. Fargate for EKS removes node management but costs more per workload and has limitations.
AKS offers managed Kubernetes with good integration into Azure’s networking and identity systems. It’s reached feature parity with competitors but lacks the operational maturity of GKE.
Serverless Compute
AWS Lambda dominates the serverless space with the most mature ecosystem and extensive integration with other AWS services. Cold start times have improved but remain a consideration for latency-sensitive applications. Lambda’s pricing charges for execution time and memory allocation.
Google Cloud Functions and Cloud Run offer similar serverless capabilities. Cloud Run stands out by supporting arbitrary container images and allocating more generous resource limits per instance. Cold starts are generally faster than Lambda for equivalent workloads.
Azure Functions mirrors Lambda’s capabilities with strong integration for Microsoft-centric stacks. Durable Functions provides stateful serverless workflows that simplify building complex coordination logic.
Storage and Database Services
Data persistence requirements often drive platform choice more than compute considerations.
Object Storage
S3 is the de facto standard for object storage. Every other platform offers S3-compatible APIs specifically because S3 became ubiquitous. Performance, durability, and feature depth are excellent. Pricing complexity comes from data transfer costs, request pricing, and storage class options.
Google Cloud Storage offers simpler pricing with four storage classes and no data transfer fees between storage and compute within the same region. This can significantly reduce costs for data-intensive applications.
Azure Blob Storage provides equivalent functionality with good performance. Hot, cool, and archive tiers match different access patterns to cost structures.
Managed Databases
RDS supports multiple database engines including PostgreSQL, MySQL, and SQL Server with managed backups, replication, and scaling. Aurora offers MySQL and PostgreSQL compatibility with better performance and availability characteristics but at higher cost.
Cloud SQL provides managed PostgreSQL, MySQL, and SQL Server with straightforward configuration and good performance. Cloud Spanner offers globally distributed relational databases with strong consistency.
Azure Database services cover PostgreSQL, MySQL, and SQL Server with managed operations. Cosmos DB provides globally distributed multi-model database capabilities with multiple consistency levels.
Networking and Traffic Management
Network architecture affects performance, costs, and operational complexity significantly.
Load Balancing
AWS offers multiple load balancer types. Application Load Balancers handle HTTP/HTTPS with advanced routing. Network Load Balancers provide TCP/UDP with ultra-low latency. Each has different pricing models based on capacity units.
GCP’s load balancing provides global load balancing by default, routing traffic to the nearest healthy backend automatically. A single global IP address can distribute traffic across regions without DNS-based routing.
Azure Load Balancer and Application Gateway provide standard load balancing capabilities. Azure Front Door offers global load balancing similar to GCP’s approach with WAF integration.
CDN and Edge Computing
CloudFront integrates deeply with other AWS services and provides extensive edge locations worldwide. Lambda@Edge enables running code at edge locations for request/response manipulation.
Cloud CDN integrates with GCP’s load balancing infrastructure cleanly. Cache hit rates are generally excellent. The simpler pricing model makes costs more predictable than CloudFront’s region-based structure.
Azure CDN offers similar capabilities with good integration into the Azure ecosystem. Azure Front Door combines CDN with global load balancing and WAF.
Operational Tooling and Observability
Production systems require comprehensive monitoring, logging, and debugging capabilities.
Monitoring and Metrics
CloudWatch provides basic monitoring for all AWS services with custom metrics support. The retention periods are limited without additional cost, and the query language is less powerful than alternatives.
Cloud Monitoring offers generous free tiers and better query capabilities through PromQL support. The unified monitoring approach across all GCP services simplifies observability.
Azure Monitor consolidates metrics, logs, and application performance data. Integration with Application Insights provides detailed application-level telemetry.
Logging Infrastructure
CloudWatch Logs handles log aggregation but querying large log volumes becomes expensive quickly. Many production systems export logs to Elasticsearch or dedicated logging platforms.
Cloud Logging includes generous free tiers and efficient log querying. Log sinks enable routing logs to BigQuery for long-term analysis without retention limitations.
Azure Monitor Logs uses Kusto Query Language for powerful log analysis. Cost optimization requires careful retention policy configuration.
Pricing Model Considerations
Understanding pricing structures prevents budget surprises at scale.
Commitment Discounts
AWS Reserved Instances and Savings Plans require upfront commitment but offer 30-70% discounts. The secondary marketplace allows selling unused reservations, providing some flexibility.
GCP provides sustained use discounts automatically based on monthly usage without commitment. Committed use contracts offer additional savings but with less flexibility than AWS’s marketplace.
Azure Reserved Instances work similarly to AWS with various term lengths and payment options. Azure also offers spot instances with deep discounts for interruptible workloads.
Data Transfer Costs
Data egress charges often exceed compute costs for bandwidth-intensive applications. AWS charges for data leaving regions at rates varying by destination. Architecture decisions that minimize cross-region traffic significantly reduce bills.
GCP doesn’t charge for egress to other GCP services in the same region, simplifying cost modeling. Egress to internet follows similar pricing to AWS but with simpler tier structures.
Azure’s egress pricing falls between AWS and GCP in complexity. Zone-to-zone and region-to-region transfers incur charges.
Vendor Lock-In and Portability
Platform-specific services increase lock-in but often provide better operational characteristics than portable alternatives. Using platform-agnostic tools like Kubernetes, PostgreSQL, and Redis maximizes portability at the cost of managing more infrastructure yourself.
Terraform enables infrastructure-as-code across platforms, making multi-cloud or migration scenarios more feasible. However, platform-specific services don’t have direct equivalents elsewhere, requiring architectural changes during migration.
The realistic approach is accepting some lock-in for core services where managed offerings provide significant operational value, while maintaining portability for application code and data formats. Complete platform independence is rarely worth the additional complexity.
Making the Decision
Start by documenting your actual requirements. Compute characteristics, data storage needs, geographic distribution, compliance requirements, and existing team expertise all influence the best choice. If you’re already using Microsoft enterprise services, Azure’s integration value is substantial. If your workload is heavily containerized, GKE’s operational maturity matters. If you need the widest service catalog and ecosystem, AWS provides that breadth.
Run proof-of-concept implementations on your top candidates. Replicate critical workload patterns to understand actual operational characteristics and costs. Theoretical pricing calculators help but nothing replaces real-world testing under production-like conditions.
Consider the long-term operational requirements. The platform with lower compute costs might have higher operational overhead, requiring more engineering time for maintenance. Factor in the fully loaded cost of running systems including engineering time, not just infrastructure bills.