Covers microservices decomposition, inter-service communication (synchronous and asynchronous), API gateway and service mesh patterns, distributed transactions, and observability across service boundaries. Applicable when applications require independent deployment, scaling, and team ownership of individual services.
Microservices decompose an application into small, independently deployable services. Each service owns its data and communicates via APIs or messaging.
Microservices enable independent deployment, scaling, and team ownership, but they introduce significant distributed systems complexity. Too many services too early creates operational overhead without proportional benefit -- start with a modular monolith. Shared databases between services create tight coupling that defeats the purpose of decomposition. Synchronous chains across many services compound latency and fragility. Missing circuit breakers allow cascading failures to propagate across the system. Without distributed tracing, debugging cross-service issues becomes impossible. Inconsistent API contracts cause breaking changes that ripple through consumers.
Disclaimer: Prices are rough estimates based on AWS us-east-1 pricing as of early 2025. Actual costs vary by region, reserved instance commitments, and usage patterns. Prices change over time — always verify with the provider's pricing calculator.
Disclaimer: Azure prices are approximate, based on East US region pricing as of early 2025. Actual costs vary by region, commitment tier, and usage patterns. Always verify with the Azure Pricing Calculator.
Disclaimer: GCP prices are approximate, based on us-central1 region pricing as of early 2025. Actual costs vary by region, commitment tier, and usage patterns. Always verify with the GCP Pricing Calculator.
Disclaimer: All prices are approximate monthly estimates as of early 2025. Actual costs vary significantly based on region, commitment discounts, negotiated contracts, and usage patterns. Always verify with each provider's pricing calculator.
Scale
AWS
Azure
GCP
Small (5 Services)
~$490/mo
~$500/mo
~$420/mo
Medium (15 Services)
~$4,725/mo
~$5,415/mo
~$4,200/mo
Large (50 Services)
~$22,250/mo
~$24,390/mo
~$20,330/mo
Notes:
- GCP tends to be more cost-effective for container workloads due to GKE Autopilot's efficient bin-packing and free cluster management fees (Autopilot).
- Azure API Management at Standard/Premium tier is significantly more expensive than AWS API Gateway; consider Kong or Envoy on AKS for cost savings.
- All three providers offer Kubernetes-based platforms, but managed service costs (databases, messaging) vary significantly.
Databases — each service owning its database multiplies database costs. Typically 35-45% of total spend.
Observability — distributed tracing, centralized logging, and metrics across many services grow significantly. Third-party tools (Datadog, New Relic) charge per host/service.
Messaging/Streaming — Kafka (MSK) clusters are expensive at scale. SQS is cheap per-message but costs grow with volume.
Container platform overhead — EKS control plane ($74/mo) plus sidecar proxies for service mesh add 10-15% compute overhead.