Great question! You’ve already mapped out some key comparison points, but here are several more critical factors to include in your evaluation of Docker-based container solutions (such as ECS/EKS) and container-image-enabled Lambda:

• Resource & Runtime Limits: Lambda enforces strict caps on resources (e.g., max memory of 10GB, execution time capped at 15 minutes) and container image size (10GB maximum). In contrast, ECS/EKS lets you provision much larger instances, support long-running tasks (hours or even days), and has far looser restrictions on image sizes. This makes container services a better fit for workloads like batch processing, continuous background services, or resource-heavy computations.

• Auto-scaling Behavior: Lambda’s auto-scaling is fully managed and automatic, handling sudden traffic spikes seamlessly—but it has default concurrency limits (adjustable via support tickets). ECS/EKS requires manual setup of Auto Scaling Groups and Cluster Autoscalers, which adds operational overhead but gives you full control over scaling policies (e.g., scaling based on custom metrics, scheduled scaling) for more complex workloads.

• Network Control & Isolation: Lambda runs in AWS-managed networks by default; accessing VPC resources requires extra configuration. ECS/EKS deployments live directly in your custom VPC, letting you fine-tune security groups, subnets, route tables, and network policies. This is essential for applications that need direct access to internal databases, on-premises resources, or require strict network isolation.

• Operational Overhead & Monitoring: Lambda is fully serverless—you don’t manage underlying servers, and monitoring is streamlined via CloudWatch metrics. ECS/EKS demands more operational work: you’re responsible for cluster health, node management, and container orchestration. While this adds complexity, it also lets you use tools like Prometheus/Grafana for deeper performance visibility and granular troubleshooting.

• Stateful Workload Support: Lambda is inherently stateless; any persistent state must be stored in external services (S3, DynamoDB). Container services like ECS/EKS can run stateful applications (e.g., databases, caches) or mount persistent storage (EBS volumes, EFS) to retain state across container restarts. This is a must if your workload needs session persistence or local data caching.

• Runtime & Language Flexibility: Even with container support, Lambda requires adherence to its runtime API (e.g., specific entry points, environment variable conventions). ECS/EKS supports any OCI-compliant container, no matter the language, runtime, or custom configuration—perfect for legacy app migrations or specialized runtimes that don’t fit Lambda’s constraints.

• Deployment & CI/CD Granularity: Lambda container deployments are simplified with ECR integration and tools like SAM or Serverless Framework. ECS/EKS supports more advanced deployment strategies (blue-green deployments, rolling updates, canary releases) via tools like CodePipeline or Argo CD, giving you tighter control over production releases for mission-critical applications.

• Compliance & Audit Controls: For workloads with strict compliance requirements (e.g., data residency, HIPAA, GDPR), ECS/EKS offers finer-grained control over infrastructure—like custom node encryption, detailed audit logs, and network segmentation. While Lambda meets most compliance standards, you have less visibility and control over the underlying infrastructure, which may be a dealbreaker for highly regulated use cases.

Depending on your specific use case—whether you’re building event-driven functions, long-running services, or migrating legacy apps—these factors will carry different weights. Happy evaluating!

内容的提问来源于stack exchange，提问作者Kapoor