Serverless vs Containers: Use Cases Questions and Answers for Viva

Answer-1: Yes, with services like AWS Amplify or Netlify; though it's not the function execution but the deployment.

Answer-2: Using Serverless for API gateways or background tasks, and containers for core business logic or persistent workloads.

Answer-3: Serverless abstracts server management entirely, while containers package code with dependencies but still require infrastructure management.

Answer-4: Use Serverless for lightweight, event-driven, short-lived tasks with unpredictable traffic.

Answer-5: Use Containers for long-running applications, custom runtime environments, or legacy systems migration.

Answer-6: Yes, Serverless can host web apps using services like AWS Lambda with API Gateway.

Answer-7: Event-driven processing, APIs, cron jobs, backend tasks, and lightweight microservices.

Answer-8: Microservices, custom apps, legacy application migration, CI/CD pipelines, and large-scale services.

Answer-9: Serverless auto-scales instantly per request; containers scale based on defined metrics or orchestration rules.

Answer-10: Yes, cold starts can introduce latency during the first invocation after inactivity.

Answer-11: High-performance computing, streaming, machine learning, and stateful applications.

Answer-12: Containers encapsulate the app and its environment, enabling consistent deployment across environments.

Answer-13: Yes, Serverless is cost-effective for infrequent workloads since you only pay per execution.

Answer-14: Through container orchestration tools like Kubernetes with Ingress, services, and DNS.

Answer-15: Yes, services like AWS Lambda can process data from Kinesis or S3 events.

Answer-16: No, Serverless is not suitable for persistent databases; use external services for data storage.

Answer-17: With volume mounts and persistent storage options through container orchestration platforms.

Answer-18: Yes, for light inference tasks with fast execution time; heavy models are better suited for containers.

Answer-19: Yes, because Serverless offerings are platform-specific (e.g., AWS Lambda, Azure Functions).

Answer-20: Containers integrate well with CI/CD pipelines and support infrastructure as code.

Answer-21: Containers are better suited due to the need for persistent connections.

Answer-22: Yes, Serverless is ideal for background jobs triggered by events.

Answer-23: Yes, you can mix both by calling Serverless functions from containerized apps.

Answer-24: Node.js, Python, Java, Go, .NET, and more.

Answer-25: Yes, containers can use any custom runtime or base image.

Answer-26: Containers, as they can package and run legacy software with minimal code changes.

Answer-27: Milliseconds to a few seconds, depending on cold or warm start.

Answer-28: Using network policies, image scanning, secrets management, and runtime protection.

Answer-29: Through role-based access control, environment isolation, and IAM policies.

Answer-30: Yes, containers offer excellent portability across on-premises and cloud environments.

Answer-31: Yes, it is ideal for running short-lived batch jobs in parallel.

Answer-32: Serverless is ideal for lightweight, scalable APIs; containers offer more control for complex APIs.

Answer-33: Yes, with advanced orchestration tools like Knative or Fargate, but not all platforms support it natively.

Answer-34: Containers require more setup and operational overhead than Serverless.

Answer-35: Using built-in services like AWS CloudWatch or Azure Monitor.

Answer-36: Through sidecar logging agents or centralized tools like Fluentd and ELK stack.

Answer-37: Yes, using pipelines and frameworks like Serverless Framework, SAM, or Terraform.

Answer-38: Yes, but require more configuration than Serverless, which is built for event-driven models.

Answer-39: Serverless costs per request; containers cost per allocated resources.

Answer-40: Containers are better for sustained high-throughput workloads.

Answer-41: Using provider-native tools (e.g., AWS CloudWatch) or third-party monitoring services.

Answer-42: With tools like Prometheus, Grafana, Datadog, and Kubernetes-native observability.

Answer-43: Serverless Framework, AWS SAM, Terraform, and Pulumi.

Answer-44: Docker, Kubernetes, Helm, and OpenShift.

Answer-45: Easier with containers due to long-lived connections; Serverless may face connection limits.

Answer-46: Containers due to long execution times and better resource control.

Answer-47: Yes, containers provide full control over OS, libraries, and dependencies.

Answer-48: Serverless allows function-level scaling by design.

Answer-49: Serverless is ideal for lightweight services; containers suit complex, stateful, or long-lived microservices.

Answer-50: Containers can run GPU-intensive tasks; Serverless generally lacks GPU support.