Serverless Frameworks (AWS Lambda, Azure Functions) Questions and Answers for Viva

Answer-1: Serverless computing allows developers to build and run applications without managing servers. The cloud provider handles infrastructure management.

Answer-2: They are serverless computing platforms that allow running code in response to events without provisioning or managing servers.

Answer-3: AWS Lambda runs code in response to triggers such as changes in data or system state and automatically manages the compute resources.

Answer-4: Azure Functions is tightly integrated with the Azure ecosystem and provides more built-in templates and orchestration via Durable Functions.

Answer-5: Use cases include data processing,REST APIs,IoT backends,automation,chatbots,and file transformation.

Answer-6: A function is a small unit of logic triggered by an event,such as HTTP request,database change,or message queue.

Answer-7: Supported languages include Python,Node.js,Java,C#,Go,Ruby,and custom runtimes via Lambda Layers.

Answer-8: Languages include C#,JavaScript,Python,Java,PowerShell,and custom handlers.

Answer-9: Cold start is the delay that occurs when a function is invoked for the first time or after a period of inactivity.

Answer-10: Use provisioned concurrency (Lambda) or Always On (Azure),and choose languages with faster startup like Node.js or Python.

Answer-11: The maximum timeout for AWS Lambda is 15 minutes per invocation.

Answer-12: It depends on the hosting plan; Consumption Plan allows up to 5 minutes,Premium/DEDICATED plans allow longer.

Answer-13: Lambda automatically scales by running multiple instances of the function in response to incoming requests.

Answer-14: Azure Functions auto-scale based on demand,especially under the Consumption or Premium Plan.

Answer-15: Yes,Lambda can be configured to run inside a VPC to access private resources.

Answer-16: It is an extension of Azure Functions that enables stateful workflows using code in a serverless environment.

Answer-17: Lambda Layers are a way to package libraries and dependencies separately from the function code.

Answer-18: AWS Lambda charges are based on number of invocations and duration of execution,measured in milliseconds.

Answer-19: Pricing depends on the number of executions and execution time under the Consumption Plan.

Answer-20: It is a design pattern where services communicate via events and triggers rather than direct API calls.

Answer-21: Deployment can be done using the AWS Console,CLI,SDKs,or frameworks like Serverless Framework and SAM.

Answer-22: You can deploy using Visual Studio,Azure CLI,GitHub Actions,or Azure DevOps pipelines.

Answer-23: It is an open-source CLI tool for deploying and managing serverless applications across cloud providers.

Answer-24: It provides configuration files and CLI commands to easily deploy,manage,and monitor Lambda functions.

Answer-25: Yes,it has plugins and templates to deploy Azure Functions using the same framework.

Answer-26: You can use Amazon CloudWatch to collect logs,metrics,and set up alerts.

Answer-27: Azure Monitor and Application Insights provide detailed logs,metrics,and diagnostics.

Answer-28: Yes,they can connect to databases like RDS,Cosmos DB,or DynamoDB via SDKs or connectors.

Answer-29: A trigger is an event source that causes the function to execute,such as HTTP request or database update.

Answer-30: Bindings are declarative way to connect input/output to data sources like queues,blobs,or HTTP.

Answer-31: Yes,Lambda functions invoked synchronously (e.g.,via API Gateway) can return HTTP responses or data.

Answer-32: They use IAM roles (AWS),managed identities (Azure),encryption,and secure coding practices.

Answer-33: Challenges include cold starts,vendor lock-in,debugging complexity,and limits on runtime or payload size.

Answer-34: Yes,AWS Lambda supports versioning and aliases to manage different stages of a function.

Answer-35: A Function App is a container for multiple Azure Functions sharing the same hosting plan and resources.

Answer-36: It is a feature that pre-allocates containers to avoid cold starts and guarantee low-latency execution.

Answer-37: AWS Lambda supports up to 10 GB of memory per function.

Answer-38: It varies by hosting plan,but Consumption Plan allows up to 1.5 GB,and Premium/Dedicated can be higher.

Answer-39: Logs are automatically sent to CloudWatch Logs,and can be analyzed or exported.

Answer-40: Logs can be streamed to Azure Monitor,Application Insights,or exported to external systems.

Answer-41: Lambda@Edge is a feature of CloudFront that allows running Lambda functions at AWS edge locations.

Answer-42: Use AWS SAM CLI,Docker containers,or the Serverless Framework for local testing.

Answer-43: Use Azure Functions Core Tools and Visual Studio Code or Visual Studio.

Answer-44: It is the maximum duration a function is allowed to run before it's forcibly stopped.

Answer-45: They are key-value pairs injected into the runtime environment for configuration or secrets.

Answer-46: AWS retries failed asynchronous invocations by default,and you can configure DLQs for failures.

Answer-47: Azure Functions have built-in retry policies that can be configured in host.json.

Answer-48: It is a queue that stores failed messages or events that couldn?t be processed after retries.

Answer-49: Yes,both AWS Lambda (via CloudWatch Events) and Azure Functions (via Timer Trigger) support scheduled executions.

Answer-50: Benefits include reduced operational overhead,automatic scaling,cost-efficiency,and faster development cycles.