Editing AWS Lambda (section)

= AWS Lambda =
AWS Lambda is Amazon’s event-driven, serverless compute service that runs code in response to triggers without provisioning or managing servers.

== Remembering (Knowledge / Recall) ==
🧠 At this level, an expert can **define** AWS Lambda and **name** its core components, terminology, and usage contexts.

* '''Core terminology & definitions'''
** '''[https://en.wikipedia.org/wiki/AWS_Lambda AWS Lambda]''' – Amazon Web Services’ serverless compute platform that executes functions in response to events.
** '''[https://en.wikipedia.org/wiki/Serverless_computing Serverless computing]''' – A cloud execution model where infrastructure, scaling, and capacity are fully managed by the provider.
** '''[https://en.wikipedia.org/wiki/Function_as_a_Service Function-as-a-Service (FaaS)]''' – A cloud model where applications run as stateless functions invoked on demand.
** '''[https://en.wikipedia.org/wiki/Event-driven_programming Event-driven programming]''' – A programming paradigm in which execution is triggered by external events.
** '''[https://en.wikipedia.org/wiki/Amazon_Web_Services Amazon Web Services (AWS)]''' – The cloud platform that provides Lambda and related services.

* '''Key components & services involved'''
** '''[https://en.wikipedia.org/wiki/Amazon_S3 Amazon S3]''' – Can trigger Lambda functions on object events.
** '''[https://en.wikipedia.org/wiki/Amazon_DynamoDB Amazon DynamoDB]''' – Can invoke Lambda on table streams.
** '''[https://en.wikipedia.org/wiki/Amazon_API_Gateway Amazon API Gateway]''' – Routes API requests to Lambda.
** '''[https://en.wikipedia.org/wiki/Amazon_CloudWatch Amazon CloudWatch]''' – Stores logs and metrics for Lambda.

* '''Canonical tools & frameworks'''
** '''[https://en.wikipedia.org/wiki/AWS_CloudFormation AWS CloudFormation]''' – Infrastructure-as-code deployment.
** '''[https://en.wikipedia.org/wiki/Amazon_Web_Services#Developer_tools AWS CLI / SDKs]''' – Programmatic Lambda management.
** '''[https://en.wikipedia.org/wiki/Integrated_development_environment IDEs]''' – Used to write, package, and test Lambda code.
** '''[https://en.wikipedia.org/wiki/Continuous_delivery CI/CD pipelines]''' – Commonly automate Lambda deployments.

* '''Where AWS Lambda is commonly used'''
** Serverless APIs, microservices, backend automation
** Data processing pipelines and batch jobs
** Real-time file, stream, or database event handling
** Cloud automation and DevOps workflows

* '''Typical recall-level facts'''
** Introduced by AWS in **2014**.
** Supports multiple languages (e.g., Python, Node.js, Java, Go).
** Billed based on requests and execution duration.
** Functions run in short-lived, stateless execution environments.

----

== Understanding (Comprehension) ==
📖 At this level, an expert can **describe**, **summarize**, and **compare** AWS Lambda concepts and behaviors.

* '''Conceptual relationships & contrasts'''
** AWS Lambda vs. '''[https://en.wikipedia.org/wiki/Cloud_computing cloud VMs]''' – No servers to manage or provision.
** Serverless vs. '''[https://en.wikipedia.org/wiki/Microservices microservices]''' – Lambda can implement microservice patterns but is not required.
** AWS Lambda vs. '''[https://en.wikipedia.org/wiki/Containerization containerization]''' – Lambda abstracts runtime environments and scaling.

* '''Core principles & paradigms'''
** Stateless execution — functions do not retain memory between invocations.
** Automatic scaling — concurrency increases as events increase.
** Pay-per-use — costs align with actual execution time.
** Event-driven architecture — workloads react to triggers.

* '''How AWS Lambda works'''
** Code + runtime + configuration = deployed function.
** Execution environments are created on demand.
** Events trigger invocation; outputs return to the calling service.

* '''Producer vs. consumer perspectives'''
** Developer – Writes and packages function logic.
** Platform engineer – Secures, monitors, and manages scaling.
** Application user – Interacts indirectly through APIs, apps, or event triggers.

* '''Typical comprehension-level abilities'''
** Can explain why Lambda is useful.
** Can identify services that can trigger a Lambda function.
** Can describe cold starts and their impact.

----

== Applying (Use / Application) ==
🛠️ At this level, an expert can **use** AWS Lambda to build functioning workloads.

* '''"Hello, World" examples'''
** Creating a simple function triggered by API Gateway.
** Uploading a Lambda function package via AWS Console or CLI.

* '''Guides for core task loops'''
** Develop → package → deploy → test → monitor.
** Connecting Lambda to S3, DynamoDB, or SNS event sources.
** Wiring Lambda behind an HTTP endpoint.

* '''Common commands / operations'''
** Deploy function with AWS CLI (`aws lambda create-function`).
** Update code or configuration (`aws lambda update-function-code`).
** View logs in CloudWatch (`aws logs tail`).

* '''Real-world use cases'''
** Image or document processing on S3 upload.
** Scheduled maintenance via CloudWatch Events.
** ETL workloads on DynamoDB Streams or Kinesis.

* '''Typical application-level abilities'''
** Can deploy and invoke Lambda functions.
** Can attach appropriate event sources.
** Can troubleshoot basic permission or runtime issues.

----

== Analyzing (Break Down / Analysis) ==
🔬 At this level, an expert can **examine**, **compare**, and **diagnose** AWS Lambda behavior and architecture.

* '''Comparative analysis'''
** Lambda vs. EC2 — operational burden vs. flexibility.
** Lambda vs. ECS/EKS — ephemeral execution vs. container orchestration.
** Lambda vs. Cloud Functions / Azure Functions — cross-provider trade-offs.

* '''Failure modes & root causes'''
** Timeout due to slow dependencies or networking.
** Throttling caused by insufficient concurrency limits.
** Permissions failures from incorrect IAM roles.

* '''Troubleshooting & observability techniques'''
** Use CloudWatch Logs for debugging errors.
** Inspect distributed traces with AWS X-Ray.
** Monitor concurrency, durations, and error rates.

* '''Architectural insights'''
** Event fan-out through SNS, SQS, or EventBridge.
** Managing shared dependencies using Lambda layers.

* '''Typical analysis-level abilities'''
** Can identify performance bottlenecks.
** Can map system behavior across multiple event sources.
** Can choose between compute options based on workload.

----

== Creating (Synthesis / Create) ==
🏗️ At this level, an expert can **design**, **compose**, and **optimize** systems using AWS Lambda.

* '''Design patterns & best practices'''
** Event-driven microservices using SNS or EventBridge.
** Reusable logic via Lambda layers.
** Idempotent execution to handle retries safely.

* '''Security & authentication patterns'''
** Principle of least privilege in IAM roles.
** Secret storage using AWS Systems Manager Parameter Store or Secrets Manager.
** VPC-integrated Lambda for private networking.

* '''Lifecycle management strategies'''
** Automated deployments with CI/CD pipelines.
** Versioning and aliasing for staged rollouts.
** Traffic shifting (blue-green or canary deployments).

* '''Scalability & optimization patterns'''
** Asynchronous processing with SQS.
** Provisioned concurrency for latency-sensitive workloads.
** Efficient packaging and dependency management.

* '''Typical creation-level abilities'''
** Can architect multi-service solutions using Lambda.
** Can design cost-efficient, scalable serverless systems.
** Can enforce security, resiliency, and maintainability.

----

== Evaluating (Judgment / Evaluation) ==
⚖️ At this level, an expert can **assess**, **compare**, and **justify** AWS Lambda adoption and system quality.

* '''Evaluation frameworks & tools'''
** Load-testing APIs backed by Lambda.
** Reviewing CloudWatch metrics for performance and cost.
** Security audits for IAM roles, triggers, and data handling.

* '''Maturity & adoption considerations'''
** Team familiarity with serverless development.
** Operational readiness for monitoring and incident response.

* '''Key performance indicators'''
** Execution duration, memory usage, concurrency.
** Error rate, cold-start latency, throughput.
** Cost per workload or per invocation.

* '''Strategic decision criteria'''
** Choose Lambda when workloads are event-driven, bursty, or unpredictable.
** Prefer EC2/ECS/EKS when workloads require long-running compute or custom OS access.

* '''Holistic impact analysis'''
** Cost efficiency vs. operational control.
** Vendor lock-in and portability considerations.
** Developer productivity and release velocity.

* '''Typical evaluation-level abilities'''
** Can defend or reject Lambda adoption based on workload needs.
** Can recommend service boundaries and compute alternatives.
** Can prioritize improvements using objective data.

[[Category:AWS]]
[[Category:Cloud Computing]]
[[Category:Serverless Architecture]]