Everything you need to know about AWS Lambda, API Gateway, Step Functions, EventBridge, and how PrecisionTech builds serverless applications for businesses in India.
1
What is AWS Lambda?
AWS Lambda is a serverless compute service that runs your code in response to events — without provisioning or managing servers. You upload your function code (or a container image), configure a trigger (API Gateway request, S3 upload, DynamoDB stream, EventBridge rule, SQS message, etc.), and Lambda executes your code automatically. Lambda scales from zero to thousands of concurrent executions in seconds, and you pay only for the compute time consumed — measured in milliseconds. Each Lambda function can use up to 10 GB of memory, run for up to 15 minutes per invocation, and use up to 10 GB of ephemeral storage. Lambda supports Node.js, Python, Java, .NET, Go, Ruby, Rust, and custom runtimes via container images. With two India regions (Mumbai ap-south-1 and Hyderabad ap-south-2), Lambda delivers low-latency serverless compute for Indian businesses while ensuring data residency compliance.
2
What are Lambda cold starts and how do you mitigate them?
A cold start occurs when Lambda creates a new execution environment for your function — downloading the deployment package, initializing the runtime, and running your initialization code. Cold starts add latency (typically 100ms–3s depending on runtime and package size) to the first invocation after a period of inactivity or during scale-up events. Mitigation strategies: Provisioned Concurrency — pre-initializes a specified number of execution environments so they are always warm and ready. Eliminates cold starts entirely for those instances. Lambda SnapStart (Java) — takes a snapshot of the initialized execution environment and restores it on invocation, reducing Java cold starts from 5–10s to under 200ms. Smaller deployment packages — reduce initialization time by minimizing dependencies. Keep-alive invocations — schedule periodic invocations (every 5 minutes) via EventBridge to keep environments warm. Choose lighter runtimes — Python and Node.js cold starts are typically 100–300ms vs 3–10s for unoptimized Java. PrecisionTech analyzes your latency requirements and configures the optimal cold start mitigation strategy for each function.
3
What is Lambda SnapStart and which runtimes support it?
Lambda SnapStart is an AWS feature that dramatically reduces cold start latency for Java functions (Java 11, Java 17, Java 21 on Corretto). When you publish a function version with SnapStart enabled, Lambda initializes your function, takes a Firecracker microVM snapshot of the initialized execution environment (memory + disk state), and caches it. On subsequent invocations, Lambda restores the snapshot instead of re-initializing — reducing Java cold starts from 5–10 seconds to under 200 milliseconds. SnapStart works with Spring Boot, Quarkus, Micronaut, and other Java frameworks. Important considerations: your initialization code must be idempotent (SnapStart restores the same snapshot multiple times), you should generate unique values (UUIDs, random numbers) at invocation time rather than initialization, and network connections established during init will be stale after restore. PrecisionTech configures SnapStart for Java Lambda functions and validates that initialization code is snapshot-safe.
4
What is Lambda@Edge and how is it different from standard Lambda?
Lambda@Edge runs Lambda functions at CloudFront edge locations worldwide — executing code closer to end users for ultra-low latency. Unlike standard Lambda (which runs in a specific AWS Region), Lambda@Edge functions are triggered by CloudFront events: Viewer Request (before CloudFront checks cache), Viewer Response (before responding to viewer), Origin Request (before forwarding to origin), and Origin Response (after receiving from origin). Use cases: URL rewrites and redirects, A/B testing, header manipulation, bot detection, authentication at the edge, image transformation, and dynamic content personalization. Lambda@Edge has tighter limits than standard Lambda: 5s timeout (viewer events) or 30s (origin events), 128–10,240 MB memory, and 50 MB deployment package. For more flexible edge compute, CloudFront Functions offer sub-millisecond execution for lightweight tasks (viewer request/response only) at 1/6th the cost. PrecisionTech architects edge compute solutions using the right mix of Lambda@Edge and CloudFront Functions.
5
What are Lambda Layers and how do they work?
Lambda Layers are ZIP archives containing libraries, custom runtimes, or other dependencies that you can share across multiple Lambda functions. Instead of bundling common dependencies in every function deployment package, you package them once as a Layer and attach it to any function that needs it. Benefits: Smaller deployment packages — functions stay lean (faster deployments and cold starts). Shared dependencies — update a library in one Layer and all attached functions get the new version on next deployment. Separation of concerns — application code in the function, dependencies in Layers. Custom runtimes — use Layers to bring any runtime (Rust, C++, PHP, Bash) to Lambda. Each function can use up to 5 Layers, and the total unzipped size (function + all Layers) must be under 250 MB. AWS provides managed Layers for popular libraries (AWS SDK, pandas for Python, etc.), and you can publish your own. PrecisionTech creates shared Layer libraries for common utilities, database connectors, and monitoring agents across your serverless functions.
6
What is the difference between API Gateway REST API and HTTP API?
Amazon API Gateway offers two serverless API products: REST API — the original, feature-rich API type. Supports: API keys, usage plans, request/response transformation, request validation, WAF integration, caching, custom domain mapping, canary deployments, mutual TLS, resource policies, and private APIs via VPC endpoints. Best for: enterprise APIs needing fine-grained access control, monetization, and request transformation. HTTP API — a newer, faster, and cheaper API type. Supports: JWT authorizers (Cognito, Auth0), Lambda and HTTP backend integrations, CORS, custom domains, and auto-deployment. Up to 71% cheaper than REST API and delivers lower latency. Does NOT support: usage plans, API keys, request/response transformation, caching, or WAF integration. Best for: simple proxies to Lambda or HTTP backends where you need speed and low cost. WebSocket API — for real-time bidirectional communication (chat apps, live dashboards, gaming). PrecisionTech evaluates your API requirements and recommends REST API for enterprise features or HTTP API for cost-optimized, low-latency endpoints.
7
What are AWS Step Functions and when should I use them?
AWS Step Functions is a serverless workflow orchestration service that coordinates multiple AWS services (Lambda, ECS, Fargate, SNS, SQS, DynamoDB, Glue, SageMaker, and more) into visual state machine workflows. You define workflows using Amazon States Language (ASL) — a JSON-based specification that includes states for Task execution, Choice branching, Parallel execution, Map iteration, Wait delays, and error handling with Retry/Catch. Two workflow types: Standard Workflows — run up to 1 year, exactly-once execution, audit history stored for 90 days. Best for: long-running processes (order fulfilment, ETL pipelines, human approval workflows). Express Workflows — run up to 5 minutes, at-least-once execution, high-volume event processing at lower cost. Best for: IoT data ingestion, streaming data transformation, and high-throughput microservices orchestration. Distributed Map — process millions of items from S3 in parallel (up to 10,000 concurrent executions). PrecisionTech designs Step Functions workflows that replace fragile Lambda-calling-Lambda chains with resilient, observable, and maintainable orchestration patterns.
8
What is Amazon EventBridge and how does it fit into serverless?
Amazon EventBridge is a serverless event bus that connects applications using events — decoupling producers from consumers. EventBridge receives events from AWS services (EC2 state changes, S3 uploads, CodePipeline status), SaaS applications (Shopify, Zendesk, Auth0, Datadog — 30+ integrations), and your custom applications. You define rules that match event patterns and route matching events to targets: Lambda functions, Step Functions, SQS queues, SNS topics, API Gateway, Kinesis streams, and more. Key features: Schema Registry — auto-discovers and stores event schemas for code generation. Archive & Replay — archive all events and replay them for testing or recovery. Event Pipes — point-to-point integrations with filtering, enrichment, and transformation without code. Scheduler — create scheduled events (cron/rate expressions) that trigger targets at specified times. EventBridge is the backbone of event-driven serverless architectures — enabling loose coupling, async processing, and fan-out patterns. PrecisionTech architects EventBridge-centric systems that replace synchronous API chains with resilient event-driven flows.
9
What is the difference between Amazon SQS and Amazon SNS?
Amazon SQS (Simple Queue Service) is a fully managed message queue for decoupling application components. Messages are stored in the queue until a consumer processes and deletes them. Two queue types: Standard — unlimited throughput, at-least-once delivery, best-effort ordering. FIFO — exactly-once processing, strict ordering, up to 3,000 messages/second (with batching). SQS is a pull-based model — consumers poll the queue. Best for: load levelling, work distribution, and async processing where consumers process at their own pace. Amazon SNS (Simple Notification Service) is a fully managed pub/sub messaging service. Publishers send messages to topics, and all subscribers to that topic receive a copy. Subscribers can be: Lambda functions, SQS queues, HTTP/HTTPS endpoints, email, SMS, or mobile push notifications. SNS is a push-based model — messages are pushed to all subscribers immediately. Best for: fan-out (one event triggers multiple consumers), notifications, and alerting. Common pattern: SNS → SQS fanout — SNS topic fans out to multiple SQS queues, each processed by a different consumer at its own pace. PrecisionTech designs messaging architectures using the right combination of SQS and SNS for your workload patterns.
10
What is AWS AppSync and how does it enable serverless GraphQL?
AWS AppSync is a fully managed service for building GraphQL APIs and real-time APIs backed by serverless data sources. AppSync connects your GraphQL schema to DynamoDB tables, Lambda functions, Aurora Serverless, OpenSearch, HTTP endpoints, and other AWS services — without writing backend code for data fetching. Key capabilities: Real-time subscriptions — push data updates to connected clients via WebSocket (live dashboards, chat, collaboration). Offline support — built-in conflict detection and resolution for mobile apps that work offline and sync when reconnected. Pipeline resolvers — chain multiple data sources in a single GraphQL query (e.g., fetch user from DynamoDB, then fetch orders from Aurora). Merged APIs — combine multiple AppSync APIs from different teams into a single GraphQL endpoint. Caching — built-in server-side caching with configurable TTL. AppSync eliminates the need to build and maintain a custom GraphQL server — you define the schema, configure resolvers, and AppSync handles scaling, security, and real-time delivery. PrecisionTech builds AppSync-powered APIs for mobile apps, real-time dashboards, and multi-source data aggregation.
11
What is Amazon Cognito and how does it handle serverless authentication?
Amazon Cognito provides serverless authentication, authorization, and user management for web and mobile applications. Two components: User Pools — a managed user directory that handles sign-up, sign-in, MFA, password recovery, email/phone verification, and social identity federation (Google, Facebook, Apple, Amazon). User Pools issue JWTs (JSON Web Tokens) that integrate directly with API Gateway for request authorization. Identity Pools — provide temporary AWS credentials to authenticated (or unauthenticated) users, enabling direct access to AWS services (S3, DynamoDB) from client applications with fine-grained IAM policies. Key features: adaptive authentication (risk-based MFA), custom authentication flows via Lambda triggers, SAML 2.0 and OpenID Connect federation for enterprise SSO, and compliance certifications (SOC, PCI-DSS, HIPAA). Cognito scales to millions of users with no server management. PrecisionTech configures Cognito User Pools with custom domains, branded UI, Lambda triggers for workflow customization, and integration with API Gateway authorizers.
12
What is the difference between AWS SAM and AWS CDK for serverless?
AWS SAM (Serverless Application Model) is an open-source framework for building serverless applications. SAM extends CloudFormation with simplified syntax for defining Lambda functions, API Gateway APIs, DynamoDB tables, Step Functions, and event sources. SAM CLI provides local testing (sam local invoke, sam local start-api), guided deployments (sam deploy --guided), and CI/CD pipeline generation. SAM templates are YAML/JSON — familiar to anyone who knows CloudFormation. Best for: serverless-focused teams who want a simple, opinionated framework. AWS CDK (Cloud Development Kit) lets you define infrastructure using general-purpose programming languages — TypeScript, Python, Java, C#, Go. CDK compiles to CloudFormation templates. CDK provides higher-level constructs (L2/L3) that bundle best practices (e.g., a single construct creates a Lambda + API Gateway + CloudWatch alarms + X-Ray tracing). Best for: teams building complex infrastructure who prefer code over YAML and want to share reusable constructs. CDK + SAM together: you can use SAM CLI to locally test Lambda functions defined in CDK stacks. PrecisionTech uses SAM for straightforward serverless projects and CDK for complex multi-service architectures requiring custom constructs and cross-stack references.
13
What is AWS Amplify and how does it complement Lambda?
AWS Amplify is a full-stack development platform for building serverless web and mobile applications. Amplify provides: Amplify Hosting — CI/CD-connected hosting for static sites and SSR apps (Next.js, Nuxt, React, Angular, Vue). Amplify Studio — visual development environment for building UI components, data models, and authentication flows. Amplify Libraries — client-side SDKs (JavaScript, iOS, Android, Flutter) for connecting to AWS services (Cognito auth, AppSync GraphQL, S3 storage, Lambda functions, analytics). Amplify Backend — define backend resources (auth, API, storage, functions) using TypeScript that Amplify deploys as Lambda functions, AppSync APIs, Cognito User Pools, DynamoDB tables, and S3 buckets. Amplify is ideal for frontend developers who want to build full-stack serverless applications without deep AWS infrastructure knowledge. It complements Lambda by providing the frontend framework, CI/CD pipeline, and client-side libraries that connect to Lambda-powered backends. PrecisionTech uses Amplify for rapid MVP development and customer-facing portals backed by Lambda, AppSync, and DynamoDB.
14
What is Provisioned Concurrency and when should I use it?
Provisioned Concurrency pre-initializes a specified number of Lambda execution environments so they are always warm, ready, and respond to invocations with consistent low latency — eliminating cold starts entirely. When you configure Provisioned Concurrency on a function version or alias, Lambda maintains that many initialized environments regardless of current traffic. If traffic exceeds the provisioned level, Lambda still scales on-demand (with cold starts for the additional instances). Use cases: Latency-sensitive APIs — payment processing, real-time pricing, authentication endpoints where cold start latency is unacceptable. Predictable traffic patterns — configure Provisioned Concurrency with Application Auto Scaling to match daily traffic curves (high during business hours, low at night). Java/heavy runtime functions — where cold starts exceed 3–5 seconds even with SnapStart. Cost consideration: you pay for Provisioned Concurrency whether functions are invoked or not (similar to reserved capacity). PrecisionTech uses Lambda Power Tuning to optimize memory settings first, then applies Provisioned Concurrency only to functions where cold start latency exceeds your SLA requirements.
15
What are the AWS Lambda execution limits?
Key Lambda limits (as of 2026): Timeout — maximum 15 minutes (900 seconds) per invocation. Memory — 128 MB to 10,240 MB (10 GB) in 1 MB increments. CPU power scales proportionally with memory. Ephemeral storage (/tmp) — 512 MB to 10,240 MB (10 GB). Deployment package — 50 MB zipped (direct upload), 250 MB unzipped (including Layers), or 10 GB as a container image. Concurrent executions — 1,000 per account per region (default, can be increased to tens of thousands via AWS support). Burst concurrency — 3,000 in US East, 1,000 in most regions including ap-south-1. Environment variables — 4 KB total. Invocation payload — 6 MB synchronous, 256 KB asynchronous. Layers — 5 per function. Function URL — built-in HTTPS endpoint (no API Gateway needed for simple use cases). PrecisionTech architects Lambda solutions within these limits — recommending Step Functions for processes exceeding 15 minutes, S3 for large payloads, and EFS for persistent shared storage.
16
How does serverless compare to containers (ECS/EKS/Fargate)?
Serverless (Lambda) — no infrastructure management, automatic scaling from zero, pay-per-invocation (millisecond billing), max 15-minute execution, max 10 GB memory, cold start latency, limited runtime control. Best for: event-driven workloads, APIs with variable traffic, data processing pipelines, scheduled tasks, and functions that complete in under 15 minutes. Containers (ECS/EKS on Fargate) — you manage container images and task definitions, Fargate handles underlying infrastructure. Scales based on task count (not to zero by default), pay per vCPU-second and GB-second, no execution time limit, full control over runtime, networking, and sidecar containers. Best for: long-running processes, workloads needing full OS control, applications with consistent high traffic, and microservices requiring complex networking. When to choose what: Lambda for event-driven, variable-traffic, short-duration functions. Fargate for long-running services, consistent traffic, and workloads needing containers. Many modern architectures use both — Lambda for APIs and event processing, Fargate for background services and batch jobs. PrecisionTech evaluates each workload component and recommends the optimal compute model.
17
How does AWS Lambda compare to Azure Functions and Google Cloud Functions?
AWS Lambda — most mature serverless platform (launched 2014). 10 GB memory, 15-min timeout, 10 GB ephemeral storage, SnapStart for Java, Lambda@Edge, Provisioned Concurrency, Lambda Layers, container image support (10 GB), most event source integrations (200+ AWS services), two India regions (Mumbai + Hyderabad). Azure Functions — deep integration with .NET, Visual Studio, and Azure DevOps. Durable Functions for stateful workflows (similar to Step Functions). Premium Plan with VNET integration and pre-warmed instances. Consumption plan scales to zero. India regions: Pune, Mumbai, Chennai (3 regions — more than AWS). Google Cloud Functions — second generation runs on Cloud Run (container-based). 32 GB memory, 60-min timeout, concurrency up to 1,000 per instance. Tight integration with Firebase, Firestore, and BigQuery. India region: Mumbai only (1 region). For Indian enterprises, Lambda leads in: event source breadth, ecosystem maturity, edge compute (Lambda@Edge), Java optimization (SnapStart), and overall AWS service integration. Azure Functions wins for Microsoft-centric shops. Google Cloud Functions excels at per-instance concurrency and Firebase integration. PrecisionTech recommends Lambda for most Indian enterprise serverless workloads.
18
How does Lambda pricing work?
Lambda pricing has three components: Request charges — you pay per invocation (request). Duration charges — you pay for compute time measured in milliseconds, based on the amount of memory allocated to the function. More memory = more CPU = higher per-ms rate. Provisioned Concurrency charges (optional) — you pay for pre-initialized execution environments whether they are invoked or not. Key pricing facts: Free tier — 1 million requests and 400,000 GB-seconds of compute per month (always free, not just first 12 months). No charge for idle — when no invocations occur, you pay nothing (unlike EC2 instances running 24×7). Pay-per-millisecond — billing rounds up to the nearest 1 ms (was 100 ms prior to 2020). Data transfer — standard AWS data transfer rates apply for data leaving Lambda to the internet or other regions. Cost optimization strategies PrecisionTech applies: right-size memory with Lambda Power Tuning (optimal cost-performance point), use ARM/Graviton2 Lambda for 20% cost reduction, minimize execution time with efficient code, use Reserved Concurrency to prevent runaway costs, and choose HTTP API over REST API (71% cheaper) where features permit.
19
How do you secure serverless applications on AWS?
Serverless security follows the shared responsibility model — AWS secures the infrastructure (OS, hypervisor, hardware), you secure your application code, IAM permissions, data, and configurations. PrecisionTech implements: IAM least privilege — each Lambda function gets its own execution role with only the permissions it needs (never AmazonDynamoDBFullAccess — only specific table-level actions). VPC integration — Lambda functions accessing private resources (RDS, ElastiCache, internal APIs) run inside your VPC with Security Groups. Encryption — environment variables encrypted with KMS, data at rest encrypted in DynamoDB/S3/SQS, data in transit via HTTPS. API Gateway security — Cognito authorizers, Lambda authorizers, API keys, WAF integration (REST API), mutual TLS, and throttling. Input validation — API Gateway request validators and Lambda function-level input sanitization to prevent injection attacks. Dependency scanning — automated scanning of Lambda deployment packages for CVEs using Amazon Inspector. Secrets management — AWS Secrets Manager or SSM Parameter Store for database credentials, API keys, and tokens (never hardcoded in environment variables). X-Ray tracing — end-to-end request tracing across Lambda, API Gateway, DynamoDB, and SQS for security observability.
20
Is AWS Lambda suitable for enterprise workloads?
Yes. Lambda is production-ready for enterprise use cases across industries: Financial services — real-time transaction processing, fraud detection, regulatory reporting (RBI/SEBI compliance with ap-south-1 data residency). E-commerce — order processing, inventory updates, dynamic pricing, payment webhooks (handling millions of events during sale events). Healthcare — HIPAA-eligible workload processing, lab result notifications, appointment scheduling APIs. Manufacturing — IoT sensor data processing, equipment monitoring alerts, quality control image analysis. SaaS platforms — multi-tenant API backends, webhook processing, usage metering, and billing event pipelines. Enterprise considerations PrecisionTech addresses: VPC integration for accessing private resources. Provisioned Concurrency for SLA-bound latency. Reserved Concurrency for blast radius control. Dead letter queues for failed invocation capture. X-Ray + CloudWatch for observability at scale. Multi-region active-active for disaster recovery. SAM/CDK pipelines for enterprise CI/CD with approval gates and canary deployments.
21
What serverless expertise does PrecisionTech bring?
PrecisionTech is an Authorized AWS Partner delivering end-to-end serverless services: Serverless Architecture Design — event-driven architecture patterns, CQRS, event sourcing, saga patterns, and fan-out/fan-in topologies using Lambda, Step Functions, EventBridge, SQS/SNS. API Development — RESTful and GraphQL APIs on API Gateway and AppSync with Cognito/JWT authentication, custom domains, throttling, and caching. Workflow Orchestration — Step Functions state machines for complex business processes — order fulfilment, document processing, ETL pipelines, and approval workflows. Event-Driven Integration — EventBridge event buses connecting AWS services, SaaS applications, and custom microservices. Migration to Serverless — decomposing monolithic applications into Lambda functions with incremental migration (strangler fig pattern). Performance Optimization — Lambda Power Tuning, Provisioned Concurrency configuration, cold start mitigation, and X-Ray performance analysis. Cost Optimization — right-sizing Lambda memory, ARM/Graviton2 functions, reserved concurrency controls, and HTTP API migration for cost reduction. 24×7 Managed Operations — CloudWatch dashboards, alarms, anomaly detection, X-Ray tracing, monthly cost and performance reports. All services backed by 30+ years of IT infrastructure experience, AWS-certified architects, and India-based support.
22
What is Lambda Power Tuning?
Lambda Power Tuning is an open-source tool (also available as a SAR application) that helps you find the optimal memory configuration for your Lambda functions — balancing cost and performance. It works by invoking your function multiple times with different memory settings (128 MB to 10 GB) and measuring execution time and cost at each level. The output is a visualization showing the cost-performance curve — identifying the sweet spot where increasing memory no longer significantly reduces execution time. Key insight: Lambda allocates CPU proportional to memory. A function with 1,769 MB gets 1 full vCPU. Functions that are CPU-bound (data processing, encryption, image manipulation) run faster with more memory — and sometimes cheaper too, because the reduced execution time offsets the higher per-ms cost. PrecisionTech runs Power Tuning on every Lambda function during the optimization phase, typically finding 20–40% cost savings or 50–80% latency reduction by adjusting memory from the default 128 MB to the optimal value.