Presented by: Thejaswi S
MCA Final Year
Date: June 14, 2025
Serverless computing is a cloud architecture that allows organizations to get on-demand access to computing resources without managing underlying infrastructure
It's not actually "without servers" - servers still exist, but they're abstracted away from developers
Developers focus on writing code, not managing infrastructure
Functions execute in response to events and scale automatically
HTTP request, file upload, timer, or other event occurs
Cloud provider spins up a container and executes your function
Multiple instances created automatically based on demand
You only pay for the compute time you actually use
Pay only for actual compute time used, not idle time
Instantly scales up or down based on demand
No server management, patching, or maintenance
Focus on business logic, not infrastructure
Initial delays when functions haven't been used recently
Tight coupling with specific cloud provider services
Less control over underlying infrastructure
Shared infrastructure and limited visibility
Functions triggered by events from various sources
RESTful APIs backed by serverless functions
Publish-subscribe messaging for loose coupling
Command Query Responsibility Segregation
File processing, real-time data streaming, webhooks
RESTful APIs, mobile app backends, microservices
ETL pipelines, batch processing, real-time analytics
Device data ingestion, sensor data processing
Uses AWS Lambda for encoding video files and managing platform modifications
Implemented serverless for IoT-powered smart vending machines
Uses AWS Lambda for processing massive amounts of trading data
Cloud provider manages infrastructure security, you manage application security
IAM roles, least privilege access, secure coding practices
Authentication, authorization, rate limiting, input validation
Environment variables for secrets, secure dependencies, monitoring
Each function execution should be independent
Minimize cold starts, efficient algorithms
Logging, metrics, distributed tracing
Keep functions warm, optimize initialization
Metrics, logs, alarms for AWS Lambda functions
Track requests across multiple services
Structured logging, correlation IDs
Limited local debugging, ephemeral environments
No idle time charges, automatic scaling cost benefits
No need to provision for peak capacity
Track execution time, memory usage, request counts
Set budgets, alerts, optimize function memory
CAGR (Compound Annual Growth Rate)
Current market valuation
Expected market size
Projected market size
• Increased adoption in AI/ML workloads
• Growing integration with edge computing
• Rise of multi-cloud serverless solutions
WebAssembly, event-driven architectures, low-code platforms
Serverless frameworks supporting multiple cloud providers
Serverless functions at the edge for reduced latency
Serverless containers for longer-running applications
AWS Lambda, Azure Functions, or Google Cloud Functions
Understand event-driven architecture and stateless design
Serverless Framework, SAM, Terraform for infrastructure
Begin with simple functions and gradually build complexity
Questions & Discussion