A serverless platform is a cloud computing service that allows developers to build, deploy, and run applications or functions without managing or provisioning the underlying server infrastructure. The term “serverless” doesn’t mean there are no servers—it means that the servers, scaling, and maintenance are abstracted away from the user, allowing developers to focus purely on application logic.
Key characteristics of a serverless platform
- Event-driven architecture – Applications are triggered by events, such as HTTP requests, file uploads, or database changes.
- Pay-as-You-Go pricing – Users are charged only for the compute time and resources used during execution, rather than paying for idle or reserved capacity.
- Automatic scaling – Serverless platforms automatically scale up or down based on demand, handling workloads of any size without manual intervention.
- Managed infrastructure – The cloud provider manages all server provisioning, patching, and maintenance tasks, allowing developers to focus on writing and deploying code.
- Stateless functions – Serverless functions are stateless, meaning they don’t retain data between executions. State is typically managed using external databases or storage systems.
Most leading cloud platforms offer robust serverless solutions
1. Compute & Function-as-a-Service (FaaS)
- AWS Lambda – Event-driven, on-demand execution of code without managing servers.
- Azure Functions – Serverless compute with event-driven execution.
- Google Cloud Functions – Lightweight event-driven function execution.
- IBM Cloud Functions – OpenWhisk-based FaaS offering.
- Oracle Functions – Serverless function execution based on Fn Project.
2. Container & Application Services
- AWS Fargate – Serverless compute for containers (ECS & EKS).
- Azure Container Apps – Managed serverless container execution.
- Google Cloud Run – Serverless container execution for stateless applications.
- IBM Code Engine – Serverless container runtime and app deployment.
3. Serverless Databases & Storage
- AWS DynamoDB – Serverless NoSQL database with auto-scaling.
- Amazon Aurora Serverless – Auto-scaling relational database (PostgreSQL/MySQL).
- Azure Cosmos DB – Globally distributed NoSQL database.
- Azure SQL Database Serverless – Auto-scaling SQL database.
- Google Firestore – NoSQL document database.
- Google BigQuery – Serverless data warehouse.
- Azure Blob Storage – Serverless object storage.
- Google Cloud Storage – Object storage with intelligent tiering.
4. Event-Driven & Messaging Services
- Amazon EventBridge – Event bus for serverless application integration.
- AWS Step Functions – Serverless orchestration and workflow automation.
- Azure Event Grid – Event routing service.
- Azure Logic Apps – Serverless workflow automation.
- Google Cloud Pub/Sub – Scalable event messaging service.
- Amazon SQS & SNS – Managed queuing and notification services.
5. API & Edge Computing
- Amazon API Gateway – Serverless API management.
- Azure API Management (Consumption Plan) – Serverless API gateway.
- Google Cloud Endpoints – Serverless API gateway based on OpenAPI.
- AWS CloudFront with Lambda@Edge – Serverless edge computing.
6. Identity & Security
- AWS Cognito – Serverless authentication and authorization.
- Azure AD B2C – Identity management for serverless apps.
- Google Firebase Authentication – Serverless identity authentication.
Serverless use case scenario
Web applications and APIs
- Applicable Area – Build scalable backends, web apps, and APIs.
- Example – RESTful APIs, single page app backends, real time APIs for mobile apps.
- Why serverless – Scalability, cost efficiency, minimal infrastructure management.
Event driven applications
- Applicable Area – Trigger functions based on events like file uploads, database updates, etc.
- Example – Image processing (S3 + Lambda), database changes (DynamoDB Streams).
- Why serverless – Native event triggers, rapid execution, cost savings for intermittent use.
Data processing & analytics
- Applicable Area – Real time or batch processing for large or streaming datasets.
- Example – Log processing, ETL pipelines, IoT data processing.
- Why serverless – Scalable, supports unpredictable workloads, integrates with data services.
Microservices
- Applicable Area – Create modular, scalable services that communicate via APIs.
- Example – Payment processing, user authentication, email notifications.
- Why serverless – Decoupled architecture, individual service scaling, operational simplicity.
Automation & Scheduled Tasks
- Applicable Area – Automate periodic or scheduled tasks.
- Example – Nightly batch jobs, backups, report generation.
- Why serverless – Cost effective for intermittent tasks, no persistent servers needed.
Internet of Things (IoT)
- Applicable Area – Process and analyze IoT device data in real time.
- Example – Smart home automation, sensor data analysis, predictive maintenance
- Why serverless – Scales with device data, integrates with IoT platforms.
ML model serving
- Applicable Area – Deploy ML models as APIs for real time predictions.
- Example – Image classification, sentiment analysis, fraud detection.
- Why serverless – Cost effective for sporadic inference, auto scaling for predictions.
Chatbots and virtual assistants
- Applicable Area – Deploy chatbots for real time user interactions.
- Example – Customer support bots, Slack or Teams bots.
- Why serverless – Low latency responses, efficient event handling.
Mobile backends
- Applicable Area – Backend services for mobile applications.
- Example – User authentication, backend for user preferences/data.
- Why serverless – Cost efficient, supports traffic spikes, reduces infrastructure overhead.
CI/CD pipelines
- Applicable Area – Automate testing, deployments, and infrastructure provisioning.
- Example – Trigger builds/tests on code commits, infrastructure as code deployment.
- Why serverless – Integrates with CI/CD tools, reduces server costs for pipelines.
Low traffic websites
- Applicable Area – Host websites or microsites without maintaining servers.
- Example – Static websites with dynamic APIs, landing pages with form submissions.
- Why serverless – Cost effective for low usage, auto scaling, integrates with cloud storage.
Workload migration to serverless platform – Considerations
Migrating on-premises applications to a serverless environment offers a range of benefits but also requires careful evaluation to determine its suitability.
Pros and cons of serverless platform services
Cost
- Pros – Pay per use: You pay only for the actual usage of resources.
- Cons – Unpredictable costs: High traffic or heavy workloads can lead to unexpected costs.
Scalability
- Pros – Auto scaling: Automatically adjusts to handle variable workloads.
- Cons – Cold start delays: Scaling from zero may introduce latency for idle functions.
Management
- Pros – No infrastructure management: Providers handle servers, scaling, and updates.
- Cons – Limited control: Less flexibility to optimize infrastructure for specific use cases.
Speed
- Pros – Fast deployment: Focus on application logic instead of managing infrastructure.
- Cons – Execution limits: Maximum function runtime (e.g., 15 minutes on AWS Lambda).
Agility
- Pros – Supports rapid development: Perfect for MVPs, prototypes, and event driven architectures.
- Cons – Architecture redesign: May require rearchitecting applications to fit stateless models.
Integration
- Pros – Wide ecosystem: Easily integrates with other cloud services (e.g., databases, APIs).
- Cons – Vendor lock in: Dependency on specific platforms (e.g., AWS, Azure, GCP).
Performance
- Pros – Efficient resource usage: Optimized for short lived, event driven tasks.
- Cons – Latency issues: Data transfer and cold starts can impact performance.
Security
- Pros – Built in security: Providers manage patching and updates.
- Cons – Shared responsibility: Users are responsible for securing application logic and data.
Flexibility
- Pros – Event driven execution: Triggered by HTTP requests, database changes, etc.
- Cons – Not suitable for all workloads: Poor fit for long running or resource intensive tasks.
Conclusion
Embracing a serverless platform offers significant benefits, including cost efficiency, scalability, and reduced operational overhead. It enables organizations to focus on application development rather than infrastructure management, making it a compelling choice for modern cloud-native architectures. However, careful evaluation is required to determine suitability, considering factors like workload characteristics, integration challenges, and potential vendor lock-in. By following a strategic migration approach, organizations can leverage serverless computing to enhance agility, optimize costs, and drive innovation while ensuring security and compliance requirements are met.
Author
Kannan Gopalan | Director of Technology Architecture
at GS Lab | GAVS
Kannan Gopalan is an experienced technology leader with over 30 years in IT Infrastructure Services, currently serving as our Director of Technology Architecture for Application Services. He specializes in Cloud, Hybrid, and Conventional platforms, leading teams to deliver complex solutions that align with business goals. As a Multi-Cloud Architect and Data Engineer, Kannan is committed to exploring innovative solutions to meet customer needs, evaluating provider options for optimal value. His strong leadership, technical expertise, and global experience enable him to guide teams and support clients across diverse regions.
