Serverless systems manage session state by offloading state storage to external services, since serverless functions themselves are stateless and ephemeral. When a user interacts with a serverless application, each function invocation operates independently, without retaining data between requests. To maintain session state (like user authentication, preferences, or temporary data), developers must explicitly store it outside the function runtime. This is typically done using databases, key-value stores, or client-side mechanisms, ensuring state persists across multiple function calls.
For example, a common approach is to use a database or caching service like Amazon DynamoDB or Redis. When a user logs in, a serverless function might generate a session ID, store user data in DynamoDB with an expiration time, and send the session ID to the client as a cookie. Subsequent requests from the client include this ID, allowing the function to retrieve the session data from the database. Alternatively, developers might use JSON Web Tokens (JWT) to encode session data directly in a client-side token. The token is signed by the server, sent to the client, and included in future requests. The function can validate the token and extract session data without needing to query a database, reducing latency.
However, this approach requires trade-offs. Storing session data externally introduces latency, especially if the storage isn’t optimized for low-lookup times. For high-performance scenarios, in-memory caches like Redis are preferred over traditional databases. Security is another concern: client-side tokens must be encrypted and signed to prevent tampering, and database-stored sessions need strict access controls. Developers must also handle session expiration and cleanup, often using time-to-live (TTL) policies in databases or cache services. By design, serverless shifts the complexity of state management to external systems, requiring careful integration to balance performance, security, and scalability.