How do serverless platforms handle data storage?

Serverless platforms handle data storage by relying on external, managed services rather than local storage. Since serverless functions are stateless and ephemeral, they can’t store data between invocations. Instead, they integrate with cloud-based storage solutions like databases, object storage, or caching systems. For example, AWS Lambda functions might use Amazon S3 for file storage, DynamoDB for NoSQL data, or RDS for relational databases. This separation ensures data persistence and scalability while letting the serverless platform focus on executing code without managing storage infrastructure.

Developers typically connect to these services using APIs or SDKs provided by the cloud provider. For instance, a function might read configuration data from a DynamoDB table at startup or write logs to an S3 bucket after processing a request. To optimize performance, connections to databases are often managed via connection pooling or serverless-optimized database options like AWS Aurora Serverless, which scales automatically with demand. This approach minimizes latency and avoids overwhelming traditional databases with sudden spikes in connections from scaling serverless functions. Data is stored redundantly in these services, ensuring durability without requiring manual intervention from the developer.

Security and access control are handled through the platform’s identity and permissions systems. For example, AWS Lambda uses IAM roles to grant functions access to specific storage resources, preventing unauthorized data access. Developers must also consider data consistency patterns: since serverless functions can run in parallel, distributed transactions or idempotent operations may be needed to avoid conflicts. For temporary data, some platforms offer ephemeral storage (like AWS Lambda’s 512 MB /tmp directory), but this is cleared between invocations and not suitable for persistent data. By offloading storage to dedicated services, serverless architectures maintain scalability while letting developers leverage robust, managed data solutions.