Make services stateless where possible

Designing services to be stateless is vital for maintaining reliability in distributed systems. Stateless services do not retain information between requests, allowing for seamless service replacement and scaling without availability risk. By leveraging external data stores, workloads can better endure network failures and reduce recovery times.

Best Practices

Implement Stateless Services

• Design services to be stateless, meaning they do not retain user session information between requests. This approach simplifies scaling and improves reliability as any instance can handle any request without the need for session persistence.
• Utilize external storage solutions like Amazon ElastiCache for caching and Amazon DynamoDB for data persistence. This decouples the state from service instances, allowing you to replace or scale instances without downtime.
• Incorporate load balancers to distribute traffic evenly across stateless service instances, ensuring that failures in one instance do not affect the overall system availability.
• Consider using API Gateway to manage request routing and authentication without embedding state information, allowing backend services to remain stateless.
• Implement robust logging and monitoring solutions to track user interactions and service health in real-time, enabling quick diagnostics without relying on historical state.
• Provide a means for clients to initiate requests for state as needed, such as via an API call, rather than persisting state on the server side, ensuring that the client manages its own context.

Questions to ask your team

• Have you analyzed your services to identify opportunities for statelessness?
• What strategies do you use to offload state from your services?
• How do you ensure that replacing server instances does not disrupt workloads?
• Are there specific services, like Amazon ElastiCache or DynamoDB, that you utilize for managing state?
• How do you handle session management in a stateless architecture?
• What mechanisms are in place for data consistency when using distributed state management?
• How do you monitor and test the resilience of your stateless services?
• What processes do you have for scaling stateless services during peak traffic?

Who should be doing this?

Cloud Architect

• Design stateless services architecture to ensure high availability and resilience.
• Identify appropriate tools for state management, such as Amazon ElastiCache or Amazon DynamoDB.
• Develop guidelines for offloading state to enhance performance and reliability.
• Conduct regular reviews of service interactions to assess and improve statelessness.

DevOps Engineer

• Implement CI/CD pipelines to facilitate rapid deployment and testing of stateless services.
• Automate infrastructure provisioning and scaling to support stateless systems.
• Monitor service performance and state management to identify potential bottlenecks or issues in real-time.
• Collaborate with development teams to ensure adherence to stateless design principles.

Software Developer

• Create and maintain services that do not rely on locally stored state.
• Write code that interacts with state management solutions for data retrieval and storage.
• Conduct unit and integration testing to ensure stateless interactions function as intended.
• Participate in code reviews to ensure adherence to stateless architecture guidelines.

Site Reliability Engineer (SRE)

• Establish metrics and monitoring for service reliability and performance in a distributed system.
• Develop incident response plans for failure scenarios involving state-dependent services.
• Analyze failures and system behavior to improve state management and service interaction designs.
• Collaborate with development and operations teams to enhance overall system reliability.

What evidence shows this is happening in your organization?

• Stateless Service Architecture Diagram: A visual representation illustrating the architecture of stateless services, highlighting how they interact with external state stores like Amazon ElastiCache and Amazon DynamoDB to manage session data.
• State Management Best Practices Guide: A detailed manual outlining best practices for managing state in distributed systems, emphasizing the importance of statelessness and providing examples of state offloading techniques.
• Stateless Service Implementation Checklist: A checklist designed to guide teams through the implementation of stateless services, ensuring that local state dependencies are minimized and that external state storage systems are correctly utilized.
• Reliability Strategy Report: A comprehensive report that evaluates the organization’s current distributed system architecture for reliability, specifically focusing on how stateless services are implemented and their impact on overall system resilience.
• Service Replacement Runbook: A runbook that provides step-by-step instructions for replacing stateless services in the architecture, including procedures for ensuring zero downtime and maintaining service availability.

Cloud Services

AWS

• Amazon ElastiCache: A fully managed in-memory caching service that allows you to offload state from application servers, improving performance and reducing latency.
• Amazon DynamoDB: A fully managed NoSQL database service that provides fast and predictable performance with seamless scalability, enabling services to be stateless by offloading data storage.
• Amazon S3: A scalable object storage service that can be used to store state data independently from application logic, enabling stateless service design.

Azure

• Azure Cache for Redis: A caching service that provides a distributed, in-memory store for managing application state and improving application performance by reducing latency.
• Azure Cosmos DB: A fully managed NoSQL database service that allows for high availability and horizontal scaling, enabling offloading of state while maintaining fast access to data.
• Azure Blob Storage: An object storage solution for storing large amounts of unstructured data, enabling services to remain stateless by storing application data externally.

Google Cloud Platform

• Google Cloud Memorystore: A managed Redis service that enables you to add caching to your applications, reducing the need for state to reside in local memory.
• Google Cloud Firestore: A NoSQL document database that provides easy synchronization and state management, allowing applications to operate in a stateless manner while maintaining data integrity.
• Google Cloud Storage: A scalable object storage service where applications can offload data storage, promoting stateless service interactions.

Question: How do you design interactions in a distributed system to mitigate or withstand failures?
Pillar: Reliability (Code: REL)