Designing a Dynamic Configuration Platform: Airbnb's Sitar

Dynamic configuration is a critical infrastructure component in modern distributed systems, enabling changes to service behavior without restarts or redeployments. Airbnb's Sitar platform addresses the inherent challenge of balancing rapid iteration with system stability. The article outlines essential requirements for a modern dynamic config platform, including a coherent management experience, strong reliability guarantees, safe testing, flexible multi-tenant support, and fast, controlled incident response. These principles guide the architectural decisions for Sitar, making it a robust solution for large-scale operations.

Sitar: High-Level Architecture Overview

Sitar comprises four main logical components: a developer-facing layer, a control plane, a data plane, and client/agent components. The developer-facing layer handles config creation and review, primarily through a Git-based workflow. The control plane orchestrates changes, enforcing validation, authorization, and rollout strategies. The data plane provides scalable storage and efficient distribution, serving as the source of truth. Finally, agent sidecars and client libraries fetch configs, maintain local caches, and expose them to application logic.

Key Design Choices for Reliability and Flexibility

• <b>Configs as Code with Git-based Workflow:</b> By default, configs are managed via GitHub Pull Requests, leveraging existing CI/CD pipelines, mandatory reviews, and version history. This provides a consistent developer experience similar to code changes. A UI portal exists for emergency updates that bypass standard CI/CD.
• <b>Staged Rollouts and Fast Rollbacks:</b> Config changes undergo schema validation and automated checks in CI, followed by review. The control plane then performs staged rollouts, gradually expanding scope with evaluation at each stage. This reduces the blast radius of bad changes and supports rapid rollbacks.
• <b>Separated Control and Data Planes:</b> This architectural separation (decoupling 'decide' from 'deliver') allows independent evolution of rollout strategies/policies in the control plane and storage/distribution mechanisms in the data plane, improving modularity and maintainability.
• <b>Local Caching and Resilient Clients:</b> Agent sidecars running alongside services fetch and persist configs locally. Client libraries read from this cache, ensuring services can continue operating on the last known good configurations even if the backend data plane is temporarily unavailable.

These design choices significantly impact product teams by making rollouts safer and more predictable, offering flexibility in config management, and accelerating incident mitigation through improved observability and emergency update capabilities. The platform's continuous evolution focuses on refining rollout strategies, enhancing testing, and investing in smart incident response tools.