State management for durable execution focuses on reliably persisting workflow progress so that processes can survive failures and restarts. Core techniques include event sourcing, where each state change is recorded as an immutable event, and periodic snapshotting to limit replay time. Deterministic replay engines reconstruct current state from logs, ensuring exactly‑once semantics when combined with idempotent handlers. Durable Functions and similar orchestration frameworks rely on external storage (e.g., Azure Storage tables) with built‑in deduplication to guarantee precise execution. Consistency models such as linearizability guarantee that once a change commits, all subsequent reads reflect it, while eventual consistency trades immediacy for performance. The transactional outbox pattern decouples state changes from message dispatch, and the saga pattern coordinates distributed transactions with compensating actions. Checkpointing strategies range from lightweight in‑memory checkpoints to heavyweight persistent snapshots, each balancing latency, I/O overhead, and storage cost. Choosing the right combination—event logs, snapshots, deterministic replay, and appropriate consistency guarantees—enables robust, fault‑tolerant, and scalable long‑running applications.