Memory Sidecar v3.5.1 brings production hardening fixes for AI agent memory layer

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Memory Sidecar v3.5.1 is a stability-focused update for the open, framework-agnostic HTTP service that provides persistent memory to AI agents across backends like PostgreSQL, Redis, and SQLite. The release addresses real-world failure modes observed in long-running deployments, including socket leaks under high concurrency, which are resolved through a new bounded connection pool implementation. Backend reliability is improved via jittered exponential backoff when stores become temporarily unreachable, and the health check endpoint now verifies actual backend connectivity rather than just HTTP server status. Additional changes include reduced memory footprint through pre-allocated buffers and a graceful shutdown sequence that ensures in-flight requests and pending writes complete before exit. The companion hermes-memory-installer script also received updates adding checksum verification, idempotent re-runs safe for CI/CD pipelines, and version pinning for reproducible deployments.

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