Unpredictable Latency in Azure SQL Managed Instance: What It Means for Real-World Apps

Azure SQL Managed Instance can stall for up to 60 seconds on storage, and that reality is shaping how teams plan SLAs and user experience ^[1].

What the 60-second stall means for SLAs and UX That kind of stall challenges SLAs built on predictable latency and steady throughput. A 60-second hiccup can push end-to-end response times into the realm of delay, trigger retries, and leave users staring at loading spinners ^[1].

Transactional workloads vs analytics during stalls Transactional workloads demand quick, deterministic writes and reads; stalls throw off commit windows and backpressure can ripple into queues ^[1]. Analytics workloads can tolerate longer runtimes, but dashboards and BI users still feel the pain when data pipelines stall.

Mitigations and architecture choices - Separate transactional and analytical workloads to limit stall impact. - Add caching and resilient retry/backoff in applications. - Move long-running analytics off the critical path or onto separate compute/storage. - Use asynchronous processing and queues to absorb latency spikes.

Closing thought: Latency hiccups like this push teams to design for resilience, not just speed, and to align expectations with the realities of cloud storage.

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