Integration Execution Duration: Find Slowdowns before They Fail

Integration execution duration measures the elapsed time from an accepted trigger or start event to successful completion or failure, helping teams identify integrations that technically succeed but deliver data too late for downstream processes or customer deadlines. Effective measurement requires consistent definitions of start and end points, including clear decisions about whether queueing, dependency waits, retries, replay, and recovery are included, along with contextual data such as flow, customer, trigger type, payload size, outcome, and retry status. Rather than relying on averages alone, teams should monitor median, p95, and p99 durations to reveal slow-running outliers and segment results by comparable workloads, integrations, customers, connectors, and execution types. Retries should be reported separately because they can improve eventual success while extending customer wait times, and duration trends should be assessed alongside retry, recovery, success, throughput, and operational response metrics. Investigations should use step-level timing and dependency data to distinguish causes such as large payloads, API latency, queue pressure, rate limits, or inefficient repeated calls, while alerts should reflect each integration’s specific freshness requirements and focus on sustained breaches.

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