An automated workflow that fails silently is worse than no automation -- because the process still isn't happening, but nobody knows.

Immutable log of every workflow execution: trigger timestamp, trigger source, each step name and execution time, step input and output payload, final success or failure status. Searchable by workflow name, date range, trigger source, and execution status so finding a specific failed execution doesn't require scrolling through thousands of log lines. Individual execution trace showing the full path a specific event took through the workflow -- every step, every decision point, every system call -- so investigation of an anomalous execution starts from a complete picture rather than inference.

Real-time alert on workflow failure delivered to Slack, email, or PagerDuty within seconds of the failure being detected. Alert payload includes workflow name, the step that failed, the error message returned, and the original event that triggered the execution -- everything the investigating engineer needs to start diagnosis without opening the monitoring dashboard. Failure classification by error type (authentication failure, timeout, validation error, downstream system error) for pattern analysis over time. Suppression rules to avoid alert storms during known downtime windows when the failure volume is expected and already being addressed.

Expected duration configuration per workflow: how long a normal execution should take end-to-end based on observed baseline. Alert when an execution exceeds the expected duration -- catching workflows that are hanging or degraded rather than failing explicitly, which would otherwise not trigger a failure alert. Percentile latency tracking (p50, p95, p99 execution time) for identifying performance regressions before they become outages. SLA compliance reporting showing the percentage of executions completing within the expected window, by workflow and by time period, for operational review.

Failed events stored in a dead letter queue with the full original payload and complete failure context -- the error, the step, and the execution trace at the point of failure. Manual review interface for inspecting a failed event and understanding whether the failure was a data problem, a system problem, or a logic problem before deciding to retry. One-click replay of a single event or bulk replay of all events from a specific time range after the underlying issue is resolved. Replay with a modified payload for cases where the original event contained a data error that needs correction before reprocessing. Audit log of all replay actions.

Operational dashboard showing all monitored workflows with success rate, failure rate, execution volume, and average duration for each. Trend view showing whether each workflow's health metrics are improving or degrading over the selected time window. Cross-workflow failure correlation to identify systemic issues -- all workflows failing simultaneously suggests an infrastructure or shared dependency problem, while a single workflow failing in isolation suggests a logic or data problem specific to that workflow. Executive summary view for stakeholders who need operational status without the technical detail of individual execution traces.

Expected execution volume baseline per workflow per time period, based on historical patterns. Alert when execution volume drops significantly below baseline -- indicating that trigger events are not arriving as expected, which is a failure mode that produces no individual execution failures to alert on. Alert when execution volume spikes significantly above baseline, indicating a trigger event flood that may indicate a bug or upstream system issue. Business impact estimation showing how many downstream records are affected by a given failure count. Weekly workflow health summary report for operational teams.