From Alerting to Observability: Building a ServiceNow Reliability Engineering Dashboard
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7 hours ago
From Alerting to Observability: Building a ServiceNow Reliability Engineering Dashboard
Over the past week, I set out to answer a simple question:
How do we know ServiceNow is healthy before users tell us it isn't?
What started as a review of MID Server monitoring evolved into the development of a ServiceNow Reliability Engineering Dashboard built around observability and Site Reliability Engineering (SRE) principles.
The Journey
The initial objective was to improve operational monitoring of our ServiceNow environment.
As part of that effort, I reviewed ServiceNow sysevent activity and evaluated candidate signals that could provide meaningful indicators of platform health, including:
- mid_server.down
- mid_server.up
- glide.heartbeat
- notification_engine.process
- email_diagnostics.process
- Import processing events
Rather than focusing exclusively on error events, I wanted to identify signals that could be used to measure normal system behavior and detect when expected activity stops.
The Most Interesting Discovery
The standout event was:
glide.heartbeat
A seven-day analysis revealed:
- Approximately one heartbeat per minute
- Nearly perfect consistency
- Roughly 1,440 heartbeats per day
- Continuous 24x7 activity
The only significant interruption occurred during a planned ServiceNow maintenance window, where heartbeat activity stopped for approximately 34 minutes before resuming normally.
That immediately raised an interesting possibility:
Could the absence of heartbeat activity become a platform health indicator?
Monitoring by Exception
Rather than alerting on failures alone, we began exploring "silence monitoring."
Examples:
- No heartbeat for 10 minutes
- No scheduled import completion within an expected window
- No notification processing activity
The goal is to detect degradation in expected operational behavior before user-facing impact occurs.
Introducing the ServiceNow Reliability Engineering Dashboard
To support this effort, I built a Splunk-based dashboard focused on ServiceNow reliability and observability.
Platform Health
- ServiceNow heartbeat continuity
- Heartbeat trend analysis
- Event-processing health
Availability
- MID Server operational status
- MID Server lifecycle events
- Current platform availability indicators
Import Health
- Scheduled import activity
- Time since last successful import
- Data freshness monitoring
Notification Health
- Notification engine activity
- Email diagnostics activity
Reliability Indicators
- Failure event trending
- Authentication failures
- Import failures
- Execution tracking failures
Applying SRE Concepts
Although this started as a monitoring exercise, it naturally evolved into an observability discussion.
Potential Service Level Indicators (SLIs) identified include:
- MID Server Availability: Availability of production MID Servers
- Platform Heartbeat Continuity: Ongoing glide.heartbeat activity
- Import Processing Health: Successful execution of scheduled imports
- Notification Processing Activity: Ongoing notification engine activity
- Operational Failure Rate: Failure event frequency
Potential Service Level Objectives (SLOs) are now being discussed around:
- MID Server availability
- Heartbeat continuity
- Import freshness
- Notification processing health
Lessons Learned
A few takeaways from this effort:
- Not all monitoring signals are errors.
- Silence can be a valuable monitoring indicator.
- Operational dashboards should focus on service health, not just event volume.
- SRE concepts translate surprisingly well to ServiceNow operations.
- A reliable heartbeat event can provide a powerful foundation for platform-level monitoring.
Looking Ahead
Next steps include:
- Platform heartbeat missing alerting
- Scheduled import silence monitoring
- Notification processing silence monitoring
- Additional SLI/SLO development
- Expansion of ServiceNow observability practices
I'm curious how others are approaching observability within ServiceNow.
What events, indicators, or SLIs have you found most useful for measuring overall ServiceNow health and reliability?
