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Project Detail
Analytics Dashboard
Summary
An automation analytics dashboard that helped DevOps teams understand usage, reliability, and operational performance.
StackStorm made automation executable, but teams also needed to understand how that automation behaved over time. Without analytics, it was hard to see which rules, actions, and triggers were trusted, failing, or heavily used.
I designed an analytics experience that translated automation activity into operational insight, helping teams monitor reliability, adoption, and system behavior from a single dashboard.
The Problem
Automation platforms can become opaque once teams start using them at scale.
Actions run in the background, rules fire automatically, and failures may only become visible when something breaks.
Teams needed a way to answer practical questions: Which automations are active? Which actions are trusted? Which rules are used most? Where are failures happening? Is automation improving operations or creating hidden risk?
The challenge was to design analytics for operators, not executives. This was not a vanity dashboard. It needed to surface signals that helped technical teams understand reliability, adoption, and operational confidence.
Solution
An Analytics app as a monitoring layer for the automation ecosystem.
The dashboard combined activity trends, execution volume, reputation signals, and usage breakdowns into one operational view.
The main activity chart gave users a temporal view of system behavior. The circular summaries made key totals easy to scan: triggers, rules, and actions. The right-side reputation panel introduced a trust signal, showing which automations were performing well and which deserved attention.
The design kept the product visually aligned with StackStorm’s technical identity: dark navigation, dense information, strong contrast, and focused data panels.
The most important design decision was to treat analytics as part of the automation feedback loop. Users were not just looking at charts. They were learning which automations worked, which needed refinement, and where the system was gaining adoption.
Outcome
The Analytics app helped StackStorm complete the automation loop.
Actions and workflows were no longer just configured and executed. They could be observed, evaluated, and improved over time.
The product gave teams a stronger sense of control over their automation environment. It helped turn invisible background activity into a measurable, inspectable system.
Key outcomes:
- Made automation activity easier to monitor.
- Surfaced usage patterns across triggers, rules, and actions.
- Helped teams identify trusted and problematic automations.
- Supported better troubleshooting and operational confidence.
- Reinforced StackStorm as a full automation control platform, not just an execution engine.
