28 lines
1.2 KiB
Markdown
28 lines
1.2 KiB
Markdown
# Dashboard Improvements — Research Phase
|
|
|
|
## Summary
|
|
Researched 10 comparable monitoring/dashboard systems to inform swactor's dashboard improvement plan.
|
|
|
|
## Systems Analyzed
|
|
- **Actor runtimes**: Erlang Observer (GUI/CLI/Web), Akka Insights, Ray Dashboard, Orleans Dashboard
|
|
- **Async/runtime tools**: tokio-console, Lunatic
|
|
- **Message/infrastructure**: RabbitMQ Management, Consul UI, Nomad UI
|
|
- **Web frameworks**: Phoenix LiveDashboard
|
|
|
|
## Key Findings
|
|
1. **Time-series history** is table-stakes — every system provides it
|
|
2. **Actor detail drill-down** is universal (Observer has 6-tab process info, Orleans has grain state inspection)
|
|
3. **Search/filter** exists in every system
|
|
4. **Warning/anomaly detection** (tokio-console's lint system) is a high-value differentiator
|
|
5. **Topology visualization** (Consul golden metrics, Observer supervision tree) is rare but powerful
|
|
|
|
## Implementation Plan
|
|
8 feature stages defined (see `CLAUDE/notes/feature-stages/`):
|
|
1. Time-Series History Infrastructure
|
|
2. Actor Detail Drill-Down
|
|
3. Search and Filter
|
|
4. Per-Worker Utilization Visualization
|
|
5. Warning/Anomaly Detection
|
|
6. Actor-to-Actor Message Flow Topology
|
|
7. Per-Actor Logging
|
|
8. Per-Message-Type Breakdown
|