a1f5f581fe
Cycle 0 research complete. Analyzed Erlang Observer, observer_cli, wobserver, Phoenix LiveDashboard, Akka Insights, Ray Dashboard, Orleans Dashboard, tokio-console, RabbitMQ Management, and Consul/Nomad UIs. Identified 8 implementation stages prioritized P0-P2: time-series history, actor detail drill-down, search/filter, worker viz, warning detection, topology, logging, and msg-type breakdown. Full research notes in CLAUDE/notes/ (gitignored, session-local). Authored by Claude, lovingly guided by Zachery Aaron Shores-Chmielewski
28 lines
1.2 KiB
Markdown
28 lines
1.2 KiB
Markdown
# Dashboard Improvements — Research Phase
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## Summary
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Researched 10 comparable monitoring/dashboard systems to inform swactor's dashboard improvement plan.
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## Systems Analyzed
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- **Actor runtimes**: Erlang Observer (GUI/CLI/Web), Akka Insights, Ray Dashboard, Orleans Dashboard
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- **Async/runtime tools**: tokio-console, Lunatic
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- **Message/infrastructure**: RabbitMQ Management, Consul UI, Nomad UI
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- **Web frameworks**: Phoenix LiveDashboard
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## Key Findings
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1. **Time-series history** is table-stakes — every system provides it
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2. **Actor detail drill-down** is universal (Observer has 6-tab process info, Orleans has grain state inspection)
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3. **Search/filter** exists in every system
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4. **Warning/anomaly detection** (tokio-console's lint system) is a high-value differentiator
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5. **Topology visualization** (Consul golden metrics, Observer supervision tree) is rare but powerful
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## Implementation Plan
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8 feature stages defined (see `CLAUDE/notes/feature-stages/`):
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1. Time-Series History Infrastructure
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2. Actor Detail Drill-Down
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3. Search and Filter
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4. Per-Worker Utilization Visualization
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5. Warning/Anomaly Detection
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6. Actor-to-Actor Message Flow Topology
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7. Per-Actor Logging
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8. Per-Message-Type Breakdown
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