System Observability Sweep

System Observability Sweep Workflow

CONCEPT:INFRA-001

Cross-system health and resource check combining system metrics with Langfuse observability status.

Steps

Step 0: Systems Manager

Agent: discovery-agent Tools: tun_tm_system, tun_tm_hosts

Get the system memory usage, CPU stats, and disk utilization Expected: memory, cpu

Step 1: inspect-langfuse-health [skill: langfuse-mcp]

Agent: deployer-agent Tools: pt_stack, cnt_cm_compose_operations

Check the Langfuse health endpoint and list all current datasets Expected: health, dataset

Step 2: list-recent-traces [skill: langfuse-mcp]

Agent: verifier-agent Tools: pt_docker, cnt_cm_container_operations

List the most recent traces and their status Expected: trace

Step 3: KG Persistence [depends_on: Step 1, Step 2]

Agent: verifier-agent Tools: graph_write

Persist workflow results as nodes and edges in the Knowledge Graph. Create appropriate typed nodes with metadata and link to existing domain entities.

Output

• System Observability Sweep results persisted in KG
• Structured report (MD/PDF)
• Audit trail with timestamps and agent attributions

Execution

Run this workflow as a dependency-ordered DAG. Steps with no unmet depends_on run in parallel; dependents run after their prerequisites complete.

• Run first (in parallel): Step 0 — Systems Manager; Step 1 — inspect-langfuse-health; Step 2 — list-recent-traces
• After level 0: Step 3 — KG Persistence

Execution: If graph-os is reachable, offload the whole DAG via graph_orchestrate action=execute_workflow (or the kg-delegate skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet depends_on in parallel, then their dependents.