Telemetry alone is not operational context. For agents to act safely and effectively, you need additional layers:
System Map (Topology & Dependencies)
Services, APIs, microservices, data stores, queues, third‑party integrations, infrastructure (clusters, nodes, VMs, containers, serverless functions, network paths), and the dependency graph that ties them together. This tells the agent what is connected to what and where a failure can propagate.
Ownership & Change Context
Service owners, escalation paths, on‑call schedules, recent deployments, config changes, feature flags, infrastructure changes, PRs, change windows, and maintenance windows. This tells the agent who is responsible and what changed recently, which is critical for root‑cause analysis and safe action.
Operational Memory
Runbooks and playbooks for specific failure modes, postmortems, known errors, recurring incident patterns, architecture decisions, and prior mitigations with their outcomes. This gives the agent institutional knowledge, so it doesn’t reinvent solutions or repeat mistakes.
Governance & Decision Context
Policies that define what actions are allowed or forbidden for a service or environment, approval boundaries (which changes require human approval vs. full autonomy), risk classifications, compliance constraints, audit requirements, and human‑in‑the‑loop rules for high‑risk operations. This tells the agent what it may recommend, what it may execute, and what must be escalated.
FinOps & Efficiency Context
Budgets, forecasts, and cost allocations by service, environment, and team; unit economics (cost per transaction, per user, per API call); utilization and cloud resource waste signals (idle VMs, over‑provisioned clusters, unused storage); and FinOps policies and guardrails (spend caps, instance‑type preferences, region cost tiers, sustainability constraints). This tells the agent how its actions impact cost and efficiency, and what financial guardrails it must respect when recommending or executing changes.
Freshness & Trust Metadata
Every context element should carry metadata like source system, owner, timestamp, confidence score, last validation event, and permitted AI use (read‑only, read‑write, no‑action). This allows the agent to reason about how fresh and trustworthy each piece of context is before acting.
Mansi Singh