HireNinja: Blog

TL;DR: In one week, you’ll pick high‑impact agent flows, define SLOs, instrument with OpenTelemetry’s GenAI conventions, wire dashboards and alerts, and enforce SLAs with guardrails—without stalling your roadmap.

Why now

Enterprise agent platforms are landing fast (e.g., Microsoft’s Agent 365 with an agent registry and real‑time oversight), making reliability and policy enforcement table stakes. citeturn7view0 Interop is also improving via open protocols like Google’s Agent2Agent (A2A), now supported by Microsoft tooling, which means multi‑agent workflows will cross clouds—and your SLOs must, too. citeturn9view0turn13search0 Meanwhile, OpenTelemetry has published Generative AI semantic conventions so you can standardize metrics, traces, and spans across models and providers. citeturn14search1turn12view0

What you’ll ship in 7 days

A practical SLO/SLA baseline for your most critical agent journeys—think checkout recovery, refund automation, lead qualification, tier‑1 support—complete with dashboards, burn‑rate alerts, and policy guardrails.

Core SLOs (start here)

• Task Success Rate (≥ X%): percentage of end‑to‑end agent runs that achieve the intended outcome.
• TTFT (Time‑to‑First‑Token ≤ Y s): speed to the agent’s first response. Map to gen_ai.client.operation.duration and model‑specific spans. citeturn14search1
• TPOT (Time‑Per‑Output‑Token ≤ Z ms): sustained decode performance; track with GenAI server metrics. citeturn14search1
• Tool Call Success Rate (≥ A%): successful external action invocations vs attempts (payments, CRM writes).
• Safe Handoff Rate (≤ B%): share of runs requiring human takeover; lower is better, but never zero for high‑risk flows.
• Cost per Resolved Task (≤ $C): tokens + tools + infra divided by successful outcomes.
• Guardrail Block Rate (track): proportion of attempts blocked by content/policy guardrails; sudden spikes indicate drift. citeturn10view0

Day‑by‑Day Plan

Day 1 — Pick flows and write SLIs/SLOs

List your top 2–3 revenue‑or mission‑critical agent flows. For each, define SLIs (what to measure) and targets (SLOs). Keep one “fast path” SLO (TTFT/TPOT) and one “outcome” SLO (success rate or handoffs). If you’re standardizing agents across vendors, note where A2A or MCP is involved so you can follow a common schema across systems. citeturn9view0turn13search0turn13search3

Related reads: build a formal Agent Registry and Control Plane to keep identities, policies, and telemetry consistent.

Day 2 — Instrument with OpenTelemetry GenAI

Add OpenTelemetry to the agent app and gateways. Emit GenAI client metrics (gen_ai.client.operation.duration, gen_ai.client.token.usage) and model/agent spans so TTFT, TPOT, and tool calls are visible by provider and model. citeturn14search1turn12view0 If you call OpenAI, include their provider‑specific attributes for tiering/fingerprints to correlate performance with service tier. citeturn3search4

Tip: Microsoft’s Agent Framework integrates with OpenTelemetry; use it if you’re in that stack. citeturn14search0

Day 3 — Dashboards and SLO math

Build Grafana dashboards for each flow: TTFT, TPOT, tool success, success rate, handoffs, and cost per task (join token/cost metrics with result outcomes). Use rolling windows and budget burn charts so on‑call sees “minutes to breach” at a glance. The GenAI metric buckets are already suggested in the spec to keep histograms comparable. citeturn14search1

Day 4 — Alerts, error budgets, and on‑call

Create multi‑window burn alerts (fast/slow) for your SLOs. Route to Slack/PagerDuty with run‑id, model, provider, and last tool call. Define a simple error budget policy: if you burn 30%+ of the monthly budget, pause risky experiments and switch to safer model tiers or narrower tools until stability returns. Tie alert playbooks into your Agent CI/CD kill switches.

Day 5 — Shadow tests, canaries, and synthetic checks

Before making SLAs public, shadow new prompts/tools behind production traffic and run synthetic checks (hourly) on the top 10 intents. Track pass/fail, latency, and drift. Promote only after the new config stays within SLO for 72 hours. See our 7‑day safe browser agent and agent memory guides for test patterns.

Day 6 — Enforce SLAs with guardrails and policies

Wire content safety and jailbreak defenses at ingress and before tool calls; many teams use lightweight, specialized models and explicit allowlists here. citeturn10view0 For cross‑vendor workflows (A2A/MCP), centralize policies in your registry so enforcement remains consistent across agents and clouds. citeturn9view0turn13search0

Day 7 — Governance and sign‑off

Document your SLOs/SLA, error budgets, and on‑call runbooks. Map the controls to ISO/IEC 42001 (AIMS) and EU AI Act timelines so stakeholders know owners and evidence paths. citeturn4search0turn4search3 If you operate in the EU, note that GPAI obligations began applying on August 2, 2025, with broader enforcement phases through 2027; align your audit trail now. citeturn4search4 Also see our 48‑hour governance checklist.

SLOs → OTel mapping (copy/paste)

• TTFT: derive from gen_ai.client.operation.duration and the model/server spans’ first‑token timing. citeturn14search1turn12view0
• TPOT: use GenAI server time‑per‑token and request duration metrics. citeturn14search1
• Tool Success: custom counter on tool invocations + span status; attach gen_ai.operation.name, model, provider. citeturn14search1
• Success Rate: custom event at end of run with outcome attribute; join to upstream spans.
• Handoffs: event when a human takeover occurs; alert on spikes.
• Cost/Task: combine token usage (gen_ai.client.token.usage) with model/tool price tables and infra costs. citeturn14search1

What this unlocks next

With SLAs in place, you can confidently compare agent platforms—OpenAI AgentKit, Microsoft Agent 365, or others—using apples‑to‑apples SLOs, and even write SLO clauses into vendor contracts. citeturn8view0turn7view0

Common pitfalls

• Only latency, no outcomes: Latency SLOs without a success‑rate SLO can drift into fast‑but‑wrong behavior.
• No policy telemetry: If guardrails block silently, you can’t see jailbreak attempts or prompt‑injection exposure. Log and meter them. citeturn10view0
• Unobservable multi‑agent workflows: When agents call agents (A2A) across clouds, require shared IDs and GenAI spans in contracts. citeturn9view0turn13search0
• Skipping canaries: Rollouts that skip shadow/canary stages often burn error budgets in hours. Use the CI/CD patterns we covered here.

Example SLA language (starter)

“Provider guarantees ≥98.5% monthly success rate for Checkout Recovery Agent (defined by confirmed order completion), TTFT ≤1.2s P95 and TPOT ≤120 ms/token P95 during business hours, tool call success ≥99.0% P99 for payments API; monthly error budget 1.5%. Breach triggers fee credits and right to fail‑open to human agents.”

Resources

• OpenTelemetry GenAI metrics, agent and model spans. citeturn14search1turn12view0
• Microsoft Agent 365 background (registry, real‑time oversight). citeturn7view0
• A2A protocol and Microsoft adoption for cross‑vendor workflows. citeturn13search0turn9view0
• Guardrail patterns for enterprise agents. citeturn10view0
• EU AI Act timeline and GPAI obligations; ISO/IEC 42001. citeturn4search3turn4search4turn4search0
• Reality check on agent reliability at scale. citeturn11view0

---

Next up: See our AI Agent FinOps 30‑Day Playbook and 48‑Hour Governance Checklist to round out your production readiness.

Call to action: Subscribe for weekly agent ops playbooks—or message us to get the SLO dashboard templates and alert rules we used in this guide.