DEVOPS
On-Demand Latency Scaling Advisor Chat
An on-demand chat where an engineer names a service and the agent fetches its live latency percentiles from Datadog, checks current Vercel scaling.
How it runs
The automated pipeline, trigger to output.
- TriggerEngineer asks in chat with service name
- ActionQuery Datadog live p95/p99 latency and request rateDatadog
- ActionRead current Vercel scaling configurationVercel
- LogicReason about SLO fit and compute recommended instance count
- OutputReply with recommendation and confidence note in chat
What it does
Lets an engineer ask, in chat, whether a given service needs to scale right now. The agent fetches that service's live p95/p99 latency from Datadog, reads its current Vercel scaling configuration, and replies with a recommended instance count, the headroom math behind it, and a confidence note — all in the conversation.
When to use it
Use it during an incident or a traffic ramp when you want a fast, data-backed second opinion before touching scaling settings, without leaving chat to assemble dashboards yourself.
How it works
- 1An engineer triggers the chat with a service name and optional target SLO.
- 2The agent queries Datadog for the service's current p95/p99 latency and request rate.
- 3It reads the current Vercel scaling configuration for that service.
- 4It reasons about whether current capacity meets the SLO and computes a recommended instance count.
- 5It returns the recommendation, supporting numbers, and a confidence note in the chat reply.
Set it up
What you configure once, before turning it on.
- 1Connect DatadogMetrics, traces, log search.
- 2Connect VercelDeploys, runtime logs, analytics.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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