docs(day0): OTEL feedback talk

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---
title: "Scaling on satisfaction: Automated Rollouts Driven By User Feedback"
weight: 7
tags:
- platformengineeringday
- staging
- rollout
- feedback
- otel
---
<!-- {{% button href="https://youtu.be/rkteV6Mzjfs" style="warning" icon="video" %}}Watch talk on YouTube{{% /button %}} -->
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## What they are actually talking about
- A way of creating metrics/traces from an llm and anlyzing them
- The integration of the user's feedback
- Basicly the integration of what the variant did on the server to the vote event to promote based on feedback
- Combined with an into to OTEL
## Baseline
- Question: How do we know that content generated by llms and delivered to our users is good or bad
- Idea: Using OTEL and user feedback to drive canary deployments and rollout
- Needed: A standardized vocabulary (so we can talk to any telemetry system)
## Demo Architecture
The start of the talk featured an evolving story (5 parts) and let the attendees vote on if they like it or not to emulate rollouts of a new application version with immideate user feedback. It was based on flagger deciding every thrity seconds if the user feedback allows promotion of new versions.
- Audience get's plit to two variants running as knative deployments
- OTEL Collector collects telementry data and the platform (Flagger) uses it as the basis for it's decisions
- The collection was done by creating a user session span with a span event (aka a log) regarding the voting -> Span events are deprecated and will be moved to a logs api
## Now to our platform
- Stack: Kubernetes on hetzner with components (cert-manager, ingress, knative, ...) packaged by carvel
- knative as the deployment target for apps
- Flagger as the release decision tools
- OTEL for instrumentation
- Crossplane
- API: StoryApp CRD as the main interface for controlling what we want to deploy
## Takeaway
- Include user feedback in the decision process for new rollouts
- OTel can be used to automate thes