Intelligent Operations
Upbound control planes combine deterministic control (like reconciliation and policy) with intelligent control (driven by embedded AI agents). Bring intelligence into the execution flow of your Operations with AI-embedded operation functions.
AI-embedded operation functions are standard functions designed to integrate with popular Large Language Model providers, such as from OpenAI and Anthropic. You can supplement existing function pipelines with these AI-embedded functions.
Example AI-embedded function
Operation functions are a fundamental unit of work in a control plane. Here's an
example of an Operation that uses a function to determine why a set of pods are
stuck in a CrashLoopBackoff:
apiVersion: ops.crossplane.io/v1alpha1
kind: WatchOperation
metadata:
name: analyze-events-for-pod-distress
spec:
watch:
apiVersion: v1
kind: Event
namespace: crossplane-system
# Make sure we are only creating 1 operation at a time.
concurrencyPolicy: Forbid
successfulHistoryLimit: 2
failedHistoryLimit: 1
operationTemplate:
spec:
mode: Pipeline
pipeline:
# Needed to help reduce noise funneling to claude.
- step: filter-noisy-events
functionRef:
name: function-event-filter
input:
apiVersion: filter.event.fn.upbound.io/v1alpha1
kind: Input
type: Warning
# Needed to not overly call claude if we already have an analysis.
- step: analysis-gate
functionRef:
name: function-analysis-gate
input:
apiVersion: gate.analysis.fn.upbound.io/v1alpha1
kind: Input
# Let's see what's going on.
- step: analyze
functionRef:
name: function-claude
input:
apiVersion: claude.fn.upbound.io/v1alpha1
kind: Prompt
systemPrompt: |
You are a Kubernetes infrastructure monitoring expert tasked with analyzing
pod logs and events to identify potential deployment issues.
You will receive an event that includes an involvedObject that will
include the namespace and name of the pod to examine.
userPrompt: |
You should use the tools available to you to look up events and logs related
to the pod in order to identify what's wrong.
REQUIRED OUTPUT FORMAT:
{
"apiVersion": "ops.upbound.io/v1alpha1",
"kind": "Analysis",
"metadata": {
"name": <the name of the pod>,
"namespace": <the namespace of the pod>
},
"spec": {
"involvedObjectRef: {
"kind": "Pod",
"apiVersion": "v1",
"namespace": <the namespace of the pod>,
"name": <the name of the pod>,
"uid": <the uid of the pod>
},
"analysis": "<The analysis of the issues with the pod.>",
"remediations": [
{
"name": "<A name for the remediation that is unique to the remediations array. The name must be alphanumeric and must be no longer than 10 characters.>",
"description": "< a short description for the remediation steps that will follow>",
"steps": [
{
"name": "<a unique name for the step>",
"instruction": "<The instruction for this step>"
}
]
}
]
}
}
You can suggest multiple remediation strategies. Each array item in the
"remediations" array above will correspond to a strategy. Each strategy must
have a short description and a set of steps to fix the identified issue.
Begin analysis now using the available tools.
Event Spec:
{{ .Resources }}
credentials:
- name: claude
source: Secret
secretRef:
namespace: crossplane-system
name: claude
The WatchOperation above uses function-claude to look up events and logs
related to the pod in order to identify what is wrong, and it outputs a
remediation strategy to fix the issue for the said pod.
Official AI-embedded function
Upbound offers Official Functions that have AI capabilities and are suitable for composition: