Agent Declarative Configuration

Agents are treated as immutable. Once an agent pod is instantiated from a declarative spec, it is not modified in-place. Any configuration change requires a new declaration, triggering the orchestration system to:

• Roll out a new pod with the updated configuration.
• Terminate the old pod after the new one is healthy (in strategies like rolling updates). This principle eliminates configuration drift, ensures consistency, and provides a clear audit trail for changes, as every state is defined by a specific version of the declarative file.

Declarative configuration enforces a clean separation between the agent application logic and its operational specifications. The developer or ML engineer defines the agent's purpose and code. The platform or DevOps engineer defines how it runs through declarative manifests, specifying:

• Scheduling constraints (node affinity, tolerations).
• Storage volumes for state persistence.
• Quality of Service (QoS) classes.
• Security contexts and secrets injection. This separation allows specialized teams to manage their respective domains efficiently using a common interface.

A concrete example is a Kubernetes Deployment manifest for a query-processing agent:

yamlCopy
apiVersion: apps/v1
kind: Deployment
metadata:
  name: query-agent
spec:
  replicas: 3
  selector:
    matchLabels:
      app: query-agent
  template:
    metadata:
      labels:
        app: query-agent
    spec:
      containers:
      - name: agent
        image: myregistry/query-agent:v2.1.0
        resources:
          requests:
            memory: "512Mi"
            cpu: "250m"
          limits:
            memory: "1Gi"
        env:
        - name: API_ENDPOINT
          value: "https://api.internal"
        livenessProbe:
          httpGet:
            path: /health
            port: 8080

This file declares the desired state: three replicas of version v2.1.0 with specific resources and health checks. The Kubernetes scheduler and controller-manager make it so.

Agent Configuration Drift is the undesirable state where an agent's running configuration diverges from its declared source-of-truth specification. This can occur due to:

• Manual hotfixes applied directly to a running agent.
• Environmental variables changed outside of the deployment pipeline.
• Failed or partial updates. A key goal of declarative configuration with a reconciliation loop is to automatically detect and correct this drift, enforcing configuration immutability and ensuring all deployments are idempotent.

Agent Self-Healing is a capability enabled by declarative configuration and health monitoring. When an orchestration system detects an agent failure (via a failed liveness probe) or a pod termination, it automatically takes corrective action based on the declarative spec. This action is typically to restart the failed agent or reschedule it onto a healthy node. The system's goal is to return the cluster to the declared state (e.g., '3 replicas running') without human intervention, increasing overall system resilience and availability.

Immutable Infrastructure is a foundational paradigm for declarative configuration. Instead of modifying running agents (mutable), agents are treated as immutable artifacts. To update an agent, you declare a new version in your configuration, and the orchestrator replaces the old agent instances with new ones built from a fresh image. This eliminates configuration drift, ensures consistency between testing and production, and simplifies rollback (redeploy the old image). Declarative agent specs define what the immutable deployment should be, not how to change a live one.