🧠 Infrastructure Engineer Agent Specification¶

🎯 Agent Purpose¶

The Infrastructure Engineer Agent is responsible for generating the deployable infrastructure layer for every microservice, API gateway, background task, or system component in the factory.

It bridges the gap between logical service architecture and runnable, traceable cloud-native infrastructure, ensuring that each generated component is:

🧩 Deployable
🔍 Observable
🔐 Secure
☁️ Cloud-ready
🎯 Trace-linked

It converts architecture blueprints into Kubernetes manifests, Helm charts, Bicep modules, service mesh configs, OTEL telemetry hooks, and more — fully aligned to ConnectSoft’s DevOps and GitOps pipelines.

🧭 Strategic Role in the Factory¶

Layer	Role
Software Engineering	Converts architectural outputs into deployment-ready specs
Infrastructure Layer	Creates declarative infrastructure code
DevOps Layer	Supplies deployable YAMLs, Helm, ARM/Bicep, etc.
Observability Layer	Injects OpenTelemetry configuration for traceability
Security Layer	Applies security baselines, RBAC, service identity bindings

🔄 How It Differs from Infrastructure Architect Agent¶

Agent	Role
🧠 Infrastructure Architect Agent	Designs templates, defines policies, sets constraints (high-level)
🔧 Infrastructure Engineer Agent	Instantiates, populates, configures, and emits deployable artifacts (concrete)

🧱 What It Builds¶

Kubernetes manifests:
Deployment, Service, Ingress, ConfigMap, Secret, HPA
Helm charts for versioned deployment
Azure DevOps YAML templates (CI/CD hooks, liveness, rollout)
OTEL trace injection via sidecars or environment variables
Azure Bicep or Pulumi for resource provisioning (optional phase 2)

🔍 Purpose Summary¶

The Infrastructure Engineer Agent automates the generation of cloud-native infrastructure as code artifacts, enriched with traceability metadata, observability instrumentation, and policy-aligned deployment standards — ensuring each software component becomes immediately deployable and auditable in production.

🧩 Alignment with ConnectSoft Principles¶

Principle	Alignment
Clean Architecture	Isolates infrastructure layer from core service logic
Traceability	Attaches trace_id and blueprint refs to all artifacts
Event-Driven	Listens to blueprint & commit events, emits manifest-ready notifications
Observability-First	Injects metrics and OTEL automatically
Security-First	Supports identity bindings, secret scanning, RBAC output
Cloud-Native	Produces Kubernetes-native YAML, Helm, and Azure-compatible artifacts
Multi-Tenant SaaS	Supports tenant-specific namespaces, config overlays, scaling policies

🧠 Summary¶

The Infrastructure Engineer Agent is a deterministic, trace-aware infrastructure generation agent that:

Instantiates real-world runtime definitions,
Embeds observability and security best practices,
And enables immediate deployment of every microservice and system component across environments.

It is the “compiler” of platform operations — turning abstract architecture into concrete, cloud-executable reality.

📌 Core Responsibilities¶

The Infrastructure Engineer Agent is accountable for transforming architectural service definitions and operational context into fully structured infrastructure-as-code artifacts. These artifacts are ready for consumption by the DevOps Architect Agent, Security Architect Agent, and Deployment Pipelines.

🔧 Functional Responsibilities¶

✅ 1. Generate Kubernetes Resource Definitions¶

Deployment, Service, Ingress, ConfigMap, Secret, PersistentVolumeClaim, etc.
All YAML output is versioned and validated
Namespaced per component and tenant

✅ 2. Emit Helm Charts¶

Wrap manifests into reusable Helm templates
Support overrides for:
Environment (dev/staging/prod)
Multi-tenant values
Resource scaling
Populate Chart.yaml, values.yaml, templates

✅ 3. Inject Observability Configuration¶

Generate OpenTelemetry sidecar or env injection
Create config maps for:
Tracing exporter config
Sampling policies
Propagation context (trace_id, blueprint_id)

✅ 4. Generate Azure DevOps CI/CD Deployment YAML¶

Creates deployment job fragments (kustomize, kubectl apply, helm upgrade)
Publishes deployment stages for use in CI/CD pipelines

✅ 5. Embed Traceability Metadata¶

Inject trace_id, blueprint_id, component_scope into:
Annotations
Labels
Helm chart metadata
Ensures all infrastructure is auditable and reversible

✅ 6. Apply Platform Security Requirements¶

Auto-generate:
Pod security context
Identity bindings
RBAC roles (e.g., service-reader, queue-publisher)
Emit Azure Key Vault integration config if required

✅ 7. Environment-Specific Variants¶

Supports overlays for:
dev, qa, staging, production
Scaled replicas, node affinity, tolerations
May interface with environment policies (from Infra Architect Agent)

✅ 8. Publish Manifest & Helm Events¶

Emit:
InfrastructureGenerated
HelmChartReady
ManifestPublished
Events are consumed by: DevOps Agent, Security Agent, Observability Agent

✅ 9. Store and Version Output¶

Persist generated files to:
Agent workspace
Blob storage
Git repository (via GitOps commit)
Include manifest signatures and hash digests

✅ 10. Support Future IaC Backends¶

Bicep, Terraform, Pulumi (for Azure-native services or preview environments)
Optional, depending on blueprint source

📌 Summary Table¶

Category	Deliverable
K8s Resources	`deployment.yaml`, `service.yaml`, etc.
Helm Artifacts	`Chart.yaml`, `values.yaml`, `templates/*.yaml`
Observability	OTEL config maps, sidecars, labels
Security	RBAC, Key Vault, pod policies
CI/CD YAML	`azure-pipelines-deploy.yaml`
Events	`InfrastructureGenerated`, `HelmChartReady`
Storage Targets	Git, Blob, Agent Memory

🧠 Summary¶

The Infrastructure Engineer Agent is a production-grade infrastructure generator, tasked with producing cloud-native, policy-compliant, tenant-aware, and trace-annotated artifacts that form the foundation of runtime environments in the ConnectSoft platform.

📥 Inputs¶

The Infrastructure Engineer Agent requires a well-structured input context that includes:

Traceable component metadata
Deployment constraints and scaling rules
Architectural output from upstream agents
Template IDs and reusable configurations
Platform policy overlays (e.g., observability, security)

Inputs may be passed via event payloads, context memory, or agent-to-agent transfer.

🔑 Primary Inputs¶

✅ 1. Trace Metadata¶

Provided by: Code Committer Agent or Blueprint Registry

Field	Description
`trace_id`	Unique ID linking infra to its originating blueprint
`blueprint_id`	Identifier for use case or microservice
`component_scope`	Domain-level scope (e.g., Billing, Identity)
`agent_origin`	Source agent (e.g., Microservice Generator Agent)

✅ 2. Component Runtime Definition¶

Provided by: Microservice Generator Agent or Architect Agents

component:
  name: OrderService
  type: microservice
  transport: http
  replicas: 2
  container_image: ghcr.io/connectsoft/orderservice:1.0.0
  env:
    - name: ORDER_QUEUE
      value: queue.order.processing
  ports:
    - name: http
      port: 80
      targetPort: 8080

This is the minimal unit of infrastructure to render.

✅ 3. Deployment Policy Overlay¶

Provided by: Infrastructure Architect Agent

environments:
  dev:
    replicas: 1
    otel_sampling: 100
    enable_ingress: true
  prod:
    replicas: 4
    otel_sampling: 20
    enable_ingress: true
    enable_hpa: true
    autoscale:
      minReplicas: 2
      maxReplicas: 10

✅ 4. Template References¶

Provided via policy memory or skill parameters:

Type	Examples
Helm template ID	`standard-microservice-helm-template-v3`
Deployment YAML template	`k8s-deployment-v2.yaml`
OTEL injection template	`otel-sidecar-v1`
CI/CD pipeline block	`azure-pipelines-k8s-deploy-v1`

✅ 5. Observability Injection Parameters¶

Injected or resolved from Observability Policy Agent:

observability:
  otel_enabled: true
  otel_exporter: "otlp"
  otel_endpoint: "http://otel-collector.monitoring:4317"
  propagation: "trace_id,blueprint_id"

✅ 6. Security Baseline Profile¶

Provided by: Security Architect Agent

security_profile:
  enable_rbac: true
  rbac_roles: ["reader", "publisher"]
  enable_identity_binding: true
  enforce_resource_limits: true

✅ 7. Environment Selector¶

From the orchestration agent or blueprint:

target_environment: "staging"

Used to pick appropriate overlays, Helm values, autoscaling profiles, etc.

📂 Optional Inputs¶

existing_config_map_refs – to mount external configuration
tls_secret_name – if ingress requires HTTPS
service_mesh_enabled – flags sidecar injection templates (e.g., Istio)

🧠 Example Consolidated Input Bundle¶

{
  "trace_id": "trace-infra-8128",
  "component": {
    "name": "UserService",
    "type": "microservice",
    "container_image": "ghcr.io/connectsoft/userservice:1.0.0",
    "transport": "grpc"
  },
  "target_environment": "dev",
  "template_id": "helm-microservice-template-v2",
  "observability": {
    "otel_enabled": true,
    "otel_endpoint": "http://otel.default:4317"
  },
  "security_profile": {
    "enable_rbac": true
  }
}

🧠 Summary¶

The Infrastructure Engineer Agent relies on a compositional input model, where it aggregates structured metadata from multiple upstream agents, policies, and runtime definitions to generate complete, traceable, and deployable infrastructure blueprints.

📤 Outputs¶

The Infrastructure Engineer Agent emits infrastructure-as-code artifacts, enriched with trace metadata, and aligned with ConnectSoft standards. These outputs serve as:

Direct inputs to CI/CD pipelines
Deployment descriptors for Kubernetes clusters
Observability + security-enforced definitions
Immutable GitOps assets

Outputs are produced in Helm-compatible, Kubernetes-native, and optionally Azure-native (Bicep) formats.

🧾 Output Categories¶

✅ 1. Kubernetes YAML Manifests¶

Generated per microservice or component:

File	Purpose
`deployment.yaml`	Deploys the container with env vars, probes, labels
`service.yaml`	Internal service definition (ClusterIP or LoadBalancer)
`ingress.yaml`	Ingress routing (if `enable_ingress = true`)
`configmap.yaml`	Runtime configuration (non-sensitive)
`secret.yaml`	Encodes sensitive config (e.g., credentials, tokens)
`hpa.yaml`	Horizontal Pod Autoscaler config
`serviceaccount.yaml`	For pod identity / RBAC

📌 Annotations include:

trace_id, blueprint_id, component_scope
agent_origin, factory_execution_id

✅ 2. Helm Chart Bundle¶

Directory output:

chart/
├── Chart.yaml
├── values.yaml
├── templates/
│   ├── deployment.yaml
│   ├── service.yaml
│   ├── ingress.yaml
│   └── otel-configmap.yaml

All charts follow ConnectSoft Helm scaffolding template version (v2+)

🧠 `Chart.yaml` includes:¶

name: userservice
version: 1.0.0
appVersion: 1.0.0
annotations:
  trace_id: trace-user-122
  blueprint_id: usecase-user-register
  generated_by: infrastructure-engineer-agent

✅ 3. OpenTelemetry Configuration (Optional)¶

Output	Description
`otel-configmap.yaml`	Configures exporters, endpoints, and context injection
`otel-sidecar.yaml`	If service mesh or injected tracing agent is needed

✅ 4. Azure DevOps CI/CD Deployment YAML Block¶

# azure-pipelines.deploy.yaml (fragment)
- stage: deploy_dev
  jobs:
    - deployment: deploy_userservice
      environment: dev
      strategy:
        runOnce:
          deploy:
            steps:
              - task: HelmDeploy@0
                inputs:
                  chartPath: ./charts/userservice

Automatically emitted to CI/CD repo if GitOps push is enabled

✅ 5. Event: `InfrastructureGenerated`¶

Sent to the event bus for downstream agents (DevOps, Observability, Security, Orchestration):

{
  "event": "InfrastructureGenerated",
  "trace_id": "trace-user-122",
  "repo": "UserService",
  "chart_path": "charts/userservice/",
  "target_environment": "dev",
  "agent": "infrastructure-engineer-agent",
  "timestamp": "2025-05-07T22:45:12Z"
}

✅ 6. Artifact Storage Locations¶

Output	Location
YAML files	Local execution output, Git repo, or blob
Helm chart	Git (Helm repo), Agent memory, or tarball
OTEL config	Shared observability mount or ConfigMap definition
Events	MCP Event Bus (JSON), Event Grid (optional)

🧠 Summary¶

The Infrastructure Engineer Agent produces:

🔧 YAMLs (ready-to-apply)
📦 Helm charts (reusable, traceable)
🔭 Observability configs
🔁 Event hooks
⚙️ CI/CD blocks

All aligned to ConnectSoft’s multi-tenant, trace-first, cloud-native delivery model — ensuring every component is ready for deployment, auditing, and extension.

📚 Knowledge Base¶

The Infrastructure Engineer Agent operates as a template-driven, policy-aware generation engine, relying on a rich knowledge base of:

Infrastructure templates
Cloud-native patterns
Multi-tenant deployment overlays
Security and observability guidelines
Repository conventions and naming standards

This allows the agent to generate predictable, reusable, and compliant outputs at scale.

📘 Core Knowledge Categories¶

✅ 1. Infrastructure Templates¶

Template Type	Examples
Kubernetes YAML	`k8s-deployment-v2.yaml`, `service.yaml`, `hpa.yaml`
Helm Scaffolding	`Chart.yaml`, `values.yaml`, `template/*.yaml`
Ingress / Mesh	`ingress-istio.yaml`, `gateway-api.yaml`
DevOps YAML	`azure-pipelines.deploy.yaml`, `helm-release-stage.yaml`

Versioned, stored centrally, and referenced by template ID.

✅ 2. Observability Injection Blocks¶

Knowledge	Use
OTEL sidecar / environment templates	Add tracing exporters, propagators
Trace metadata schema	Define how to inject `trace_id`, `blueprint_id` into `metadata.labels` and `annotations`
Environment-specific propagation rules	e.g., only enable in staging/prod

✅ 3. Security Enforcement Snippets¶

Knowledge	Action
RBAC role templates	Generate `Role`, `RoleBinding`, `ServiceAccount`
Pod security context rules	Enforce non-root, seccomp, capabilities
Vault + Secret annotations	Template for injecting Key Vault or sealed secrets

✅ 4. Scaling and Environment Overlays¶

Environment	Config
`dev`	Single replica, permissive probes, tracing = 100%
`qa`	2–3 replicas, autoscaling on CPU
`prod`	HPA enabled, ingress secured, OTEL = sampling 20%

Overlays define:

Replica counts
Autoscaling configs
Resource limits/requests
Ingress TLS and domain mapping

✅ 5. Naming and Repo Conventions¶

Type	Pattern
Namespace	`cs-${tenant}-${component}`
Helm chart name	`${component}-chart`
Git path	`infrastructure/${component}/`
Secret name	`cs-${component}-secrets-${env}`

✅ 6. Reusable Metadata Definitions¶

Field	Use
`trace_id`	Embedded in `metadata.annotations`
`blueprint_id`	Embedded in `labels` and `Chart.yaml`
`agent_origin`	Logged in `InfrastructureGenerated` events
`execution_id`	Linked across commit → PR → manifest flow

✅ 7. Policy Definitions (from Infra Architect Agent)¶

Policy	Example
Max replicas	`10` in non-prod, `100` in prod
Allow ingress	Only in `staging`, `prod`
Secret volume mount path	Must match `/mnt/secrets/<name>`
Mandatory labels	`team`, `component`, `trace_id`, `env`

🗂️ Knowledge Storage Options¶

Source	Type
SK Planner Memory	Templates and transformation prompts
Blob Storage / Git	Helm scaffolding, reusable YAMLs
Redis / Cosmos DB	Policy overlays and trace mappings
Vector DB	Embedded blueprint-usecase → manifest similarity search (future phase)

🧠 Summary¶

The Infrastructure Engineer Agent’s knowledge base enables it to:

Enforce infrastructure standards
Apply reusable and modular templates
Respect multi-environment policies
Maintain consistency across 1000s of services
Produce fully traceable, auditable, and secure infrastructure

It transforms infrastructure generation into a policy-bound AI reasoning task, not a copy/paste exercise.

🔄 Process Flow¶

flowchart TD
    A[Receive Input Bundle (CommitCompleted / BlueprintReady)] --> B[Resolve Component + Env Config]
    B --> C[Load Templates + Overlays]
    C --> D[Render YAMLs (Deployment, Service, HPA)]
    D --> E[Inject Trace + Metadata]
    E --> F[Assemble Helm Chart (Optional)]
    F --> G[Validate Artifacts (Schema, Policy)]
    G --> H[Emit Output Files + Events]

Hold "Alt" / "Option" to enable pan & zoom

🪜 Step-by-Step Breakdown¶

✅ Step 1: Input Ingestion¶

Input event or task provides:
trace_id, blueprint_id, component_scope
Target environment
Component metadata (image, ports, env, etc.)

If any required input is missing, agent halts and emits correction event.

✅ Step 2: Resolve Configuration Context¶

Look up:
Tenant/environment overlays
Default scaling rules
Observability and security policies
Determine which templates to use based on component type

✅ Step 3: Load and Merge Templates¶

Load:
Kubernetes YAML templates
Helm scaffold (if enabled)
OTEL and security stubs
Merge overlays based on environment profile

✅ Step 4: Render Infrastructure Artifacts¶

Populate:
deployment.yaml, service.yaml, hpa.yaml
Inject container image, env vars, probes, ports
Derive name/namespace using naming policy
Add config maps, secrets, identity bindings if defined

✅ Step 5: Inject Traceability Metadata¶

Into every artifact:
metadata.labels.trace_id
metadata.annotations.blueprint_id, component_scope, generated_by
Also inject into Chart.yaml, OTEL config maps, and release metadata

✅ Step 6: Helm Chart Assembly (Optional)¶

If Helm is enabled:
Populate Chart.yaml, values.yaml, and templates/*
Export as chart directory or .tgz bundle
Add version from execution context

✅ Step 7: Validate Outputs¶

Run:
Kubernetes schema validation (kubectl apply --dry-run=client)
Helm lint checks (helm lint)
Policy validation:
- Prohibited ports
- Missing labels
- Disallowed node selectors
- If invalid → retry or escalate to HumanOpsAgent

✅ Step 8: Emit Artifacts and Events¶

Save YAMLs to:
Blob storage
Agent workspace
Git repo (via GitOps push, optional)
Emit:
InfrastructureGenerated event
Trace linkage log
Make artifacts available for DevOps pipeline and Observability Agent

📦 Parallel Paths (Optional)¶

Flow	Trigger
Azure Bicep or Pulumi	Component needs cloud resource (e.g., storage, identity)
Config-only Mode	Only `ConfigMap` or Helm `values.yaml` generation
Multi-env mode	Generate `dev`, `qa`, and `prod` overlays in one pass

📋 Process Guardrails¶

Guardrail	Result
Missing trace ID	Abort with validation error
PR exists but not linked to trace	Emit warning, block generation
Helm chart fails lint	Retry + emit event for TechLeadAgent
Environment undefined	Fallback to default overlay (`dev`)

🧠 Summary¶

The Infrastructure Engineer Agent follows a deterministic, modular pipeline, transforming architecture + policy into validated, traceable, and production-ready infrastructure artifacts.

Its flow enforces:

Clean separation of concern
Trace integrity
Policy application
AI-powered reproducibility

🧩 Skills & Kernel Functions¶

The Infrastructure Engineer Agent uses Semantic Kernel (SK) plugins, LLM-assisted planners, and template resolution functions to transform architectural inputs into structured infrastructure code.

Its skills are composable, reusable, and enforce policy compliance, trace embedding, and platform compatibility.

🛠️ Core Skills & Functions¶

Skill	Purpose
`TemplateResolverSkill`	Load and resolve YAML/Helm templates using variable substitution
`OverlayMergeSkill`	Apply environment-specific configuration overlays (e.g., `prod`, `dev`)
`TraceMetadataInjectorSkill`	Insert `trace_id`, `blueprint_id`, `component_scope` into all outputs
`HelmChartBuilderSkill`	Assemble Helm `Chart.yaml`, `values.yaml`, and `templates/`
`OtelInjectionSkill`	Add OTEL exporter config, environment variables, or sidecars
`SecurityContextBuilderSkill`	Generate pod security policies, service accounts, identity bindings
`K8sValidatorSkill`	Perform dry-run validations of rendered YAML
`ArtifactEmitterSkill`	Persist generated files, emit event with output paths and metadata
`EventEmitterSkill`	Send events like `InfrastructureGenerated`, `HelmChartReady`, `InfraValidationFailed`

🔁 Example SK Function Flow¶

→ TemplateResolverSkill.Load("k8s-deployment-v2.yaml")
→ OverlayMergeSkill.Merge(environment="prod")
→ TraceMetadataInjectorSkill.Inject(trace_id="trace-xyz")
→ HelmChartBuilderSkill.Build(component="orderservice")
→ K8sValidatorSkill.Validate()
→ ArtifactEmitterSkill.Save(path="/charts/orderservice")
→ EventEmitterSkill.Emit("InfrastructureGenerated")

🔧 Semantic Kernel Planner Composition¶

The agent's execution plan is built using SK’s planner + skill chaining, which allows it to:

Dynamically choose the correct environment overlay
Reuse templates across services and components
Inject trace metadata everywhere (including Helm chart metadata, labels, annotations)

🧠 AI-Powered Code Synthesis (Optional Phase)¶

Function	Use
`LLMTemplateExpander`	Given blueprint + resource description → generate YAML draft
`PromptBasedValidator`	Ask: “Is this YAML compliant with ConnectSoft standards?”
`PostProcessorSkill`	Format YAML, compress, inject final metadata block

Used to fine-tune low-confidence scenarios or novel component types.

🔐 Security-Scoped Skill Usage¶

Each skill enforces least-privilege file access
Template paths are read-only (no overwrite unless approved)
Helm chart builder operates within a sandboxed path per tenant/project

🧠 Summary¶

The Infrastructure Engineer Agent is powered by a modular, SK-based skillset that enables:

Template-driven infrastructure synthesis
Trace-aware manifest generation
Secure, policy-aligned Helm packaging
Observability-first automation across environments

It transforms declarative specs into validated, versioned, cloud-native infrastructure, ready for GitOps deployment or DevOps orchestration.

🧰 Core Technology Stack¶

The Infrastructure Engineer Agent is implemented as a modular, containerized, policy-driven agent, using Semantic Kernel, OpenAI, Kubernetes-native tooling, and Azure-native infrastructure.

⚙️ Platform Technologies¶

Layer	Technology	Purpose
Agent Orchestration	MCP Server (Model Context Protocol)	Lifecycle orchestration, event flow
Execution Engine	.NET 8 + Semantic Kernel	Agent runtime, skills, plan composition
LLM Backend	Azure OpenAI (GPT-4 Turbo)	Prompt expansion, reasoning (e.g., trace-to-template logic)
Memory	Redis / Cosmos DB / Qdrant	Store overlays, trace-mapping, and reusable templates
Container Host	Azure Kubernetes Service (AKS) or Container Apps	Runs the agent securely and scalably

📦 Infrastructure-Specific Tools¶

Tool	Use
Helm	Chart generation, packaging, and linting
Kustomize (optional phase)	Layered overlay generation for complex resources
kubectl	YAML dry-run validation, apply tests
Yamllint	Schema checking and formatting
OpenTelemetry SDK	Instrument infrastructure artifacts and agent telemetry
Azure CLI / Bicep CLI (optional)	Provision cloud resources if blueprint defines service-dependent infrastructure

📘 Agent Libraries & Skills¶

Library	Use
`ConnectSoft.Skills.Kubernetes`	Loads and fills K8s YAML templates
`ConnectSoft.Skills.Helm`	Helm chart scaffolding, value injection, metadata mapping
`ConnectSoft.Skills.TraceInjection`	Labels + annotations for observability and traceability
`ConnectSoft.Skills.Validation`	YAML linting, policy checks, schema enforcement
`ConnectSoft.Skills.Eventing`	Infrastructure lifecycle events for downstream use (DevOps, QA, Docs, etc.)

🔐 Security & Policy Enforcement¶

Feature	Technology
RBAC/PodSecurity	Enforced via YAML + policy overlays
Key Vault Integration	Injected via annotation + secret template
Identity binding	Uses Azure AD pod identity (via service account config)
File sandboxing	Helm and YAML writers scoped to tenant/workspace only

📈 Observability Stack¶

Tool	Use
OpenTelemetry (OTEL)	Agent-level spans, operation metrics
Azure Monitor / Grafana	Dashboards and alert rules for generation failures
Span Tags	Include: `trace_id`, `component_scope`, `chart_status`, `helm_lint_passed`

📂 Output Integration Targets¶

Target	Technology
GitOps Repo	Git CLI or GitHub/Azure DevOps REST API
Artifact Blob	Azure Blob Storage
Event Bus	Azure Event Grid or MCP Server Messaging
Helm Repo	Git-based or OCI Helm registry (future phase)

🧠 Summary¶

The Infrastructure Engineer Agent uses a composable AI + DevOps toolchain, grounded in:

Kubernetes-native standards
Trace-first automation
Policy-bound execution
Multi-environment and multi-tenant support

It brings together the power of AI reasoning with the determinism of IaC templates, ensuring that infrastructure generation is autonomous, auditable, and production-safe.

📜 System Prompt¶

The System Prompt is the initial instruction injected into the agent’s LLM-backed planning kernel to define its:

Mission
Scope boundaries
Output format expectations
Compliance rules
Error handling mindset

It ensures consistent, secure, and traceable infrastructure generation across environments and tenants.

🧠 Infrastructure Engineer Agent — System Prompt¶

You are the Infrastructure Engineer Agent in the ConnectSoft AI Software Factory.

Your primary task is to generate complete, traceable, policy-compliant infrastructure definitions for microservices, APIs, event processors, or system components. These definitions are consumed by CI/CD pipelines, observability layers, and DevOps systems.

You never invent functionality — instead, you populate infrastructure templates with correct values, following environment overlays and platform policies.

You always include:
- Required Kubernetes resources: deployment, service, ingress, configmap
- Helm charts if requested
- Traceability metadata in labels and annotations
- OpenTelemetry configuration (if enabled)
- RBAC roles, service account, or security context (if required)

You must:
- Follow infrastructure naming policies
- Ensure output is YAML-compliant
- Validate using linting and schema checks
- Halt on invalid or incomplete input

You emit both:
- Infrastructure files (YAML, Helm, OTEL config)
- Lifecycle event: InfrastructureGenerated

All output must be:
- Cleanly formatted
- Deterministic and reproducible
- Enriched with trace and blueprint metadata

Do not guess, hallucinate, or fabricate. Work strictly from templates and policy overlays.

🔍 Key Behavioral Constraints¶

Rule	Purpose
No hallucination	Enforces deterministic IaC
Always inject trace_id	Enables audit and rollback
Fail fast on policy violation	Prevents insecure or unscoped artifacts
Use reusable templates	Ensures consistency across 1000s of components

📘 Sample Manifest Annotation Output (Required)¶

metadata:
  labels:
    trace_id: trace-ord-8128
    component_scope: Order
  annotations:
    blueprint_id: usecase-create-order
    generated_by: infrastructure-engineer-agent

🧠 Summary¶

This System Prompt ensures the Infrastructure Engineer Agent always:

Acts with trace-first discipline
Embeds security and observability standards
Produces CI/CD- and GitOps-ready infrastructure artifacts
Behaves with AI safety and operational rigor

It is the foundation of agentic reproducibility in infrastructure synthesis.

📥 Input Prompt Template¶

The Input Prompt Template provides a structured and parameterized instruction to the agent, combining:

Component metadata
Trace linkage
Environment overlays
Template resolution instructions

This prompt is either fed into the Semantic Kernel planner or expanded by the LLM-backed function to generate YAML, Helm, and event outputs.

🧩 Prompt Template (YAML-Injection Style)¶

You are generating Kubernetes infrastructure definitions for the following component:

Trace ID: {{trace_id}}  
Blueprint ID: {{blueprint_id}}  
Component Name: {{component_name}}  
Component Scope: {{component_scope}}  
Component Type: {{component_type}} (e.g., microservice, api-gateway, job)  
Image: {{container_image}}  
Transport: {{transport}} (http, grpc, queue, etc.)  
Target Environment: {{target_environment}}  
Environment Overlays:
{{env_overlay_block}}

Security Profile:
{{security_profile}}

Observability Settings:
{{observability_block}}

Template ID: {{template_id}}  
Output Format: Kubernetes YAML + Helm Chart (if enabled)

Instructions:
1. Fill deployment, service, ingress, and configmap templates using the inputs above.
2. Apply environment-specific overlays (replicas, resources, ingress rules).
3. Inject traceability metadata into all `metadata.labels` and `metadata.annotations`.
4. Add OTEL config or sidecar (if observability enabled).
5. Assemble a valid Helm chart (if requested).
6. Validate all YAMLs using schema-aware linting.
7. Emit: output files + InfrastructureGenerated event

Your output must be:
- Complete, valid YAML
- Compliant with all input policies
- Clearly traceable via metadata
- Stored and emitted according to factory standards

Do not generate sample values. Use only inputs provided.

🧾 Substituted Prompt Example (Partial)¶

Trace ID: trace-auth-9042  
Blueprint ID: usecase-auth-token-grant  
Component Name: AuthService  
Component Scope: Identity  
Component Type: microservice  
Image: ghcr.io/connectsoft/authservice:1.3.1  
Transport: http  
Target Environment: staging  

Observability Settings:
  otel_enabled: true  
  otel_endpoint: http://otel.default.svc.cluster.local:4317  
  propagation_fields: trace_id, blueprint_id  

Template ID: helm-microservice-template-v3  
Output Format: Helm + YAML

🔧 Required Template Variables¶

Variable	Description
`{{trace_id}}`	Critical for linking infra to blueprint
`{{component_name}}`	Used in file names, chart IDs, metadata
`{{transport}}`	Determines port schema and service mapping
`{{observability_block}}`	Dictates if sidecars or OTEL configmaps are needed
`{{security_profile}}`	Triggers RBAC and pod policy generation
`{{target_environment}}`	Chooses overlays and resource profiles

🧠 Prompt Behavior Summary¶

Area	Role
🧠 Contextual	Provides LLM or planner everything needed to render valid infrastructure
🔒 Safe	Explicitly disables guessing, hallucination
📦 Reusable	Can be versioned or replayed for the same component
🎯 Deterministic	Ensures output matches blueprint, not improvisation

✅ Summary¶

The Input Prompt Template enables the Infrastructure Engineer Agent to operate in a strict, controlled, and reproducible manner — generating infrastructure that is:

Trace-linked
Policy-driven
Cloud-native
Composable via agent-to-agent flow

📦 Output Expectations¶

The Infrastructure Engineer Agent emits infrastructure-as-code artifacts that are:

Valid Kubernetes YAML manifests
Optional Helm charts
OTEL and security config files
CI/CD deployment fragments
Event payloads describing success/failure

All outputs must be traceable, policy-compliant, and ready for automation.

✅ YAML File Expectations¶

🧾 Structure¶

Each YAML manifest must be:

Fully structured and schema-valid
Separated per Kubernetes kind
Commented (optional) for readability
Labeled and annotated for traceability

🧾 Required Files (per component)¶

File	Description
`deployment.yaml`	Includes image, env vars, probes, replica spec
`service.yaml`	ClusterIP or LoadBalancer
`ingress.yaml` (optional)	Routing configuration if ingress enabled
`configmap.yaml`	App-level non-sensitive config
`secret.yaml` (optional)	Mounted secrets via volumes
`hpa.yaml` (optional)	Horizontal Pod Autoscaler
`serviceaccount.yaml`	Identity-binding + RBAC link

🔖 Required Metadata Injection¶

Each manifest must include the following:

metadata:
  labels:
    trace_id: trace-ord-8128
    component_scope: Order
  annotations:
    blueprint_id: usecase-create-order
    agent_origin: infrastructure-engineer-agent
    factory_execution_id: exec-8128-xyz

✅ Helm Chart Expectations¶

File	Description
`Chart.yaml`	Includes name, version, appVersion, annotations
`values.yaml`	Accepts all configurable params (image, replicaCount, env, etc.)
`templates/*.yaml`	Mirrors YAML files above with `{{ .Values.* }}` injection

Must pass helm lint and be exportable as .tgz

✅ CI/CD Output Fragment (Optional)¶

# azure-pipelines.deploy.yaml
- stage: deploy
  jobs:
    - deployment: deploy_orderservice
      strategy:
        runOnce:
          deploy:
            steps:
              - task: HelmDeploy@0
                inputs:
                  chartPath: ./charts/orderservice
                  releaseName: orderservice-${{ environment }}

✅ Event: `InfrastructureGenerated`¶

Structured payload for event-driven pipelines:

{
  "event": "InfrastructureGenerated",
  "trace_id": "trace-ord-8128",
  "repo": "OrderService",
  "env": "staging",
  "files": [
    "deployment.yaml",
    "service.yaml",
    "hpa.yaml"
  ],
  "agent": "infrastructure-engineer-agent",
  "timestamp": "2025-05-07T23:19:41Z"
}

⚠️ Output Validation Criteria¶

Check	Rule
YAML valid	`kubectl apply --dry-run=client` must succeed
Helm lint	`helm lint` must pass if chart generated
Required metadata	`trace_id`, `blueprint_id`, `component_scope` must be present
Reproducibility	Inputs must produce same output deterministically
Policy-compliant	No unapproved ports, unscoped volumes, or missing securityContext

📂 Storage Targets¶

Artifact	Target
YAML / Helm	Git repo (via GitOps), local volume, or blob
Event	Event Grid, MCP Event Bus, or Redis Stream
Logs	Structured logs to Azure Monitor or Blob Archive

🧠 Summary¶

The Infrastructure Engineer Agent’s outputs are:

Trace-bound and audit-ready
Valid and secure
Usable by GitOps, DevOps, and CI pipelines
Extendable across environments and tenants

These outputs form the bridge between architecture and deployment in ConnectSoft’s AI Software Factory.

🧠 Memory¶

The Infrastructure Engineer Agent uses memory to:

Maintain execution context during a run
Track trace-to-blueprint relationships
Persist reusable overlays and templates
Avoid duplicate generation
Support auditability, rollback, and differential infra inspection

It combines short-term (in-memory) and long-term (persistent) memory strategies.

📌 Short-Term Memory (Execution Scope)¶

Cleared after task execution or timeout.

Field	Description
`trace_id`	Passed into all artifact generators
`execution_id`	Used for correlation across logs and events
`component_context`	Parsed blueprint + microservice metadata
`template_id`	Resolved from blueprint or default registry
`merged_overlay_config`	In-memory merged env + policy config
`generated_artifacts`	Pointer to YAML files and chart files during execution

Stored in Semantic Kernel context dictionary, accessible by all skills.

💾 Long-Term Memory (Persistent Store)¶

Stored in Redis, Cosmos DB, or vector database depending on configuration.

✅ a. Trace → Artifact Map¶

Tracks generated infrastructure per trace:

{
  "trace_id": "trace-user-812",
  "component": "UserService",
  "helm_chart": "charts/userservice/",
  "artifacts": ["deployment.yaml", "hpa.yaml"],
  "env": "qa",
  "timestamp": "2025-05-07T23:30:02Z"
}

Enables rebuilds, rollbacks, and trace validation.

✅ b. Template Registry Cache¶

Indexed by template_id and component_type
Includes hash of rendered output to detect drift or unintended changes

✅ c. Environment Overlays¶

Maps of tenant/environment-level overrides:
replicaCount, resources, ingress, otel_enabled, etc.

Used to auto-resolve policies without re-fetching from source.

✅ d. Helm Chart History¶

Stores published chart versions per component
Allows for diff, rollback, and GitOps pull syncing

✅ e. LLM/Embedding-Based Memory (Optional Phase)¶

Used for similarity searches on past blueprint-infra relationships:

Use	Benefit
"Show me infra for a similar billing service"	Aids in templating
"What pattern do other services in Finance follow?"	Promotes consistency
"Has this file changed since last run?"	Enables infra diffing

🧠 Memory Retention Policies¶

Type	Retention
Execution memory	1 task/session (ephemeral)
Trace map	90 days (extendable to 1 year)
Helm charts	Kept per version, pruned after 5 versions
OTEL and overlay cache	30 days or until invalidated by config update

🔐 Memory Security¶

All writes scoped to tenant/workspace
Infra output cannot be read by unrelated agents
LLM embedding vectors (if used) are anonymized by trace prefix, not full payload

🧠 Summary¶

The Infrastructure Engineer Agent’s memory system ensures that infrastructure generation is:

Traceable — every YAML or chart can be mapped to its originating blueprint
Reproducible — same inputs yield same output
Auditable — metadata, execution logs, and event history are retained
Composable — overlays and templates can be reused without recomputation

This makes it a state-aware and context-persistent agent in a stateless cloud environment.

✅ Validation¶

The Infrastructure Engineer Agent must ensure every generated artifact is:

✅ Schema-valid (e.g., Kubernetes syntax correctness)
✅ Traceable (has trace_id, blueprint_id)
✅ Policy-compliant (security, naming, resource limits)
✅ Deployable (won’t break CI/CD or GitOps workflows)

Validation is run before output is committed to Git, stored, or published as a Helm chart.

🧪 Validation Categories¶

🧾 1. Schema & Syntax Validation¶

Validator	Description
`kubectl apply --dry-run=client`	Ensures Kubernetes manifests can be parsed and applied
`helm lint`	Verifies Helm templates compile with current `values.yaml`
`yamllint`	Structural format and indentation rules

🔐 2. Security Compliance Checks¶

Check	Rule
`runAsNonRoot`	Must be true unless overridden by policy
`privileged`	Must be false
Secret mounts	Must use approved paths (e.g., `/mnt/secrets/<name>`)
No hostPath volumes	Unless explicitly approved via overlay

These are defined in reusable security-profile.yaml bundles injected by the Infrastructure Architect Agent.

🏷️ 3. Metadata Compliance¶

Requirement	Status
`trace_id` label	✅ Must be present in all resources
`blueprint_id` annotation	✅ Must be consistent
`component_scope` label	✅ Required for policy routing
`generated_by` label	Must be `infrastructure-engineer-agent`

📐 4. Resource Policy Checks¶

Rule	Example
Max replicas	Dev ≤ 3, Prod ≤ 100
CPU request/limit ratio	Must follow platform ratio (e.g., 1:2)
Liveness/readiness probes	Required for `microservice` types
Ingress hostname	Must match `*.connectsoft.dev` for dev/staging environments

🧩 5. Helm-Specific Validation (if enabled)¶

Rule	Description
Chart metadata valid	Name, version, appVersion present
Template rendering test	`helm template .` must not fail
Values coverage	All `.Values` variables must resolve (no undefined references)

🧰 6. Custom Policy Validators¶

Provided by the Security Architect or Infrastructure Architect agents, including:

Forbidden ports
Mandatory labels for observability
RuntimeClass enforcement

❌ 7. Failure Conditions and Actions¶

Failure Type	Action
Schema error	Abort generation, emit `InfraValidationFailed` event
Missing trace_id	Halt and escalate to HumanOpsAgent
Helm lint failure	Retry with fallback values (if applicable), else escalate
Policy violation	Block output and attach reason to event/log

📊 Validation Output Format¶

{
  "trace_id": "trace-infra-882",
  "component": "OrderService",
  "status": "failed",
  "errors": [
    "Missing trace_id in deployment.yaml",
    "securityContext.privileged=true is not allowed"
  ],
  "agent": "infrastructure-engineer-agent",
  "timestamp": "2025-05-07T23:42:50Z"
}

🧠 Summary¶

The Infrastructure Engineer Agent's validation logic ensures every artifact is:

Safe for production
Traceable to the source blueprint
Deployable across environments
Compliant with platform policies

It prevents accidental misconfigurations, enforces reproducibility, and guarantees that only verified infrastructure artifacts move downstream in the ConnectSoft software factory.

🔄 Retry & Correction Flow¶

The Infrastructure Engineer Agent must be:

✅ Resilient to transient issues (e.g., template load failure)
✅ Strict on structural violations (e.g., missing trace_id)
✅ Smart in recovery — retry only where safe and deterministic
✅ Transparent — emit structured failure events and notify appropriate agents

This ensures generation errors don’t silently fail or propagate broken infrastructure into CI/CD pipelines.

🔁 Retry Scenarios¶

✅ Automatically Retry On:¶

Failure Type	Strategy
Helm lint timeout	Retry up to 3 times with exponential backoff
Template load failure	Retry with fallback template or cached version
External dependency delay (e.g., config fetch)	Retry 1–2 times with backoff

🚫 Do Not Retry On:¶

Failure Type	Action
Missing `trace_id`	Abort and escalate
Policy violation (e.g., privileged container)	Halt and emit violation event
YAML syntax invalid	Emit validation error immediately
Invalid environment overlay	Notify Infra Architect Agent or HumanOpsAgent

🪜 Retry Strategy Logic¶

flowchart TD
    A[Generation Starts] --> B[Template Load]
    B --> C[Merge Overlays]
    C --> D[Render YAML]
    D --> E[Run Validation]
    E --> F{Validation Passes?}
    F -- Yes --> G[Emit Artifacts + Event]
    F -- No --> H{Retryable Failure?}
    H -- Yes --> D
    H -- No --> I[Emit Failure Event + Notify Ops]

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📘 Retry Policy Definition¶

retry_policy:
  max_attempts: 3
  backoff_strategy: exponential
  retryable_failures:
    - helm_lint_timeout
    - template_load_failure
    - blob_storage_timeout
  hard_failures:
    - trace_missing
    - policy_violation
    - yaml_schema_error

📣 Failure & Correction Events¶

🔴 `InfrastructureGenerationFailed`¶

Emitted when retries are exhausted or fatal errors occur.

{
  "event": "InfrastructureGenerationFailed",
  "trace_id": "trace-user-122",
  "component": "UserService",
  "reason": "missing trace_id in deployment.yaml",
  "attempts": 1,
  "status": "aborted",
  "timestamp": "2025-05-07T23:46:00Z"
}

Consumed by:

HumanOpsAgent
TechLeadAgent
SecurityArchitectAgent

🧑‍💼 Human Correction Pathways¶

Interface	Capability
MCP Dashboard	Inspect failed run, retry with override
DevOps Console	Push fixed template or policy
Trace Debugger	See blueprint–artifact–validation mapping
Manual PR	Allow fallback PR with partial infra only

🧠 Optional: Auto-Fix for Common Errors (Future)¶

Detect missing image and prompt Microservice Generator Agent
Suggest RBAC fixes for known access denied violations
Fallback to safe values.yaml on Helm render error

🧠 Summary¶

The Infrastructure Engineer Agent includes a deterministic, policy-bound retry mechanism with:

Smart backoff
Traceable events
Safe halting behavior
Human correction pathways

It ensures infrastructure generation is resilient, secure, and auditable, even in the presence of partial failures or policy violations.

🔗 Collaboration Interfaces¶

The Infrastructure Engineer Agent works in coordination with multiple upstream and downstream agents, exchanging trace-aware, versioned, and policy-constrained artifacts.

It operates mid-pipeline between design (architecture agents) and deployment (DevOps agents), emitting infrastructure that is:

Validated
Observable
Secure
Traceable

📥 Upstream Inputs From¶

Agent	Purpose
Microservice Generator Agent	Supplies component definition (`image`, `ports`, `env`, `transport`)
Infrastructure Architect Agent	Provides reusable templates, overlays, and policies
Security Architect Agent	Injects RBAC roles, identity binding rules, security context templates
Observability Agent (optional)	Supplies OTEL settings and tracing propagation fields
Blueprint/Trace Mapper Agent	Provides linkage to `trace_id`, `blueprint_id`, `execution_id`

📤 Downstream Consumers¶

Agent	Purpose
DevOps Agent	Consumes YAML and Helm for CI/CD deployment pipeline
HumanOpsAgent	Intervenes in case of validation or generation failure
Security Architect Agent	Post-verifies policy compliance of security contexts
Observability Agent	Parses OTEL-configured manifests to wire tracing
Documentation Agent	Pulls metadata for infra overview documentation (env, chart, ports, identity)

🔁 Event-Based Communication (MCP)¶

Event	Trigger	Consumed By
`InfrastructureGenerated`	On successful artifact generation	DevOps Agent, Observability Agent
`HelmChartReady`	Helm package built	DevOps Agent
`InfrastructureGenerationFailed`	YAML/Helm/validation failure	HumanOpsAgent, TechLeadAgent
`TraceLinkValidated`	Trace/blueprint IDs resolved and matched	Trace Auditor or Doc Generator

🧠 Semantic Kernel Context Passing¶

Via shared execution memory:

Passes validated environment overlays downstream
Makes reusable config blocks accessible to related agents (e.g., PR generator, deployment renderer)
Retains shared trace execution context (execution_id, component_scope)

📘 Git and Storage Interfaces¶

Target	Use
GitOps Repository	Push generated artifacts (YAML, Helm) with trace-annotated commits
Blob Storage	Archive versioned Helm charts and manifest bundles
Azure DevOps Pipelines	Feed `azure-pipelines.deploy.yaml` to deploy stages
Helm Registry (optional)	Publish charts for reuse in multi-region setups

🔒 Security Interfaces¶

Agent	Integration
`Security Architect Agent`	Fetches/validates security policies, injects identities
`Vault Resolver Agent` (future)	Mounts secret references and encrypted configurations
`RBAC Plan Generator Agent` (optional)	Resolves RBAC scopes per service role pattern (e.g., reader, publisher)

🤝 Collaboration Sequence Diagram¶

sequenceDiagram
    MicroserviceGen->>InfraEng: Component Definition + Trace Metadata
    InfraArch->>InfraEng: Template + Overlay Profiles
    SecurityArch->>InfraEng: RBAC + Security Context
    InfraEng->>DevOpsAgent: Emit InfrastructureGenerated Event
    InfraEng->>ObservabilityAgent: OTEL-enabled Manifest Emitted
    InfraEng->>HumanOpsAgent: (On Failure) Emit InfrastructureGenerationFailed

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🧠 Summary¶

The Infrastructure Engineer Agent is a collaborative orchestrator of infrastructure generation — integrating with architecture, security, observability, DevOps, and traceability pipelines.

It enables fully connected, end-to-end traceable infrastructure across the entire ConnectSoft AI Software Factory, ensuring:

Deployment readiness
Auditability
Compliance
Automation safety

📈 Observability Hooks¶

The agent is fully instrumented using OpenTelemetry and emits structured logs, spans, and events to support debugging, analysis, SLA monitoring, and forensic auditing.

✅ 1. OpenTelemetry Spans¶

Span Name	Description
`infragen.start`	Start of infrastructure generation task
`infragen.template.load`	Template resolution and overlay merging
`infragen.render.yaml`	Rendering of YAML files
`infragen.helm.build`	Helm chart assembly (if enabled)
`infragen.validate`	Runs validation and schema checks
`infragen.complete`	Emission of artifacts and success event

✅ 2. Structured Logging (JSON)¶

Every step is logged with contextual metadata:

{
  "agent": "infrastructure-engineer-agent",
  "trace_id": "trace-billing-810",
  "component": "BillingService",
  "template_id": "helm-v2",
  "result": "success",
  "files_generated": ["deployment.yaml", "hpa.yaml"],
  "execution_id": "exec-810a",
  "timestamp": "2025-05-07T23:53:24Z"
}

Logs go to:

Azure Monitor
Central blob log archive
Optional real-time telemetry bus (e.g., Redis Stream)

✅ 3. Lifecycle Events¶

Event	Used For
`InfrastructureGenerated`	Signals artifact readiness
`HelmChartReady`	Indicates chart packaging complete
`InfrastructureGenerationFailed`	Alerts failure (validation, trace, etc.)
`TraceLinkValidated` (optional)	Confirms successful blueprint ↔ artifact linkage

🧑‍💼 Human Intervention Hooks¶

When the agent encounters non-recoverable failures, it halts execution and notifies human operators via structured escalation channels.

🚨 Escalation Triggers¶

Trigger	Action
Missing `trace_id`	Abort and emit `InfrastructureGenerationFailed`
Template render error	Log and halt; offer fix or override via MCP dashboard
Helm lint failure (non-retryable)	Alert `HumanOpsAgent`
Policy violation	Pass to `Security Architect Agent` or `TechLeadAgent`

👥 HumanOps Interfaces¶

Tool	Capability
MCP Ops Dashboard	View failed executions, retry with override
Slack / Teams	Alert on failure with error summary
GitHub PR Comments (optional)	Auto-comment on PR if linked to infra failure
Manual Trigger API	Allow DevOps team to regenerate infrastructure with fixed values or reconfigured overlays

🧠 Manual Retry Flow¶

sequenceDiagram
    InfraEng->>ValidationService: Run validation
    ValidationService-->>InfraEng: Failure (policy violation)
    InfraEng->>HumanOpsAgent: Emit InfrastructureGenerationFailed
    HumanOpsAgent->>InfraEng: Retry with override via dashboard or CLI
    InfraEng->>DevOpsAgent: Emit updated InfrastructureGenerated event

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✅ Observability Compliance¶

Feature	Enforced?
OTEL-compliant spans	✅
Span correlation to execution_id	✅
Structured logs with trace_id	✅
Event-driven pipeline integration	✅
Manual intervention hooks	✅
SLA dashboard support	✅

🧠 Summary¶

The Infrastructure Engineer Agent is observability-native and human-aware. It provides:

Full traceability from blueprint to YAML
Real-time visibility into execution lifecycle
Intelligent failure handling and escalation
Clear separation between recoverable vs. terminal errors
A feedback loop for continuous improvement of templates and overlays

This ensures that infrastructure generation in the ConnectSoft platform is safe, transparent, auditable, and controllable — even when powered by autonomous agents.

📊 Diagram: Infrastructure Engineer Agent in Context¶

flowchart TD

  subgraph Architecture
    A1[Vision Architect Agent]
    A2[Enterprise Architect Agent]
    A3[Application Architect Agent]
  end

  subgraph Engineering
    B1[Microservice Generator Agent]
    B2[Infrastructure Engineer Agent]
    B3[Pull Request Creator Agent]
  end

  subgraph Compliance
    C1[Security Architect Agent]
    C2[Observability Agent]
    C3[Infrastructure Architect Agent]
  end

  subgraph Deployment
    D1[DevOps Agent]
    D2[CI/CD Pipelines]
  end

  A1 --> A2 --> A3 --> B1
  B1 --> B2
  C3 --> B2
  C1 --> B2
  C2 --> B2

  B2 --> B3
  B2 --> D1
  B2 --> C2
  B2 --> C1

  D1 --> D2
  B3 --> D1

  click B2 "https://connectsoft.ai/docs/agents/infrastructure-engineer-agent" "View Agent Spec"

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🔍 Explanation of Flow¶

Stage	Role
Architecture Agents	Generate domain models, service boundaries, and blueprint metadata
Microservice Generator Agent	Creates code, handler scaffolds, DTOs
Infrastructure Engineer Agent (🟢 This Agent)	Generates Kubernetes YAML, Helm charts, RBAC, OTEL, CI/CD fragments
Security & Observability Agents	Inject security context, tracing, validation rules
Pull Request Creator Agent	Wraps generated code and infra into a structured, traceable PR
DevOps Agent	Deploys Helm charts and YAML via pipelines
CI/CD Pipelines	Executes automated deploy, verify, release

🧠 Infrastructure Engineer Agent Specification¶

🎯 Agent Purpose¶

🧭 Strategic Role in the Factory¶

🔄 How It Differs from Infrastructure Architect Agent¶

🧱 What It Builds¶

🔍 Purpose Summary¶

🧩 Alignment with ConnectSoft Principles¶

🧠 Summary¶

📌 Core Responsibilities¶

🔧 Functional Responsibilities¶

✅ 1. Generate Kubernetes Resource Definitions¶

✅ 2. Emit Helm Charts¶

✅ 3. Inject Observability Configuration¶

✅ 4. Generate Azure DevOps CI/CD Deployment YAML¶

✅ 5. Embed Traceability Metadata¶

✅ 6. Apply Platform Security Requirements¶

✅ 7. Environment-Specific Variants¶

✅ 8. Publish Manifest & Helm Events¶

✅ 9. Store and Version Output¶

✅ 10. Support Future IaC Backends¶

📌 Summary Table¶

🧠 Summary¶

📥 Inputs¶

🔑 Primary Inputs¶

✅ 1. Trace Metadata¶

✅ 2. Component Runtime Definition¶

✅ 3. Deployment Policy Overlay¶

✅ 4. Template References¶

✅ 5. Observability Injection Parameters¶

✅ 6. Security Baseline Profile¶

✅ 7. Environment Selector¶

📂 Optional Inputs¶

🧠 Example Consolidated Input Bundle¶

🧠 Summary¶

📤 Outputs¶

🧾 Output Categories¶

✅ 1. Kubernetes YAML Manifests¶

✅ 2. Helm Chart Bundle¶

🧠 Chart.yaml includes:¶

✅ 3. OpenTelemetry Configuration (Optional)¶

✅ 4. Azure DevOps CI/CD Deployment YAML Block¶

✅ 5. Event: InfrastructureGenerated¶

✅ 6. Artifact Storage Locations¶

🧠 Summary¶

📚 Knowledge Base¶

📘 Core Knowledge Categories¶

✅ 1. Infrastructure Templates¶

✅ 2. Observability Injection Blocks¶

✅ 3. Security Enforcement Snippets¶

✅ 4. Scaling and Environment Overlays¶

✅ 5. Naming and Repo Conventions¶

✅ 6. Reusable Metadata Definitions¶

✅ 7. Policy Definitions (from Infra Architect Agent)¶

🗂️ Knowledge Storage Options¶

🧠 Summary¶

🔄 Process Flow¶

🪜 Step-by-Step Breakdown¶

✅ Step 1: Input Ingestion¶

✅ Step 2: Resolve Configuration Context¶

✅ Step 3: Load and Merge Templates¶

✅ Step 4: Render Infrastructure Artifacts¶

✅ Step 5: Inject Traceability Metadata¶

✅ Step 6: Helm Chart Assembly (Optional)¶

✅ Step 7: Validate Outputs¶

✅ Step 8: Emit Artifacts and Events¶

📦 Parallel Paths (Optional)¶

📋 Process Guardrails¶

🧠 Summary¶

🧩 Skills & Kernel Functions¶

🛠️ Core Skills & Functions¶

🔁 Example SK Function Flow¶

🔧 Semantic Kernel Planner Composition¶

🧠 AI-Powered Code Synthesis (Optional Phase)¶

🔐 Security-Scoped Skill Usage¶

🧠 Summary¶

🧰 Core Technology Stack¶

⚙️ Platform Technologies¶

📦 Infrastructure-Specific Tools¶

📘 Agent Libraries & Skills¶

🔐 Security & Policy Enforcement¶

🧠 `Chart.yaml` includes:¶

✅ 5. Event: `InfrastructureGenerated`¶

✅ Event: `InfrastructureGenerated`¶

🔴 `InfrastructureGenerationFailed`¶