🧠 DevOps Engineer Agent Specification¶

🎯 Core Purpose¶

The DevOps Engineer Agent is the automation orchestrator and delivery enabler within the ConnectSoft AI Software Factory. Its job is to transform infrastructure, service, and security artifacts into automated, observable, traceable CI/CD pipelines that can deploy any generated software product — microservice, API, background job, UI app, or system component — into a compliant, cloud-native environment.

It turns code and configs into running systems — securely, repeatedly, and autonomously.

📌 Position in the Platform¶

The DevOps Engineer Agent operates at the intersection of engineering outputs and deployment pipelines, ensuring that all generated artifacts become deployable units, with health probes, rollout strategies, approvals, and secrets management pre-integrated.

🧭 Execution Layer Role¶

Factory Layer	Agent Role
Architecture	Consumes infrastructure structure and security rules
Engineering	Coordinates with Infra, Security, PR, and Build Agents
DevOps & Delivery	Owns CI/CD generation, deployment rollout, multi-stage strategies
Orchestration	Triggered as part of project lifecycle or component upgrade flow
Audit & Observability	Emits deployment metadata, compliance events, OTEL spans

🛠️ Responsibilities at a Glance¶

🔧 Generate Azure DevOps pipeline YAMLs, fully linked to trace_id and environments
🔐 Integrate with secrets stores and config maps
🚦 Insert environment-specific rollout gates (e.g., manual approval, auto-rollback)
📡 Emit observability metadata (for deployment dashboards, failure diagnostics)
🧪 Inject hooks for post-deploy tests or validation pipelines
💬 Communicate with other agents to embed security, RBAC, health check, and tracing logic into deployment steps

📊 Position in Execution Flow¶

flowchart TD

  subgraph Engineering
    A[Infrastructure Engineer Agent]
    B[Security Engineer Agent]
    C[Pull Request Creator Agent]
  end

  subgraph DevOps
    D[DevOps Engineer Agent]
  end

  subgraph Deployment
    E[CI/CD Pipelines]
    F[Observability Agent]
    G[QA Agent]
  end

  A --> D
  B --> D
  C --> D
  D --> E
  D --> F
  D --> G

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

🧩 Strategic Importance¶

Bridges static generation with live deployment
Executes automation without human handoff
Ties deployments back to trace_id, security_policy_id, and blueprint
Supports multi-stage promotion (dev → staging → prod)
Enables rollback and versioned infrastructure

✅ Summary¶

The DevOps Engineer Agent is the automated DevOps pipeline composer in the AI Software Factory. It connects the dots between infrastructure, configuration, observability, and automation, enabling:

⏱️ Fast delivery
🔒 Secure deployments
📦 Repeatable promotion
🔍 Traceable execution

This agent ensures that every component is production-ready from the moment it's generated.

📌 Responsibilities¶

The DevOps Engineer Agent is tasked with transforming service blueprints, infrastructure artifacts, and deployment requirements into production-grade CI/CD pipeline automation and runtime integration points.

Its responsibilities span both pipeline composition and deployment execution readiness, including the injection of secrets, validation gates, rollout strategies, and observability hooks.

🔧 Key Responsibilities¶

✅ 1. Generate CI/CD Pipeline YAML¶

Creates Azure DevOps multi-stage pipelines or GitHub Actions workflows
Stages include:
Build
Package
Security scan
Deploy to dev/staging/prod
Post-deploy validation

Fully parameterized and trace-linked via trace_id and execution_id

✅ 2. Manage Deployment Environments¶

Injects environment-specific configurations:
Replica counts
Feature flags
Deployment strategy (rolling, canary, blue/green)
Namespace isolation

Extracted from policy overlays provided by Infrastructure and Security agents

✅ 3. Integrate Secrets and Vaults¶

Mount secrets from:
Azure Key Vault
Kubernetes secrets
Sealed secrets
Injects into:
Deployment YAML
Helm values
CI pipeline env steps

✅ 4. Insert Rollout Gates & Manual Approvals¶

Supports policy-driven controls for:
Promotion between stages
Manual approval workflows
Canary or % rollout
Auto-rollback on failure detection

Logic based on environment type (staging, prod) and trace metadata

✅ 5. Emit Deployment Metadata¶

Writes:
deployment-report.json
Deployment spans (devops.deploy.start, .validate, .complete)
Rollout status logs for dashboards

✅ 6. Post-Deployment Validation & Hooks¶

Triggers:
Health checks
Canary verifier jobs
Contract tests (e.g., TestAgent or ConsumerContractValidatorAgent)
Alert simulations

✅ 7. Collaborate With Other Agents¶

Reads:
deployment.yaml, Chart.yaml (from Infra Agent)
security_policy_id, RBAC bindings (from Security Agent)
PR artifacts (from Pull Request Creator Agent)
Outputs to:
Observability Agent (for rollout tracing)
QA/Test Agent (for post-deploy verification)

✅ 8. Publish CI/CD Pipelines to Source Control¶

Commits generated pipelines to GitOps repo:
pipelines/service-name/azure-pipelines.yml
Includes trace metadata and compliance tags

✅ 9. Trigger Execution via MCP or External Signal¶

Once published, the pipeline may be triggered by:
MCP Event: PullRequestMerged
Manual UI command
Downstream AI agent signal (e.g., AutoPromoterAgent)

🧩 Output-Linked Responsibilities¶

Output Type	Responsibility
`azure-pipelines.yml`	Generated and updated for each service
`deployment.yaml`	Receives injected rollout strategy
`infra-events.json`	Emitted to Observability Agent
`manual-approvals.yaml`	Used by release pipeline approvers

🧠 Summary¶

The DevOps Engineer Agent owns the automated delivery lifecycle, ensuring every generated component:

🚀 Ships securely
✅ Passes through traceable validation
🔐 Respects secrets and runtime policies
🧭 Is promoted across environments with full control and observability

It brings the execution layer to life — making build, deploy, and operate phases autonomous, compliant, and trace-first.

📥 Input¶

The DevOps Engineer Agent consumes a rich, traceable set of inputs from engineering, infrastructure, security, and architecture layers, as well as orchestration triggers.

All inputs are structured, linked to execution metadata (trace_id, blueprint_id, execution_id), and environment-aware (dev, qa, staging, prod).

🔑 Primary Inputs¶

✅ 1. Trace Metadata¶

trace_id: trace-orders-1098
blueprint_id: usecase-submit-order
execution_id: exec-orders-1098-b
component_scope: Order

Used to inject into:

Pipeline YAML headers
Logs and spans
Emitted events

✅ 2. Infrastructure Artifacts¶

From the Infrastructure Engineer Agent:

Artifact	Purpose
`deployment.yaml`	Defines replicas, containers, probes
`service.yaml`, `ingress.yaml`	Needed for deployment stages
`Chart.yaml`, `values.yaml`	Helm-based deploys
`hpa.yaml`, `configmap.yaml`	Environment runtime configs

✅ 3. Security Enforcement Data¶

From the Security Engineer Agent:

security_policy_id: sec-profile-orders
rbac_roles: [publisher, db-reader]
vault_mounts:
  - name: db-conn
    source: azure-keyvault
    mountPath: /mnt/secrets/db

Used to:

Inject RBAC references into pipeline
Mount secrets securely into runtime
Annotate rollout stages with policy context

✅ 4. Deployment Environment Profile¶

From Infra Architect or Orchestrator Agent:

environments:
  dev:
    approval: none
    rollout: immediate
    observability: basic
  staging:
    approval: manual
    rollout: canary
    observability: full
  prod:
    approval: manual
    rollout: blue-green
    alerts: true

Defines stage logic for promotion, health gates, rollback, etc.

✅ 5. Post-Deploy Test Configuration¶

From QA Agent, Test Generator Agent, or defined in blueprint:

post_deploy_tests:
  - type: healthcheck
  - type: canary-verification
  - type: loadtest

Each becomes a pipeline step or job dependency.

✅ 6. Repository Context¶

From Pull Request Creator Agent or MCP Trigger:

repo: orderservice
branch: main
pipeline_path: pipelines/orderservice/
auto_trigger: true

Determines where the pipeline YAML should be committed or updated.

✅ 7. Orchestration Trigger¶

Agent is activated by:

Trigger	Source
`PullRequestMerged`	Git/MCP
`ComponentAssembled`	Orchestration Agent
`AutoPromoterAgent`	Autonomous promotion logic

Trigger context defines execution window and environment target.

🧩 Optional Inputs¶

Input	Use
`custom_pipeline_overrides.yaml`	For tenant-specific pipeline customization
`previous_execution_state`	To support delta diffs or targeted redeploys
`canary_config.json`	Canary rules, thresholds, rollback conditions

📘 Example Consolidated Input Context¶

trace_id: trace-orders-1098
security_policy_id: sec-profile-orders
environment: staging
repo: orderservice
deployment_file: deployment.yaml
post_deploy_tests: [healthcheck, loadtest]
vaults: [auth-secret, db-conn]
approval_required: true

🧠 Summary¶

The DevOps Engineer Agent consumes a comprehensive set of trace-aware, policy-driven inputs, enabling it to:

Compose CI/CD pipelines with full execution lineage
Apply deployment controls, vault integration, and validation gates
Ensure automation is secure, environment-specific, and reproducible

Every pipeline starts from blueprint + trace + policy — nothing is guessed, everything is tracked.

📤 Outputs¶

The DevOps Engineer Agent emits deployable automation assets, traceable metadata, and lifecycle events. All outputs are structured, compliant with ConnectSoft platform standards, and designed to run autonomously with observability and policy alignment.

✅ Primary Outputs¶

1️⃣ CI/CD Pipeline Definition¶

Azure DevOps (default):¶

# azure-pipelines.yml
trigger:
  branches:
    include:
      - main
stages:
  - stage: Build
    jobs:
      - job: BuildAndPush
        steps:
          - script: dotnet build ...
  - stage: Deploy_Staging
    condition: succeeded()
    jobs:
      - deployment: DeployChart
        environment: staging
        strategy:
          runOnce:
            deploy:
              steps:
                - task: HelmDeploy@0
                  inputs:
                    chartPath: charts/orderservice

Variants exist for GitHub Actions or Jenkins (via template registry).

2️⃣ Post-Deploy Test Triggers¶

- stage: PostDeployTests
  dependsOn: Deploy_Staging
  jobs:
    - job: CanaryValidation
      steps:
        - script: ./scripts/verify-canary.sh

3️⃣ Deployment Strategy Patches¶

rollout:
  strategy: canary
  thresholds:
    maxUnavailable: 1
    maxSurge: 2
approval:
  manual: true

Injected into Helm values.yaml or passed as pipeline variables.

4️⃣ Secrets + Vault Mapping Blocks¶

variables:
  - group: orderservice-secrets
  - name: VAULT_DB_CONN
    value: $(auth-secret)

Also generates ConfigMap / SecretRef injection into manifests when needed.

5️⃣ Deployment Events¶

✅ `PipelineGenerated`¶

{
  "event": "PipelineGenerated",
  "trace_id": "trace-orders-1098",
  "pipeline_path": "pipelines/orderservice/azure-pipelines.yml",
  "policy": "sec-profile-orders",
  "environment": "staging",
  "status": "ready",
  "timestamp": "2025-05-08T00:20:01Z"
}

🔁 `PipelineRevised` (if existing pipeline updated)¶

Includes a diff summary of previous vs. updated structure.

6️⃣ Deployment Metadata Snapshot¶

{
  "deployment_config": {
    "component": "OrderService",
    "trace_id": "trace-orders-1098",
    "rollout_strategy": "canary",
    "vault_mounts": ["/mnt/secrets/db"],
    "rbac": ["publisher", "reader"],
    "env": "staging"
  }
}

Used by:

Observability dashboards
HumanOpsAgent (approval visibility)
Rollback/restore modules

7️⃣ GitOps Commit (Optional)¶

File	Location
`azure-pipelines.yml`	`/pipelines/orderservice/`
`manual-approvals.yaml`	`/pipelines/_meta/`
`deployment-snapshot.json`	`/artifacts/deployment-reports/`

Pushes pipeline output back into the project Git repo (with trace annotations in commit message).

📊 Observability Hooks¶

Output	Description
OTEL spans	`devops.pipeline.generated`, `deploy.started`, `deploy.completed`
Structured logs	Pipeline creation, stage status, trace cross-link
Metrics	Time-to-deploy, rollback rate, approval duration

🧠 Summary¶

The DevOps Engineer Agent outputs enable full-stack, secure, traceable software delivery:

✅ CI/CD pipelines (with secrets, security, health checks)
🧩 Post-deploy tests and gate integrations
🔁 Event signals for system orchestration
📊 Metadata for observability and audit

It turns infrastructure into live, governed deployment — fully automated, never ad-hoc.

📚 Knowledge Base¶

The DevOps Engineer Agent is powered by a curated and versioned DevOps knowledge base, which includes:

CI/CD pipeline templates (Azure DevOps, GitHub Actions, etc.)
Deployment strategies (e.g., rolling, canary, blue-green)
Secret injection models
Helm and YAML scaffolds
Validation patterns and fallback recovery blocks
Agent-to-pipeline binding models (trace, security, environment)

This allows it to generate fully compliant pipelines without ad-hoc scripting.

🧩 Key Knowledge Artifacts¶

✅ 1. CI/CD Pipeline Templates¶

Type	Location
Azure DevOps multi-stage	`templates/azure-pipeline-multi-env.yml`
GitHub Actions workflows	`templates/github-pipeline-workflow.yml`
Modular task blocks	`tasks/helm-deploy.yml`, `tasks/dotnet-build.yml`
Approval templates	`meta/manual-approval.yaml`

Each is parameterized with:

component_name
target_environment
trace_id
vault_group
deployment_strategy

✅ 2. Deployment Strategy Profiles¶

Used to configure rollout behavior and environment staging:

staging:
  strategy: canary
  healthcheck: true
  approval: true
prod:
  strategy: blue-green
  auto_rollback: true
  maxSurge: 2

These are retrieved from deployment-policy.yaml aligned with the current trace.

✅ 3. Secret Injection Patterns¶

Strategy	Output
`env`	Pipelines inject `variables: group:` and env maps
`volumeMount`	Used in Helm overrides + `deployment.yaml`
`vault-agent-sidecar`	Rendered as an optional init container block

✅ 4. Trace Metadata Blocks¶

Templates to embed metadata into:

Pipeline YAML headers
Observability tags
Git commits
Event payloads

metadata:
  trace_id: trace-auth-778
  blueprint_id: usecase-token-grant
  execution_id: exec-778d
  agent_origin: devops-engineer-agent

✅ 5. Post-Deploy Validation Templates¶

Library of reusable test hooks:

Health probes (/healthz)
Load test injectors
Canary checkers
Contract test triggers

Added conditionally based on post_deploy_tests[] input.

✅ 6. Rollback & Promotion Policies¶

Auto-rollback on OTEL span failure
Canary metrics integration with alert pipelines
Promotion rules to next environment on success

auto_promote: true
rollback_on_failure: true
promotion_targets:
  - staging
  - prod

✅ 7. Environment Gate Rules¶

Defined per-environment in overlay:

dev:
  approval: none
staging:
  approval: manual
  observability: full
prod:
  approval: required
  rollout: blue-green

Used to:

Inject pre-deploy or manual intervention stages
Emit metadata for trace-based dashboards

📦 Knowledge Base Storage¶

Store	Purpose
Blob/Git (pipeline templates)	Source-controlled, versioned templates
Redis/CosmosDB (overlays + memory)	Policy lookups, last-used strategy
Semantic Kernel Memory	Active in-session context
MCP Registry (global overlays)	Stores defaults across tenant/workspace hierarchy

🧠 Summary¶

The DevOps Engineer Agent’s knowledge base enables:

🔁 Consistent, reusable CI/CD generation
🔐 Secure, secrets-aware deployments
📊 Trace-annotated automation
🧠 Policy-aligned execution across any environment or blueprint

It transforms DevOps intelligence into a fully autonomous decision engine, powering hands-free deployment at enterprise scale.

🔄 Process Flow¶

flowchart TD
    A[Trigger Received (PullRequestMerged / Orchestration Signal)] --> B[Load Component Metadata + Trace Context]
    B --> C[Resolve Security + Environment Overlays]
    C --> D[Select and Load Pipeline Template]
    D --> E[Render Pipeline with Component Variables]
    E --> F[Validate Pipeline Syntax + Security Compliance]
    F --> G{Validation Passes?}
    G -- Yes --> H[Emit Pipeline + Deployment Snapshot + Events]
    G -- No --> I[Retry or Emit Violation + Notify HumanOps]

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

🪜 Step-by-Step Breakdown¶

✅ Step 1: Trigger Reception¶

Activated by:

PullRequestMerged (from GitHub or DevOps)
ComponentAssembled event
Manual retry via MCP or dashboard
AutoPromoterAgent (for cross-environment promotion)

✅ Step 2: Context Aggregation¶

Extract:
trace_id, blueprint_id, execution_id
component_name, repo, branch
security_policy_id, rbac_roles
vault mounts, environment overlays

✅ Step 3: Pipeline Template Resolution¶

Load:
Appropriate azure-pipelines.yml or GitHub Actions template
Merge overlay for target_environment
Apply policy for rollout strategy and approval gates

✅ Step 4: Dynamic Rendering¶

Inject variables:
trace_id, agent_origin, repo, branch, vault_refs
Rollout strategy, RBAC checks, post-deploy tests
Output:
Final pipeline YAML (multi-stage)
Optional manual-approvals.yaml, deployment-snapshot.json

✅ Step 5: Validation¶

YAML schema validation (Azure/GitHub)
Helm render check (if required)
RBAC and secrets reference sanity check
Check for required trace + metadata fields

✅ Step 6: Emission¶

Save to:
Git repo (pipelines/{component}/)
Artifact storage (for backup or trace logs)
Emit:
PipelineGenerated event
Deployment metadata block
OTEL span devops.pipeline.generated

📌 Conditional Flow Variants¶

Condition	Flow
`approval_required = true`	Inject manual approval stage before deploy
`target_environment = prod`	Use hardened release strategy (e.g., blue-green)
`post_deploy_tests defined`	Append testing stage with probes and test scripts
`vault_strategy = sidecar`	Inject init container config to deployment stage

🔁 Re-trigger Scenarios¶

Scenario	Trigger
Source changed	PR merge triggers full regeneration
Policy updated	Orchestration sends `RerunPipelineWithPolicyChange`
Human override	`retry-security-agent` from UI or CLI

📘 Audit Flow Snapshot¶

Every run is recorded with:

trace_id, execution_id, security_policy_id
Time-to-generate, validation success/failure
Output hash for audit diffing
User-trigger info (if manually triggered)

🧠 Summary¶

The DevOps Engineer Agent’s process flow is:

🧱 Modular and reusable
🔄 Trigger-driven and stateful
🔐 Secure and policy-bound
📡 Trace-first and event-aware

It delivers automated deployment infrastructure that is safe, scalable, and observable — a core capability in ConnectSoft’s agentic software factory.

🧩 Skills and Kernel Functions¶

The DevOps Engineer Agent uses a set of reusable Semantic Kernel (SK) skills and custom pipeline logic functions to:

Load and render CI/CD templates
Inject traceable metadata and policy overlays
Validate YAML, secret maps, and strategy declarations
Emit fully structured pipelines and lifecycle events
Auto-correct common config issues or retry failed renders

Each skill operates within a policy-bound execution graph, with step dependencies resolved by the SK planner.

🔧 Core Skills & Functions¶

Skill	Purpose
`TemplateResolverSkill`	Load pipeline YAML from registry (Azure DevOps, GitHub Actions, etc.)
`OverlayMergeSkill`	Apply environment-specific pipeline overlays (e.g., approval, rollout)
`PipelineRendererSkill`	Inject variables into CI/CD templates and produce the final pipeline
`TraceMetadataInjectorSkill`	Add `trace_id`, `blueprint_id`, `agent_origin`, etc. to all outputs
`SecretsMapperSkill`	Inject vault references into deployment and pipeline steps
`StrategyComposerSkill`	Determine rollout strategy (canary, blue-green) based on environment and policy
`PostDeployTestHookSkill`	Append test jobs for health, load, canary checks
`PipelineValidatorSkill`	Lint and dry-run YAML to ensure structural and security correctness
`ArtifactEmitterSkill`	Emit the pipeline YAML to Git repo or blob + fire `PipelineGenerated` event

🧠 Example Skill Chain (Planner Flow)¶

→ TemplateResolverSkill.Load("azure-multi-env-v3")
→ OverlayMergeSkill.Merge(environment="staging")
→ PipelineRendererSkill.Render(trace_id, vault_refs, strategy)
→ SecretsMapperSkill.Inject(secret_mounts)
→ TraceMetadataInjectorSkill.Apply()
→ PostDeployTestHookSkill.Append(healthcheck)
→ PipelineValidatorSkill.Validate()
→ ArtifactEmitterSkill.Emit("pipelines/orderservice/")
→ EventEmitterSkill.Emit("PipelineGenerated")

🤖 AI-Enhanced Functions (Optional)¶

Used for planning or conditional prompts:

Function	Use
`RolloutStrategyRecommender`	Suggest rollout type based on component criticality or traffic pattern
`PipelineDiffSummarizer`	Summarize differences in pipeline revisions for PR commentary
`ApprovalStageGenerator`	Generates dynamic approval gates for high-risk components or tenants

These are LLM-assisted, only activated with adequate trace confidence or blueprint classification.

📌 Execution Safety Guards¶

Guard	Rule
Missing `trace_id`	Block rendering and emit error
Unscoped vault mount	Retry with fallback strategy or escalate
Broken YAML	Log, auto-fix if safe, or fail with `PipelineGenerationFailed`
Empty deploy stage	Detected and blocked before emit

🧠 Summary¶

The DevOps Engineer Agent’s skill set enables:

⚙️ Composable pipeline generation
🔁 Context-aware strategy injection
🔐 Secure secrets handling
📦 Event-driven artifact emission
📡 Trace-integrated delivery pipelines

Every skill is part of a modular, deterministic execution graph, ensuring predictable, compliant, and reproducible DevOps automation.

🧰 Core Technology Stack¶

Layer	Technology	Role
Runtime Host	.NET 8 + Semantic Kernel	Agent execution and planning engine
LLM Backend	Azure OpenAI (GPT-4 Turbo)	Prompt-based strategy selection and skill composition
Agent Orchestration	MCP Server	Registers agent, executes on trigger or signal
Memory/Cache	Redis or Cosmos DB	Pipeline overlays, last executions, approvals
Artifact Repo	GitHub / Azure Repos	CI/CD pipeline commit location
Event Transport	Event Grid or MCP Message Bus	Emits lifecycle and deployment events

🔧 DevOps-Specific Tooling¶

Tool	Use
Azure DevOps Pipelines	Default CI/CD executor (YAML-based multi-stage pipelines)
GitHub Actions	Optional pipeline backend for GitHub-managed repos
Bicep / ARM	Used in optional infrastructure provisioning phase
kubectl	For pipeline dry-runs and validation of target manifests
Helm	Package manager for deployments and chart validation
YAML Lint + Schema Validator	Ensures output CI/CD files are valid pre-commit
Vault SDKs	Securely reference Key Vault or Kubernetes secrets for runtime injection

📡 Observability Stack¶

Tool	Function
OpenTelemetry SDK	Emits spans such as `devops.pipeline.generated`, `deploy.started`, `deploy.failed`
Azure Monitor	View pipeline execution metrics and success/failure rates
Grafana Dashboards	Render visual views of rollout status, pipeline SLOs, approval duration
Loki or Blob Logging	Persist all rendered YAMLs, pipeline diffs, and trace metadata for audit

🔐 Security Integrations¶

Feature	Mechanism
Secrets injection	Via `vault_mounts`, variable groups, or init container
RBAC/Access control	Policy-driven enforcement in pipeline blocks (`allow`, `require`, `restrict`)
Agent identity	All commits and emissions are tagged with `agent_origin: devops-engineer-agent`
Deployment validation	Block rollout of pipelines lacking metadata, health checks, or secure vaults

📘 Template + Artifact Registry¶

Asset	Location
`azure-pipeline-default.yml`	Git-based template registry
`rollout-configs.yaml`	Per-environment override definitions
`manual-approvals.yaml`	Optional governance gate per policy
`deployment-snapshot.json`	Stored in blob or committed alongside pipeline for audit purposes

🔁 Trigger Interfaces¶

Trigger	Description
`PullRequestMerged`	From MCP, GitHub, or Azure DevOps hook
`PipelineRevisionRequested`	Manually or from upstream agent
`AutoPromoterAgent`	Signals readiness for next-environment promotion
`ComponentAssembled`	Sent by orchestration layer to begin CI/CD generation phase

🧱 Development + Extension Patterns¶

Scenario	Mechanism
Add new deployment backend	Inject new template into registry + bind to SK plan
Change secret mount strategy	Override overlay and re-trigger pipeline
Add new testing stage	Update `PostDeployTestHookSkill` with strategy rules
Policy profile migration	Agent reads from `security_policy_id` version mappings and emits diff event if drift detected

🧠 Summary¶

The DevOps Engineer Agent’s technology foundation is:

☁️ Cloud-native (Azure-first)
🧠 Agent-orchestrated and LLM-assisted
🔄 Template-driven, policy-aware, and environment-specific
🔍 Fully observable, trace-bound, and auditable

It enables hands-free deployment generation at scale, with full reproducibility, policy enforcement, and human escalation when needed.

🧾 System Prompt¶

The System Prompt is a permanent internal instruction that activates when the DevOps Engineer Agent is initialized. It defines:

The agent’s core mission
Its scope and boundaries
Its security and traceability responsibilities
Its formatting and validation expectations

This prompt ensures deterministic, policy-compliant behavior across all executions.

📜 System Prompt (Full Text)¶

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

Your responsibility is to generate secure, traceable, policy-compliant CI/CD pipelines for services, APIs, jobs, and components that have been assembled by engineering agents.

You consume structured inputs including:
- Trace metadata (trace_id, blueprint_id, execution_id)
- Deployment artifacts (deployment.yaml, Helm charts, service configs)
- Security policies (RBAC roles, vault mounts, approval strategies)
- Environment overlays (staging, prod, canary, rollback)
- Post-deployment test hooks (healthcheck, loadtest, canary verification)

Your mission is to:
- Select the correct pipeline template for the project (Azure DevOps or GitHub)
- Render the template with traceable metadata and vault secrets
- Apply rollout strategies (canary, blue-green, rolling)
- Inject approval gates and manual promotion steps when policy requires it
- Append validation and observability hooks to monitor deployments
- Validate all YAML and outputs for schema compliance
- Emit events such as `PipelineGenerated` and `DeploymentReady`
- Optionally commit pipeline artifacts to source control with proper annotations

You must:
- Never generate pipelines without a trace_id
- Never allow insecure deployments (e.g., missing vaults or RBAC)
- Always include metadata annotations in your YAML
- Automatically correct recoverable formatting issues, and emit violations for critical errors

You must not:
- Execute the pipelines directly
- Invent policies or rollouts beyond what the input or environment overlay specifies
- Skip emitting deployment metadata or observability events

Your goal is to produce **production-ready delivery automation** that is **reproducible, secure, and audit-linked** to the component’s blueprint and environment.

🎯 Behavior Controlled by Prompt¶

Area	Rule
Metadata enforcement	Must inject `trace_id`, `execution_id`, `agent_origin`
Policy application	Applies only validated rollout and vault profiles
Output responsibility	CI/CD pipelines, event payloads, deployment snapshots
Validation enforcement	Blocks misconfigured, missing, or insecure pipelines
Human override support	Recognizes `techlead_override: true` in prompt/context metadata

🔐 Sample Output Annotations Required by Prompt¶

metadata:
  trace_id: trace-orders-1080
  agent_origin: devops-engineer-agent
  rollout_strategy: canary
  security_policy_id: sec-profile-orders

📡 Triggered Events from Prompt Behavior¶

PipelineGenerated
PipelineValidationFailed
PipelineRevised
PromotionReady (optional for staging → prod flow)

🧠 Summary¶

The System Prompt ensures that the DevOps Engineer Agent behaves as:

A deterministic executor of CI/CD logic
A policy enforcer for secrets, approvals, and environments
A traceable participant in the AI Software Factory
A zero-guess, event-aware orchestrator of delivery infrastructure

This makes the agent safe, reliable, and autonomous, yet fully governable and auditable.

📥 Input Prompt Template¶

The Input Prompt Template defines the structured payload the agent receives when it is invoked. This payload is consumed either by:

The Semantic Kernel planner (context dictionary)
The LLM-backed execution prompt (when human-readable transformation is needed)

It includes trace metadata, environment overlays, and component-specific configurations, which guide pipeline rendering and post-deploy strategy.

📋 YAML-Based Template (Injected via MCP or Orchestration)¶

trace_id: {{trace_id}}
blueprint_id: {{blueprint_id}}
execution_id: {{execution_id}}
component_name: {{component_name}}
repo: {{repo}}
branch: {{branch}}
environment: {{target_environment}}

security_policy_id: {{security_policy_id}}
vault_mounts:
  - name: {{vault_name}}
    source: azure-keyvault
    mountPath: /mnt/secrets/{{vault_name}}

rbac_roles:
  - {{role_1}}
  - {{role_2}}

rollout_strategy: {{strategy}}  # e.g., canary, blue-green, rolling
approval_required: {{true_or_false}}

post_deploy_tests:
  - healthcheck
  - canary-validation
  - loadtest

pipeline_type: azure-devops | github-actions
auto_promote: true | false

🔁 Example Filled Prompt (Azure DevOps, Staging)¶

trace_id: trace-orders-1080
blueprint_id: usecase-submit-order
execution_id: exec-orders-1080-a
component_name: OrderService
repo: orderservice
branch: main
environment: staging

security_policy_id: sec-profile-orders
vault_mounts:
  - name: db-conn
    source: azure-keyvault
    mountPath: /mnt/secrets/db

rbac_roles:
  - publisher
  - config-reader

rollout_strategy: canary
approval_required: true

post_deploy_tests:
  - healthcheck
  - canary-validation

pipeline_type: azure-devops
auto_promote: false

🧠 Key Fields Required¶

Field	Purpose
`trace_id`	Primary trace binding; required for all outputs
`execution_id`	Correlates logs, spans, events
`component_name`, `repo`	Used to route pipeline to correct directory and path
`vault_mounts`	Ensures secrets are injected securely and traceably
`rollout_strategy`	Selects the strategy block to inject into pipeline YAML
`approval_required`	Adds manual approval stages (if true)
`post_deploy_tests`	Adds verification blocks at the end of deploy stage

📡 Planner Context Template (Semantic Kernel)¶

{
  "trace_id": "trace-orders-1080",
  "repo": "orderservice",
  "target_environment": "staging",
  "rollout_strategy": "canary",
  "vault_strategy": "env",
  "approval_required": true
}

Used when executing planner-based skill orchestration.

🚦 Safeguard Conditions in Prompt¶

Condition	Action
`trace_id` missing	Execution aborts with validation failure
`rollout_strategy` undefined	Defaults to `rolling`
`vault_mounts` empty	Pipeline flagged for manual review
`pipeline_type` unsupported	Fall back to default (`azure-devops`)

🧠 Summary¶

The DevOps Engineer Agent’s Input Prompt Template enables it to:

Generate accurate, trace-bound delivery pipelines
Render reusable, environment-aware YAMLs
Inject secrets, rollout strategies, test hooks, and metadata
Validate everything against policy, profile, and component context

This input model ensures predictable, auditable, automated delivery generation.

📤 Output Expectations¶

The DevOps Engineer Agent emits a structured set of outputs that must be:

🔄 Reproducible
📦 Deployable in CI/CD systems
🔐 Policy- and security-compliant
🔍 Trace-bound to the blueprint and execution context
📡 Observable by downstream agents

All artifacts are emitted in machine-readable formats (YAML, JSON), and optionally committed to Git-based pipeline registries or artifact storage.

✅ Primary Output Artifacts¶

1️⃣ CI/CD Pipeline YAML¶

# azure-pipelines.yml
trigger:
  branches:
    include:
      - main
stages:
  - stage: Build
    jobs:
      - job: Build
        steps:
          - script: dotnet build ...
  - stage: Deploy_Staging
    dependsOn: Build
    jobs:
      - deployment: DeployApp
        environment: staging
        strategy:
          runOnce:
            deploy:
              steps:
                - task: HelmDeploy@0

🔖 Required Annotations (YAML header or metadata block):

metadata:
  trace_id: trace-1080
  blueprint_id: usecase-submit-order
  security_policy_id: sec-profile-orders
  agent_origin: devops-engineer-agent
  rollout_strategy: canary

2️⃣ Deployment Strategy Patch¶

Used for Helm or manifest overlays.

rollout:
  strategy: canary
  maxSurge: 2
  maxUnavailable: 1
  observability:
    enable_tracing: true
    emit_spans: true

3️⃣ Approval and Promotion Configs¶

approval:
  required: true
  approver_group: DevSecOpsTeam
  gating_tests:
    - healthcheck
    - api-contract-test

These are either added as YAML fragments or as Azure DevOps pipeline environments: settings.

4️⃣ Post-Deploy Test Hook Blocks¶

- stage: PostDeployVerification
  dependsOn: Deploy_Staging
  condition: succeeded()
  jobs:
    - job: CanaryVerification
      steps:
        - script: ./scripts/check_canary.sh

5️⃣ Metadata Snapshots (JSON)¶

{
  "component": "OrderService",
  "environment": "staging",
  "pipeline_path": "pipelines/orderservice/azure-pipelines.yml",
  "rollout_strategy": "canary",
  "trace_id": "trace-orders-1080",
  "security_policy_id": "sec-profile-orders",
  "generated_by": "devops-engineer-agent"
}

6️⃣ Lifecycle Event Payloads¶

✅ `PipelineGenerated`¶

{
  "event": "PipelineGenerated",
  "trace_id": "trace-orders-1080",
  "pipeline_path": "pipelines/orderservice/azure-pipelines.yml",
  "status": "ready",
  "agent": "devops-engineer-agent",
  "timestamp": "2025-05-08T00:33:21Z"
}

❌ `PipelineGenerationFailed`¶

Includes reason, trace, and remediation hint.

🧪 Output Validation Requirements¶

Field	Must Exist
`trace_id`, `blueprint_id`	✅
`security_policy_id`	✅
`rollout_strategy`	✅
`agent_origin`	✅
`vault_mounts` (if used)	Must point to valid source
`post_deploy_tests`	Must be injected if specified in input

📂 Storage & Integration Targets¶

Output	Destination
Pipeline YAML	`/pipelines/{component}/azure-pipelines.yml` in Git
Deployment snapshot	Blob storage or Git commit (`deployment-snapshot.json`)
Events	MCP Bus or Event Grid
Logs	Structured JSON to Azure Monitor or Grafana/Loki

🧠 Summary¶

All outputs from the DevOps Engineer Agent must be:

✅ Traceable (via trace_id, agent_origin, etc.)
🔐 Secure (vaulted secrets, RBAC-aware)
📦 Deployable (CI-compatible, schema-valid)
📊 Observable (with spans, logs, and events)

It guarantees delivery automation you can trust, inspect, and reproduce.

📦 Memory¶

The DevOps Engineer Agent uses memory to:

Maintain trace-linked pipeline history
Recall previous rollout strategies, vault maps, and approval flows
Enable diffs, rollbacks, and controlled regeneration
Cache rendered pipeline fragments for reuse in multi-environment promotion

The agent uses both short-term (execution memory) and long-term (persistent memory).

🧠 Short-Term (Execution Scope)¶

Cleared after a single pipeline generation or triggered flow.

Field	Purpose
`trace_id`, `execution_id`	Shared across all artifacts, logs, events
`resolved_overlay`	Merged environment policy
`rendered_pipeline`	YAML held in memory for lint/validation before emission
`secret_map`, `rbac_roles`	Temporary policy-resolved security context
`post_deploy_hooks`	Execution config for downstream QA/Test agents

Stored in Semantic Kernel context or task-local execution plan.

💾 Long-Term Memory (Persistent)¶

Stored in Cosmos DB, Redis, or optionally Blob for snapshots and diffs.

✅ 1. Pipeline History per Component¶

{
  "component": "OrderService",
  "trace_id": "trace-orders-1080",
  "pipeline_path": "pipelines/orderservice/azure-pipelines.yml",
  "hash": "abc123",
  "rollout_strategy": "canary",
  "vaults": ["auth-secret"],
  "generated_at": "2025-05-08T00:33:21Z"
}

Used to compare old vs. new pipeline configs and emit PipelineRevised.

✅ 2. Approval Flow Memory¶

Field	Description
`last_approver`	Identity of human/manual approver (if applicable)
`previous_approval_duration`	Used for SLA or auto-promotion timeouts
`override_reason`	Stored if `techlead_override = true` used in pipeline YAML

✅ 3. Vault Mount Resolution History¶

Tracks secrets and mount paths per environment:

{
  "component": "InvoiceService",
  "env": "prod",
  "vault_strategy": "env",
  "secret_refs": ["invoice-db", "stripe-token"]
}

Used to detect drift or injection strategy mismatch.

✅ 4. Trace-to-Pipeline Link Map¶

Correlates a trace_id with:

pipeline_path
Git commit SHA (if emitted to repo)
Output hash (for diff comparison)
Associated rollout metadata

Enables reproducibility and rollback inspection.

✅ 5. Promotion-Aware Cache (Multi-Env)¶

Stores a frozen rendered pipeline and promotion checklist:

{
  "trace_id": "trace-orders-1080",
  "base_env": "staging",
  "ready_for_promotion": true,
  "test_status": "passed",
  "next_env": "prod"
}

Used by AutoPromoterAgent and HumanOpsAgent.

🧪 Memory Retention Policies¶

Type	Retention
Pipeline YAMLs	365 days or last 5 versions
Trace maps	180 days
Vault usage logs	90 days
Approval logs	60 days (unless flagged for compliance snapshot)

🔐 Access and Security Controls¶

Memory writes always scoped to trace_id + component + environment
Agent memory reads allowed by:
ObservabilityAgent
AutoPromoterAgent
HumanOpsAgent (via dashboard)

Unauthorized memory access is blocked at the execution layer.

🧠 Summary¶

The DevOps Engineer Agent’s memory system enables:

📎 Trace-aligned reproducibility
🔁 Version-aware diff and rollback
🔐 Vault-aware policy enforcement
🚦 Approval-aware promotion orchestration

It ensures every pipeline can be audited, rebuilt, or inspected with zero ambiguity.

🎯 Validation¶

Validation ensures that the generated pipeline:

✅ Is syntactically correct and tool-compatible
🔐 Complies with security policies and vault strategies
📦 Has all required metadata for traceability and execution
📊 Can be safely committed, observed, and approved

The DevOps Engineer Agent performs validation before:

Emitting YAML to Git
Sending a PipelineGenerated event
Triggering post-deploy test hooks

✅ Validation Categories¶

1️⃣ YAML & CI/CD Schema Validation¶

Check	Tool
Azure DevOps schema	`az pipelines validate` or schema linter
GitHub Actions structure	`act` dry-run or YAML schema parser
General YAML syntax	`yamllint`, semantic validators

2️⃣ Required Metadata Validation¶

All pipeline files must include:

metadata:
  trace_id: trace-orders-1080
  blueprint_id: usecase-submit-order
  execution_id: exec-orders-1080-a
  agent_origin: devops-engineer-agent
  security_policy_id: sec-profile-orders

Missing any field triggers hard failure with PipelineGenerationFailed event.

3️⃣ Vault + Secrets Enforcement¶

Check	Rule
Secret referenced in `vault_mounts`	Must exist in secret registry
Mount strategy	Must match policy (`env`, `volume`, or `sidecar`)
No hardcoded secrets	All secrets must resolve from vault references

4️⃣ Rollout Strategy Sanity Check¶

Check	Rule
Strategy present	Must be defined (`rolling`, `canary`, `blue-green`)
Approval block present	If `approval_required: true`, pipeline must include approval stage
Canary hooks valid	If `canary`, test hooks must be injected or referenced in post-deploy phase

5️⃣ Post-Deploy Test Consistency¶

Check	Rule
Test hooks match input	`healthcheck`, `loadtest`, `contract-test` must be rendered
Retry on test hook error	Up to 2 retries allowed for test stage injection
QA-ready emit	Test config must be accessible to QA/Test agents downstream

6️⃣ Observability Metadata Validation¶

Requirement	Status
OTEL tags	Required in emitted spans: `trace_id`, `component`, `env`, `status`
Event emission	Must include structured `PipelineGenerated` payload or emit `PipelineGenerationFailed`
Span correlation	Must include `execution_id` in all spans

❌ Failure Conditions and Response¶

Failure Type	Action
YAML schema invalid	Block emission, emit `PipelineGenerationFailed`
Missing trace_id or execution_id	Abort with high-severity error
Vault resolution fails	Retry with fallback strategy or emit violation
Insecure config (e.g., wildcard RBAC)	Escalate to `HumanOpsAgent` or block commit

📄 Sample Validation Error¶

{
  "event": "PipelineGenerationFailed",
  "trace_id": "trace-orders-1080",
  "component": "OrderService",
  "reason": "Missing rollout_strategy in deployment stage",
  "severity": "high",
  "agent": "devops-engineer-agent",
  "timestamp": "2025-05-08T00:36:44Z"
}

🧪 Validation Flow Snapshot¶

flowchart TD
    A[Pipeline Rendered] --> B[Lint & Syntax Check]
    B --> C[Metadata Check]
    C --> D[Security & Secrets Check]
    D --> E[Rollout & Approval Validity]
    E --> F{All Passed?}
    F -- Yes --> G[Emit YAML + Events]
    F -- No --> H[Emit PipelineGenerationFailed + Halt]

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

🧠 Summary¶

The DevOps Engineer Agent ensures that:

📦 Every output is structurally sound
🔐 Secrets and policies are enforced
📡 Metadata is complete for traceability
❌ Failures are caught before propagation

Validation is the last gate before automation becomes execution — and the first line of defense for delivery integrity.

🔁 Retry & Correction Flow¶

The DevOps Engineer Agent is expected to:

🚫 Prevent invalid or insecure pipelines from reaching deployment
🔄 Retry and recover from transient errors (vault resolution, YAML patch conflicts)
📣 Escalate critical failures to human agents with full trace context
📎 Ensure no duplication, infinite loop, or non-deterministic generation occurs

🔄 Retry Scenarios (Automatic)¶

Failure Type	Action
Vault resolution delay	Retry with exponential backoff (max 3 times)
Overlay merge conflict	Retry with safe fallback environment overlay
Missing optional field	Use default or profile-level fallback (`rolling` for `rollout_strategy`)
Test hook rendering error	Skip optional test, emit warning, proceed with success event

🚫 Non-Retryable / Escalation Scenarios¶

Failure Type	Action
Missing `trace_id` or `execution_id`	Hard stop — emit `PipelineGenerationFailed`
Invalid YAML structure	Retry once, then fail with error snapshot
RBAC misalignment (e.g., wildcard roles)	Escalate to `Security Engineer Agent` or `HumanOpsAgent`
Vault reference not found	Fail, emit `PipelineGenerationFailed`, notify Vault Resolver Agent

🧪 Correction Strategies (Self-Healing Logic)¶

Condition	Auto-Correction
Missing rollout strategy	Use default per environment (`rolling`, `canary`)
Missing post-deploy test	Inject healthcheck if test phase required
Vault mount method undefined	Default to `env` and log fallback
YAML with known lint error	Auto-fix indentation, quoting, ordering (SK correction skill)

Auto-corrected steps are tagged in the logs and telemetry.

🪜 Retry Flow Diagram¶

flowchart TD
    A[Trigger Pipeline Generation] --> B[Render Pipeline]
    B --> C[Run Validation]
    C --> D{Validation Passes?}
    D -- Yes --> E[Emit PipelineGenerated]
    D -- No --> F{Retryable Error?}
    F -- Yes --> B
    F -- No --> G[Emit PipelineGenerationFailed + Notify HumanOps]

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

📡 Emitted on Retry/Correction¶

Each retry or correction emits an annotated log and optional event:

{
  "trace_id": "trace-orders-1080",
  "component": "OrderService",
  "correction": "rollout_strategy set to default (rolling)",
  "status": "corrected",
  "retry_attempt": 1
}

These are consumed by the Observability Agent and optionally displayed in dashboards.

👥 Human Intervention Triggers¶

If automated correction fails or is disallowed (e.g., secure mode), the agent emits:

PipelineGenerationFailed
Tags HumanOpsAgent with remediation suggestions
Optionally offers override instructions (techlead_override: true)

🔐 Policy-Aware Correction Limits¶

No secret fallback unless policy allows it
No pipeline emission if trace_id or security_policy_id is missing
No default approval skips — human approval logic must be honored

✅ Summary¶

The DevOps Engineer Agent’s Retry and Correction Flow ensures:

🤖 Safe self-healing for common issues
🧠 Smart fallback for policies and strategy gaps
📣 Clear escalation when automation fails
🔍 Audit-ready logs of every retry, correction, and failure

It provides resilience and trace-aligned enforcement, without compromising on delivery integrity.

🤝 Collaboration Interfaces¶

The DevOps Engineer Agent is a central automation orchestrator that:

💬 Receives artifacts and metadata from upstream engineering agents
🛠️ Applies policies and configuration from architectural/security agents
🔁 Triggers and coordinates with downstream delivery and observability systems
🧠 Integrates into MCP-based agent orchestration and event-driven flows

Its design is event-driven, contract-bound, and trace-first, ensuring consistent collaboration without ambiguity.

🔗 Upstream Inputs (Agent Dependencies)¶

Agent	Role
Infrastructure Engineer Agent	Provides `deployment.yaml`, Helm charts, runtime configs
Security Engineer Agent	Supplies RBAC, vault mount strategies, `security_policy_id`
Pull Request Creator Agent	Supplies repository context and triggers (e.g., `PullRequestMerged`)
Test Generator Agent (optional)	Defines post-deploy test hooks (`healthcheck`, `loadtest`, etc.)
Vault Resolver Agent (optional)	Resolves secret mapping metadata for target environment

📤 Downstream Consumers (Event & Artifact Integration)¶

Consumer	Purpose
CI/CD Runtime	Consumes emitted `azure-pipelines.yml`, GitHub workflows, or deployment packages
Observability Agent	Receives spans (`devops.pipeline.generated`, `deploy.started`) and deployment metadata
HumanOpsAgent	Triggered for manual approval or pipeline failure intervention
AutoPromoterAgent	Ingests pipeline + snapshot to evaluate readiness for promotion (e.g., staging → prod)
Compliance/Audit Agents (future)	Consume emitted deployment snapshots and approval timelines

📡 Event-Based Communication¶

Emitted Events¶

Event	Trigger	Consumed By
`PipelineGenerated`	On successful pipeline render	Observability Agent, AutoPromoterAgent
`PipelineGenerationFailed`	On hard failure or policy breach	HumanOpsAgent, AuditLogService
`PipelineRevised`	When existing pipeline is updated	GitOps repo, Dashboards
`PromotionReady` (optional)	Post-deploy tests passed, staging complete	AutoPromoterAgent

🔁 Agent-to-Agent Data Contracts¶

Interface	Description
`trace_id`, `execution_id`, `component_scope`	Shared across all collaborating agents
`vault_mounts`, `security_policy_id`	Passed from Security to DevOps Agent
`rbac_roles`, `approval_required`	Shared from blueprint or Security profile
`test_hooks`, `post_deploy_tests`	Passed from QA/Test agents or config overlays

🧩 Coordination Flow Diagram¶

flowchart TD
  A[Infrastructure Engineer Agent]
  B[Security Engineer Agent]
  C[Pull Request Creator Agent]
  D[DevOps Engineer Agent]
  E[Observability Agent]
  F[AutoPromoterAgent]
  G[HumanOpsAgent]

  A --> D
  B --> D
  C --> D
  D --> E
  D --> F
  D --> G

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

📘 Collaboration Summary Table¶

Direction	Agents	Payload
⬅️ Input	Infra, Security, PR	Deployment, secrets, trace metadata
➡️ Output	Observability, CI/CD, Ops	Pipelines, events, rollout metadata
🔁 Bi-directional	AutoPromoter, HumanOps	Promotion signals, intervention triggers

🧠 Summary¶

The DevOps Engineer Agent is a hub node in the software factory’s delivery mesh. It:

🔗 Consumes structured, trace-aligned inputs
⚙️ Generates automation with secure, validated outputs
📡 Emits events to orchestrate the next steps
🧠 Shares trace state and policy with adjacent agents

It embodies ConnectSoft’s principle of agentic collaboration with zero drift, zero guessing, and full traceability.

🎯 Observability Hooks¶

The DevOps Engineer Agent is a trace-first automation generator. Every pipeline it produces must be:

📡 Observable across stages
🧭 Trace-linked to blueprint and component lineage
📊 Auditable across delivery phases
📁 Stored for compliance and reproducibility

Observability hooks allow downstream systems and humans to analyze deployments, detect regressions, track approvals, and verify SLA compliance.

📈 OpenTelemetry Spans (Mandatory)¶

✅ Emitted Spans¶

Span Name	Description
`devops.pipeline.generated`	When pipeline YAML is successfully rendered
`devops.pipeline.validation`	Runs validation checks on schema, metadata, vaults
`devops.pipeline.emit`	Uploads artifact to Git or blob
`devops.pipeline.failed`	Triggered on unrecoverable error
`devops.promotion.ready`	Post-deploy test passed and eligible for env promotion

📌 Standard Span Tags¶

trace_id: trace-orders-1080
component: OrderService
execution_id: exec-orders-1080-a
agent_origin: devops-engineer-agent
environment: staging
rollout_strategy: canary
status: success | failed | pending

📊 Metrics Tracked (via Grafana / Azure Monitor)¶

Metric	Meaning
`pipelines.generated.count`	Total rendered pipelines (per environment)
`pipeline.validation.failures`	Count of failed schema/metadata validations
`approval.duration.avg`	Mean time between pipeline readiness and manual approval
`promotion.success.rate`	% of staging → prod promotions without rollback
`auto.corrected.count`	Number of self-healed pipeline generations

📘 Structured Logs¶

Format	JSON
Location	Blob storage or Azure Monitor / Loki
Example

{
  "event": "PipelineGenerated",
  "trace_id": "trace-orders-1080",
  "agent": "devops-engineer-agent",
  "component": "OrderService",
  "pipeline_path": "pipelines/orderservice/azure-pipelines.yml",
  "rollout_strategy": "canary",
  "status": "success",
  "timestamp": "2025-05-08T00:40:32Z"
}

📣 Events Emitted for Observability¶

Event	Consumed By
`PipelineGenerated`	ObservabilityAgent, Dashboards
`PipelineGenerationFailed`	HumanOpsAgent, AuditAgent
`PipelineRevised`	Source control notification service
`PromotionReady`	AutoPromoterAgent, Approval dashboard

Each includes full trace metadata and diff comparison if applicable.

📁 Audit & Reproducibility¶

✅ Deployment Snapshots¶

File	Example
`deployment-snapshot.json`	Includes all resolved values, strategy, vaults, and trace metadata
`pipeline-hash.log`	SHA of rendered pipeline, used for diff tracking

All stored alongside pipelines or in the MCP artifact archive.

📤 Observability System Integration¶

Target	Format
OpenTelemetry Collector	Spans + Tags
Azure Monitor Logs	JSON logs
Grafana	Metrics dashboards
MCP Trace System	Agent-to-agent linkage across full blueprint execution
Slack / Teams	Pipeline summary alerts, failure diagnostics, approval pings

🧠 Summary¶

The DevOps Engineer Agent delivers first-class observability by design:

🧭 Every pipeline is trace-linked and telemetry-rich
🔔 Every failure is logged and escalated
📊 Every deployment is measured, audited, and reproducible

This guarantees that automation is not only secure — but also fully visible, diagnosable, and governable.

👤 Human Intervention Hooks¶

While the DevOps Engineer Agent operates autonomously, ConnectSoft mandates:

🔐 Human-in-the-loop capabilities for critical environments
🛑 Escalation paths for unrecoverable or policy-blocked executions
✅ Manual approval and override workflows aligned with enterprise governance and compliance standards

🚨 Intervention Triggers¶

When the agent requires human action:¶

Scenario	Trigger
Missing `security_policy_id`	Halt with `PipelineGenerationFailed`
Vault reference cannot be resolved	Notify `HumanOpsAgent`
Approval required in production	Manual gate injected into pipeline
Policy violation (e.g., wildcard RBAC)	Notify `Security Architect Agent` and halt
Overridden default detected	Raise flag to `TechLeadAgent`
Rollout risk flagged	Require manual confirmation for staging → prod promotion

✅ Supported Human Actions¶

Action	Agent or Role
Retry failed generation	`HumanOpsAgent`, via MCP UI or CLI
Approve staging → prod promotion	`DevOps Supervisor` or `TechLeadAgent`
Apply override for test bypass	`TechLeadAgent` with `techlead_override: true` in prompt
Inject custom environment variables	`TenantOpsAdmin` via YAML diff or policy patch
Revoke promotion or rollback	`Platform SRE` via post-deploy test feedback

📬 Channels for Human Interaction¶

Channel	Capability
MCP Dashboard	Approve, reject, retry, override pipeline
GitHub PR Comment	`/retry-pipeline` or `/override-approval` triggers
Slack / Teams Bot	Alert on failure or approval gate, includes CTA buttons
Notification Email	With trace info, file paths, event logs, and override link
Approval CLI	`mcp approve --trace trace-orders-1080 --env prod`

🔐 Governance Controls¶

✅ Manual Approval Blocks¶

environments:
  - name: production
    approval:
      required: true
      approver_group: DevSecOpsTeam
      metadata:
        trace_id: trace-orders-1080
        component: OrderService

Included directly in the pipeline YAML or registered with Azure DevOps environments.

🧾 Override Declaration (Traceable)¶

Overrides require:

override: true
approved_by: techlead-agent
reason: "Temporary vault fallback"

All overrides are:

Logged in pipeline-override.log
Emitted via PipelineRevised event
Monitored by AuditAgent and compliance hooks

🧠 Feedback Loop from HumanOps¶

If a human intervenes, the result is stored in memory:

{
  "trace_id": "trace-orders-1080",
  "override_applied": true,
  "approved_by": "TechLeadAgent",
  "action": "RetryWithFallbackVault",
  "timestamp": "2025-05-08T00:45:08Z"
}

Used for audit replay, policy refinement, or rollback planning.

📡 Agent Response to Human Signals¶

Signal	Result
`/retry-pipeline`	Re-renders pipeline with previous context
`/force-approve`	Adds manual override metadata, emits new event
Dashboard override	Re-plans SK execution flow with override allowed
Approval timeout	Escalates to fallback approver or logs timeout incident

🧠 Summary¶

The DevOps Engineer Agent is:

💬 Fully collaborative with authorized humans
🛑 Capable of pausing or escalating on error or policy conflict
✅ Governed by traceable approval, override, and retry mechanics

This ensures delivery automation with human awareness, respecting ConnectSoft’s Security-First + Observability-First platform mandates.

✅ Summary¶

The DevOps Engineer Agent is ConnectSoft’s fully autonomous, policy-aware CI/CD automation orchestrator. It transforms infrastructure, component metadata, and security overlays into:

📦 Reproducible, version-controlled pipelines
🛠️ Rollout strategies tailored per environment
🔐 Secure vault and RBAC integration
🔁 Multi-stage deployment logic with approvals
📊 Fully observable telemetry and audit snapshots

It is one of the final executors in the software factory flow, ensuring every generated component becomes:

Deployable
Traceable
Secure-by-default
Production-grade

🧩 Agent Roles Recap¶

Area	Responsibilities
CI/CD Rendering	Azure DevOps / GitHub Actions pipeline generation
Policy Enforcement	Rollout, secrets, approvals, RBAC injection
Observability	Emit spans, logs, metrics, and events
Promotion Handling	Supports staging-to-prod workflows
Retry & Intervention	Handles failures, retry logic, human escalation

🔄 Execution Flow Summary¶

flowchart TD
  A[Trigger: PR Merged / Component Assembled / AutoPromoter]
  A --> B[DevOps Engineer Agent]
  B --> C[Load Inputs: deployment.yaml, policy, trace_id]
  C --> D[Render Pipeline YAML]
  D --> E[Validate (schema, secrets, metadata)]
  E --> F{Valid?}
  F -- Yes --> G[Emit Pipeline + Metadata + Events]
  F -- No --> H[Retry or Notify HumanOpsAgent]
  G --> I[CI/CD System Executes Pipeline]
  I --> J[Post-Deploy Tests + Observability Hooks]

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🤝 Collaboration Summary¶

Collaborator	Role
Infrastructure Engineer Agent	Provides runtime artifacts
Security Engineer Agent	Injects secrets, RBAC, policy IDs
Pull Request Creator Agent	Initiates generation on PR merge
Observability Agent	Receives telemetry, metrics
AutoPromoterAgent	Triggers environment progression
HumanOpsAgent	Approves or overrides promotion/rollback

🧠 Final Thoughts¶

The DevOps Engineer Agent completes the vision of agentic software delivery:

🚀 From idea → blueprint → component → CI/CD → deployment
✅ Secure, compliant, and deterministic
📎 Traceable from first prompt to final span
🤖 Auto-healing, human-aware, and observability-first

It is a cornerstone of ConnectSoft's Autonomous SaaS Factory — delivering software without silos, errors, or delay.

🧠 DevOps Engineer Agent Specification¶

🎯 Core Purpose¶

📌 Position in the Platform¶

🧭 Execution Layer Role¶

🛠️ Responsibilities at a Glance¶

📊 Position in Execution Flow¶

🧩 Strategic Importance¶

✅ Summary¶

📌 Responsibilities¶

🔧 Key Responsibilities¶

✅ 1. Generate CI/CD Pipeline YAML¶

✅ 2. Manage Deployment Environments¶

✅ 3. Integrate Secrets and Vaults¶

✅ 4. Insert Rollout Gates & Manual Approvals¶

✅ 5. Emit Deployment Metadata¶

✅ 6. Post-Deployment Validation & Hooks¶

✅ 7. Collaborate With Other Agents¶

✅ 8. Publish CI/CD Pipelines to Source Control¶

✅ 9. Trigger Execution via MCP or External Signal¶

🧩 Output-Linked Responsibilities¶

🧠 Summary¶

📥 Input¶

🔑 Primary Inputs¶

✅ 1. Trace Metadata¶

✅ 2. Infrastructure Artifacts¶

✅ 3. Security Enforcement Data¶

✅ 4. Deployment Environment Profile¶

✅ 5. Post-Deploy Test Configuration¶

✅ 6. Repository Context¶

✅ 7. Orchestration Trigger¶

🧩 Optional Inputs¶

📘 Example Consolidated Input Context¶

🧠 Summary¶

📤 Outputs¶

✅ Primary Outputs¶

1️⃣ CI/CD Pipeline Definition¶

Azure DevOps (default):¶

2️⃣ Post-Deploy Test Triggers¶

3️⃣ Deployment Strategy Patches¶

4️⃣ Secrets + Vault Mapping Blocks¶

5️⃣ Deployment Events¶

✅ PipelineGenerated¶

🔁 PipelineRevised (if existing pipeline updated)¶

6️⃣ Deployment Metadata Snapshot¶

7️⃣ GitOps Commit (Optional)¶

📊 Observability Hooks¶

🧠 Summary¶

📚 Knowledge Base¶

🧩 Key Knowledge Artifacts¶

✅ 1. CI/CD Pipeline Templates¶

✅ 2. Deployment Strategy Profiles¶

✅ 3. Secret Injection Patterns¶

✅ 4. Trace Metadata Blocks¶

✅ 5. Post-Deploy Validation Templates¶

✅ 6. Rollback & Promotion Policies¶

✅ 7. Environment Gate Rules¶

📦 Knowledge Base Storage¶

🧠 Summary¶

🔄 Process Flow¶

🪜 Step-by-Step Breakdown¶

✅ Step 1: Trigger Reception¶

✅ Step 2: Context Aggregation¶

✅ Step 3: Pipeline Template Resolution¶

✅ Step 4: Dynamic Rendering¶

✅ Step 5: Validation¶

✅ Step 6: Emission¶

📌 Conditional Flow Variants¶

🔁 Re-trigger Scenarios¶

📘 Audit Flow Snapshot¶

🧠 Summary¶

🧩 Skills and Kernel Functions¶

🔧 Core Skills & Functions¶

🧠 Example Skill Chain (Planner Flow)¶

🤖 AI-Enhanced Functions (Optional)¶

📌 Execution Safety Guards¶

🧠 Summary¶

🧰 Core Technology Stack¶

🔧 DevOps-Specific Tooling¶

📡 Observability Stack¶

🔐 Security Integrations¶

✅ `PipelineGenerated`¶

🔁 `PipelineRevised` (if existing pipeline updated)¶

✅ `PipelineGenerated`¶

❌ `PipelineGenerationFailed`¶