Observability and Telemetry System Design

Overview

This document specifies the observability infrastructure for agentic software development systems. It covers metrics, logging, tracing, dashboards, and alerting across all SDLC phases.

Date: 2026-02-06
Scope: End-to-end SDLC observability
Status: Specification

---

1. Metrics Architecture

1.1 Metric Categories

1.2 Metric Definitions by Phase

Phase 1: Planning & Requirements

Phase 2: Implementation

Phase 3: Code Review

Phase 4: Testing

Phase 5: CI/CD & Deployment

Phase 6: Monitoring & Feedback

Cross-Cutting: Agent Behavior

1.3 Metric Collection Methods

yaml
collection_methods:
  # Push-based: Agents send metrics directly
  push:
    - agent_internal_metrics    # Built-in agent telemetry
    - custom_business_metrics   # Application-specific
  
  # Pull-based: Scraped by collector
  pull:
    - prometheus_exporters      # Standard exporters
    - application_endpoints     # /metrics endpoints
  
  # Derived: Computed from other metrics
  derived:
    - rate_calculations         # rates_over_time()
    - aggregations              # sum by (label)
    - ratios                    # error_rate / total

---

2. Logging and Tracing Strategy

2.1 Structured Logging

Log Levels

Log Schema

typescript
interface AgentLogEntry {
  // Identity
  timestamp: string;           // ISO 8601 with nanoseconds
  trace_id: string;            // W3C trace context
  span_id: string;
  parent_span_id?: string;
  
  // Source
  agent_id: string;
  agent_type: 'planner' | 'implementer' | 'reviewer' | 'tester' | 'deployer' | 'monitor' | 'orchestrator';
  phase: 'planning' | 'implementation' | 'review' | 'testing' | 'deployment' | 'monitoring';
  version: string;
  
  // Content
  level: 'DEBUG' | 'INFO' | 'WARN' | 'ERROR' | 'CRITICAL';
  message: string;
  event_type: string;
  
  // Context
  context: {
    project_id: string;
    task_id: string;
    iteration?: number;
    session_id: string;
  };
  
  // Payload
  payload?: {
    input?: unknown;
    output?: unknown;
    duration_ms?: number;
    token_usage?: {
      prompt: number;
      completion: number;
      total: number;
    };
    cost_usd?: number;
  };
  
  // Metadata
  labels: Record<string, string>;
}

2.2 Event Schemas

Event Types by Phase

typescript
// Planning Phase Events
interface PlanningStarted {
  event_type: 'planning.started';
  payload: {
    requirements_summary: string;
    estimated_complexity: 'low' | 'medium' | 'high';
  };
}

interface PlanningCompleted {
  event_type: 'planning.completed';
  payload: {
    stories_count: number;
    architecture_selected: string;
    duration_ms: number;
  };
}

// Implementation Phase Events
interface ImplementationStarted {
  event_type: 'implementation.started';
  payload: {
    module_count: number;
    parallel_workers: number;
  };
}

interface ToolExecution {
  event_type: 'tool.executed';
  payload: {
    tool_name: string;
    tool_version: string;
    input_hash: string;
    output_hash: string;
    duration_ms: number;
    success: boolean;
    retry_count: number;
  };
}

interface AgentLoopIteration {
  event_type: 'agent.loop_iteration';
  payload: {
    iteration_number: number;
    perception_summary: string;
    reasoning_summary: string;
    action_taken: string;
    outcome: 'success' | 'failure' | 'retry';
  };
}

// Review Phase Events
interface ReviewStarted {
  event_type: 'review.started';
  payload: {
    files_changed: number;
    lines_changed: number;
    risk_score: number;
  };
}

interface FindingDetected {
  event_type: 'review.finding_detected';
  payload: {
    severity: 'low' | 'medium' | 'high' | 'critical';
    category: string;
    file: string;
    line: number;
    analyzer: string;
    confidence: number;
    message: string;
  };
}

interface ReviewCompleted {
  event_type: 'review.completed';
  payload: {
    findings_count: number;
    by_severity: Record<string, number>;
    approved: boolean;
    requires_human: boolean;
  };
}

// Testing Phase Events
interface TestExecutionStarted {
  event_type: 'test.execution_started';
  payload: {
    test_count: number;
    selection_strategy: string;
    estimated_duration_ms: number;
  };
}

interface TestCompleted {
  event_type: 'test.completed';
  payload: {
    test_id: string;
    test_name: string;
    suite: string;
    result: 'passed' | 'failed' | 'skipped' | 'flaky';
    duration_ms: number;
    assertions: number;
    error?: string;
  };
}

interface CoverageReported {
  event_type: 'test.coverage_reported';
  payload: {
    line_coverage: number;
    branch_coverage: number;
    function_coverage: number;
    uncovered_lines: number;
  };
}

// Deployment Phase Events
interface DeploymentStarted {
  event_type: 'deployment.started';
  payload: {
    deployment_id: string;
    strategy: 'canary' | 'blue_green' | 'rolling' | 'immediate';
    target_environment: string;
    artifact_version: string;
  };
}

interface TrafficShifted {
  event_type: 'deployment.traffic_shifted';
  payload: {
    deployment_id: string;
    previous_percent: number;
    new_percent: number;
    duration_ms: number;
  };
}

interface DeploymentValidated {
  event_type: 'deployment.validated';
  payload: {
    deployment_id: string;
    checks_passed: number;
    checks_failed: number;
    error_rate: number;
    latency_p95: number;
  };
}

interface RollbackInitiated {
  event_type: 'deployment.rollback_initiated';
  payload: {
    deployment_id: string;
    reason: string;
    trigger: 'automatic' | 'manual';
    metrics_at_trigger: Record<string, number>;
  };
}

// Monitoring Phase Events
interface AnomalyDetected {
  event_type: 'monitoring.anomaly_detected';
  payload: {
    metric: string;
    expected_value: number;
    actual_value: number;
    deviation_percent: number;
    severity: string;
  };
}

interface AlertFired {
  event_type: 'monitoring.alert_fired';
  payload: {
    alert_id: string;
    alert_name: string;
    severity: 'warning' | 'critical' | 'emergency';
    condition: string;
    value: number;
    threshold: number;
  };
}

// Orchestration Events
interface PhaseTransition {
  event_type: 'orchestration.phase_transition';
  payload: {
    from_phase: string;
    to_phase: string;
    checkpoint_id: string;
    duration_in_previous_ms: number;
  };
}

interface HumanInterventionRequested {
  event_type: 'orchestration.human_intervention_requested';
  payload: {
    reason: string;
    urgency: 'low' | 'medium' | 'high';
    estimated_response_time: number;
    context_summary: string;
  };
}

interface CheckpointCreated {
  event_type: 'orchestration.checkpoint_created';
  payload: {
    checkpoint_id: string;
    phase: string;
    state_size_bytes: number;
    validation_passed: boolean;
  };
}

2.3 Distributed Tracing

Trace Structure

Trace: sdlc_execution (root)
├── Span: planning_phase
│   ├── Span: requirements_analysis
│   ├── Span: architecture_design
│   └── Span: story_generation
├── Span: implementation_phase
│   ├── Span: module_implementation (parallel)
│   │   ├── Span: code_generation
│   │   ├── Span: self_validation
│   │   └── Span: iteration_loop (repeated)
│   └── Span: integration
├── Span: review_phase
│   ├── Span: static_analysis
│   ├── Span: security_scan
│   └── Span: ai_review
├── Span: testing_phase
│   ├── Span: test_selection
│   ├── Span: test_execution (parallel per worker)
│   └── Span: failure_analysis
├── Span: deployment_phase
│   ├── Span: build
│   ├── Span: canary_deploy
│   │   ├── Span: traffic_shift (repeated)
│   │   └── Span: health_check (repeated)
│   └── Span: full_rollout
└── Span: monitoring_phase
    ├── Span: synthetic_test
    └── Span: metric_collection

Span Attributes

typescript
interface SDLCSpanAttributes {
  // Standard OpenTelemetry attributes
  'service.name': string;
  'service.version': string;
  'deployment.environment': string;
  
  // SDLC-specific attributes
  'sdlc.project_id': string;
  'sdlc.phase': string;
  'sdlc.agent_id': string;
  'sdlc.agent_type': string;
  
  // Cost attributes
  'cost.tokens_prompt': number;
  'cost.tokens_completion': number;
  'cost.usd': number;
  
  // Performance attributes
  'performance.iteration_count': number;
  'performance.tool_calls': number;
  'performance.cache_hits': number;
}

2.4 Context Propagation

typescript
// W3C Trace Context propagation
interface TraceContext {
  traceparent: string;  // 00-{trace_id}-{span_id}-{flags}
  tracestate: string;   // Vendor-specific context
}

// SDLC-specific baggage
interface SDLCBaggage {
  'sdlc.project_id': string;
  'sdlc.session_id': string;
  'sdlc.human_owner': string;
  'sdlc.criticality': 'low' | 'medium' | 'high';
}

---

3. Storage Recommendations

3.1 Storage Architecture

┌─────────────────────────────────────────────────────────────────┐
│                      Storage Layer                              │
├─────────────────────────────────────────────────────────────────┤
│                                                                 │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐          │
│  │  Hot Storage │  │  Warm Storage│  │  Cold Storage│          │
│  │  (Real-time) │  │  (Analytics) │  │  (Archive)   │          │
│  ├──────────────┤  ├──────────────┤  ├──────────────┤          │
│  │ Prometheus   │  │ ClickHouse   │  │ S3/GCS       │          │
│  │ Redis        │  │ BigQuery     │  │ Glacier      │          │
│  │ InfluxDB     │  │ Snowflake    │  │              │          │
│  └──────────────┘  └──────────────┘  └──────────────┘          │
│                                                                 │
│  ┌──────────────────────────────────────────────────┐          │
│  │              Event Store                         │          │
│  │  (Kafka / Pulsar / EventStoreDB)                │          │
│  └──────────────────────────────────────────────────┘          │
│                                                                 │
│  ┌──────────────────────────────────────────────────┐          │
│  │              Trace Store                         │          │
│  │  (Jaeger / Tempo / Honeycomb)                   │          │
│  └──────────────────────────────────────────────────┘          │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘

3.2 Storage by Data Type

3.3 Schema Design

Time-Series Metrics Schema (ClickHouse)

sql
CREATE TABLE sdlc_metrics (
    timestamp DateTime64(9),
    metric_name LowCardinality(String),
    metric_value Float64,
    
    -- Labels
    project_id LowCardinality(String),
    phase LowCardinality(String),
    agent_id LowCardinality(String),
    agent_type LowCardinality(String),
    environment LowCardinality(String),
    
    -- Dynamic labels as Map
    labels Map(LowCardinality(String), String),
    
    -- Aggregation
    INDEX idx_project project_id TYPE bloom_filter GRANULARITY 4,
    INDEX idx_phase phase TYPE bloom_filter GRANULARITY 4
)
ENGINE = MergeTree()
PARTITION BY toYYYYMM(timestamp)
ORDER BY (metric_name, project_id, timestamp);

Events Schema (ClickHouse)

sql
CREATE TABLE sdlc_events (
    timestamp DateTime64(9),
    trace_id String,
    span_id String,
    parent_span_id String,
    
    event_type LowCardinality(String),
    level LowCardinality(String),
    
    agent_id LowCardinality(String),
    agent_type LowCardinality(String),
    phase LowCardinality(String),
    project_id LowCardinality(String),
    
    message String,
    payload JSON,
    
    -- Cost tracking
    cost_usd Float64,
    tokens_prompt UInt32,
    tokens_completion UInt32,
    
    -- Performance
    duration_ms UInt32,
    
    INDEX idx_trace trace_id TYPE bloom_filter GRANULARITY 4,
    INDEX idx_event_type event_type TYPE bloom_filter GRANULARITY 4
)
ENGINE = MergeTree()
PARTITION BY toYYYYMMDD(timestamp)
ORDER BY (event_type, project_id, timestamp);

Trace Schema (Jaeger/Tempo compatible)

yaml
trace:
  trace_id: string
  span_id: string
  parent_span_id: string
  
  service_name: string
  operation_name: string
  
  start_time: timestamp
  duration_ms: int
  
  tags:
    - key: string
      value: any
      type: string
  
  logs:
    - timestamp: timestamp
      fields: map<string, any>
  
  references:
    - ref_type: child_of | follows_from
      trace_id: string
      span_id: string

3.4 Sampling Strategies

yaml
sampling:
  # Head-based sampling for normal operations
  head_sampling:
    rate: 0.1  # 10% of traces
    
  # Tail-based sampling for interesting traces
  tail_sampling:
    policies:
      # Always sample errors
      - name: errors
        type: status_code
        status_codes: [ERROR]
        
      # Sample slow operations
      - name: slow_requests
        type: latency
        threshold_ms: 5000
        
      # Sample high-cost operations
      - name: expensive
        type: attribute
        key: cost.usd
        threshold: 0.10
        
      # Sample specific phases
      - name: critical_phases
        type: attribute
        key: sdlc.phase
        values: [deployment, review]

---

4. Query Patterns

4.1 Operational Queries

Real-Time Monitoring

promql
# Error rate by phase
sum(rate(sdlc_events_total{level="ERROR"}[5m])) by (phase)
/
sum(rate(sdlc_events_total[5m])) by (phase)

# Current active agents
sum(sdlc_active_agents) by (agent_type)

# Deployment success rate (last hour)
sum(rate(sdlc_deployment_completed_total{status="success"}[1h]))
/
sum(rate(sdlc_deployment_completed_total[1h]))

# Cost per project (current day)
sum(increase(agent_cost_total_usd[1d])) by (project_id)

Health Checks

sql
-- Stuck agents (no activity for >5 minutes)
SELECT 
    agent_id,
    agent_type,
    max(timestamp) as last_seen,
    now() - max(timestamp) as idle_duration
FROM sdlc_events
WHERE timestamp > now() - INTERVAL 1 HOUR
GROUP BY agent_id, agent_type
HAVING idle_duration > 300;

-- Failed deployments requiring attention
SELECT 
    deployment_id,
    project_id,
    timestamp,
    payload.reason
FROM sdlc_events
WHERE event_type = 'deployment.rollback_initiated'
  AND timestamp > now() - INTERVAL 24 HOURS
ORDER BY timestamp DESC;

4.2 Debugging Queries

Trace Analysis

sql
-- Find slow traces
SELECT 
    trace_id,
    duration_ms,
    phase,
    agent_id
FROM sdlc_spans
WHERE duration_ms > 60000
  AND timestamp > now() - INTERVAL 1 HOUR
ORDER BY duration_ms DESC
LIMIT 100;

-- Error trace details
SELECT 
    trace_id,
    span_id,
    event_type,
    message,
    payload.error
FROM sdlc_events
WHERE level = 'ERROR'
  AND trace_id IN (
    SELECT trace_id 
    FROM sdlc_events 
    WHERE event_type = 'orchestration.phase_transition'
      AND timestamp > now() - INTERVAL 1 HOUR
  )
ORDER BY timestamp;

Agent Behavior Analysis

sql
-- Agent loop efficiency
SELECT 
    agent_id,
    avg(iteration_count) as avg_iterations,
    avg(duration_ms) as avg_duration,
    countIf(outcome = 'success') / count() as success_rate
FROM sdlc_events
WHERE event_type = 'agent.loop_iteration'
  AND timestamp > now() - INTERVAL 24 HOURS
GROUP BY agent_id;

-- Tool usage patterns
SELECT 
    payload.tool_name,
    count() as call_count,
    avg(payload.duration_ms) as avg_latency,
    countIf(payload.success = false) / count() as error_rate
FROM sdlc_events
WHERE event_type = 'tool.executed'
  AND timestamp > now() - INTERVAL 7 DAYS
GROUP BY payload.tool_name
ORDER BY call_count DESC;

4.3 Analytics Queries

Performance Trends

sql
-- Phase duration trends
SELECT 
    toStartOfDay(timestamp) as day,
    phase,
    avg(duration_ms) / 1000 as avg_duration_seconds,
    quantile(0.95)(duration_ms) / 1000 as p95_duration_seconds
FROM sdlc_events
WHERE event_type LIKE '%.completed'
  AND timestamp > now() - INTERVAL 30 DAYS
GROUP BY day, phase
ORDER BY day, phase;

-- Cost trends by agent type
SELECT 
    toStartOfWeek(timestamp) as week,
    agent_type,
    sum(cost_usd) as total_cost,
    avg(cost_usd) as avg_per_operation
FROM sdlc_events
WHERE cost_usd > 0
  AND timestamp > now() - INTERVAL 90 DAYS
GROUP BY week, agent_type
ORDER BY week, total_cost DESC;

Quality Metrics

sql
-- Defect escape analysis
SELECT 
    review_phase.findings_count,
    post_deploy.defects_found,
    review_phase.findings_count > 0 as review_caught
FROM (
    SELECT 
        project_id,
        sum(payload.findings_count) as findings_count
    FROM sdlc_events
    WHERE event_type = 'review.completed'
    GROUP BY project_id
) review_phase
JOIN (
    SELECT 
        project_id,
        count() as defects_found
    FROM sdlc_events
    WHERE event_type = 'monitoring.defect_detected'
    GROUP BY project_id
) post_deploy
ON review_phase.project_id = post_deploy.project_id;

-- Test flakiness trends
SELECT 
    test_name,
    count() as total_runs,
    countIf(result = 'flaky') as flaky_runs,
    flaky_runs / total_runs as flakiness_rate
FROM sdlc_events
WHERE event_type = 'test.completed'
  AND timestamp > now() - INTERVAL 30 DAYS
GROUP BY test_name
HAVING flakiness_rate > 0.05
ORDER BY flakiness_rate DESC;

4.4 Cost Optimization Queries

sql
-- High-cost operations
SELECT 
    event_type,
    agent_type,
    count() as operation_count,
    sum(cost_usd) as total_cost,
    avg(cost_usd) as avg_cost,
    max(cost_usd) as max_cost
FROM sdlc_events
WHERE cost_usd > 0.01
  AND timestamp > now() - INTERVAL 7 DAYS
GROUP BY event_type, agent_type
ORDER BY total_cost DESC
LIMIT 50;

-- Cache effectiveness
SELECT 
    agent_type,
    sum(payload.cache_hits) as hits,
    sum(payload.cache_misses) as misses,
    hits / (hits + misses) as hit_ratio
FROM sdlc_events
WHERE event_type = 'agent.loop_iteration'
  AND timestamp > now() - INTERVAL 7 DAYS
GROUP BY agent_type;

---

5. Dashboard Requirements

5.1 Dashboard Hierarchy

Observability Dashboards
│
├── Executive Overview
│   ├── SDLC Velocity
│   ├── Cost Summary
│   └── Quality Scorecard
│
├── Operational
│   ├── Real-Time Pipeline Status
│   ├── Agent Health
│   └── System Performance
│
├── Phase-Specific
│   ├── Planning Dashboard
│   ├── Implementation Dashboard
│   ├── Review Dashboard
│   ├── Testing Dashboard
│   ├── Deployment Dashboard
│   └── Monitoring Dashboard
│
├── Debugging
│   ├── Trace Explorer
│   ├── Error Analysis
│   └── Cost Investigation
│
└── Analytics
    ├── Trends & Forecasting
    ├── Comparative Analysis
    └── Capacity Planning

5.2 Executive Overview Dashboard

5.3 Real-Time Pipeline Status

yaml
dashboard:
  title: "SDLC Pipeline Status"
  refresh: 5s
  
  panels:
    # Global health
    - title: "Active Executions"
      type: stat
      query: count(sdlc_active_executions)
      
    - title: "Queue Depth"
      type: gauge
      query: avg(sdlc_queue_depth)
      thresholds: [10, 50, 100]
      
    # Phase status
    - title: "Phase Distribution"
      type: pie
      query: |
        SELECT phase, count() 
        FROM sdlc_events 
        WHERE event_type = 'orchestration.phase_transition'
          AND timestamp > now() - INTERVAL 1 HOUR
        GROUP BY phase
      
    # Error heatmap
    - title: "Error Rate Heatmap"
      type: heatmap
      query: |
        SELECT 
          toStartOfFiveMinute(timestamp) as time,
          phase,
          count() as errors
        FROM sdlc_events
        WHERE level = 'ERROR'
        GROUP BY time, phase
      
    # Cost rate
    - title: "Real-Time Cost"
      type: graph
      query: |
        rate(agent_cost_total_usd[5m])

5.4 Agent Health Dashboard

5.5 Phase-Specific Dashboards

Implementation Dashboard

yaml
panels:
  - title: "Code Generation Rate"
    query: rate(sdlc.implementation.lines_written[5m])
    
  - title: "Validation Success Rate"
    query: |
      1 - (
        rate(agent.implementer.validation_failures[5m])
        /
        rate(sdlc.implementation.modules_completed[5m])
      )
      
  - title: "Tool Usage Distribution"
    type: pie
    query: |
      SELECT tool_name, count() 
      FROM sdlc_events 
      WHERE event_type = 'tool.executed'
      GROUP BY tool_name
      
  - title: "Iteration Count Distribution"
    type: histogram
    query: |
      SELECT iteration_count, count()
      FROM sdlc_events
      WHERE event_type = 'agent.loop_iteration'
      GROUP BY iteration_count

Deployment Dashboard

yaml
panels:
  - title: "Deployment Success Rate"
    query: sdlc.cicd.success_rate
    
  - title: "Canary Health"
    query: |
      SELECT 
        deployment_id,
        error_rate,
        latency_p95
      FROM sdlc_events
      WHERE event_type = 'deployment.validated'
      ORDER BY timestamp DESC
      LIMIT 10
      
  - title: "Rollback Timeline"
    type: timeline
    query: |
      SELECT timestamp, deployment_id, reason
      FROM sdlc_events
      WHERE event_type = 'deployment.rollback_initiated'
      
  - title: "Traffic Distribution"
    type: stacked_area
    query: |
      SELECT 
        timestamp,
        deployment_id,
        payload.new_percent as traffic_percent
      FROM sdlc_events
      WHERE event_type = 'deployment.traffic_shifted'

---

6. Alerting Thresholds

6.1 Severity Levels

6.2 Alert Rules by Category

System Health Alerts

yaml
alerts:
  - name: AgentStuck
    severity: P2
    condition: |
      max_over_time(
        (time() - sdlc_agent_last_activity_timestamp)[5m:]
      ) > 300
    for: 2m
    annotations:
      summary: "Agent {{ $labels.agent_id }} has been stuck for 5+ minutes"
      
  - name: HighErrorRate
    severity: P1
    condition: |
      (
        sum(rate(sdlc_events_total{level="ERROR"}[5m])) 
        / 
        sum(rate(sdlc_events_total[5m]))
      ) > 0.1
    for: 2m
    annotations:
      summary: "Error rate above 10%"
      
  - name: QueueBackup
    severity: P2
    condition: sdlc_queue_depth > 50
    for: 5m
    annotations:
      summary: "Pipeline queue backing up ({{ $value }} items)"

Performance Alerts

yaml
alerts:
  - name: SlowAgentLoop
    severity: P3
    condition: |
      histogram_quantile(0.99, 
        sum(rate(agent_loop_duration_bucket[5m])) by (le, agent_type)
      ) > 30
    for: 5m
    annotations:
      summary: "P99 agent loop duration > 30s for {{ $labels.agent_type }}"
      
  - name: HighLatency
    severity: P3
    condition: |
      histogram_quantile(0.95, 
        sum(rate(sdlc_phase_duration_bucket[5m])) by (le, phase)
      ) > 300
    for: 10m
    annotations:
      summary: "P95 phase duration > 5 minutes for {{ $labels.phase }}"
      
  - name: CacheHitRateLow
    severity: P4
    condition: |
      (
        sum(rate(agent_cache_hits[5m]))
        /
        sum(rate(agent_cache_operations[5m]))
      ) < 0.5
    for: 15m
    annotations:
      summary: "Cache hit rate below 50%"

Cost Alerts

yaml
alerts:
  - name: CostSpike
    severity: P3
    condition: |
      (
        sum(increase(agent_cost_total_usd[1h]))
        >
        2 * sum(increase(agent_cost_total_usd[1h] offset 24h))
      )
    for: 15m
    annotations:
      summary: "Cost spike detected: 2x normal hourly rate"
      
  - name: HighCostProject
    severity: P4
    condition: |
      sum(increase(agent_cost_total_usd[24h])) by (project_id) > 100
    for: 1h
    annotations:
      summary: "Project {{ $labels.project_id }} exceeded $100/day"
      
  - name: ExpensiveOperation
    severity: P4
    condition: agent_cost_per_operation > 0.5
    for: 0m
    annotations:
      summary: "Single operation cost > $0.50"

Quality Alerts

yaml
alerts:
  - name: DeploymentFailure
    severity: P1
    condition: |
      increase(sdlc_deployment_completed_total{status="failed"}[5m]) > 0
    for: 0m
    annotations:
      summary: "Deployment failure detected"
      
  - name: HighRollbackRate
    severity: P2
    condition: |
      (
        sum(rate(sdlc_cicd_rollback_total[1h]))
        /
        sum(rate(sdlc_cicd_deployment_total[1h]))
      ) > 0.05
    for: 10m
    annotations:
      summary: "Rollback rate above 5%"
      
  - name: TestPassRateLow
    severity: P2
    condition: sdlc_testing_pass_rate < 0.9
    for: 5m
    annotations:
      summary: "Test pass rate below 90%"
      
  - name: FlakyTestsDetected
    severity: P4
    condition: sdlc_testing_flakiness_rate > 0.1
    for: 1h
    annotations:
      summary: "Flaky test rate above 10%"

Security Alerts

yaml
alerts:
  - name: SecurityFindingCritical
    severity: P1
    condition: |
      increase(sdlc_review_findings_total{severity="critical"}[5m]) > 0
    for: 0m
    annotations:
      summary: "Critical security finding detected"
      
  - name: SecretsExposed
    severity: P1
    condition: |
      increase(sdlc_cicd_security_scan_secrets_found[5m]) > 0
    for: 0m
    annotations:
      summary: "Potential secrets exposed in code"

6.3 Alert Routing

yaml
routing:
  default: team-sdlc-oncall
  
  routes:
    - match:
        severity: P1
      receiver: pagerduty-critical
      continue: true
      
    - match:
        severity: P2
      receiver: slack-alerts-high
      
    - match:
        severity: P3
      receiver: slack-alerts-medium
      
    - match:
        alertname: CostSpike
      receiver: finance-team
      
    - match:
        alertname: SecretsExposed
      receiver: security-team
      
    - match:
        agent_type: deployer
      receiver: platform-team
      
receivers:
  pagerduty-critical:
    pagerduty_configs:
      - service_key: "${PAGERDUTY_KEY}"
        severity: critical
        
  slack-alerts-high:
    slack_configs:
      - channel: "#sdlc-alerts-high"
        send_resolved: true
        
  slack-alerts-medium:
    slack_configs:
      - channel: "#sdlc-alerts-medium"
        send_resolved: true
        
  finance-team:
    email_configs:
      - to: "finance@company.com"
        
  security-team:
    slack_configs:
      - channel: "#security-incidents"
        send_resolved: true

6.4 Alert Suppression

yaml
inhibition_rules:
  # Suppress lower-severity alerts when critical is firing
  - source_match:
      severity: P1
    target_match:
      severity: P2
    equal: ['project_id', 'phase']
    
  # Suppress agent-specific alerts when orchestrator is down
  - source_match:
      alertname: OrchestratorDown
    target_match_re:
      alertname: Agent.*
    equal: ['environment']
    
silences:
  # Maintenance windows
  - matchers:
      - name: environment
        value: staging
    startsAt: "2026-02-07T02:00:00Z"
    endsAt: "2026-02-07T04:00:00Z"
    comment: "Scheduled maintenance"

---

7. Implementation Checklist

Phase 1: Foundation

• Deploy Prometheus for metrics collection
• Deploy Loki for log aggregation
• Deploy Jaeger/Tempo for distributed tracing
• Configure OpenTelemetry SDK in agents
• Set up Kafka for event streaming

Phase 2: Storage

• Deploy ClickHouse for analytics
• Configure S3 lifecycle policies
• Set up Thanos for long-term metric storage
• Deploy vector database for agent memory

Phase 3: Visualization

• Deploy Grafana
• Create executive dashboard
• Create operational dashboards
• Create phase-specific dashboards

Phase 4: Alerting

• Deploy Alertmanager
• Configure PagerDuty integration
• Set up Slack notifications
• Define alert routing rules
• Create runbooks for each alert

Phase 5: Optimization

• Implement sampling strategies
• Tune retention policies
• Optimize query performance
• Set up cost monitoring
• Create anomaly detection

---

8. References

Related Research

• 01 - Agentic Loops and Orchestration Patterns
• 02 - Feedback Loops and Reflection Mechanisms
• 03 - Automated Code Review Systems
• 04 - Automated Testing and Quality Assurance
• 05 - CI/CD Pipeline Automation and Deployment
• 06 - End-to-End SDLC Orchestration

External Standards

• OpenTelemetry Specification
• Prometheus Best Practices
• W3C Distributed Tracing
• CloudEvents Specification

---

Generated: 2026-02-06
Version: 1.0