Cost Optimization Intelligence

Version: 0.4.0 Status: Production Last Updated: 2025-12-01

azlin provides comprehensive cost optimization intelligence to help you minimize Azure spending while maintaining performance.

Overview

The cost optimization system provides:

Real-Time Cost Dashboard - Monitor current spending across all VMs
Budget Alerts & Forecasting - Get notified before exceeding budgets
Optimization Recommendations - AI-powered suggestions to reduce costs
Cost History & Trends - Track spending patterns over time
Automated Optimization - Schedule actions to reduce costs automatically

Quick Start

# View real-time cost dashboard
azlin costs show

# Set budget and enable alerts
azlin costs budget set 500

# Get optimization recommendations
azlin costs recommendations

# View cost forecast
azlin costs forecast

# Enable automated cost optimization
azlin costs optimize --enable

Commands

Real-Time Cost Dashboard

View current spending across all VMs with real-time updates from Azure Cost Management API.

# Show dashboard for current resource group
azlin costs show

# Show dashboard for specific resource group
azlin costs show --rg my-resource-group

# Show per-VM breakdown
azlin costs show --by-vm

# Refresh dashboard (bypass cache)
azlin costs show --refresh

Output Example:

================================================================================
Azure Cost Dashboard (Real-Time)
================================================================================
Resource Group: azlin-rg-1234567890
Last Updated: 2025-12-01 14:30:00 UTC
Billing Period: Dec 1 - Dec 31, 2025

Total Spending (This Month):  $247.50
Daily Average:                $23.45
Projected Month-End Total:    $726.39

Running VMs: 3
Stopped VMs: 1

================================================================================
Per-VM Breakdown
================================================================================
VM NAME                   STATUS    DAILY COST   MONTH-TO-DATE   PROJECTED
azlin-vm-001             Running   $9.60        $105.60         $297.60
azlin-vm-002             Running   $8.32        $91.52          $257.92
azlin-vm-003             Running   $5.53        $60.83          $171.33
azlin-vm-004             Stopped   $0.00        $0.00           $0.00

================================================================================

Performance: Response time < 2 seconds (includes 5-minute cache)

Budget Management

Set budgets and receive alerts when spending reaches thresholds.

# Set monthly budget
azlin costs budget set 500

# Set budget with custom thresholds
azlin costs budget set 500 --thresholds 75,85,95

# Check budget status
azlin costs budget status

# Disable budget alerts
azlin costs budget disable

Budget Alert Thresholds:

80% threshold: Warning notification
90% threshold: Critical notification
100% threshold: Alert + optional auto-shutdown of non-essential VMs

Output Example:

================================================================================
Budget Status
================================================================================
Monthly Budget:           $500.00
Current Spending:         $247.50 (49.5%)
Remaining Budget:         $252.50
Projected Month-End:      $726.39

⚠️  WARNING: Projected spending ($726.39) will exceed budget by $226.39 (45%)

Alert Thresholds:
  ✓ 80% ($400.00) - Not reached
  ✓ 90% ($450.00) - Not reached
  ✓ 100% ($500.00) - Not reached

Recommendation: Consider optimization actions to stay within budget
================================================================================

Cost Forecasting

Predict end-of-month costs based on current usage patterns and historical data.

# Show forecast for current month
azlin costs forecast

# Show forecast with confidence intervals
azlin costs forecast --confidence

# Forecast specific resource group
azlin costs forecast --rg my-resource-group

Forecast Accuracy: Within 10% of actual costs (based on 30-day rolling average)

Output Example:

================================================================================
Cost Forecast
================================================================================
Current Month: December 2025
Days Elapsed: 10 / 31 (32%)
Days Remaining: 21

Current Spending:         $247.50
Daily Average:            $24.75

End-of-Month Projection:  $767.25
Confidence Interval:      $690.53 - $843.98 (90% confidence)
Forecast Accuracy:        92% (based on historical data)

Trend Analysis:
  - Spending increased 15% compared to last month
  - Highest cost VM: azlin-vm-001 ($297.60 projected)
  - Potential savings with optimization: $150 - $200/month

================================================================================

Optimization Recommendations

Get AI-powered recommendations to reduce costs without sacrificing performance.

# Show all recommendations
azlin costs recommendations

# Filter by savings potential
azlin costs recommendations --min-savings 50

# Show only high-confidence recommendations
azlin costs recommendations --confidence high

# Export recommendations to file
azlin costs recommendations --export recommendations.json

Recommendation Types:

Downsize VMs - Identify over-provisioned VMs
Schedule Start/Stop - Automate VM shutdown during off-hours
Cheaper VM Sizes - Suggest cost-effective alternatives
Region Migration - Recommend lower-cost regions
Reserved Instances - Identify VMs suitable for reservations

Output Example:

================================================================================
Cost Optimization Recommendations
================================================================================
Total Potential Savings: $180.25/month (24% reduction)

[1] Downsize VM: azlin-vm-001
    Current: Standard_D8s_v3 ($297.60/month)
    Recommended: Standard_D4s_v3 ($148.80/month)
    Savings: $148.80/month (50% reduction)
    Confidence: High (85%)
    Reason: Average CPU utilization <15% for past 30 days
    Action: azlin costs optimize downsize azlin-vm-001 --size Standard_D4s_v3

[2] Schedule Stop/Start: azlin-vm-002
    Current: Running 24/7 ($257.92/month)
    Recommended: Stop 8PM-8AM weekdays
    Savings: $77.38/month (30% reduction)
    Confidence: Medium (70%)
    Reason: No activity detected outside business hours
    Action: azlin costs optimize schedule azlin-vm-002 --hours "8-20" --days "Mon-Fri"

[3] Switch to AMD: azlin-vm-003
    Current: Standard_D2s_v5 Intel ($171.33/month)
    Recommended: Standard_D2as_v5 AMD ($154.20/month)
    Savings: $17.13/month (10% reduction)
    Confidence: High (90%)
    Reason: AMD equivalent performs identically at lower cost
    Action: azlin costs optimize migrate azlin-vm-003 --size Standard_D2as_v5

================================================================================

Cost History & Trends

Analyze spending patterns over 30, 60, or 90 days.

# Show 30-day cost history
azlin costs history

# Show 90-day trend
azlin costs history --days 90

# Compare periods
azlin costs history --compare

# Export to CSV
azlin costs history --export history.csv

Output Example:

================================================================================
Cost History (Last 30 Days)
================================================================================

Daily Spending Trend:
Dec 1:  $23.45  ████████████████
Dec 2:  $24.10  ████████████████▌
Dec 3:  $22.80  ███████████████
Dec 4:  $25.50  ████████████████████
...

Weekly Averages:
Week 1 (Dec 1-7):   $23.12/day  ($161.84 total)
Week 2 (Dec 8-14):  $25.45/day  ($178.15 total)

Monthly Comparison:
November 2025:  $687.50
December 2025:  $726.39 (projected) [+5.7%]
October 2025:   $642.10

Cost by VM (30-day total):
azlin-vm-001:  $288.00 (40%)
azlin-vm-002:  $249.60 (35%)
azlin-vm-003:  $166.40 (23%)
azlin-vm-004:  $15.00 (2%)

================================================================================

Automated Optimization

Enable automated cost optimization actions with approval workflows.

# Enable automated optimization
azlin costs optimize --enable

# Configure optimization rules
azlin costs optimize config

# Show optimization status
azlin costs optimize status

# Manually trigger optimization
azlin costs optimize run

# Disable automated optimization
azlin costs optimize --disable

Optimization Actions:

Auto-Shutdown - Stop VMs exceeding idle thresholds
Scheduled Start/Stop - Automate VM schedules
Auto-Downsize - Resize underutilized VMs (requires approval)
Budget Protection - Stop non-essential VMs when budget limit reached

Approval Workflow:

No approval: Schedule stop/start
Auto-approval: Auto-shutdown after 24h idle
Manual approval: VM downsizing, region migration

Output Example:

================================================================================
Automated Optimization Status
================================================================================
Status: Enabled
Last Run: 2025-12-01 08:00:00 UTC
Next Run: 2025-12-02 08:00:00 UTC (daily at 8 AM)

Active Rules:
[✓] Auto-shutdown idle VMs after 24 hours
[✓] Enforce business-hours schedule for dev VMs (tag: env=dev)
[✓] Budget protection at 95% threshold
[✗] Auto-downsize (requires manual approval)

Recent Actions (Last 7 Days):
- 2025-11-30: Stopped azlin-vm-004 (idle 48 hours) - Saved $2.30
- 2025-11-29: Applied schedule to azlin-vm-002 - Projected $77/month savings
- 2025-11-28: Budget alert sent (85% threshold)

Total Savings (This Month): $45.60

================================================================================

Configuration

Cost optimization settings stored in ~/.azlin/config.toml:

[costs]
# Cache API responses for 5 minutes
cache_ttl = 300

# Budget settings
monthly_budget = 500.00
budget_alerts = [80, 90, 100]

# Optimization settings
auto_optimization = true
require_approval_for_downsize = true
idle_threshold_hours = 24

# Data storage
storage_backend = "json"  # "json" or "sqlite"
history_retention_days = 90

Data Storage

Cost data stored in ~/.azlin/costs/:

~/.azlin/costs/
├── history.json          # Cost history (30/60/90 days)
├── budgets.json          # Budget configurations
├── cache.json            # API response cache
└── recommendations.json  # Optimization recommendations

API Integration

Uses Azure Cost Management API for real-time cost data:

Authentication: Azure SDK credentials (same as azlin)
API: azure-mgmt-costmanagement
Caching: 5-minute TTL to meet <2s response time
Fallback: Uses estimation if API unavailable

Performance

Dashboard load time: < 2 seconds (with caching)
Forecast accuracy: Within 10% of actual costs
Cache TTL: 5 minutes
Data retention: 90 days

Best Practices

Set budgets early - Enable alerts before costs spiral
Review recommendations weekly - Act on high-confidence suggestions
Use tags - Tag VMs by environment for better tracking
Schedule dev VMs - Stop development VMs outside business hours
Monitor forecasts - Track trends to avoid budget surprises

Troubleshooting

Cost data not updating

# Refresh cache
azlin costs show --refresh

# Check Azure credentials
azlin auth test

Budget alerts not working

# Verify budget configuration
azlin costs budget status

# Check notification settings
cat ~/.azlin/config.toml | grep budget

Recommendations seem inaccurate

Recommendations based on 30-day rolling average. For newly created VMs, wait 7-14 days for accurate utilization data.

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Cost Optimization Intelligence

Overview

Quick Start

Commands

Real-Time Cost Dashboard

Budget Management

Cost Forecasting

Optimization Recommendations

Cost History & Trends

Automated Optimization

Configuration

Data Storage

API Integration

Performance

Best Practices

Troubleshooting

Cost data not updating

Budget alerts not working

Recommendations seem inaccurate

Related Documentation

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Cost Optimization Intelligence

Overview

Quick Start

Commands

Real-Time Cost Dashboard

Budget Management

Cost Forecasting

Optimization Recommendations

Cost History & Trends

Automated Optimization

Configuration

Data Storage

API Integration

Performance

Best Practices

Troubleshooting

Cost data not updating

Budget alerts not working

Recommendations seem inaccurate

Related Documentation