Scheduled Cost Optimization Reports

Infrastructure costs can spiral out of control without regular oversight. Idle resources, oversized instances, forgotten test environments, and unattached volumes quietly drain budgets month after month. Most engineering teams know they should review costs regularly, but manual audits are time-consuming and often get deprioritized during busy sprints. What makes cost optimization particularly challenging is the need for consistent, periodic review. One-time audits catch current waste but don’t prevent future problems. You need ongoing monitoring, but dedicating team time to monthly cost reviews is difficult to maintain. The investigation follows predictable patterns: identify underutilized resources, check for orphaned volumes, review instance sizing, and flag opportunities for savings. In this example, we’ll show how to create a scheduled SRE agent using Unpage that automatically generates monthly cost optimization reports, identifying savings opportunities in your AWS infrastructure without requiring manual effort.

Why Schedule This Agent?

Unlike incident response agents that react to alerts, cost optimization benefits from proactive, scheduled analysis:

Consistent monitoring: Runs automatically on the same schedule every month
No input needed: Gathers data directly from your infrastructure using tools
Actionable reports: Identifies specific resources and potential savings
No alert fatigue: Generates insights on your schedule, not random alert timing

Scheduled agents are perfect for “background chores” like cost analysis, security audits, and compliance checks that should happen regularly but don’t require immediate response.

Creating A Scheduled Cost Optimization Agent

Let’s create an agent that runs on the 1st of every month, analyzes your AWS infrastructure, and generates a report of cost optimization opportunities. After installing Unpage, create the agent by running:

unpage agent create cost_optimization_monthly

A YAML file will open in your $EDITOR. Paste the following agent definition:

description: Generate monthly cost optimization reports for AWS infrastructure

schedule:
  cron: "0 9 1 * *"  # 9:00 AM on the 1st of every month

prompt: >
  You are a cost optimization specialist analyzing AWS infrastructure for potential savings.

  Generate a comprehensive monthly cost optimization report by:

  1. Using graph tools to discover all AWS EC2 instances and EBS volumes in the infrastructure
  2. For each EC2 instance:
     - Check current instance type and size
     - Analyze CPU and memory utilization metrics from the past 30 days
     - Identify instances with consistently low utilization (< 20% average)
     - Flag instances that appear oversized for their workload
  3. For EBS volumes:
     - Identify unattached volumes that are incurring costs
     - Check for volumes attached to stopped instances
     - Note volumes larger than 1TB that may warrant review
  4. Check for:
     - EC2 instances running in non-production environments
     - Old snapshots that could be deleted
     - Resources tagged as 'temporary' or 'test'

  Format your findings as a structured report with:
  - Executive summary with total estimated monthly savings
  - Detailed findings organized by opportunity type
  - Specific resource IDs, current costs, and recommended actions
  - Priority levels (high, medium, low) for each recommendation

  Be specific with numbers and resource identifiers. Only recommend changes you have
  data to support. If you cannot access certain data, note that in your report.

  At the end, use the pagerduty_create_incident tool to create a low-priority incident
  with your report, so the team can review and act on the recommendations.

tools:
  - "core_current_datetime"
  - "core_calculate"
  - "graph_search_resources"
  - "graph_get_resource_details"
  - "graph_get_resource_map"
  - "metrics_get_metrics_for_node"
  - "metrics_list_available_metrics_for_node"
  - "aws_*"
  - "pagerduty_create_incident"

Let’s break down each section:

Description: What the agent does

The description explains the agent’s purpose. For scheduled agents, this helps you remember what each agent does when reviewing your list of agents.

Schedule: When the agent runs

The schedule section defines when the agent runs automatically. Unpage supports multiple cron formats: Standard 5-field format (minute precision):

schedule:
  cron: "0 9 1 * *"  # 9:00 AM on the 1st of every month

Extended 6-field format (second precision):

schedule:
  cron: "*/30 * * * * *"  # Every 30 seconds

Convenient aliases:

schedule:
  cron: "@monthly"  # Same as "0 0 1 * *"
  cron: "@weekly"   # Same as "0 0 * * 0"
  cron: "@daily"    # Same as "0 0 * * *"
  cron: "@hourly"   # Same as "0 * * * *"

Common patterns:

"0 9 1 * *" - Monthly on the 1st at 9 AM
"0 9 * * 1" - Weekly on Mondays at 9 AM
"0 0 * * *" - Daily at midnight
"0 */6 * * *" - Every 6 hours
"*/2 * * * * *" - Every 2 seconds (6-field format)

All schedules use UTC timezone. See the schedule command documentation for more details.

Prompt: What the agent should do

The prompt contains detailed instructions for the agent. Since scheduled agents receive no input payload, the prompt must specify:

How to get data: Use graph and metrics tools to discover resources
What to analyze: Clear criteria for identifying cost optimization opportunities
Output format: Structure for the report
What action to take: Create a PagerDuty incident with findings

Tools: What the agent can access

The tools section grants permissions to specific infrastructure tools:

Graph tools: Discover and query infrastructure resources
Metrics tools: Analyze resource utilization over time
AWS tools: Get detailed information about EC2 instances and volumes
PagerDuty tools: Create incidents to deliver the report

Use wildcards (aws_*) to grant access to all tools from a plugin. To see all available tools:

unpage mcp tools list

Setting Up Your Infrastructure Graph

For the agent to discover AWS resources, you need to build your infrastructure knowledge graph:

# Configure AWS plugin
unpage configure

# Build the graph (discovers all resources)
unpage graph build

The graph should be rebuilt periodically to stay up-to-date. You can run unpage graph build --interval 3600 to rebuild every hour. See the knowledge graph documentation for details.

Running The Scheduler

To start the scheduler and have your agent run automatically on its schedule:

unpage agent schedule

This starts a daemon that:

Loads all agents with schedule configurations
Sets up cron jobs for each scheduled agent
Runs agents automatically according to their schedules
Logs output of each agent run

The scheduler runs in the foreground. Press Ctrl+C to stop it.

Testing Before Scheduling

Before relying on the schedule, test your agent manually:

# Run the agent immediately to test it
unpage agent run cost_optimization_monthly

This runs the agent with no payload (same as the scheduled run) and shows you the output. Use this to verify your agent works before putting it on a schedule.

Example Output

When your scheduled agent runs, it will analyze your infrastructure and create a PagerDuty incident with findings like:

Cost Optimization Report - March 2025

EXECUTIVE SUMMARY
Estimated monthly savings: $2,847
High priority recommendations: 3
Medium priority recommendations: 7
Low priority recommendations: 4

HIGH PRIORITY OPPORTUNITIES

1. Oversized EC2 instances (Est. savings: $1,200/month)
   - i-0abc123def (t3.2xlarge → t3.large)
     Current: $0.1664/hr | Recommended: $0.0832/hr
     CPU utilization: 12% avg over 30 days
     Memory: 18% avg over 30 days

   - i-0def456ghi (m5.4xlarge → m5.xlarge)
     Current: $0.768/hr | Recommended: $0.192/hr
     CPU utilization: 8% avg over 30 days
     Memory: 15% avg over 30 days

2. Unattached EBS volumes (Est. savings: $847/month)
   - vol-0abc123 (500 GB gp3) - $40/month
     Last attached: 45 days ago
   - vol-0def456 (1 TB gp3) - $80/month
     Last attached: 87 days ago
   [... 8 more volumes]

3. Test environment running 24/7 (Est. savings: $800/month)
   - 4 instances tagged 'environment:test' running continuously
   - Recommendation: Schedule shutdown during non-business hours

MEDIUM PRIORITY OPPORTUNITIES
[...]

The incident is created with low priority, so it doesn’t wake anyone up but ensures the team reviews the recommendations.

Production Deployment

For production use, run the scheduler as a persistent service:

Using systemd (Linux)

Create /etc/systemd/system/unpage-scheduler.service:

[Unit]
Description=Unpage Agent Scheduler
After=network.target

[Service]
Type=simple
User=unpage
WorkingDirectory=/home/unpage
ExecStart=/usr/local/bin/unpage agent schedule
Restart=always
RestartSec=10

[Install]
WantedBy=multi-user.target

Enable and start:

sudo systemctl enable unpage-scheduler
sudo systemctl start unpage-scheduler
sudo systemctl status unpage-scheduler

Using Docker

FROM python:3.12-slim

RUN pip install unpage

COPY config.yaml /root/.unpage/profiles/default/config.yaml
COPY agents/ /root/.unpage/profiles/default/agents/

CMD ["unpage", "agent", "schedule"]

See the deployment guide for comprehensive production setup instructions.

More Scheduled Agent Ideas

Once you have the scheduler running, consider adding more scheduled agents:

Security Audits

schedule:
  cron: "0 10 * * 1"  # Weekly on Mondays
prompt: >
  Review security groups for overly permissive rules, check for exposed databases,
  verify encryption settings, and identify resources without proper tags.

Unused Resource Cleanup

schedule:
  cron: "0 2 * * *"  # Daily at 2 AM
prompt: >
  Identify resources tagged 'temporary' that are older than 7 days and create
  recommendations for cleanup.

Performance Trend Analysis

schedule:
  cron: "0 8 * * 5"  # Weekly on Fridays
prompt: >
  Analyze performance metrics trends over the past week, identify degrading services,
  and generate a weekly health report.

Compliance Checks

schedule:
  cron: "0 6 1 * *"  # Monthly on the 1st
prompt: >
  Review resources for compliance with tagging policies, check for unencrypted volumes,
  verify backup policies are applied, and generate compliance report.

Best Practices

When creating scheduled agents:

Test thoroughly: Run manually several times before relying on the schedule
Start conservative: Begin with weekly or monthly schedules, not daily
Set clear outputs: Have agents create incidents or send notifications with findings
Monitor execution: Check logs regularly to ensure agents are working as expected
Include timestamps: Have agents log when they started and what period they analyzed
Handle failures gracefully: Design prompts to continue even if some data is unavailable
Document expectations: Note in prompts what data sources are required

Troubleshooting

Agent not running on schedule

Check the scheduler logs:

unpage agent schedule

You should see messages like:

Loaded scheduled agent: cost_optimization_monthly
  - Schedule: 0 9 1 * *
  - Description: Generate monthly cost optimization reports

Agent failing during execution

Run manually to see errors:

unpage agent run cost_optimization_monthly

Enable debug mode for more details:

unpage agent run cost_optimization_monthly --debug

Schedule not triggering

Verify cron expression at crontab.guru. Remember schedules use UTC timezone.

Conclusion

Scheduled agents enable proactive infrastructure management without manual overhead. By running cost optimization, security audits, and compliance checks automatically, you can maintain infrastructure health while freeing up team time for higher-value work. The cost optimization example shows how scheduled agents gather data, analyze patterns, and deliver actionable insights—all on autopilot. Apply this pattern to any repetitive operational task that benefits from consistent execution.

About Unpage

Core Concepts

Example Agents

Plugins

How-To Guides

Command Reference

Scheduled Cost Optimization Reports

Why Schedule This Agent?

Creating A Scheduled Cost Optimization Agent

Description: What the agent does

Schedule: When the agent runs

Prompt: What the agent should do

Tools: What the agent can access

Setting Up Your Infrastructure Graph

Running The Scheduler

Testing Before Scheduling

Example Output

Production Deployment

Using systemd (Linux)

Using Docker

More Scheduled Agent Ideas

Security Audits

Unused Resource Cleanup

Performance Trend Analysis

Compliance Checks

Best Practices

Troubleshooting

Agent not running on schedule

Agent failing during execution

Schedule not triggering

Conclusion

​Why Schedule This Agent?

​Creating A Scheduled Cost Optimization Agent

​Description: What the agent does

​Schedule: When the agent runs

​Prompt: What the agent should do

​Tools: What the agent can access

​Setting Up Your Infrastructure Graph

​Running The Scheduler

​Testing Before Scheduling

​Example Output

​Production Deployment

​Using systemd (Linux)

​Using Docker

​More Scheduled Agent Ideas

​Security Audits

​Unused Resource Cleanup

​Performance Trend Analysis

​Compliance Checks

​Best Practices

​Troubleshooting

​Agent not running on schedule

​Agent failing during execution

​Schedule not triggering

​Conclusion

Why Schedule This Agent?

Creating A Scheduled Cost Optimization Agent

Description: What the agent does

Schedule: When the agent runs

Prompt: What the agent should do

Tools: What the agent can access

Setting Up Your Infrastructure Graph

Running The Scheduler

Testing Before Scheduling

Example Output

Production Deployment

Using systemd (Linux)

Using Docker

More Scheduled Agent Ideas

Security Audits

Unused Resource Cleanup

Performance Trend Analysis

Compliance Checks

Best Practices

Troubleshooting

Agent not running on schedule

Agent failing during execution

Schedule not triggering

Conclusion