Presence-Aware Infrastructure: My Lab Knows When I'm Home (and Saves Me $$$)

Building the Ultimate R&D Cloud Lab: How I Achieved Real-Time Cost Control and Zero-Waste AWS Experimentation

TL;DR: Built a sophisticated AWS R&D environment with real-time cost tracking ($0.01/day for visibility), automated shutdown systems based on sleep detection, and seamless hybrid cloud integration. The result? Cost visibility + intelligent automation = zero waste and maximum experimentation velocity.

The R&D Cost Problem Every Technical Leader Knows

Let's be honest,I traditional R&D labs suffer from two critical flaws that'll make your wallet weep:

• No cost visibility until the monthly AWS bill lands like a financial haymaker

• Always-on infrastructure burning cash 24/7, even when you're sleeping

I decided to solve this properly. No more monthly surprises, no more "oops, I left that GPU instance running for three weeks" moments. (I unfortunately know the pain)

The Solution: Real-Time Cost Intelligence That Actually Works

Daily Cost Tracking: The $0.01 Investment That Saves Thousands

Here's the game-changer: I know exactly what my experiments cost the day after I run them. Using the AWS Cost Explorer API, my system delivers:

• Immediate feedback loop on experimental costs

• Daily spending attribution to specific tests and infrastructure changes

• Proactive budget management instead of monthly financial surprises

The monitoring itself costs roughly $0.01 per day, an acceptable overhead that pays for itself within hours of preventing a single oversized experiment.

Why This Beats Every Alternative

Traditional Setup: Spin up instances → Run experiments → Hope for the best → Get shocked by the monthly bill

My Smart R&D Lab: Daily cost reports → Instant experiment attribution → Sleep-based automation → 60-80% cost savings

The difference? Real-time awareness creates behavioural change. When you see the daily cost impact of your experiments, you naturally optimise.

The Architecture: Hybrid Intelligence Done Right

Multi-Location Home DC Foundation

My setup starts with a distributed home data centre (please, i really, really want to call them a DC even tho they are not) across 4 physical locations:

• ARM hardware for lightweight processing

• IoT and industrial systems for specialised testing

• High-performance CPU/RAM for compute-intensive workloads

• GPU hardware for GPU workloads

AWS Cloud Integration via WireGuard S2S VPN

The home infrastructure connects securely to AWS through WireGuard site-to-site VPN, enabling:

• Secure data extraction from home lab to AWS for processing

• Private workload testing without public exposure

• Hybrid analytics process home-generated data using AWS services

VPC Architecture: Security Without Complexity

Public Subnet:

• Bastion host (auto-managed based on presence)

• NAT Gateway for private subnet access

• Security groups locked to trusted IPs only

Private Subnet:

• Development and testing instances

• Database resources

• No direct internet access, everything routes through NAT

The Automation That Changes Everything

Presence Detection: Your Lab Knows When You're Home

The system detects my presence through WiFi network monitoring when my phone connects to the home WiFi, the automation triggers. This approach is:

• Zero battery impact (uses existing WiFi connection)

• Instant detection (phone connects within seconds of arriving)

• 100% reliable (can't fake being home unless you're actually there)

Sleep Detection: Smart Resource Management

Here's where it gets sophisticated. The system monitors network activity patterns to detect sleep cycles:

• Network activity monitoring of phone and laptop usage

• Pattern recognition when activity drops below the working baseline

• Time-based logic (only between 20:00-04:00)

• Multi-device correlation to avoid false positives

  • It uses my phone and laptop in an OR condition

    • If any one of the devices (laptop or phone ) is active means I am awake.

  • This works in a 30-minute interval to decide if I am awake

• If any of my servers in any of these locations are talking to the server in AWS, it (in the 2 VPC) it keeps the AWS environment active, since I might be running an experiment

  • I am yet to implement this function

  • The idea is that the AWS env is meant for testing ideas, or if there is an active connection to them means I might be running some kind of test or taking logs, or something

  • The plan to do this is similar to how I built my WireGuard tracking system

    • It basically checks `wg show` and sees the networks transfer data

Database-Driven Configuration

Similar to Windows Registry for key-value management, I use a database to store:

• Instance lists for automated shutdown

• Sleep detection thresholds

• Cost alert parameters

• Environment-specific configurations

This enables runtime parameter adjustments without code changes.

Why n8n Crushes Lambda for R&D Automation

Lambda Reality Check: Per-invocation pricing + cold starts + debugging nightmares

n8n Advantages:

• Fixed cost (it's self-hosted, you can't beat that AWS) vs per-execution pricing (99% cheaper for frequent workflows)

• Visual workflow debugging that actually helps troubleshoot

• No cold starts for consistent performance

• Webhook reliability without the serverless complexity

For daily cost notifications and automation workflows, n8n delivers enterprise-grade functionality at a fraction of Lambda's cost.

The Business Impact: Numbers That Matter

Cost Optimisation Results

Metric	Traditional Setup	Smart R&D Lab	Savings
24/7 running instances	Always on	Sleep-based shutdown	60-80%
Cost visibility	Monthly surprises	Daily tracking	Immediate
Management overhead	Manual processes	Automated workflows	25+ hours/month
Workflow costs	Lambda functions	n8n automation	99% cheaper

Technical Advantages

Hybrid Intelligence: Home lab handles persistent workloads, AWS scales for experiments

Presence-Based Resource Management: Infrastructure mirrors your actual work patterns

Real-Time Cost Attribution: Every experiment's financial impact is immediately visible

Secure Network Integration: Private connectivity without compromising security

Implementation Insights: What Actually Matters

Cost Monitoring Setup

1. Enable Cost Explorer API with minimal permissions

2. Deploy n8n workflow for daily cost tracking

3. Configure Discord webhooks for instant notifications

4. Set up attribution logic to track experiment impacts

Infrastructure Automation

1. Deploy VPC with public/private subnet architecture

2. Configure the bastion host with presence-based auto-startup

3. Set up sleep detection automation with database configuration

Security Implementation

• IP-restricted access from home DC locations

• Audit-ready connections for compliance requirements(yeah, what better than saying I have audit logs for my homelab, maybe even get an ISO27001, cause why not)

Key Takeaways for Technical Leaders

Cost Visibility = Control: The $0.01/day investment in cost monitoring prevents $1000+ monthly surprises

Automation Prevents Waste: Sleep-based shutdown saves 60-80% on compute costs without impacting productivity

Hybrid Approach Maximises Value: Home lab for persistence, AWS for scalability, VPN for security

n8n > Lambda for Workflow Automation: Fixed pricing, visual debugging, and no cold starts win for R&D workflows

Presence Detection Eliminates Manual Management: Your infrastructure should adapt to your work patterns, not the other way around

The Bottom Line

This architecture transforms R&D experimentation from a cost centre into a controlled, measurable, and highly automated technical asset.

The system knows when I'm home, when I'm sleeping, and exactly what each experiment costs. Infrastructure starts up as I walk in the door and shuts down when I'm inactive, all while maintaining enterprise-grade security and providing immediate cost feedback.

Result: Maximum experimentation velocity with zero waste and complete cost transparency.

Your R&D environment should serve your curiosity, not drain your budget. This setup delivers both.

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Enterprise Application: Smart Cost Control for Development Teams

For businesses with development teams, this system automatically shuts down infrastructure when developers aren't actively using it. The beauty lies in the database-driven override mechanism—unless a developer explicitly changes the shutdown prevention value to 1 In the database, the system will power down non-critical services when the team isn't in the office.

This creates a default-to-savings approach while giving developers full control when they need 24/7 uptime for critical testing or deployment cycles. No more forgotten instances burning budget overnight, yet no friction when teams genuinely need persistent infrastructure.

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Want to build something similar? Start with cost monitoring, add presence detection, and let automation handle the rest. The future of R&D infrastructure is intelligent, hybrid, and cost-aware.