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Real-World Case Studies

How leading organizations achieved compliance, scalability, and developer productivity with Cloud Development Environments

From healthcare to fintech - see how CDEs solve real infrastructure challenges

MedSecure Health

Healthcare Technology Platform

200
Developers
Healthcare
Industry
HIPAA/HITRUST

The Challenge

MedSecure Health, a rapidly growing EHR platform handling PHI (Protected Health Information), faced critical security and compliance challenges with their traditional development model.

Compliance Risk
HIPAA/HITRUST audits flagged PHI on developer laptops
Data Exfiltration Concerns
Production database backups on unsecured personal devices
Audit Trail Gaps
No centralized logging of who accessed what data
Slow Onboarding
5 days to configure secure workstations for new hires

The Solution

Deployed self-hosted Coder on AWS GovCloud with strict network isolation and comprehensive audit logging.

Platform: Coder (self-hosted)
Infrastructure: AWS GovCloud
Workspaces: EKS pods in private VPC
Access: VS Code Remote SSH + Web IDE
Auth: Okta SSO + MFA
Zero PHI on local machines
All workspace activity logged to CloudWatch
Network-isolated dev/staging/prod environments

Key Results

100%
Audit Compliance
Passed HITRUST certification
80%
Faster Onboarding
5 days to 1 day
0
Data Breaches
Zero PHI on endpoints
$2.1M
Risk Reduction
Avoided breach insurance costs

Lessons Learned

  • Start with a pilot team before company-wide rollout
  • GovCloud requirement added 2 weeks to setup - plan accordingly
  • Web IDE worked better than expected for junior developers
  • CloudWatch log integration was critical for audit success
Sarah Chen
VP of Engineering

"Coder transformed our security posture overnight. When auditors asked to see our PHI access controls, we showed them the Coder audit logs and they were impressed. We went from compliance risk to compliance showcase in 8 weeks."

PayFlow

Digital Payment Processing Startup

50
Developers
Fintech
Industry
SOC 2

The Challenge

PayFlow needed SOC 2 Type II certification to close enterprise deals, but their startup pace conflicted with security requirements.

Audit Gaps
No centralized access controls or activity monitoring
Scaling Pain
Hiring 5-10 developers per month, onboarding chaos
Environment Drift
"Works on my machine" bugs delaying releases
Cost Pressure
Buying MacBook Pros for every new hire ($3K+ each)

The Solution

Adopted GitHub Codespaces with strict security controls and automated compliance monitoring.

Platform: GitHub Codespaces
Infrastructure: GitHub-managed
Dev Containers: Docker-based templates
Access: VS Code browser + desktop
Monitoring: GitHub Advanced Security
Audit logs via GitHub Enterprise
Pre-built dev containers for instant consistency
Auto-stop after 30 min idle for cost control

Key Results

3 mo
SOC 2 Achieved
From audit start to certification
60%
Cost Reduction
vs buying hardware
15 min
New Hire Setup
Down from 2 days
95%
Dev Satisfaction
Internal survey score

Lessons Learned

  • GitHub native integration was huge - no new tools to learn
  • Dev containers took 2 weeks to perfect but saved months later
  • Some devs preferred desktop VS Code over browser - offer both
  • Auto-stop saved $18K/month in forgotten workspaces
Marcus Rodriguez
CTO & Co-Founder

"Codespaces was the secret weapon for our SOC 2 sprint. When auditors saw our GitHub audit logs showing every code access, every commit, every workspace creation - they were satisfied immediately. Plus, we closed our first enterprise deal 2 weeks after certification."

GlobalTech Corp

Fortune 500 Technology Conglomerate

2,000
Developers
Enterprise
Industry
Multi-Region

The Challenge

GlobalTech struggled with massive environment drift across 2,000 developers spanning 47 countries and dozens of tech stacks.

"Works on My Machine" Epidemic
30% of production bugs were environment-related
3-Day Onboarding
New hires spent first week fighting setup issues
Support Ticket Overload
400+ environment tickets per month to DevOps
Hardware Sprawl
Mix of Windows, Mac, Linux - impossible to standardize

The Solution

Deployed self-hosted Coder on Kubernetes clusters in AWS (US/EU) and Azure (APAC) for multi-region low latency.

Platform: Coder (self-hosted)
Infrastructure: AWS EKS + Azure AKS
Regions: us-east-1, eu-west-1, ap-southeast-1
Templates: 15 pre-built (Node, Java, Python, .NET, Go)
Integration: Okta SSO, Datadog monitoring
Platform team maintains 15 golden templates
Regional deployment for <50ms latency globally
Automated workspace provisioning via Terraform

Before vs After

Before CDEs

Onboarding Time 3 days
Environment Tickets/Month 400+
Environment Bugs 30%
Dev Satisfaction 67%

After CDEs

Onboarding Time 4 hours
Environment Tickets/Month 45
Environment Bugs 3%
Dev Satisfaction 89%

Key Results

4 hrs
Onboarding Time
Down from 3 days
90%
Fewer Tickets
400 to 45 per month
27%
Bug Reduction
Eliminated environment drift
$3.8M
Annual Savings
Productivity + hardware costs

Lessons Learned

  • Multi-region deployment required upfront but paid off for APAC devs
  • Platform team of 4 engineers now maintains templates vs 12 support staff
  • Phased rollout by team (6 months) prevented chaos
  • Early adopter program (50 volunteers) surfaced critical issues
Jennifer Park
SVP, Global Engineering

"The ROI was undeniable. We calculated that environment-related bugs were costing us $2.4M annually in lost productivity. Six months after rolling out Coder, those bugs dropped by 90%. The business case sold itself."

NeuralWorks

AI/ML Research & Development Lab

100
ML Engineers
AI/ML
Industry
GPU Compute

The Challenge

NeuralWorks struggled with GPU access bottlenecks and slow model training iteration cycles limiting research velocity.

GPU Scarcity
Only 20 local GPUs shared across 100 researchers
Slow Iteration
Training runs took 8+ hours, blocking daily experiments
Environment Complexity
CUDA, cuDNN, TensorFlow version hell on local machines
Hardware Waste
GPUs idle overnight and weekends, burning $40K/month

The Solution

Deployed Coder with NVIDIA GPU templates on AWS EC2 P4d instances for on-demand high-performance compute.

Platform: Coder (self-hosted)
Infrastructure: AWS EC2 P4d (8x A100 GPUs)
Templates: PyTorch, TensorFlow, JAX pre-configured
Storage: FSx for Lustre for dataset access
Scheduling: Auto-stop after 1 hour idle
Spin up 8xA100 workspace in 90 seconds
Pre-built images with CUDA 12.x + cuDNN 8.x
Jupyter + VS Code access built-in

Key Results

10x
Faster Iteration
Training time: 8hr to 45min
$500K
Annual Savings
vs buying GPUs
3x
More Experiments
Per researcher per week
90 sec
GPU Provisioning
From request to ready

GPU Resource Utilization

Before (On-Premise GPUs)
Utilization 40%
- Idle nights/weekends
- Queue wait times 2-4 hours
- $1.2M capital expense
After (Cloud CDEs)
Utilization 95%
- Pay per second of use
- Zero wait time (on-demand)
- $700K annual OpEx

Lessons Learned

  • FSx for Lustre was essential for multi-TB dataset performance
  • Pre-built Docker images saved 15 min per workspace spin-up
  • Spot instances reduced costs 70% for non-critical experiments
  • Jupyter integration was more popular than expected
Dr. Aisha Patel
Head of ML Infrastructure

"The velocity increase was staggering. Our researchers went from 2-3 training runs per day to 20+. When you can iterate 10x faster, you find better models 10x faster. This directly contributed to our breakthrough in computer vision that closed our Series B."

SecureGov Solutions

Federal Government Contractor

300
Developers
GovTech
Industry
FedRAMP High

The Challenge

SecureGov needed FedRAMP High authorization for classified government contracts, requiring air-gapped development environments with zero internet exposure.

Air-Gap Requirement
No cloud solutions allowed - must be on-premises
Strict Audit Controls
Every action must be logged and reviewed
Contractor Challenges
40% workforce is contractors - code security risk
Physical Security
SCIF access required for development - costly

The Solution

Deployed self-hosted Coder on air-gapped on-premises Kubernetes cluster with hardware security modules (HSMs).

Platform: Coder (self-hosted)
Infrastructure: On-prem Kubernetes
Network: Air-gapped (no internet)
Auth: CAC/PIV card + HSM
Audit: Splunk SIEM integration
Fully isolated network - zero external connectivity
All workspace activity logged to SIEM
Contractors access via thin clients (no code download)

Key Results

FedRAMP
High Authorization
Achieved in 8 months
100%
Audit Pass Rate
Zero findings in 3 audits
$1.9M
SCIF Cost Savings
Reduced physical space needs
0
Security Incidents
Since deployment (18 months)

Security Architecture Highlights

Network Isolation

  • - Air-gapped environment
  • - No internet access
  • - Internal-only DNS
  • - Hardened firewalls

Access Control

  • - CAC/PIV card required
  • - HSM-backed encryption
  • - Role-based access (RBAC)
  • - Session recording

Compliance

  • - Real-time SIEM logging
  • - Automated compliance checks
  • - Quarterly audits
  • - Incident response playbooks

Lessons Learned

  • Air-gap setup took 4 months - budget time for network config
  • CAC/PIV integration was critical for government acceptance
  • Splunk SIEM integration provided real-time compliance visibility
  • Contractors loved not needing SCIF badge - productivity boost
Colonel James T. Mitchell (Ret.)
Chief Security Officer

"FedRAMP High is one of the most stringent security certifications in existence. Coder's architecture allowed us to meet every requirement without sacrificing developer productivity. The authorization opened $400M in contract opportunities."

Common Themes Across All Case Studies

While each organization had unique challenges, several patterns emerged across all successful CDE implementations.

Faster Onboarding

Average 75% reduction in new hire setup time

Enhanced Security

Zero code on endpoints, comprehensive audit logs

Cost Optimization

Auto-stop and resource pooling drove savings

Developer Happiness

Consistent environments eliminated frustration

Ready to Write Your Own Success Story?

Whether you're in healthcare, fintech, enterprise, AI/ML, or government - Cloud Development Environments can transform your development workflow.