Real systems. Measured results.

The problem

Texas Roadhouse was dealing with inconsistent infrastructure, manual processes and deployments that carried too much risk across a large multi-location environment.

What we changed

• AWS infrastructure redesign
• Terraform / Infrastructure as Code
• Automated deployment pipelines
• Security improvements
• Monitoring
• Operational improvements

Outcome

• Repeatable deployments
• More consistent environments
• Better operational visibility
• Improved confidence during peak traffic

The problem

Infrastructure costs were higher than necessary, while deployments and monitoring were also consuming engineering time.

What we changed

• Rightsizing
• Resource cleanup
• Storage optimization
• Caching improvements
• Autoscaling
• CI/CD
• CloudWatch monitoring

Outcome

A 40% reduction in AWS costs with no loss of capability — and the team moved from weekly releases toward daily deployments.

The problem

The platform was supporting more than 500,000 daily active users and demanding AI workloads, while provisioning a new environment still took days.

What we changed

• Reusable Terraform modules
• VPC
• ECS
• RDS
• ALB
• WAF
• GitLab CI
• AWS CodePipeline
• CodeDeploy
• Docker
• ECS autoscaling
• CloudWatch observability

Outcome

New environments in under 30 minutes instead of three days, capacity that scales from 50 to 500 containers in about three minutes, and deployments 65% faster.

The problem

Manual patch management was consuming approximately 40 hours every week across a large cloud environment.

What we changed

• AWS Systems Manager
• Bash automation
• Operational runbooks
• Escalation workflows
• IAM security improvements
• Single-point-of-failure analysis
• Cost governance

Outcome

Patching went from a weekly manual effort to an automated process — freeing more than 36 hours a week, with infrastructure availability at 99.95%.

The problem

Teams were spending time moving information between tools, checking emails, creating reports, following up with leads and publishing content by hand.

What we changed

• n8n
• APIs
• Webhooks
• Python
• AI
• Workflow monitoring
• Retry handling
• Error handling
• System integrations

For example: approved content moves automatically from Airtable through the workflow and into publishing platforms, with logging, retries and failure handling.

Outcome

Manual processes became repeatable workflows. Information moves between systems on its own, and when something fails, it's detected — instead of silently breaking the process.