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Interactive Engineering Playground

Engineering Labs & Architecture Simulators

Hands-on technical artifacts and simulators replicating real production challenges: GPU serving bottlenecks, multi-stage RAG indexing, Kubernetes incident response, and FinOps calculators.

Live Simulator

Multi-Stage RAG & Model Serving Cluster Topology

Interactive WebGL / Canvas
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Interactive Demos & Incident Simulators

Click into any workbench to run simulations and inspect logs in real time.

Kubernetes & SRELaunch Demo

Kubernetes Incident Response Simulator

Automated detection, triage, and recovery in under 42 seconds

Challenge:The production payment pod hit an out-of-memory crash in a 12-node EKS cluster. Liveness probes were failing, the Horizontal Pod Autoscaler could not scale because the node pool was already at capacity, and alert fatigue from over 200 non-critical alerts was drowning out the actual P0 signal. The on-call engineer had to manually SSH into nodes, figure out which pod was failing, restart it by hand, and then verify the fix. That whole cycle averaged about 45 minutes per incident.
Outcome:Mean time to recovery dropped from 45 minutes of manual firefighting to 42 seconds of fully automated response. 94% of incidents now resolve with zero human intervention. Alert noise dropped by roughly 85% after severity classification filtered non-critical signals.
KubernetesPrometheusGrafanaOPAKarpenterPagerDuty
FinOps & Cost GovernanceLaunch Demo

AWS FinOps Cost Optimizer

Line-by-line cloud cost audit that cut $40,920/year

Challenge:Client AWS bill was $6,400/mo for a mid-size SaaS platform. Over-provisioned EC2 instances running in ap-southeast-1 instead of us-east-1, 3 NAT Gateways routing S3/DynamoDB traffic over public internet at $0.045/GB, no CDN so every API response served directly from ALB, RDS running db.r5.xlarge 24/7 at 3 AM, and orphaned resources (3 unattached 500GB EBS volumes, 2 floating Elastic IPs).
Outcome:Monthly bill dropped from $6,400 to $2,990 (53% reduction), saving $40,920/year. Aurora Serverless alone saved $180/mo by scaling to 0.5 ACU during off-peak hours.
AWSCloudWatchCost ExplorerS3CloudFrontAuroraEC2VPC
Model Serving & PerformanceLaunch Demo

18GB ML Model Cold Start Optimizer

Reduced serverless cold start from 2+ minutes to 8 seconds

Challenge:An 18GB chatbot model deployed on GCP Cloud Run took over 2 minutes to cold-start. The container downloaded full model weights from GCS on every scale-from-zero event. Max memory allocation of 32GB was barely enough — the model plus Python runtime consumed 28GB at peak. During business hours, cold starts caused 504 Gateway Timeouts for the first users after an idle period.
Outcome:Cold start dropped from 2+ minutes to 8 seconds (15x improvement). Zero 504 errors during business hours. Infrastructure cost increase was negligible ($12/mo for keepalive scheduler + min instance).
GCP Cloud RungcsfusePythonDockerCloud Scheduler
Developer Tooling & SRELaunch Demo

Infrastructure CLI Emulator

Web-based terminal simulating kubectl, docker, and terraform commands

Challenge:Onboarding new DevOps engineers required giving them access to production Kubernetes clusters for hands-on training. This posed security risks — one accidental kubectl delete could take down a service. Sandbox environments were expensive ($800/mo per engineer) and constantly drifted from production configs, making training unrealistic.
Outcome:Reduced engineer onboarding time from 2 weeks to 3 days. Eliminated $800/mo per sandbox environment. Zero production access needed for initial training — engineers get cluster access only after completing the emulator training track.
ReactTypeScriptNext.jsCSS Modules

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