Computer Science
Cloud & Infrastructure Challenges
Cloud & Infrastructure challenges put you in charge of the foundations every service runs on. You'll work through Cloud Computing fundamentals on AWS or Azure, provision environments with Terraform, control access with Cloud IAM, and ship workloads via Helm + Kubernetes deployments.
From there you'll handle the harder edges — Multi-cloud architecture, Landing zones, Advanced IaC modules, FinOps & cost optimization, and the AWS Well-Architected Framework — designing infrastructure the way platform teams actually scale it. Each challenge you solve earns a verified credential you can share with recruiters.
Recommended Challenges
· FinOps & cost optimization Clear- AnalysisBeginnerNew
Cost-Optimize an Embedding Pipeline for a Customer Support Knowledge Base
You receive: (a) the current pipeline (full re-embed on any article change, OpenAI text-embedding-3-large, 3,072 dims) with one month of cost logs, (b) a sample of 5,000 article…
- Embedding Models
- Cost Optimization
- Change Detection
Open coursework - AnalysisIntermediateNew
Cut Latency and Cost on a High-Volume Summarization Service
You receive 30 days of anonymized request logs (prompt token counts, completion token counts, latencies, models used). Profile the cost and latency distribution, then design and…
- Cost Optimization
- Latency Optimization
- Prompt Compression
Open coursework - AnalysisBeginnerNew
Flatten the Datadog Bill for a Stockholm Gaming Studio
Working only from the materials provided, audit Stagelight Games' observability spend and produce a defensible plan to flatten it. Use the metric inventory export to rank the to…
- Cardinality Control
- Datadog
- Cost Optimization
Open coursework - AnalysisIntermediateNew
Halve a Daily Spark Bill Without Breaking the SLA
Work only from the materials in this file. Read the representative PySpark module (PULSE-JOB) and the cluster configuration (PULSE-CLUSTER) to understand how the nightly job is …
- Spark
- Cost Optimization
- Etl Pipelines
Open coursework Practice your coursework on real scenarios.
Every challenge is shaped from real-world context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- AnalysisBeginnerNew
Right-Size a Real-Time Recommendation Serving Cluster
You receive 7 days of request-level telemetry (timestamp, latency, error code, pod) plus the existing Horizontal Pod Autoscaler (HPA) and node-group configs. Analyze traffic pat…
- Model Serving
- Kubernetes
- Autoscaling
Machine Learning at Scale - CodeSeniorNew
Cost-Optimize a 24/7 LLM API Cluster
Profile the current usage (24-hour trace, per-team breakdown). Pick a cost-optimization mix from: time-based autoscaling, spot/preemptible instances with graceful drain, smarter…
- LLM Serving
- Autoscaling
- Ray
ML Engineering and Production ML - AnalysisIntermediateNew
Cost-Optimize a Misshapen Kubernetes Cluster
Receive 30 days of cluster metrics (Prometheus + AWS Cost Explorer exports), Helm releases, and PodDisruptionBudgets per namespace. Profile: identify the top 3 cost drivers (lik…
- Kubernetes
- Cost Optimization
- AWS
Cloud Computing
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
Related skill families
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Sponsor a challenge and meet candidates through actual work.
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