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.
- CodeBeginnerNew
Containerize a Legacy Java Monolith and Deploy to ECS
Receive the Java 8 monolith source (around 320k lines), the current Tomcat + Apache HTTPD config, and 30 days of production traffic logs. Containerize the application (multi-sta…
- Containerization
- Docker
- AWS Or Azure
Cloud Computing - DesignSeniorNew
Multi-Region Active-Active Architecture for a Gaming Backend
Read the current architecture (single-region: ECS + RDS Aurora + Redis + S3) and traffic mix (around 60 percent APAC, 25 percent NA, 15 percent EU). Design a 3-region active-act…
- Multi Region Architecture
- AWS Or Azure
- Terraform
Cloud Computing - PresentationIntermediateNew
Digital Innovation Pitch: AI-Powered Logistics Optimization
Research the state of AI in logistics (route optimization, demand prediction, computer vision for warehouse automation). Select one innovation area and develop: (1) Problem stat…
- Digital Innovation
- Tech Enabled Business Transformation
- Cloud Computing
Open coursework - CodeIntermediateNew
Build a Self-Service Internal Developer Platform on Backstage
Stand up a Backstage instance (Docker-Compose for local, EKS for prototype hosting). Build 3 software templates: (1) New Go microservice (repo + CI + ECS service + Terraform + b…
- Internal Developer Platform
- Backstage
- Terraform
Cloud Computing Practice your coursework on real scenarios.
Every challenge is shaped from real industry context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- AnalysisIntermediateNew
Cost-Profile a Spark Job at Scale and Cut the Bill in Half
Receive the PySpark job (around 1,800 lines), 5 nights of Spark UI + EMR metrics, and the EMR cluster config. Profile to find the top 3 cost drivers (likely candidates: skewed j…
- Apache Spark
- Finops & Cost Optimization
- Etl Pipelines
Big Data and Data-Intensive Systems - 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 Orchestration
- Autoscaling
Machine Learning at Scale - CodeSeniorNew
Stand Up a Data Platform for a Mobility-Data Startup's First ML Model
As a 4-person team, build (1) a streaming ingestion path from a simulated telemetry source (Kafka + Python producer is fine); (2) a batch ETL job into a small warehouse (DuckDB …
- Data Engineering
- Streaming Ingestion
- Feature Store
AI Software Engineering Group Project - 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 - Browse challenges
Explore role
Product Manager
Ship product that solves real user problems. Combine user research, prototyping, and stakeholder alignment to turn ambiguous briefs into measurable wins — the role at the centre of modern software teams.
- CodeIntermediateNew
Build a Serverless ETL Pipeline for a Climate-Tech Sensor Fleet
Build the pipeline using managed services only (e.g., S3 + Lambda + EventBridge + Glue, or GCS + Cloud Functions + Cloud Scheduler + BigQuery external tables). Source the data f…
- Serverless Architecture
- Etl Pipelines
- Terraform
Cloud Computing for Data and ML - DesignSeniorNew
Multi-Region Failover for an Enterprise RAG Service
Design and prototype: (1) a primary-region deployment of the RAG service (vector DB + LLM inference + retrieval API), (2) a passive secondary region with replicated vector store…
- Multi Region Architecture
- Disaster Recovery
- Terraform
Cloud Computing for Data and ML - StrategyIntermediateNew
Refactor a Tangled Terraform Repo for a Multi-Account AWS Estate
Audit the existing repo and produce a dependency map across modules and accounts. Design the target layout: account-level base modules, region-level shared infra, environment-le…
- Terraform
- Terragrunt
- Terraform
DevOps and Secure Deployment - 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
- Finops & Cost Optimization
- Change Detection
Vector Databases and Embeddings Build a verifiable portfolio.
Submissions become evidence. Reviewers with shipping experience score against a rubric; the result becomes a credential anyone can verify.
Why Ewance
- DesignBeginnerNew
Scaling a Sydney D2C Cosmetics Startup's Data Pipeline
You are tasked with designing a cloud-based data pipeline for GlowUp. The pipeline must ingest real-time user events (page views, purchases, returns) from web and mobile apps, p…
- Cloud Computing
- Apache Spark
- Nosql
Big Data and Cloud Technologies - CodeIntermediateNew
Implement Authenticated Encryption for a Document Service
Design the envelope-encryption hierarchy: customer Key Encryption Key (KEK) held in AWS KMS (Key Management Service), Data Encryption Keys (DEKs) wrapped per document. Use AES-2…
- Applied Cryptography
- Aead
- Key Management
Applied Cryptography - DesignIntermediateNew
Build a Multi-Tenant SaaS Foundation on Kubernetes
Design the multi-tenant model: namespace-per-tenant for compute isolation, per-tenant Postgres schemas inside a shared RDS instance for data, per-tenant S3 prefixes with bucket …
- Kubernetes Orchestration
- Multi Tenancy Architecture
- AWS Or Azure
Cloud Computing - DesignIntermediateNew
IT Architecture Overhaul for a 40-Person SaaS Scale-Up
Design a microservices-based architecture with multi-tenancy, API gateway, and compliance features. Propose a migration strategy (strangler fig pattern) over 12 months. Deliver …
- Microservices Patterns
- Multi Tenancy Architecture
- Multi Cloud Architecture
Information Systems and IT Management - DesignIntermediateNew
Cloud Architecture Design for a Multi-Tenant SaaS Platform
Deliver a comprehensive cloud architecture design covering: (1) Multi-tenancy strategy (shared database with row-level security vs. schema-per-tenant vs. database-per-tenant — j…
- Cloud Computing
- It Security
- Web Development
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…
- Finops & Cost Optimization
- Latency Optimization
- Prompt Compression
LLM Application Development - 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 Orchestration
- Finops & Cost Optimization
- AWS Or Azure
Cloud Computing - AnalysisBeginnerNew
Cardinality and Cost Control on a Datadog-Based Gaming Platform
Receive an anonymized export of Datadog metric inventory (metric names, tag-cardinality counts, monthly cost per metric, team owner). Identify the top 30 cost-driver metrics, cl…
- Cardinality Control
- Datadog
- Finops & Cost Optimization
Software Observability
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.
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