Computer Science
DevOps & CI/CD Challenges
DevOps & CI/CD challenges put you inside the work of shipping software safely and often. You'll develop skills in Version Control with Git, build CI/CD Pipelines, and package services with Docker, then run them through Kubernetes orchestration.
From there you'll handle the harder edges — GitOps, Helm chart authoring, Multi-cluster Kubernetes, Service mesh, and Zero-downtime deploys — working with Ansible / Terraform automation the way platform teams actually do. Each challenge you solve earns a verified credential you can share with recruiters.
Recommended Challenges
· Kubernetes orchestration Clear
DesignBeginnerNewMove an EdTech Platform's 4 Clusters to GitOps with ArgoCD
Using only the materials provided — the migration case file (incident_dossier), the service inventory dataset (service_inventory), and the platform team's target-state brief (ta…
- Argocd
- Kubernetes
- Kustomize
Open coursework- CodeSeniorNew
Linkerd to Istio Migration for a Multi-Cluster Platform
Phase 1: install Istio alongside Linkerd in PERMISSIVE mode (Istio sidecars injected, Linkerd proxies remain). Phase 2: migrate non-critical namespaces first (4 namespaces) by r…
- Istio
- Linkerd
- Service Mesh
Open coursework - CodeIntermediateNew
Migrate Stateful Workloads to StatefulSets with Storage Class Tuning
Receive the current Redis Sentinel topology (3 nodes, ~120GB data), the EBS gp3 baseline performance requirements (3,000 IOPS, 125 MB/s), and the cluster (EKS 1.29 with the EBS …
- Kubernetes
- Statefulsets
- Storage Classes
Container Orchestration with Kubernetes - CodeIntermediateNew
Build a Canary Rollout for a Production Recommender
Pick a serving stack (Triton, Seldon Core, KServe, or BentoML). Implement two-model traffic splitting with a configurable percentage (start at 5%). Wire up online metric collect…
- Canary Deployment
- Kubernetes
- Ab Testing
ML Engineering and Production ML 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
- DesignBeginnerNew
Design a Golden-Path Service Template for a Scaling SaaS Platform Team
Using the current-state assessment (provided), the platform team's golden-path requirements specification (provided), and the baseline deployment-metrics dataset (provided), des…
- Platform Engineering
- Golden Paths
- Backstage
Open coursework - CodeBeginnerNew
Tune Autoscaling for a Cost-Sensitive Workload with HPA + KEDA
Receive the service's current Deployment + HorizontalPodAutoscaler config (static 12-20 replicas), 90 days of traffic logs + Kafka-lag metrics, and the SLA (p99 < 250ms, error r…
- Kubernetes
- Autoscaling
- Keda
Container Orchestration with Kubernetes - DesignIntermediateNew
Stand Up a Self-Service Developer Platform on Backstage
Read the company case file, the squad-and-service inventory, and the Platform v1 postmortem, and consult the official Backstage software-templates documentation for the mechanic…
- Internal Developer Platform
- Backstage
- Terraform
Open coursework - CodeIntermediateNew
Stand Up a Backstage Developer Portal for a Frankfurt Fintech
Using the provided service inventory, ownership map, and rollout brief, build and deploy a Backstage portal on the company's existing Kubernetes platform and populate its catalo…
- Backstage
- Platform Engineering
- Service Catalog
Open coursework - 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.
- DesignIntermediateNew
Build a Multi-Tenant Kubernetes Foundation for Veterinary-Clinic SaaS
Using the provided tenant tier specification and tenant roster, design and prototype a multi-tenant model where each tenant gets its own Kubernetes namespace for compute, its ow…
- Kubernetes
- Multi Tenancy
- AWS
Open coursework - CodeIntermediateNew
Build a GitOps Rollout Pipeline with ArgoCD Progressive Delivery
Receive the current CI pipeline (GitHub Actions runs kubectl apply against EKS), one representative service (Go API, 8 replicas, 4ms p99 SLO, 0.1 percent error-rate SLO), and ac…
- Kubernetes
- Gitops
- Argocd
Container Orchestration with Kubernetes - StrategyIntermediateNew
Migrating a 40-Person SaaS Scale-Up to Cloud-Native Architecture
You are to create a detailed migration plan for TaskFlow. The plan must include breaking the monolith into at least 4 microservices, containerizing them with Docker, orchestrati…
- Microservices
- Docker
- Kubernetes
Big Data and Cloud Technologies - 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 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
- CodeIntermediateNew
Roll Out mTLS Across 80 Microservices with Istio
Install Istio (current LTS) in ambient mode where possible, sidecar mode where ambient is not yet supported by the service. Phase 1: enable PERMISSIVE mTLS namespace by namespac…
- Istio
- Mtls
- Kubernetes
Service Mesh and Microservices Networking - DesignIntermediateNew
Build a Multi-Region Online Inference Service with SLAs
Design the topology: model artifact storage, regional inference fleets (Triton, vLLM, or BentoML), traffic router, observability stack (Prometheus + Grafana). Pick a rollout str…
- Inference Serving
- Multi Region Deployment
- Kubernetes
Machine Learning Systems - CodeIntermediateNew
Containerized Model Inference on Kubernetes for a Fintech
You receive a pre-trained credit-risk model (a LightGBM model file) and a sample request payload. Containerize a FastAPI inference service, deploy to EKS or GKE (a single-zone c…
- Kubernetes
- Containerization
- Autoscaling
Cloud Computing for Data and ML - CodeIntermediateNew
Harden a Linux Container Runtime Against Privilege Escalation
Receive the pen-test report (with attack chain), the current cluster config (EKS 1.29, default Amazon Linux 2023 worker nodes), and 3 representative workload classes (web API, a…
- Os Security
- Linux Hardening
- Apparmor
Open coursework - DesignIntermediateNew
Design Multi-Tenant Network Policies with Calico Tier Enforcement
Receive the cluster topology (120 customer namespaces + 4 platform namespaces), the application traffic patterns (frontend talks to backend talks to its tenant's database), and …
- Kubernetes
- Network Policy
- Calico
Container Orchestration with Kubernetes - CodeIntermediateNew
Roll Out OpenTelemetry Tracing Across a Microservices Fintech
Receive an anonymized service map (90 services, payment-critical path of 12), a runtime mix (Node.js, Go, Java), and existing logging/metrics setup. Define: an OTel SDK adoption…
- Distributed Tracing
- Opentelemetry
- Sampling Strategies
Software Observability - CodeIntermediateNew
Design a Multi-Tenant Kubernetes Namespace-Provisioning Self-Service
Design and build a Backstage scaffolder that lets a squad request a namespace (specifying environment, owners, expected scale). The scaffolder generates a pull request to a GitO…
- Platform Engineering
- Kubernetes
- Self Service
Platform Engineering - CodeIntermediateNew
Canary Deployments via Mesh Traffic Splitting for a Streaming Platform
Set up Flagger with Istio as the traffic provider. Define a canary policy for the playback-API service: 5 percent → 25 percent → 50 percent → 100 percent with 5-minute bake at e…
- Istio
- Flagger
- Canary Deployment
Service Mesh and Microservices Networking - 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.
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