AWS
Use a project where AWS changes a real implementation decision. Show the code, artifact, test, metric or operational evidence behind the claim.
Build deployable AWS projects spanning hosting, networking, serverless, databases, monitoring, security and cost control.
A portfolio is stronger when each project makes one or two important capabilities easy to inspect instead of trying to mention every technology at once.
Use a project where AWS changes a real implementation decision. Show the code, artifact, test, metric or operational evidence behind the claim.
Use a project where Networking changes a real implementation decision. Show the code, artifact, test, metric or operational evidence behind the claim.
Use a project where Serverless changes a real implementation decision. Show the code, artifact, test, metric or operational evidence behind the claim.
Use a project where IAM changes a real implementation decision. Show the code, artifact, test, metric or operational evidence behind the claim.
Use a project where Monitoring changes a real implementation decision. Show the code, artifact, test, metric or operational evidence behind the claim.
Use a project where Cost control changes a real implementation decision. Show the code, artifact, test, metric or operational evidence behind the claim.
Choose one project you can finish, deploy and explain deeply. Quality of proof matters more than collecting unfinished repositories.
Host a static site with S3, CloudFront, Route 53 and TLS while documenting caching and deployment.
Turn a resume into a full cloud application with frontend hosting, API, database and CI/CD.
Build a REST API with API Gateway and Lambda, least-privilege IAM and CloudWatch logs.
Process uploaded images with S3 events and Lambda while handling permissions and failures.
Deploy and secure a Linux web server on EC2 so you understand the infrastructure behind running an application.
Design a VPC with public and private subnets, route tables, internet access and controlled outbound connectivity.
Connect a deployed application to a managed relational database with backups, access controls and recovery thinking.
Instrument an AWS workload with logs, metrics, dashboards, alarms and SNS notifications so failures become visible.
Build budget thresholds and notifications that make cloud spend visible before it becomes a surprise.
Build a deployable redirect service with API Gateway, Lambda and DynamoDB, then measure latency and failure behavior.
Deploy an app across public/private subnets with controlled networking and an RDS database.
Create CloudWatch dashboards, alarms, SNS notifications and budget alerts for an existing workload.
Orchestrate a multi-step serverless workflow with retries, branching, failure handling and observable execution history.
Containerize an application and operate it on ECS with load balancing, health checks, secrets and rolling deployments.
These are optional signals from official issuers, not requirements for the role. When a pasted job explicitly mentions a credential, SkillChirp can surface it separately from project skill coverage.
Foundational AWS credential for cloud concepts, AWS services, security, architecture, pricing and support.
Architecture-focused AWS credential covering secure, resilient, high-performing and cost-aware cloud solutions.
Developer-focused AWS credential for building, testing, deploying and debugging cloud applications and delivery workflows.
Operations-focused AWS credential for deploying, managing, monitoring and operating workloads.
AWS data credential centered on data models, ingestion and transformation, lifecycle management and data quality.
Foundational Azure credential covering cloud concepts, Azure architecture and services, management and governance.
Azure operations credential covering identities, governance, storage, compute, virtual networking and monitoring.
Beginner AI credential covering AI concepts and implementing AI solutions with Microsoft Azure tooling.
Foundational credential for relational and non-relational data concepts and Azure data workloads.
Google Cloud credential for setting up, deploying, securing, operating and monitoring cloud solutions.
Advanced Google Cloud credential focused on designing and managing secure, scalable cloud architecture.
Professional credential for building scalable, reliable cloud-native applications on Google Cloud.
Professional credential centered on reliable delivery, SRE practices, CI/CD, observability and service performance.
Professional data credential for designing, building, operationalizing and securing data-processing systems.
Professional ML credential for building, productionizing and monitoring machine-learning and generative-AI solutions.
Choose the project that best fills a gap in your current portfolio rather than the one with the longest technology list.
Keep scope small enough to finish. A deployed, testable core gives you more evidence than an ambitious unfinished system.
Explain architecture, constraints, failure states, testing and what you would change with more time.
Use SkillChirp discovery and Battles where appropriate to expose the project to outside feedback instead of leaving it hidden in a repository.
After you ship it, use the rest of SkillChirp to get discovery, validation and feedback instead of leaving the work hidden in a repository.