Scalable Systems Project Report – [Project Title]

1. Business Need & Stakeholder Goals

Describe the core business challenge or opportunity. What outcome did stakeholders need? Who were the users, decision-makers, and technical owners? What assumptions were validated early?

2. My Role & Strategic Involvement

Define your role (e.g., Systems Architect, DevOps Engineer, Data Pipeline Lead). Describe how you contributed to vision-setting, architecture, security, scalability, automation, or infrastructure.

3. Initial Architecture & Key Design Choices

What architectural patterns or cloud-native designs did you use? Why? (e.g., microservices, event-driven, serverless, container orchestration). Mention trade-offs in latency, throughput, cost, or operational complexity.

4. Functional + Non-Functional Requirements

Summarize the core functionality, but also document NFRs (e.g., uptime targets, latency SLAs, autoscaling thresholds, data retention, security compliance).

5. Timeline & Delivery Flow

How did you structure development and delivery (Agile, DevOps, CI/CD)? What stages (MVP, V1, V2...) did you plan for? How did you break the system into milestones?

6. Performance, Scaling, and Observability

How did you plan to support scale to 1M users in 3 years? What stress testing, load balancing, caching, CDN, or sharding strategies did you implement? How did you monitor and log the system?

7. Risks, Constraints & Mitigations

Identify the top 2-3 risks (technical debt, vendor lock-in, downtime, legacy systems). How did you mitigate them? Include fallback plans or redundancy design if relevant.

8. Solution Evaluation & Feedback Loop

What metrics, feedback, or tests did you use to evaluate the system post-launch? What feedback did you gather from DevOps tools, users, or business owners? How did this shape the next iteration?

9. Lessons Learned & Future Roadmap

What will you improve or do differently in a future iteration? Describe key lessons, including those related to scaling, collaboration, or architecture strategy. Optionally: What’s next?

🛠️ Tools & Platforms Used

AWS / GCP / Azure

Docker + Kubernetes

Airflow / Spark / Kafka

Terraform / Pulumi

PostgreSQL / Snowflake / Redis

Prometheus + Grafana / Datadog

LangChain / LangGraph (for AI agents)