Principal Engineer

📚 Table of Contents

• 📚 Table of Contents
• 🔧 Back-end
  • 🧱 Microservices Architecture
  • ☕️ Java + Spring Boot
  • ⚙️ Apache Kafka
  • 🛢 PostgreSQL
• 🖼 Front-end
  • ⚛️ React
  • 🔗 GraphQL
• ☁️ 3. DevOps and Infrastructure
  • 🔄 Harness CI/CD
  • ☁️ AWS

🔧 Back-end

🧱 Microservices Architecture

• Principles: Domain-driven design (DDD), loose coupling, high cohesion, bounded contexts.
• Service communication: REST vs. gRPC, Kafka (event-driven), synchronous vs. asynchronous flows.
• Common patterns: API Gateway, Circuit Breaker, Saga/Orchestration, CQRS, Service Registry (e.g., Eureka), Config Server.
• Deployment: Independent service deployments, blue/green or canary releases.

☕️ Java + Spring Boot

• Core knowledge:
  • Spring Boot Autoconfiguration, Profiles, Actuators
  • Dependency injection with Spring Framework
  • Exception handling, validation, and AOP
• Advanced topics:
  • Spring Cloud: Config, Discovery, Gateway
  • Reactive programming (WebFlux) – especially with Kafka or streaming
  • Observability with Spring Boot: Micrometer, Prometheus, Zipkin

⚙️ Apache Kafka

• Concepts:
  • Topics, partitions, consumer groups, offset management
  • At-least-once vs. exactly-once semantics
• Use Cases: Event sourcing, change data capture (CDC), stream processing
• Tools: Kafka Streams, Kafka Connect, schema registry (e.g., Avro with Confluent)

🛢 PostgreSQL

• Schema design: normalization, indexing, constraints, partitioning
• Performance: query optimization (EXPLAIN ANALYZE), caching strategies, connection pooling (HikariCP)
• Advanced: JSONB support, full-text search, triggers, stored procedures
• Scaling: Replication, sharding, and failover

🖼 Front-end

⚛️ React

• Architecture: Micro frontends (MFEs), independent deployability, cross-app communication
• Patterns:
  • Component-driven design (Storybook, Atomic Design)
  • State management (Redux, Zustand, or React Query)
  • Code splitting, lazy loading, and performance optimization
• Testing: Unit (Jest), integration (React Testing Library), E2E (Playwright/Cypress)

🔗 GraphQL

• Design: Schema-first vs. code-first, queries, mutations, subscriptions
• Tooling: Apollo Client/Server, caching, batching
• Security: Depth limiting, query complexity analysis
• Performance: N+1 problem and dataloader pattern, persisted queries

☁️ 3. DevOps and Infrastructure

🔄 Harness CI/CD

• Pipelines: Understand workflows, GitOps, triggers, rollback strategies
• Templates and Reuse: Use of YAML templates, stages, and approval gates
• Governance: RBAC, policy enforcement, secrets management
• Integration: With artifact repositories (e.g., Artifactory), test tools, monitoring

☁️ AWS

• Core services:
  • Compute: EC2, ECS/EKS, Lambda (for serverless microservices)
  • Networking: VPC, ALB/NLB, Route53, PrivateLink, NAT Gateways
  • Storage: S3, EBS, EFS
  • Databases: RDS (PostgreSQL), DynamoDB, ElastiCache
• Security: IAM roles/policies, security groups, KMS, secrets manager
• DevOps on AWS: CloudWatch, CloudTrail, X-Ray, Systems Manager
• IaC: Terraform vs. AWS CDK, CloudFormation