. Data Structures & Algorithms
Topics to cover: Arrays, Linked Lists, Stacks, Queues, Trees, Graphs, Heaps, Hash Tables, Tries.
Algorithmic Techniques: Sorting, Searching, Dynamic Programming, Divide & Conquer, Greedy Algorithms, Backtracking.
Complexity Analysis: Time and Space complexity (Big O notation).
2. Cloud
Cloud Concepts: Cloud computing models (IaaS, PaaS, SaaS), Cloud providers (AWS, Azure, Google Cloud).
Services: EC2, Lambda, S3, RDS, CloudFormation, CDK, Kubernetes.
Deployment & Scalability: Autoscaling, Load balancing, Containers, Serverless architecture, CI/CD pipelines.
3. System Design
Core Topics: High-level design, Low-level design, Designing scalable systems, Distributed systems, CAP theorem, Consistency, Availability, Partition tolerance.
Architecture Patterns: Microservices, Monolithic, Event-driven architecture, CQRS.
Tools: Databases (SQL, NoSQL), Caching (Redis, Memcached), Message Queues (Kafka, RabbitMQ).
4. Scalability
Vertical vs Horizontal Scaling: When to use each approach.
Load Balancing: Types (Round-robin, Weighted, etc.), Algorithms.
Caching: Distributed caching systems, Strategies like cache eviction policies, Cache-aside pattern.
5. Behavioral Interview
STAR Method: Situation, Task, Action, Result framework for answering questions.
Leadership Qualities: Conflict resolution, Team collaboration, Problem-solving approach.