Start by strengthening core data structures — arrays, strings, linked lists, stacks, trees, graphs and heaps — then move to dynamic programming and greedy problems. Follow a pattern-based plan: learn one pattern, solve 15–20 problems on it, and revise weekly. In the final weeks, take timed mock interviews so you get comfortable explaining your approach out loud under pressure.

Use a clear structure: restate the problem and constraints, discuss a brute-force solution, optimize it with the right data structure, and state time and space complexity before coding. Interviewers evaluate your thought process as much as your final code, so think aloud throughout. If you get stuck, ask for a hint instead of going silent — communication is a big part of the evaluation.

Freshers are mostly tested on arrays and strings (two pointers, sliding window), linked lists, stacks and queues, binary search, recursion, trees and BSTs, and graph traversal like BFS and DFS. Easy-to-medium level problems dominate fresher rounds in India, sometimes along with puzzles or SQL basics. Focus on consistent practice across these patterns instead of memorizing individual solutions.

Get fluent with Java's built-in tools — ArrayList, HashMap, HashSet, PriorityQueue, ArrayDeque and Arrays.sort() — because picking the right structure often decides your solution's efficiency. Solve topic-wise problems in Java itself so you internalize edge cases like integer overflow and null handling. Sticking to one language from day one makes recall much faster during the actual interview.

Work backwards from the role: most companies test DSA, core CS fundamentals (OS, DBMS, OOPs, networks), and your projects, with system design added for senior positions. Build an 8–12 week preparation calendar, solve problems daily, prepare a crisp self-introduction and project explanation, and complete a few mock interviews beforehand. Referrals also matter a lot in India, so network with engineers at your target companies.

Google's process typically includes one or two screening rounds followed by several rounds on DSA, problem-solving and behavioral assessment, with system design for experienced roles. Prioritize medium-to-hard LeetCode problems, write clean and well-structured code, and practice explaining trade-offs clearly. Since feedback is based on how you think, timed mock interviews are one of the highest-ROI steps before you apply.

In India it usually flows like this: an online assessment or coding test, one or two technical rounds on DSA and CS fundamentals, a project or system design round for experienced roles, and finally an HR or hiring-manager discussion. Product companies often add team-matching or culture rounds. The full cycle generally takes one to three weeks, so ask your recruiter for the structure in advance and prepare round by round.

Expect one or two DSA coding problems, core subject questions on OOPs, DBMS, OS and SQL, deep-dives into your resume projects and internships, and basic HR questions like "why should we hire you?" Some companies also include aptitude or pseudocode rounds. Prepare short, confident explanations of every project on your resume — interviewers probe them closely to verify you actually built what's written.

Smart casuals are the safe default: a collared shirt or neat t-shirt with trousers and clean shoes for product companies and startups, and formal shirts or business casuals for MNCs and banking tech roles. For online interviews, put in the same effort on camera and keep your background tidy. When in doubt, being slightly overdressed never hurts — nobody penalizes neat formals.

Learn in this order: solid core Java and Spring Boot, then REST APIs and Spring Data JPA with a real database, and finally microservices concepts — service discovery, API gateway, centralized config, resilience patterns and messaging with Kafka. Build two or three small services, such as separate order and payment services, containerize them with Docker, and deploy one project on the cloud to make your resume stand out.

They are small, independently deployable services built with the Spring ecosystem — Spring Boot to create REST APIs quickly and Spring Cloud for concerns like service discovery (Eureka), API gateway, centralized configuration, circuit breakers and load balancing. Each service owns its own database and communicates over HTTP or messaging, letting Java teams scale, deploy and release parts of a large application independently.

Interviewers commonly ask about monolith vs microservices trade-offs, how services communicate (REST, gRPC or Kafka), database-per-service design, distributed transactions using the Saga pattern, API gateway responsibilities, circuit breakers, service discovery, and securing APIs with JWT or OAuth. Experienced candidates should also prepare for deep-dives on scaling, idempotency and eventual consistency, ideally explained through a real project.

Focus on API Gateway, Circuit Breaker, Saga, CQRS, Event Sourcing, Service Registry and Discovery, Strangler Fig and Backend-for-Frontend. Be ready to explain the specific problem each pattern solves with a small example — interviewers test whether you can apply these patterns in a scenario, not just define them.

Write a multi-stage Dockerfile that builds your Spring Boot JAR with Maven or Gradle and copies it onto a slim JRE base image, then expose the service port and run it with java -jar. Use docker-compose to run the service alongside dependencies like PostgreSQL and Kafka locally. Keep images small, externalize configuration through environment variables, and use docker logs to debug startup issues.

The standard path is to containerize each service with Docker, push the images to Amazon ECR, and run them on ECS (Fargate) or EKS behind an Application Load Balancer. Manage configuration with environment variables or Parameter Store, use RDS for databases, and CloudWatch for logs and monitoring. For a simpler start, deploy a single Spring Boot JAR to Elastic Beanstalk and move to ECS as your services grow.