Java (Backend / Enterprise Focus) Developer with State/Federal experience

Please make sure you are very family with Angular, Spring Boot, Spring Batch and Kafka topics

See below for a guide

Angular: Lifecycle Hooks, Pipes, Directives, Data binding

Java Interview Prep (Backend / Enterprise Focus)

Application Scale & Performance

• What is the transaction volume of your application? (requests/sec, peak load)
• How do you handle high concurrency?
• How do you optimize performance (caching, async processing, connection pools)?

Failure Handling & Reliability

• How do you handle failures in your application?
• What retry mechanisms do you use?
• Retry count, backoff strategy (exponential backoff)
• Have you used a Dead Letter Queue (DLQ)?
• When do messages go there?
• How are DLQ messages monitored and reprocessed?

Tools & Frameworks

• What frameworks/tools do you use?
• Spring Boot, Spring Retry, Resilience4j, Hystrix (legacy), etc.
• How do you monitor and log issues?
• Logs, metrics, alerts

JVM & Runtime

• Common JVM issues you ve faced
• Memory leaks, pauses, OutOfMemoryError
• How do you troubleshoot JVM issues?
• Heap dumps, logs, thread dumps

Security & Authorization

• How do you authorize a user on the UI side?
• JWT tokens, session-based auth, OAuth
• How does UI authorization connect to backend authorization?
• How do you design application security end-to-end?
• Authentication vs authorization
• Role-based access control (RBAC)
• Securing APIs

Kafka Interview Prep

Core Concepts

• Explain Producer, Consumer, and Topic
• What is a consumer group and why is it important?
• What is a partition and how does it affect performance?

Authentication & Authorization

• How does Kafka handle authentication?
• SSL, SASL
• How do you authorize producers and consumers?
• ACLs (who can publish/consume)

Kafka Operations

• How do you create topics?
• Partitions, replication factor
• How do you create a producer?
• How do you configure a consumer?

Message Flow & Behavior

• If a producer publishes a message, what happens internally?
• What happens if the consumer is not running?
• What happens if the consumer fails while processing a message?
• Offset commits
• At-least-once vs exactly-once semantics

Error Handling

• How do you handle exceptions in Kafka consumers?
• What happens when message processing fails?
• How do you use retries and Dead Letter Topics in Kafka?

Reliability & Guarantees

• How does Kafka ensure durability?
• How does replication work?
• What happens if a broker goes down?

Kafka vs Other Messaging Systems

• What makes Kafka different from RabbitMQ / ActiveMQ?
• Pull-based model
• High throughput
• Message retention
• Replayability

Scaling & Design (Scenario-Based)

• How do you scale Kafka?
• Increase partitions
• Add brokers
• How do partitions help with parallel processing?
• How do you design Kafka for high throughput and fault tolerance?