Any concept.
clear in 60 seconds.

The RED Method helps monitor microservices using Rate, Errors, and Duration metrics.

Alerting helps notify the right people about production issues quickly.

Monitoring Kafka consumer lag helps prevent production problems by ensuring consumers keep up with message traffic.

The USE Method helps find and analyze infrastructure bottlenecks in software systems.

Logs, metrics, and traces help engineers debug issues in software systems.

Observability helps engineers understand system behavior to debug production issues effectively.

ZooKeeper watches notify clients of changes, avoiding constant polling and reducing server load.

Database bottlenecks slow down performance, but identifying them helps optimize and scale effectively.

Microservices can communicate using five key patterns based on their needs.

SLIs measure service performance, SLOs set reliability targets, and SLAs are customer agreements.

The Bulkhead Pattern isolates resources to protect critical workloads from failures.

REST API design focuses on creating clean, efficient, and scalable web services.

Structured logging helps in quickly identifying issues by organizing log data consistently.

Optimizing Elasticsearch involves using filters, caching, and measuring performance.

Microservices are useful when you need independent scaling, deployment, and clear boundaries in software design.

Timeouts in distributed systems indicate suspicion, not confirmed failure.

FAANG engineers use high-level design principles to create scalable systems.

Monolithic and microservices architectures each have unique advantages and challenges for software development.

You can replay Kafka events safely by separating live and replay processes.

Choosing the right boundaries for microservices is crucial for effective architecture.

Optimistic and pessimistic locking are strategies to manage database access during concurrent transactions.

Scaling databases involves deciding whether to enhance read or write capabilities based on traffic patterns.

The Transactional Outbox Pattern ensures database updates and event publishing are synchronized to avoid losing events.

gRPC supports four communication patterns: Unary, Server Streaming, Client Streaming, and Bidirectional Streaming.

Microservices and modular monoliths differ mainly in deployment and communication methods.

FAANG interviewers evaluate problem understanding, architecture, scalability, and communication skills.

Token Bucket allows burst traffic, while Leaky Bucket smooths out traffic flow.

Distributed backpressure helps manage the flow of work between services to prevent overload.

Dependency failures can disrupt applications, but resilience patterns can help manage them.

Kafka commit strategies determine how offsets are managed during message processing.

Kafka's commitSync waits for confirmation, while commitAsync continues immediately.

Older offsets can overwrite newer ones in Kafka if not handled properly.

Choosing the right distributed lock depends on your system's needs and existing tools.

Fail Fast means stopping quickly on errors, while Fail Safe ensures safety in failures.