Author
Kim
Backend software engineer working with Java, Spring Boot, and Kafka. I write about engineering problems, performance work, and architecture decisions from development and operations.
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Kafka Broker Maintenance Without Downtime: A Rolling Restart Runbook for KRaft Clusters
A recorded rolling restart of a 3-broker Kafka 4.0.0 KRaft cluster with a live acks=all producer: what to check between brokers, what the ISR and controller do, and why the usual grep-based health check cannot fail.
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Implementing Multi-Tenant Architecture in Spring Boot for SaaS Applications
Learn how to implement schema-based multi-tenancy in Spring Boot for SaaS apps with Hibernate, managing tenant context, datasource setup, security, and production best practices.
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Building Custom Java Classloaders to Enable Plugin Architectures in Enterprise Applications
Discover techniques to create custom Java classloaders facilitating dynamic plugin architectures in enterprise apps for enhanced modularity and scalability.
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Building Automated Retraining Pipelines Triggered by Model Performance Metrics in Production
Explore building automated retraining pipelines triggered by model metrics to ensure ongoing model accuracy and seamless MLOps integration.
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Implementing Graceful Shutdowns in Production Node.js Services
A comprehensive guide to implementing graceful shutdowns in Node.js production services for reliable, clean exits and resource management.
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Implementing Kafka Transactional Outbox Pattern for Reliable Event Publishing
Explore implementing the Kafka transactional outbox pattern for reliable, exactly-once event publishing and strong data consistency in distributed architectures.
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Implementing Rate Limiting in Spring Boot APIs Using Bucket4j for Production Readiness
Comprehensive guide to implement rate limiting in Spring Boot APIs using Bucket4j, covering setup, implementation, production readiness, and testing.
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Practical Guide to Java CompletableFuture Exception Handling and Composition
A comprehensive engineering guide for Java developers mastering CompletableFuture for resilient async workflows, including exception handling, composition, verification, and best practices.
