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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Effective Strategies for Database Migrations Without Downtime
Learn how to perform zero-downtime PostgreSQL database migrations with backward-compatible schema changes, feature toggles, and phased rollouts to maintain high availability.
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Implementing Kafka Connect for Streamlined Integration with Databases and Data Lakes
Discover how Kafka Connect enables streamlined real-time data integration from databases to data lakes, optimizing your data pipeline with best practices and code samples.
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Leveraging Spring Boot Actuator for Production-Grade Monitoring and Custom Metrics
Discover effective production monitoring and custom metrics with Spring Boot Actuator, Micrometer, and visualization tools.
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Implementing Java Automated Log Correlation for Microservices Debugging
This article explains automated log correlation for Java microservices, offering practical implementation tips and code examples to simplify distributed debugging.
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Practical Guide to Managing Spring Boot Application Configuration with Spring Cloud Config
This guide shows how to implement a Spring Cloud Config Server with Git backend and a Spring Boot client with runtime config refresh and secure secrets management for microservices.
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Implementing Java Custom Metrics with Micrometer for Fine-Grained Application Monitoring
A detailed guide for Java developers on implementing custom application metrics with Micrometer, illustrating counters, gauges, and timers integrated into a user service and exposed to Prometheus.
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Implementing Scalable Fine-Tuning Workflows for Large Language Models in Production
This guide helps AI engineers build scalable fine-tuning workflows for large language models using PyTorch Lightning, PEFT, and MLFlow, balancing performance and resource use.
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Implementing Blue-Green Deployments to Minimize Downtime in Production
Implement Blue-Green Deployments to minimize production downtime and enhance deployment reliability with automated CI/CD pipelines and best practices.
