Jkoder.com Tutorials, Tips and interview questions for Java, J2EE, Android, Spring, Hibernate, Javascript and other languages for software developers
In recent years, the rise of machine learning and deep learning has made vector databases increasingly important for managing high-dimensional data... Read More »
Best practices for prompt engineering
Best Practices for Prompt Engineering: Crafting Effective Interactions with AI Models Read More »
Integrating RabbitMQ with AI-powered apps
Integrating RabbitMQ with AI-Powered Apps: A Comprehensive Guide Read More »
How to use Ollama for local LLM development
Large Language Models (LLMs) have revolutionized the way developers interact with artificial intelligence, enabling applications like chatbots, cod... Read More »
Spring Boot with Weaviate for vector search
The world of search is evolving. Traditional keyword-based search systems are giving way to vector search, which utilizes machine learning and sema... Read More »
Vue.js component development best practices
Discover essential Vue.js component development best practices with detailed explanations, examples, and code snippets for scalable applications. Read More »
GraphQL API development with Node.js and Apollo Server
Learn how to build GraphQL APIs with Node.js and Apollo Server. Step-by-step guide with code examples for schema design, resolvers, and queries. Read More »
Redis caching strategies for web applications
Explore Redis caching strategies for web applications, including cache-aside, write-through, and distributed caching with examples and code snippets. Read More »
Building microservices with Spring Boot and Kubernetes
# Building Microservices with Spring Boot and Kubernetes Microservices architecture has become a standard approach for building scalable, distributed systems. This architecture breaks down applications into smaller, independent services that can be developed, deployed, and scaled independently. Spring Boot, combined with Kubernetes, provides powerful tools for creating and managing microservices effectively. In this article, we will explore how to build ... Read More »
Docker containerization for Python applications
# Docker Containerization for Python Applications Docker has revolutionized software development by providing a lightweight and efficient method for containerizing applications. For Python developers, Docker offers a seamless way to package Python applications, dependencies, and configurations into containers that can run consistently across different environments. This blog will guide you through the basics of Docker containerization for Python applications, with ... Read More »
