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Java Web Development (JSP/Servlets) Services |
| Java became popular on the Internet due to the small java applets in 1995. Java applets provided great looking
web sites. Java became pouplar due to its cross platform support.
Java Appliction runs same on Windows as on Linux/Unix/Mac. JSP and Java Servlets are used for server side programming to create dynamic pages which change with every request.
We have JSP/ Servlet programmers/developers. We can provide all kind of java web development services.
Contact us for a free quote.
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- The Startup Time Trick Hiding Inside Your Docker Build
Every Java developer who runs services on Kubernetes has watched this scene play out. Traffic spikes, the autoscaler adds a pod, and then everyone waits. The container is running in two seconds. The application is not ready for another twelve seconds. During those ten seconds, your existing pods absorb the extra load, latency climbs, and if things are bad enough, the autoscaler panics and adds even more pods that are also not ready.
I spent years treating Spring Boot startup time as a fact of life, the way you treat weather. Then I found out the JVM has had a fix for a big chunk of it since Java 12; it works beautifully inside Docker, and almost nobody bakes it into their images. It is called Class Data Sharing, CDS for short, and this article shows you how to make your Docker build do the work
- The Bottleneck of Scaling
Any input/output operation, be it accessing a file, handling an HTTP request, or a database connection, is based on 3 fundamental system concepts — file descriptors, kernel memory, and heap size.
This article discusses how modern languages help developers handle behind-the-scenes file descriptor, kernel memory, and heap management. These three concepts are major bottlenecks for scaling.
- Pragmatic Premature Optimization
“...premature optimization is the root of all evil…”
Donald Ervin Knuth
- Running Sentiment Analysis Inside Neo4j With a Java Plugin
In a chapter of The SingleStore Cookbook, there is a complete sentiment analysis pipeline using Rust compiled to WebAssembly and loaded directly into SingleStore via its Code Engine. The result was clean: one CLI command to deploy, sentiment scoring running inside the database engine alongside the data and a full stock-price-plus-headlines analytical pipeline built on top of it.
Can we do the same thing in Neo4j?
- Part 1: Building Governed MCP Tool Services With Quarkus LangChain4j and Goose
Goose — the open-source, Rust-based AI developer agent from Block (donated to the Linux Foundation’s Agentic AI Foundation) — interacts natively with your local development environment via the Model Context Protocol (MCP). In this tutorial, you will learn how to build stateless, cloud-native Java microservices using Quarkus LangChain4j and expose them as governed MCP extensions that Goose can discover and run seamlessly.
Autonomous AI coding agents like Goose go far beyond simple code autocompletion. Built in Rust for speed and portability, Goose runs on your local machine, inspects files, runs terminal commands, and uses tools over MCP to automate complex engineering tasks.
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