SShortSingh.
Back to feed

Poja Uses Naming Conventions to Auto-Wire AWS Infrastructure for Spring Boot Apps

0
·1 views

Spring Boot developers already rely on conventions like package placement and classpath scanning to wire application internals, but AWS infrastructure — queues, retries, permissions, and routing — typically still requires manual configuration. This gap means a simple requirement like async processing translates into a complex set of infrastructure decisions that developers must declare separately from their application code. Poja, a framework built on top of Spring Boot, extends the convention-over-configuration principle to cloud infrastructure by inferring SQS queues, dead-letter queues, and visibility timeouts from just two developer-defined values in the event class. Developers need only extend a base event class, name the consumer service after the event, and place both in expected packages — Poja resolves the wiring through string concatenation and calculated timeouts. The approach aims to eliminate the split between application logic and infrastructure declaration by treating AWS resource configuration as a derivable convention rather than an explicit task.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

Developer Builds Lightweight Go Gateway to Centralize LLM Provider Setup

A developer created Go-Ai, a small open-source HTTP gateway written in Go, to eliminate repetitive LLM provider configuration across multiple projects. The tool acts as a single proxy layer between application backends and AI providers like OpenAI, handling credentials, model name aliases, and streaming without requiring each app to manage those details independently. The project was motivated by the recurring friction of managing provider keys, model slugs, and environment-specific availability every time a new AI feature was tested. Go-Ai is intentionally narrow in scope and is not designed to replace broader frameworks like LiteLLM or LangChain, which the author acknowledges serve different needs. The gateway is best suited for developers running multiple small apps who want a self-hosted, minimal service they can trace from request to response.

0
ProgrammingDEV Community ·

Rewriting Tool Descriptions Boosted AI Agent Accuracy from 34% to 100% for $4

An open-source project called Toolmetry found that vague or outdated tool descriptions — not the AI model itself — were causing agents to fail tasks at high rates. By rewriting only the text descriptions that tell agents what each tool does and how to use it, SQLite task success jumped from 34% to 100%, with the entire experiment costing just $4 in API calls. Researchers identified three root causes: overlapping tool descriptions causing wrong tool selection, implied but unnecessary prerequisite steps wasting tokens, and deprecated parameter references leading to confident but incorrect calls. For example, a git server's success rate rose from 75% to 96.7% simply by updating parameter names in its descriptions to match the current API. The findings suggest that tool descriptions function as a contract between an agent and external systems, and ambiguity in that contract reliably produces failures regardless of model quality.

0
ProgrammingHacker News ·

Developer explains AI tool calling using just 40 lines of plain JavaScript

A developer has published a concise tutorial demonstrating how AI tool calling works using only 40 lines of vanilla JavaScript, with no external libraries required. The lesson, dated September 15, 2026, is part of a series hosted on the Buttercup platform. Tool calling is a key AI capability that allows language models to invoke external functions or APIs to complete tasks. The tutorial aims to demystify the concept by breaking it down into minimal, readable code. The post was shared on Hacker News, where it attracted early attention from the developer community.

0
ProgrammingDEV Community ·

Charts.css, ProvChart, FSCSS: Three CSS-native charting tools without JS libraries

Three open-source tools — Charts.css, ProvChart, and FSCSS (st-core) — offer ways to render charts without shipping heavyweight JavaScript chart libraries, which typically add 40–150 KB to page load. Charts.css converts semantic HTML tables into visual charts using CSS classes, making it well-suited for accessible, content-driven pages like blogs and static sites. ProvChart compiles JSON data into scoped HTML, CSS, or SVG at build time, targeting performance-sensitive pages where first-paint speed and zero chart-runtime hydration are priorities. FSCSS (st-core) uses a dedicated .fscss syntax that compiles to native CSS, designed for design systems and component libraries shared across multiple frameworks. The three tools are not interchangeable but complementary, and organizations may use all three depending on whether charts appear in documentation, API-fed dashboards, or shared UI kits.