Dev Systems

Show HN: FixBugs – Reproduce production bugs and verify fixes

I built FixBugs, an agent that ingests the rich context surrounding production bugs to reproduce them in a sandbox and generate verified fixes. It's available in the form of a self-hosted VSCode extension and as a Github app:VSCode Extension: https://fixbugs.ai/go/vscode-extension - full code and data privacy. - zero data retention models opted out of training. GitHub App: https://fixbugs.ai/go/github-app - we do access your code temporarily.

Show HN: I implemented a neural network in SQL

Two weeks ago I was on my babymoon in Corfu, Greece. While in transit, I was overseeing a GSoC intern submit an important feature to my array database library, Xarray-SQL. He added `to_dataset()`, which completed the roundtrip between thinking of array data in a tabular model simultaneously as gridded rasters (the premise of the project is that every Nd array can be mapped to 2d, where orthogonal dims of the Nd array are just primary keys of a tabular representation). We discussed in chat, now t

From Policy to Proof: Governing AI to Scale Human Ambition and Machine Intelligence

Enterprises are moving from AI experiments to AI in production. Copilots are in the flow of daily work, custom applications are built on foundation models, and autonomous agents are beginning to take actions on behalf of the business. As organizations combine human ambition with machine intelligence, trust becomes the defining requirement for scaling AI responsibly and realizing AI's full potential. That shift changes the governance question from "can we use AI responsibly?" 

Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization

Hierarchical Interest Representation is a research area for Meta Ads. We’re exploring an upstream representation layer over the universe of Ads entities – users, advertisers, products, services – learning unified embeddings that connect users’ inferred interests with the breadth of what advertisers offer in their deep funnel ads.The innovations in Hierarchical Interest Representation are an in-house transformer based graph learning with bias-aware attention and self-supervised cross-view d

How bitdrift scaled to 121 million concurrent gRPC connections on Amazon CloudFront for live telemetry sporting events

When 121 million mobile devices establish persistent gRPC connections to your origin infrastructure within seconds of a live broadcast, the routing policy behind your DNS records matters far more than it does at normal traffic levels. The wrong policy can concentrate all your connections onto a single origin endpoint, turning a scaling success into an outage. bitdrift, a mobile observability platform founded by former Lyft infrastructure engineers, learned this firsthand while delivering real-ti

Ask HN: Resources for non-web software architecture?

I'm looking for resources (primarily books, papers, and YT videos) on software architecture. I'm NOT interested in Monolith vs Microservices type of material -- but rather material applicable in general, or systems programming in particular.

Show HN: Cascade Chat – A Hackable IRCv3 Client for macOS, Windows, and Linux

Hello HN! I'm Matt and today I'd like to show you Cascade Chat.One of my earliest internet experiences was with mIRC. I always admired its straightforward, pleasant UI and the way it wove a hackable core into the code. The way you could build on the visual and API layers of the underlying IRC client to me was fascinating software machinery. It was truly a client that you could build on top of.As my career has progressed, I moved away from Windows and adopted Linux as my daily driver. T

Show HN: Itara – Distributed system topology as an explicit, executable layer

Hi HN, I'm Gábor, a software engineer from Budapest.I spent almost a decade designing, building and maintaining distributed systems, and I came to truly understand why a lot of people define software architecture as "the stuff that's hard to change later". Changing service boundaries, communication protocol or serializers is time consuming and risky. The past few months, I've been building Itara, my attempt to ease that pain.Itara takes the software topology that's

Building Service Topology at Scale: Architecture, Challenges, and Lessons Learned

By Parth Jain, Rakesh Sukumar, Yingwu Zhao, Renzo Sanchez-Silva & Nathan FisherA deep dive into the engineering challenges of building a real-time service dependency map at Netflix scale: from streaming architectures and distributed aggregation pipelines to time-travel queries and the methodology that made it work.IntroductionIn our first post, we introduced the problem: engineers at Netflix needed a unified, real-time view of service dependencies to troubleshoot faster, understand blast rad

Modernizing the Meta Ads Service With an Open-Source Kernel Scheduler

TL; DRAt Meta’s scale, a few milliseconds of latency degradation can have a significant negative impact on ads performance. When a Linux kernel upgrade risked regressing latency across Meta’s ad serving fleet, we turned to sched_ext — the upstream, BPF-based extensible scheduling framework — to build a scheduling policy customized to the Ads delivery workload.The result: a 28% reduction in ads retrieval stage tail(99th percentile) latency, 3.28 megawatts(MW) power saving, and a 1.1%

Build or buy: how AI changed whether your in-house realtime system is still worth it

A dropped connection used to cost a typing indicator. With AI in the product, it costs an entire response, mid-generation. That single shift is enough to reopen a decision most teams made years ago and stopped thinking about: whether to keep building realtime infrastructure themselves, or buy it.Fin, the AI agent platform formerly known as Intercom, made the call to buy. It had run its own realtime system, Nexus, for years, at the scale of one of the biggest support platforms on the internet. It

Unlocking the future of video data: March Networks cloud storage on AWS

Enterprise video surveillance is operating at an unprecedented scale as organizations across retail, banking, quick-service restaurants (QSR), convenience stores, and transportation networks generate petabytes of video data across thousands of distributed locations. As retention requirements grow and organizations seek to extract more operational insights from video, traditional on-premise storage models are becoming increasingly difficult and expensive to scale. March Networks is a global provi

How MAPFRE USA modernized fraud claims with Amazon EMR Serverless

Insurance fraud remains a significant challenge for the insurance industry. Fraudulent claims can increase loss costs, reduce trust, and consume investigation capacity that could otherwise be focused on serving customers. Traditional fraud detection approaches typically rely on rules-based controls, manual investigation triggers, historical claim patterns, and structured-data-only analysis. These approaches are useful for known fraud patterns, but they can struggle to detect sophisticated fraud

The AI Agent Lifecycle: A Simple Guide

The Bigger PictureBuilding an AI agent is fundamentally different from building traditional software.With a website or application, teams typically design, develop, test, and release. Once deployed, the focus shifts primarily to maintenance and feature enhancements. AI agents operate differently. They don't just execute predefined instructions they interpret information, reason, and make decisions.In banking, those decisions can influence customer experiences, operational efficiency, compliance

Show HN: Hyper – distributed Firecracker microVM orchestrator written in Elixir

Hey everyone! One of the problems I ran into is that a large part of the VM-provider ecosystem is currently paid closed-source SAAS products with varying degrees of reliability. I wanted an OSS distributed microVM orchestrator and I couldn't find one.Hyper is a distributed FirecrackerVM orchestrator written in Elixir (BEAM), with gRPC support for non-BEAM clients. Hyper is:- Distributed -- it's designed to run across a cluster of bare metal machines, and will automatically connect to o

Show HN: Root cause, Reproduce and generate Verified fixes for Production Bugs

I built FixBugs after years on-call at Arista, VMware, and Google.The painful part of debugging production systems was never writing the fix: it was reproducing the issue, collecting logs, tracing where the failure actually originated, and validating that the fix actually addressed the root cause.This investigation overhead is what FixBugs is designed to eliminate.FixBugs is a debugging agent that plugs into your existing workflow (VS Code, CLI, or webhooks for GitHub/Jira/GitLab). It

Beyond the Canvas: The Azure Architecture Diagram Builder Becomes Agent-Ready

AZURE ARCHITECTURE BLOG · 8 MIN READAuthor: Arturo Quiroga, Senior Partner Solutions Architect — MicrosoftTwo months ago I published From Prompt to Production: Building Azure Architecture Diagrams with AI, introducing the open-source Azure Architecture Diagram Builder. The response was humbling — thousands of you read it, tried the tool, and filed issues and feature requests. A follow-up on how the Well-Architected Framework scoring works went deep on validation.You asked, and the tool grew. Thi

Introducing AI Transport v0.5.0: durable execution with Steps

AI Transport v0.5.0 is now available. It adds first-class support for running an agent turn inside a durable execution framework, such as Temporal or Vercel's Workflow Development Kit (WDK), while every client watching the conversation still sees one clean, resumable stream.The last release, v0.4.0, let an agent hydrate its history from your own database. This one is about what happens when the process running the agent isn't around for the whole turn.Two kinds of durabilityA durable execution f

Specification-driven composition for flexible data workflows

Specification-driven composition addresses a common scalability bottleneck in data pipelines. Data pipelines often start as simple scripts, but as they grow, you duplicate transformation logic and small changes cascade across multiple workflows. Copying and modifying data transformation logic across scripts leads to workflows that become difficult to manage at scale. Tracking what each pipeline does becomes harder because workflow intent is embedded in code. This lack of visibility complicates g

Show HN: CodeRadius, map and govern multi repo architectures

Hi HN,I deal with tens of repositories daily, in a company with thousands. Having a clear picture of real-time architecture relies on discipline and the goodwill of engineers to keep the (fragmented) documentation up to date. With coding agents, this problem grows at the speed of light.LLMs are good at explaining parts of code, but are very bad at extracting precise and reliable architecture mapping of big codebases, not to say when dealing with multiple repos of a microservices fleet (read: di