惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

P
Proofpoint News Feed
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
Cisco Talos Blog
Cisco Talos Blog
Martin Fowler
Martin Fowler
S
SegmentFault 最新的问题
宝玉的分享
宝玉的分享
T
Tenable Blog
Stack Overflow Blog
Stack Overflow Blog
P
Palo Alto Networks Blog
J
Java Code Geeks
T
True Tiger Recordings
S
Schneier on Security
C
Cybersecurity and Infrastructure Security Agency CISA
Stack Overflow Blog
Stack Overflow Blog
爱范儿
爱范儿
博客园 - 【当耐特】
WordPress大学
WordPress大学
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
H
Help Net Security
F
Future of Privacy Forum
Scott Helme
Scott Helme
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
S
Security @ Cisco Blogs
Application and Cybersecurity Blog
Application and Cybersecurity Blog
博客园 - 司徒正美
V
V2EX
Google DeepMind News
Google DeepMind News
云风的 BLOG
云风的 BLOG
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
Malwarebytes
Malwarebytes
大猫的无限游戏
大猫的无限游戏
C
Check Point Blog
The GitHub Blog
The GitHub Blog
The Hacker News
The Hacker News
博客园 - 聂微东
李成银的技术随笔
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
V
Vulnerabilities – Threatpost
O
OpenAI News
C
Cyber Attacks, Cyber Crime and Cyber Security
C
Comments on: Blog
Project Zero
Project Zero
Engineering at Meta
Engineering at Meta
Recent Announcements
Recent Announcements
N
Netflix TechBlog - Medium
博客园 - Franky
aimingoo的专栏
aimingoo的专栏
M
Microsoft Research Blog - Microsoft Research
Security Latest
Security Latest
T
Tor Project blog

DEV Community

Self-Hosted LLM Tool Calling: Forge and the Build-vs-Buy Decision ORA-00072 오류 원인과 해결 방법 완벽 가이드 OpenWA for CTOs: Self-Hosted WhatsApp Gateway Trade-Offs NotebookLM Automation With notebooklm-py: Useful, But Classify Data First Docker v29.5.x Operator Upgrade Checklist Coding-Agent Instruction Design: The CLAUDE.md File That Prevents Rework GnokeOps: Host Your Own AI House Party AI Agents in Practice — Part 2: What Makes Something an Agent Stop scattering LLM SDK/API calls across your codebase. Here is the 2-file rule that fixed mine Beyond Prompts: Structuring AI Workflows for Real Frontend Engineering From an Abandoned Hackathon Project to an AI Study Workspace 🚀 Terraform with AI: Build AWS Infra (Cursor + MCP) What If AI Didn’t Need the Internet? 750,000 Chips, 140 Trillion Tokens: The Math Behind DeepSeek's Permanent Price Cut You're Renting Someone Else's Compute — And It's Costing You More Than You Think CSS :has() Selector: The Layout Trick I Wish I Knew 5 Years Ago Five Clusters. Five Lessons. One Production System. Synaptic: A Local-First AI Dev Companion That Remembers How You Think Revolutionizing Edge MedTech: Building a Sovereign Sleep Apnea Companion ("XiHan Snore Coach") with Gemma 4 HDD Eksternal Tiba-Tiba Tidak Bisa Diakses di Windows? Ini Tiga Lapis Fix-nya DMARC p=none vs p=quarantine vs p=reject: what to use and when DSA Application in Real Life: How Git Diff Works: LCS Intuition, Myers Algorithm, and Real Code Changes I solo-built a reputation layer for AI agents on NEAR — and here's what I learned I built an AI faceless video generator in 2 months — here's the stack Diffusion Language Models: How NVIDIA Nemotron-Labs Diffusion Shatters the Autoregressive Speed Ceiling llm-nano-vm v0.8.0 — deterministic FSM runtime for LLM pipelines, now with output validation and per-step timeouts From the Renaissance to the Quantum Dawn: AI, Computation, and the Next Paradigm Shift How I Built a Review Site with 800+ Articles Using AI I Built a Smart Kitchen AI with Gemma 4 That Turns Fridge Photos Into Recipes Why your vulnerability dashboard is lying to you (and how to fix it) From Abandoned Prototype to Smart AI System: Reviving Trafiq AI with GitHub Copilot Why Country/State/City Pickers Are Weirdly Hard Node.js 22 LTS — EOL Date, Support Timeline, and What Comes Next The 7-Layer Memory Architecture Behind Modern AI Agents I Imagined Hermes Agent Running an Entire Smart City — And It Changed How I See AI One backend, four products: why we bet on platform-per-brand AI's tech debt is invisible — even to AI. I solved it at the architecture layer. Why ROAS 300% Can Still Mean Losses — Gross Margin in 5 Ecommerce Verticals You Don’t Need to Try Every AI Tool to Keep Up NovelPilot: A Novel Writing Agent Powered by Gemma 4 BoxAgnts is an Out-Of-The-Box Secure AI Agent ToolBox in a WASM SandBox Gemma 4 deep dive: why a 1.5 GB model scores 37.5% on competition mathematics, how the MoE routing actually works, and which model fits your hardware. Full breakdown inside. BeeLlama v0.2.0: 164 tok/s on a 27B model, one RTX 3090 Google Just Declared the Chat-Log Interface Dead. Here's What Neural Expressive Actually Signals for Developers. ARCHITECTURE SPECIFICATION & FORMAL SYSTEM REPORT: k501-AIONARC Notes from a Hammock What's Google Antigravity 2.0 ? Here's What the Agent Harness Actually Changes for Developers. Building an E2EE Chat App in Flask - Part 3: Keeping File Uploads Safe Google's Gemini Spark. Here's What It Actually Does for Developers. Microsoft Just Shipped MCP Governance for .NET. Here's What It Actually Enforces. How I Built a Pakistan Internet Speed Test Platform at 16 How to Build a Supervisor Agent Architecture Without Frameworks I Built My Own Corner of the Internet — Here's What It Looks Like How does VuReact compile Vue 3's defineExpose() to React? Neo-VECTR's Rift Ascent Idempotency Keys: The API Safety Net You Probably Aren't Using Building E-Commerce Sites for Niche Products: Technical Lessons from Specialty Outdoor Retailers Audit Logs: The Silent Guardian of Every Serious System Open-source SDS tooling for Japanese MHLW compliance: the gap nobody filled BetAGracevI I Built a Post-Quantum Cryptographic Identity SDK for AI Agents — Here's Why It Needs to Exist Running Claude Code across multiple repos without losing context There Are Cameras in Every Room of My House. I Put Them There. Why your AI agent loops forever (and how to break the cycle) How does VuReact compile Vue 3's defineSlots() to React? Building a Privacy-First Resume Editor with Typst WASM and React One Soul, Any Model: Portable Memory for Open-Source Agents with .klickd From Pixels to Prescriptions: Building an Autonomous Healthcare Booking Agent with LangGraph MonoGame - A Game Engine for Those Who Love Reinventing the Wheel # Day 24: In Solana, Everything is an Account Mastering Node.js HTTP Module: Build Servers, REST APIs, and Handle Requests Mastering Node.js HTTP Module: Build Servers, REST APIs, and Handle Requests RP2040 Wristwatch Tells Time With a Vintage VU Meter Needle observations about models / 2026, may From Video Transcripts to Source-Grounded AI Notes: A Practical Look at Notesnip AI Agent Dev Environment Guide — Real Experience from an AI Living Inside a Server How I Run 7 AI Models 24/7: Multi-Agent Architecture in Practice What exactly changes with the Claude Max plan? I Revived a Broken MLOps Platform — Now It's Self-Service, Policy-Guarded, and Operationally Credible OpenAI's $2M-tokens-for-equity YC deal, decoded Why DMX Infrastructure is Still Stuck in the 90s Agent Series (2): ReAct — The Most Important Agent Reasoning Paradigm Open Source Project (No.73): Sub2API - All-in-One Claude/OpenAI/Gemini Subscription-to-API Relay I Made the Wrong Bet on Event Streaming in Our Treasure Hunt Engine #ai #productivity #chatgpt #python Symbolic Constant Conundrum From Manual RAG to Real Retrieval — Embedding-Based RAG with NVIDIA NIM Building an outbound-only WebSocket bridge for local AI agents Our System's Sins in Ghana: Why We Had to Rethink Digital Product Sales Execution Governance, AI Drift, and the Security Paradox of Runtime Enforcement Differential Pair Impedance: Why USB and HDMI Routing Is a Geometry Problem Small AI database questions can become big scans Claude Code 2.1 Agent View & /goal: Autonomous Dev Guide 2026 Your AI database agent should not see every column Rust's Low-Latency Conquest: Why We Ditched C++ for a Treasure Hunt Engine Floating-point will quietly corrupt your emissions math, and 0.1 + 0.2 already warned you Autonomous Agents: what breaks first (and why that's the real product) [2026-05-23] Agent payments are the new cloud bill footgun ORA-00069 오류 원인과 해결 방법 완벽 가이드 How I Built a Local, Multimodal Gemma 4 Visual Regression & Patch Agent: Closed-Loop Validation, Canvas Pixel Diffing, and Reproducible Benchmarks
When I Finally Realized My Runtime Was Holding Me Back
pretty ncube · 2026-05-23 · via DEV Community

The Problem We Were Actually Solving

I was tasked with optimizing the performance of our treasure hunt engine, a complex system that relied on a multitude of parameters to function correctly. As a Veltrix operator, my primary concern was ensuring that the engine could handle a large volume of concurrent users without significant latency or memory issues. However, as I delved deeper into the system, I realized that our chosen runtime was becoming a major bottleneck. The engine's performance was suffering due to the runtime's inability to efficiently manage memory and handle concurrent requests. I spent countless hours poring over profiler output, allocation counts, and latency numbers, trying to identify the root cause of the issue. One particular metric that stood out to me was the average latency of 500ms, which was unacceptable for a real-time system like ours.

What We Tried First (And Why It Failed)

Initially, I attempted to optimize the engine's performance by tweaking the existing runtime configuration. I tried adjusting the garbage collection settings, increasing the heap size, and even experimenting with different concurrency models. However, despite my best efforts, the engine's performance remained subpar. The latency numbers refused to budge, and the allocation counts continued to climb. It was clear that I needed to take a more drastic approach. I tried using tools like jemalloc and tcmalloc to optimize memory allocation, but they only provided marginal improvements. I also experimented with different programming languages, including Java and C++, but they introduced their own set of problems. For instance, Java's garbage collection pauses were causing significant latency spikes, while C++'s manual memory management was prone to errors.

The Architecture Decision

After weeks of frustration and disappointing results, I made the decision to migrate the treasure hunt engine to Rust. I knew that Rust's focus on memory safety and performance would be a good fit for our system. However, I was also aware of the steep learning curve associated with Rust, and the potential risks of introducing a new language into our tech stack. Despite these concerns, I was convinced that the benefits of using Rust would outweigh the costs. I spent several weeks learning Rust and evaluating its suitability for our use case. I was impressed by Rust's ownership model and borrow checker, which ensured memory safety at compile-time. I also appreciated Rust's performance characteristics, which were on par with C++.

What The Numbers Said After

The results of the migration were nothing short of astonishing. The average latency dropped to 50ms, a 90% reduction from the previous value. The allocation counts plummeted, and the engine's overall performance increased significantly. The profiler output showed a significant reduction in memory allocation and deallocation, which was a major contributor to the improved performance. I also noticed a significant decrease in the number of errors and crashes, which was a testament to Rust's memory safety features. For instance, I no longer had to worry about null pointer dereferences or data corruption, which were common issues in our previous implementation.

What I Would Do Differently

In retrospect, I would have liked to have made the switch to Rust earlier. The learning curve was steeper than I anticipated, and it took several weeks to get up to speed. However, the benefits of using Rust far outweighed the costs. If I had to do it again, I would invest more time in learning Rust and evaluating its suitability for our use case before making the switch. I would also ensure that our team had the necessary skills and expertise to support a Rust-based system. Additionally, I would have liked to have done more extensive testing and benchmarking before deploying the new system to production. This would have helped identify potential issues earlier and reduced the risk of errors. For example, I would have liked to have tested the system under heavy load and simulated various failure scenarios to ensure that it was robust and reliable.