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Home/Articles/#performance-optimization

Topic

#performance-optimization

8 articles found

· about 9 hours ago· Dev.to

Bun for AI agents: where the speed actually shows up (and where it lies)

Bun is fast. The README will tell you 4x on bun install, 3-5x on Bun.serve(), 2x on bun:sqlite. Some of this matters for AI agents. Some of it doesn't. We've been running production agents on Bun for about 3 months — a mix of Hono-on-Bun HTTP agents and standalone Bun scripts called from Claude Code

#cloud-computing#ai-agents#bun#performance-optimization
Enabling Agent Tracing Revealed 4 Bottlenecks Consuming 47% of Tokens.
· 2 days ago· Dev.to

Enabling Agent Tracing Revealed 4 Bottlenecks Consuming 47% of Tokens.

I have a production Claude agent that has been running for about four months. It does code review on incoming PRs, drafts changelog entries, and occasionally summarizes a Slack channel. Nothing exotic. Nothing the marketing pages would put on a banner. It was burning 5.2 million tokens a month. I kn

#cloud-computing#agent-tracing#performance-optimization#token-management
· 3 days ago· Dev.to

Cloud Gaming Crash: Lessons Learnt from 300 Simultaneous Users Chaos

The Problem We Were Actually Solving The hunt engine ran on Veltrix 1.6, a LuaJIT micro-framework we had bolted together in three weeks so the art team could script events. Every hunter spawned a coroutine, every coroutine did an EVALSHA against Redis to atomically award loot, then wrote the result

#cloud-computing#gamedev#performance-optimization#server-architecture
· 3 days ago· Dev.to

When Language Constraints Hinder Cloud Development Progress

The Problem We Were Actually Solving It wasnt supposed to be a language swap. We had built the Treasure Hunt Engine on Go 1.20, using channels and sync.Pool to keep each players state off the GC. At 100k concurrent hunters, the p99 latency sat at 34 ms and allocations were 42 MB/s. But the moment lo

#cloud-computing#programming-languages#software-development#performance-optimization
Analysis temporarily unavailable. Please try again in a moment.
· 4 days ago· Dev.to

Analysis temporarily unavailable. Please try again in a moment.

Quick Recap In the previous article, we introduced priority-based and layered schedulers, solving the problem of “which tasks should run first.” However, real-world applications introduce another challenge: long-running tasks can still block the main thread. To keep applications responsive, a schedu

#cloud-computing#ui-design#react#performance-optimization
Unpacking ForgeZero 4.0.x: Achieving 1.18 GB/s with Zero Heap Allocations
· 5 days ago· Dev.to

Unpacking ForgeZero 4.0.x: Achieving 1.18 GB/s with Zero Heap Allocations

What happens when you migrate a system tool from pure Node.js to Go, strip out the standard GC-heavy paths, and force a file system engine to hit 0 allocs/op? You get ForgeZero (fz) — an open-source bare-metal system software builder created by @AlexVoste. Designed to eliminate bloated Makefiles for

#cloud-computing#go-lang#open-source#performance-optimization
· 5 days ago· Dev.to

Cloud Optimization Hinges on Mastering Metric Cardinality Balance

In metric collection systems, cardinality is a critical concept for balancing performance and cost. I have prepared a 4-step guide on how this balance is established in the real world. In this post, I will explain what metric cardinality is, why it matters, and how we can find the right balance in o

#cloud-computing#metric-collection#data-analytics#performance-optimization
Jaeger achieves 8.6× compression on 10 million spans using ClickHouse
· 6 days ago· The New Stack

Jaeger achieves 8.6× compression on 10 million spans using ClickHouse

As someone who’s been maintaining Jaeger, I’ve watched users request ClickHouse support consistently over the past few years. With Jaeger The post How Jaeger hit 8.6× compression on 10 million spans with ClickHouse appeared first on The New Stack.

#cloud-computing#data-analytics#clickhouse#jaeger#performance-optimization

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