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

H
Hackread – Cybersecurity News, Data Breaches, AI and More
U
Unit 42
Vercel News
Vercel News
Martin Fowler
Martin Fowler
云风的 BLOG
云风的 BLOG
爱范儿
爱范儿
MongoDB | Blog
MongoDB | Blog
J
Java Code Geeks
F
Fortinet All Blogs
MyScale Blog
MyScale Blog
C
Check Point Blog
N
Netflix TechBlog - Medium
Microsoft Azure Blog
Microsoft Azure Blog
aimingoo的专栏
aimingoo的专栏
博客园_首页
WordPress大学
WordPress大学
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
IT之家
IT之家
Last Week in AI
Last Week in AI
罗磊的独立博客
大猫的无限游戏
大猫的无限游戏
Jina AI
Jina AI
V
Visual Studio Blog
小众软件
小众软件

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
I Added a Pro Plan to OpenClawCloud Because Heavy Runs Hi...
João Pedro S · 2026-04-28 · via DEV Community

João Pedro Silva Setas

I Added a Pro Plan to OpenClawCloud Because Heavy Runs Hit Boring Limits First

The first limit heavier AI workloads hit is usually not intelligence.

It is the boring stuff.

CPU.
RAM.
Disk.
And a better way to see what is about to run before you let it go.

That is why I added a Pro plan to OpenClawCloud.

It is live at $29/month and keeps the same basic starting point as Hobby, but adds more headroom where it actually matters:

  • 4 vCPU
  • 8GB RAM
  • 160GB SSD storage
  • Run Preview before execution
  • Instance Activity Log
  • Priority support

Hobby still makes sense when you are exploring, testing, or just getting your first setup running. Pro is for the point where that smaller box stops being comfortable.

I wanted the step up to be practical, not ornamental. More room to run. More storage for longer-lived workspaces and heavier tasks. Better visibility into what is about to happen and what just happened.

The broader OpenClawCloud direction I care about is still governed execution: clearer review surfaces, better failure inspection, and less dependence on one provider's policy decisions. Useful product work usually starts with the boring constraints first. If the runtime does not have enough headroom, the bigger thesis does not matter yet.

So this is the current shape of the product:

  • Hobby for smaller setups and exploration
  • Pro for heavier runs that need more compute, more storage, and better visibility

That feels like the right next step for where OpenClawCloud is now.

If you are already past the point where the smallest plan feels comfortable, Pro is live.

What becomes the first bottleneck for you when AI workloads get heavier: CPU, memory, storage, or visibility into each run?