A modern web team in 2026 typically runs on something like this: GitHub for code, Linear or Jira for tasks, Vercel or Render for deploys, PlanetScale or Neon for the database, Datadog or Sentry for observability, and a Slack channel duct-taping all of it together. Every tool is good. Every tool bills separately, per seat, every month. Every tool has its own permission model, its own dashboard, and its own opinion about how your work should look.
A modern web team in 2026 typically runs on something like this: GitHub for code, Linear or Jira for tasks, Vercel or Render for deploys, PlanetScale or Neon for the database, Datadog or Sentry for observability, and a Slack channel duct-taping all of it together. Every tool is good. Every tool bills separately, per seat, every month. Every tool has its own permission model, its own dashboard, and its own opinion about how your work should look.
MonkeysCloud replaces all of that with one platform — and the entire thing is free for unlimited team members.
This post is a walkthrough of what's actually in the platform. Not the marketing slogans, the actual features. If you've seen the homepage and want to know what each piece really does, this is for you.
The starting point: $0 is not a trial
Every project on MonkeysCloud starts with two free compute instances and two free database instances. That's enough to run a real application: app server, worker, primary database, and a Redis cache, all running, all on a custom domain, all with auto-issued SSL.
A few concrete shapes of "free":
A Laravel API with a queue worker, a MySQL 8.4 database, and a Redis sessions cache. $0.
A Next.js full-stack app with a PostgreSQL 16 database and a Redis cache. $0.
A Django + Celery setup with a worker process, PostgreSQL, and Redis as the broker. $0.
Two microservices — a Go API and a Node.js service — with a PostgreSQL database and MongoDB. $0.
Free instances are shared (0.25 vCPU, 1 GB RAM) or Starter-sized (0.5 vCPU, 2 GB RAM), and they sleep after 30 minutes of inactivity, waking on the next request. That tradeoff is honest: you get real infrastructure with real databases for nothing, in exchange for cold starts when traffic is sparse. The moment you upgrade to a paid organization, every project in it gets bumped to seven free compute instances and seven free databases, which is enough to run dev, staging, and production with their own databases and caches — most of it still free.
The team-member math is what makes this stranger than the usual "free tier." MonkeysCloud doesn't charge per user. Ever. Invite your whole company, your designers, your client, your contractors — the platform is free for all of them, whether you're on a Free or Paid organization. Compute costs money. People don't.
Pillar 1: Git and code review
You can host repositories natively on MonkeysCloud, or connect GitHub, GitLab, or Bitbucket if your team already lives there. Either way, pull requests, branch protection, and code review happen inside the platform.
The differentiator here isn't the Git hosting itself — Git hosting is a commodity in 2026. It's the AI code review that runs on every PR automatically. Before a human teammate even opens the PR, MonkeysAI has already left inline comments on bugs, security issues, and performance regressions it spotted. It's not a replacement for human review. It's the senior engineer who catches the obvious stuff so your senior engineers can focus on the hard stuff.
Pillar 2: Task management linked to code
Kanban boards. Scrum sprints. Task lists. The standard primitives.
The thing that's actually different is that tasks link directly to branches, pull requests, and deployments. A task on the board shows the branch it's being worked on, the PR that resolves it, and the deploy where that PR went live. You can trace a feature from the day someone proposed it on the board to the moment it went into production, in one view. No copy-pasting URLs between Jira and GitHub. No half-stale status updates.
There's also an AI feature called Smart Task Creation: describe a task in plain English ("we need a way for users to reset their password from the login screen") and it structures it into a proper ticket with a title, labels, and an effort estimate. Cuts the friction of writing tickets, which is the unglamorous reason most engineering teams have under-described backlogs.
Pillar 3: Hosting and auto-deploy
This is the part most people came for. MonkeysCloud auto-detects your stack on git push and builds it. Thirty-two stacksare supported with zero configuration, including the ones that matter:
MonkeysLegion (PHP 8.4 / FrankenPHP) — ~45s typical build.
Laravel (PHP 8.4 / FrankenPHP) — ~60s.
WordPress (PHP 8.4 / PHP-FPM + Nginx) — ~50s.
Next.js (Node 22) — ~40s.
Django (Python 3.13 / Gunicorn) — ~55s.
Go (compiled binary) — ~30s.
Plus Rails, Flask, FastAPI, Express, Bun, Astro, Remix, Symfony, and 18 more.
Every PR gets a preview environment automatically. You push a branch, you get a URL you can share with the team or your client. The branch gets merged, the preview goes away. No more "can you redeploy staging so I can show this to the designer."
Custom domains come with auto-provisioned SSL on every instance, including the free ones. Paid tiers (Pro and up) get a CDN included.
Pillar 4: Real databases, also free
The "two free database instances per project" is worth dwelling on because almost no PaaS does this honestly. Most platforms give you a free app container and then quietly point you at a separate paid database provider, which is where the bill actually starts.
MonkeysCloud runs the databases for you. Specifically:
MySQL 8.4
PostgreSQL 16
MongoDB 7
Redis 7
Each instance can be sized independently. Each comes with automatic configuration. Each counts against the same instance pool as your app servers, so the same "Free" or "Starter" size that runs your application can also run a managed Postgres for it. Production-tier databases scale up to dedicated instances with 64 GB of RAM on the Scale tier and higher.
Pillar 5: AI workflows that aren't a chatbot
AI is the feature category where most products in 2026 are now thoroughly tired. Every dashboard has a sparkle icon. Most of them open a chat window that summarizes things you can already see.
MonkeysCloud's AI is built into the workflow primitives, not added as a sidebar:
AI Code Review runs on every PR.
Build Failure Analysis reads the full build log when something breaks and tells you the root cause with a suggested fix, instead of making you scroll through 2,000 lines of webpack output.
Deploy Risk Score looks at diff size, test coverage, and your team's historical deploy patterns to assess how risky a production deploy is before you ship it. Numerical score, plain-English reasoning.
Sprint Planning analyzes the backlog, the team's velocity, and task dependencies to suggest a sprint composition that's actually achievable.
MonkeysAI Chat is the catch-all natural language interface: "what broke?", "create a task for the auth bug", "summarize this sprint." It's there when you want it, out of the way when you don't.
The chat is the least interesting part. The interesting part is that the AI shows up at the moments in your workflow where it actually changes the outcome — at PR time, at build time, at deploy time, at planning time.
Pillar 6: Monitoring, included
Real-time metrics, logs, uptime tracking, alerts, and AI anomaly detection. Built in. Not an integration with a third-party observability vendor that bills you another $100/month.
This is the unsexy pillar. It matters because the "stop paying for Datadog" line item is one of the bigger savings the platform represents, especially for small teams that need monitoring but can't justify the price of the major observability vendors.
Putting it together
The thing the homepage table makes vivid is the duct-tape replacement story. Here's the version I find most honest:
What you do todayWhat MonkeysCloud doesGitHub + Jira + Vercel + DatadogOne platform, one dashboard$10–20/user/month, multiplied across toolsUnlimited team members, freeNo free databases; you pay a DB vendor separately2 free databases per projectSeparate billing per tool, $50–200+/month eachEverything from $0; production from $19/moAI added on if you build it yourselfAI in every workflow, out of the boxDifferent permission model per toolOne team, one role, everywhere
The point isn't that MonkeysCloud is the best at each individual pillar. GitHub is bigger. Datadog is deeper. Vercel has more edge regions. The point is that the integration is the product — that the cost of running six separate tools that don't quite know about each other is higher than most teams add up before the invoices arrive, and that a platform that genuinely covers all six pillars at a fair price is a different shape of thing than the alternatives.
That's the whole pitch. Two free servers, two free databases, unlimited free team members, 32 stacks, AI where it matters, monitoring included. Start there. Pay when you outgrow it. Leave gracefully if you ever need to.