PLATAFORMA: Dev.to
Token bills are getting out of hand. Everyone knows it. The default response has been to reach for massive, venture-backed "LLMOps" platforms that promise to solve everything. They offer observability, caching, prompt versioning, evaluation, and a dozen other features.
tbh, for most of us, that's overkill. It's like buying a full-scale CI/CD platform when all you need is a simple cron job.
The real problem for 90% of devs isn't complex prompt A/B testing or fine-tuning workflows. It's answering one basic question: "Who or what is costing me so much money?"
Usually, the answer is buried in a CSV file from OpenAI or Anthropic. You end up writing custom scripts to parse it, attribute costs to users, and hope you catch the runaway agent that's stuck in a loop summarizing the same text 1,000 times.
This isn't an "observability" problem. It's a dashboard problem.
Before you invest in a complex system, you need a clear view of three things:
- Cost per user: Which tenant is burning through your credits?
- Cost per model: Is
claude-3-opusreally worth 15x more thanhaikufor that simple task? - Real-time alerts: Can you get a Slack notification when a user's spend hits $100, before it hits $1,000?
Most enterprise tools do this, but they bundle it with features you won't touch for months. And they aren't cheap.
This is why we built LLMeter as an open-source tool. It's not a massive platform. It's a focused, self-hostable dashboard (Next.js, Supabase) that does one thing well: monitor costs across different providers (OpenAI, Anthropic, DeepSeek, OpenRouter).
It gives you multi-tenant attribution and budget alerts without the enterprise complexity. You can see which user is calling which model and how much it's costing you, in real-time. AGPL-3.0, so you can host it yourself.
fwiw, the next time your bill spikes, don't assume you need a revolutionary AI-powered solution. You might just need a better dashboard. Check out the project at llmeter.org.
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