Better Stack

Today, we're making Error Tracking generally available. Sentry-compatible. AI-native. At 1/6th the price. Here's why we built it, and how to get the most out of it. What's wrong with error tracking today? Most teams use Sentry. It's solid! But at scale, the bills get brutal. Just 100M exceptions with 90-day lookback? ~$30,000 on Sentry. We charge ~$5,000 for the exact same thing. The math isn't subtle. And so most teams still end up sampling. Which means missing the exact exception that caused the outage. The bigger problem: errors are orphaned data. Your exception lands in Sentry. Your logs are in Datadog. Your traces are somewhere else. Root cause analysis becomes a multi-tab archaeology project at 3 am. We built error tracking natively inside Better Stack: the same platform where your logs, traces, metrics, uptime checks, and on-call schedules already live. Errors are just another signal. They belong together. The part that changes how your team works: Our AI SRE doesn't just surface errors. It fixes them. See a new exception? One click. The AI SRE analyzes the full context, from stack traces, environment variables, browser sessions, related logs, and recent deploys, and opens a pull request. Not a ticket. Not a summary. A pull request with the fix. This is what happens when error tracking is fully integrated with the rest of your observability stack instead of bolted on separately. The AI has everything it needs to actually act. The migration is trivial: 1. Keep your existing Sentry SDK. Don't touch a single line of instrumentation code. 2. Point the DSN at Better Stack. 3. Done. Errors flow in. Your dashboards work. Your alerts work. 4. New exception appears. Click "Fix with AI SRE." Pull request lands in your repo. 5. Review, merge, close. That's the whole workflow. The AI angle is real, not a marketing badge. LLMs are genuinely good at fixing bugs if they have full context. The reason AI coding assistants sometimes frustrate engineers is incomplete information, not the model. We solve that by giving the AI SRE your entire telemetry stack as context. Stack traces, logs, traces, service maps, previous incidents, and much more. All of it, in one place, at the moment it matters. Observability tools are only useful if you actually ingest all your data. At current prices of other tools, most teams can't afford to. Now you can, and your AI SRE can actually do something about it.

Kokoro-82M might be the most practical open-source TTS right now. 82M params, runs locally (no GPU), and rivals cloud APIs. Demo + setup + comparison in this video.

Scale your infrastructure, not your budget, with AI-native error tracking built on Better Stack.

We use @BetterStackHQ heavily in my company. It works wonders for us, without them we couldn't possibly fix the production bugs that we get. We have BetterStack set up everywhere, and hands down, the best service for error tracking, error logging, and everything that you need, they have it.

frictionless and effective ux / ui with their sign up flow, no notes. @BetterStackHQ

Tired of rebuilding admin panels, dashboards, and CRUD apps? We built a full internal tool in under a minute with open-source Appsmith. Here's why devs are switching from Retool & Bubble.

Attackers compromised the Axios npm package and published two backdoored releases. The malicious versions introduced a hidden post-install script that silently downloaded a Remote Access Trojan onto developer machines and CI/CD runners, scanning for .env files, SSH keys, npm tokens, and more.

Cloudflare Dynamic Workers just dropped and they're rewriting compute. 100x faster than containers, AI sandboxes in milliseconds, and 1 MILLION concurrent workers per second. The future is here.

Stop paying for 1Password or Bitwarden. We tested Vaultwarden. It's self-hosted, runs locally with Docker, fully compatible, and set up in under a minute. With CLI, autofill, and full control.

Tired of Vercel, Railway, or Heroku bills? Dokploy turns any $5 VPS into your own PaaS. Git push deploys, HTTPS, DBs, monitoring, even scaling. We tested it vs Vercel… It's fast.

Using Copilot, Tabnine, or Cursor? Your code might be leaving your machine every time you hit tab. We tried Tabby, a self-hosted AI coding tool that keeps everything local. Same speed. Zero cloud.

Better Stack Podcast Ep. 14 Multi-Agent Orchestration & The Death of Human Code Review

Liquid AI just released a browser-based vision model that runs locally via WebGPU. It uses a hybrid architecture and 28 trillion tokens to deliver high performance in under 1GB of RAM.

Chrome 144 just shipped a game-changing update that auto-connects DevTools MCP to your real browser, no more Playwright or manual debugging setup. Debug actual apps behind login pages today.

We replaced Firebase with Appwrite and built a real-time app from scratch. No lock-in, no surprise bills, full control. If you're tired of Firebase, this might be the alternative you're looking for.