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Webhook debugging tool that captures every delivery, shows why it failed and lets you replay the exact payload after a fix.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Vibe-coding builder creating full-stack apps by chatting with AI.
Full-stack observability platform with an AI SRE agent that detects, debugs, and auto-fixes issues across infra, apps, and users.
No public pricing
No public pricing
No public pricing
- ✦Capture every webhook delivery with status and attempts
- ✦Inspect request, response and headers
- ✦Replay and retry exact payloads
- ✦Failure categorization by reason
- ✦Group repeated failures into incidents
- ✦Slack and webhook alerts
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦CodeFlying enables full-stack app creation via chat in minutes
- ✦Infrastructure and application performance monitoring
- ✦Log monitoring with AI insights
- ✦Real user monitoring
- ✦OpsAI SRE agent for detection and auto-fix
- ✦Synthetic and browser testing
- ✦LLM observability
- →Debugging failed Stripe, GitHub or Shopify webhooks
- →Recovering dropped events
- →Monitoring webhook reliability
- →Alerting on failures before users notice
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
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- →Monitor full-stack app and infra health
- →Debug incidents faster with AI
- →Correlate frontend and backend issues
- →Observe Kubernetes and cloud environments