Cursor realtime

Polling Causing Excessive API Calls in Cursor-Built App

Your Cursor-generated application uses client-side polling (setInterval with fetch) to check for updates, but the polling is far too aggressive. Your API is receiving thousands of unnecessary requests per minute, driving up server costs, hitting rate limits, and degrading performance for all users.

Cursor often generates polling as the simplest way to achieve "real-time" updates — a setInterval that calls the API every 1-2 seconds. This works fine with one user in development, but in production with hundreds or thousands of concurrent users, each polling at 1-second intervals, the request volume becomes unsustainable. A seemingly innocent feature like checking for new notifications can generate millions of API calls per day.

The problem compounds because the polling continues even when the browser tab is in the background, the user is idle, or there's no new data to fetch, wasting bandwidth and battery on mobile devices.

Error Messages You Might See

429 Too Many Requests Rate limit exceeded: retry after 60 seconds API quota exhausted Error: Network request failed (ERR_INSUFFICIENT_RESOURCES) Server responded with status 503 Service Unavailable
429 Too Many RequestsRate limit exceeded: retry after 60 secondsAPI quota exhaustedError: Network request failed (ERR_INSUFFICIENT_RESOURCES)Server responded with status 503 Service Unavailable

Common Causes

  • Polling interval too short — Cursor set a 1-second or 500ms polling interval when 15-30 seconds would suffice for most use cases
  • No visibility check — Polling continues at full speed when the browser tab is hidden or the user switches to another app
  • No change detection — Every poll fetches the full dataset even when nothing has changed, wasting bandwidth and server resources
  • Multiple polling loops running — Component re-renders create duplicate setInterval timers without clearing the previous ones, multiplying request volume
  • No backoff on errors — When the server returns errors (500, 429), the client keeps polling at the same rate, making the overload worse
  • Polling on every page — The polling code runs globally instead of only on pages where real-time updates are needed

How to Fix It

  1. Increase polling interval — For most features, 15-30 second intervals are sufficient. Notifications can poll every 60 seconds. Only stock tickers or live gaming truly need sub-second updates
  2. Pause when tab is hidden — Use the Page Visibility API: document.addEventListener('visibilitychange', () => { if (document.hidden) clearInterval(poll); else startPolling(); })
  3. Implement ETag/If-Modified-Since — Return 304 Not Modified when data hasn't changed, saving bandwidth and server processing. Use the ETag or Last-Modified headers
  4. Clean up intervals on component unmount — In React: return a cleanup function from useEffect. In Vue: clear the interval in onUnmounted. This prevents duplicate polling loops
  5. Add exponential backoff on errors — When the server returns 429 or 5xx, double the polling interval each time (2s, 4s, 8s, 16s...) and reset to normal when requests succeed
  6. Switch to push-based updates — Replace polling with SSE, WebSockets, or a service like Supabase Realtime, Firebase, or Pusher for truly real-time features

Real developers can help you.

David Olverson David Olverson Solo dev shipping production apps with AI-assisted development. I specialize in rescuing broken Lovable/Bolt/Cursor builds and taking them to production. 10+ apps shipped including SaaS CRMs, gaming platforms, real estate tools, and Discord bots. Stack: Next.js 16, TypeScript, Tailwind CSS, FastAPI, PostgreSQL, Prisma. I use Claude Code with 50+ custom skills for rapid delivery. Average turnaround: 2-4 weeks from broken prototype to production. PawelPloszaj PawelPloszaj I'm fronted developer with 10+ years of experience with big projects. I have small backend background too Krishna Sai Kuncha Krishna Sai Kuncha Experienced Professional Full stack Developer with 8+ years of experience across react, python, js, ts, golang and react-native. Developed inhouse websearch tooling for AI before websearch was solved : ) BurnHavoc BurnHavoc Been around fixing other peoples code for 20 years. Dor Yaloz Dor Yaloz SW engineer with 6+ years of experience, I worked with React/Node/Python did projects with React+Capacitor.js for ios Supabase expert Jacek Rozanski Jacek Rozanski Senior PHP/Symfony developer and DevOps engineer with 20+ years of professional experience, running opcode.pl (web development agency, est. 2004). Day job: I'm the sole backend developer at merketing company where I own and maintain 11 PHP/Symfony microservices on AWS (ECS Fargate, RDS, S3, CloudFront), handle the full CI/CD pipeline (Bitbucket Pipelines, Docker), and manage monitoring with Sentry and CloudWatch. These services handle high request volumes in production every month. What I bring to AI-built apps: - I audit and fix security issues (OWASP methodology), performance bottlenecks, and architectural problems in codebases generated by Cursor, Claude Code, Lovable, Bolt, and v0 - I refactor AI-generated prototypes into production-grade applications with proper error handling, testing, and clean architecture (SOLID, DDD, hexagonal architecture) - I set up the infrastructure AI tools don't touch: AWS hosting, CI/CD pipelines, automated deployments, database optimization, monitoring, and alerting - I integrate external services: payment providers, email systems, partner APIs, SSO/auth Tech stack: PHP 8.x, Symfony, React, Next.js, PostgreSQL, MySQL, Docker, AWS (ECS, RDS, S3, SQS/SNS, CloudFront), Terraform, Supabase. I also use AI tools daily (Claude Code, Cursor) in my own workflow, so I understand both the strengths and the gaps in AI-generated code. Based in Poland (CET timezone). Available for async work and calls during EU/US business hours. Anthony Akpan Anthony Akpan Developer with 8 years of experience building softwares fro startups Mehdi Ben Haddou Mehdi Ben Haddou - Founder of Chessigma (1M+ users) & many small projects - ex Founding Engineer @Uplane (YC F25) - ex Software Engineer @Amazon and @Booking.com Omar Faruk Omar Faruk As a Product Engineer at Klasio, I contributed to end-to-end product development, focusing on scalability, performance, and user experience. My work spanned building and refining core features, developing dynamic website templates, integrating secure and reliable payment gateways, and optimizing the overall system architecture. I played a key role in creating a scalable and maintainable platform to support educators and learners globally. I'm enthusiastic about embracing new challenges and making meaningful contributions. Basel Issmail Basel Issmail ’m a Senior Full-Stack Developer and Tech Lead with experience designing and building scalable web platforms. I work across the full development lifecycle, from translating business requirements into technical architecture to delivering reliable production systems. My work focuses on modern web technologies, including TypeScript, Angular, Node.js, and cloud-based architectures. I enjoy solving complex technical problems and helping teams turn product ideas and prototypes into working platforms that can grow and scale. In addition to development, I often collaborate closely with product managers, business analysts, designers, and QA teams to ensure that solutions align with both technical and business goals. I enjoy working with startups and product teams where I can contribute both as a hands-on engineer and as a technical partner in designing and delivering impactful software.

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Frequently Asked Questions

How often should I poll my API?

It depends on the use case. Chat messages: 5-10 seconds (or switch to WebSockets). Notifications: 30-60 seconds. Dashboard data: 30 seconds to 5 minutes. Always consider using push-based alternatives (SSE, WebSockets) for true real-time needs.

How do I calculate the API load from polling?

Multiply: (concurrent users) x (polls per minute) x (endpoints polled). Example: 1000 users polling 3 endpoints every 5 seconds = 1000 x 12 x 3 = 36,000 requests per minute. This adds up fast and is why push-based solutions are preferred at scale.

Related Cursor Issues

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