Experiencing Slowness in Your App? Use This Simple Checklist to Diagnose and Fix
Follow this simple guide to quickly catch slowpokes causing problems in your app!

Experiencing Slowness in Your App? Use This Simple Checklist to Diagnose and Fix

App feeling sluggish? Pages hanging? API taking ages to respond?

Performance issues aren’t just annoying, they’re a silent killer of user trust. But before you start rewriting everything, slow down (ironically!) and go through this fast, focused checklist with follow-up explanations.

Whether you're a startup or scaling company, this method will help you pinpoint slowness and ship fixes that matter.


💡 The Signal vs Noise Action Plan

Don’t guess. Go methodically:

  1. Start with metrics and logs to target your approach.
  2. Clean up your code (frontend and backend).
  3. Compress responses and payloads.
  4. Cache smartly at every layer.
  5. Paginate what’s too big to send at once.


🧭 Start With Logging and Metrics

You can’t fix what you can’t see.

  • Check your APM (Application Performance Monitoring) tools like Posthog, Datadog, oe Grafana dashboards. Where exactly is time being spent: backend, frontend, network, or database?
  • Drill into slow endpoints and identify the longest spans.
  • Look at error rates and unusual log spikes. Slowness often travels with bugs.

Bonus tip: Turn on structured logging with trace IDs to follow requests end-to-end to more quickly pinpoint issues.


🧠 Make Sure Your Code Makes Sense

After looking at logging, start with what you control.

  • Frontend: Are you blocking renders with heavy calculations or redundant API calls? Poor React state management or unbatched updates can also tank performance.
  • Backend: What worked before scaling doesn't necessarily work now. N+1 queries? Nested loops over unindexed datasets? Inefficient joins? Any part of your code that says “I’ll just brute force this for now” should be the first to go under the microscope.

Keep an eye out for overly synchronous code. Async logging and batched external calls can drastically cut response time.


📦 Payload Too Big? Compress It

Bandwidth still matters.

  • Gzipping responses can dramatically reduce payload size, speeding up load times, and improving performance with minimal effort but can add CPU overhead for both server and client.
  • Are you shipping a 2MB JSON blob when you only need the first 10 items?
  • Frontend bundles bloated? Audit unused JavaScript, reduce third-party scripts, and lazy-load only when needed.

Compression + pruning = instant wins.


⚡ Can You Cache It?

Caching is one of the most powerful tools you have if used correctly. When exactly to bust a cache can be a difficult problem to solve but finding solutions that are "good enough" for most cases can deliver significant improvements for the average user.

  • Frontend: Browser or service worker caching for static assets or repeated API results.
  • Backend: Use in-memory caches like Redis for expensive or slow-to-generate data.
  • Edge: Platforms like Cloudflare or Vercel let you push cache decisions even closer to the user.

Not everything should be cached, but almost everything worth caching definitely isn’t cached yet.


📉 Paginate Large Responses

You don’t need to send all the data all the time.

  • A common cause of app slowness is loading everything “just in case.” Add pagination and possibly infinite scrolling patterns for better UX and better performance.


🛠 Performance isn’t magic, it’s a continuous process. Most performance wins are boring and incremental. But when your app feels fast and your users are happy, boring starts to look pretty brilliant.

Have you recently optimized your app’s performance? What’s one change that made the biggest difference?

👇 Drop your best debugging tip or favorite optimization win in the comments.

Max Kind

Solving Expensive Problems | Product Management

1mo

Great checklist — and here’s the systems truth: Slowness is rarely local. The root cause is usually architectural, not technical — an overloaded feedback loop, a missing flow control, or an org that scales code faster than it scales learning. If you’re fixing performance without reviewing how decisions and feedback move through your team, you’re tuning the engine without checking the driveline. Questions I’d want any team to ask during these fixes: • What signal were we missing that allowed this to go undetected? • How often are performance regressions caught before the customer sees them? • Do we log not just slowness, but why the fix didn’t happen earlier? Your app doesn’t just need to be fast. Your team needs to be fast at learning.

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