I am a server-side developer who is used to Graphite/Promethus/Influx style solutions for monitoring application performance, as well as APM tools such as NewRelic.

For our (react-native/expo) app, it performs well on the simulator and our test phones, but we get anecdotal reports of bad performance from users in production.

What do people do about this problem?

Websites and mobile apps today are more than just digital platforms. They are often the first point of contact between businesses and their customers. Whether you're building an eCommerce store, a telemedicine platform, or a food delivery app, performance is not optional. It directly impacts user experience, SEO, and revenue.

In this article, I want to take you behind the scenes of how we, as an experienced app development company, approach the building and ongoing maintenance of high-performance websites and mobile apps. This is not just theory—it’s the same proven process we've applied across hundreds of projects for startups and enterprises alike.

Let’s break it down step-by-step.

Step 1: Defining Performance Goals Early On

Before a single line of code is written, we work with our clients to define clear performance goals. This includes:

Load time targets (e.g., under 2 seconds for mobile)

Time to Interactive (TTI)

Server response times

Expected number of concurrent users

Why is this important? Because performance isn't something you bolt on later. It must be baked into your product architecture from the beginning.

Stat to know: According to Google, the probability of a mobile site visitor bouncing increases by 32% as page load time goes from 1 second to 3 seconds.

Step 2: Choosing the Right Tech Stack

Performance often begins with the right tools. We customize our tech stack based on the product goals. Here are a few choices we make deliberately:

Frontend: ReactJS, Vue.js (for fast rendering and component reuse)

Backend: Node.js, Laravel, or Django (based on scalability needs)

Databases: PostgreSQL, MySQL, or MongoDB depending on structure and speed

Infrastructure: AWS, DigitalOcean, or Azure with CDNs like Cloudflare

Choosing a stack that complements the use case makes scaling easier and ensures better core performance.

Step 3: Performance-Focused UI/UX Design

Our design team is not just making things look good. They are making them fast. Here’s how:

Optimizing image sizes without losing quality

Avoiding heavy UI animations on mobile

Lazy loading assets and images

Using responsive design principles to speed up rendering

Pro Tip: A lean design = faster load times = better conversion rates.

Step 4: Writing Clean, Modular Code

Code is the engine behind your app. And just like with any engine, clutter slows things down. We follow clean code and modularity best practices:

Keeping functions small and single-purpose

Reducing dependencies

Avoiding unnecessary third-party plugins

Minifying CSS and JS files for faster rendering

Clean code is also easier to maintain later. And that brings us to...

Step 5: Setting Up a Scalable Architecture

We use a microservices-based architecture where needed to keep systems modular and scalable. This allows us to:

Scale individual components without affecting the whole system

Deploy updates quickly without downtime

Improve fault tolerance

Real-world impact: For one of our clients in the healthcare sector, we reduced server downtimes by 70% by breaking their monolithic system into smaller services.

Step 6: Continuous Performance Testing

Performance is not a one-time effort. We integrate performance testing in every sprint using tools like:

Lighthouse

GTMetrix

PageSpeed Insights

Apache JMeter (for backend/API load testing)

These tools help us monitor:

First Contentful Paint (FCP)

Largest Contentful Paint (LCP)

Cumulative Layout Shift (CLS)

Backend API response times

And we don’t just test—we fix. Every test report leads to actionable improvements.

Step 7: Proactive Website and App Maintenance

Post-launch, we offer website maintenance services. Here’s what that includes:

Regular security patch updates

Server health monitoring and auto-scaling setup

Bug fixes and technical SEO improvements

Performance optimization every quarter

CMS or framework updates (like WordPress core or Laravel upgrades)

Did you know? 70% of users say page speed impacts their willingness to buy from an online retailer. Maintenance isn't optional if you care about business outcomes.

Step 8: Using Analytics to Continuously Improve

You can’t improve what you don’t measure. That’s why we integrate analytics tools like:

Google Analytics 4

Hotjar or Microsoft Clarity

Firebase Performance Monitoring

These give us insight into real user experiences:

Which pages have high bounce rates?

Are certain devices slowing down performance?

Are users dropping off at specific steps in the funnel?

And yes, this data helps us decide what to optimize next.

Step 9: SEO + Performance Go Hand in Hand

Performance and SEO are best friends. Here’s how:

Google uses Core Web Vitals as a ranking factor

Fast load times improve crawlability and indexing

Optimized pages lower bounce rates and increase dwell time

Example: One of our B2B clients improved their organic search traffic by 48% in 6 months just by optimizing their app's load speed and structure.

We often collaborate with our SEO team right from day one. From sitemaps to schema to server speed, it's all part of the big picture.

Step 10: Client Education and Collaboration

Last but not least, we believe performance is a shared responsibility. We constantly educate our clients on:

How to avoid uploading large media files

Why content updates should follow SEO-friendly structure

What plugins to avoid in CMS platforms like WordPress

This keeps the site/app fast after we hand it over.

Final Thoughts

At the end of the day, high performance is not a luxury—it’s a business imperative. From the code we write to the designs we craft, every decision is performance-oriented. Because we know that:

A 1-second delay in page response can result in a 7% reduction in conversions

53% of mobile users abandon sites that take more than 3 seconds to load (Source: Google)

Pages that load in under 2 seconds see the highest conversion rates (Source: Portent)

So whether you're a startup founder building your MVP or a scaling enterprise with thousands of users, performance matters. And it’s our job to make sure you get it right from the start—and keep it right over time.

🚀 𝐑𝐞𝐝𝐮𝐜𝐢𝐧𝐠 𝐀𝐩𝐩 𝐒𝐭𝐚𝐫𝐭𝐮𝐩 𝐓𝐢𝐦𝐞 𝐢𝐧 𝐚 𝐡𝐢𝐠𝐡 𝐬𝐜𝐚𝐥𝐞 𝐎𝐓𝐓 𝐚𝐩𝐩 — 𝐌𝐢𝐬𝐭𝐚𝐤𝐞𝐬, 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠𝐬 & 𝐒𝐨𝐦𝐞 𝐏𝐚𝐢𝐧

While working on a media streaming app used by millions daily across a wide range of Android devices, I was part of a performance initiative focused on one of the most visible pain points: slow cold start time. So here’s what worked, what didn’t, and what I wish I knew earlier..

🧠 𝐋𝐞𝐬𝐬𝐨𝐧𝐬, 𝐄𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐬 & 𝐓𝐡𝐢𝐧𝐠𝐬 𝐓𝐡𝐚𝐭 𝐇𝐞𝐥𝐩𝐞𝐝:

Android has a wild variety of devices and OS nuances. Just defining "app startup time" becomes tricky — from the moment the user taps the icon to when content loads. As we had millions of data points, we could finally get a sense of where we stood. Some of the data was weird (thanks, Android ecosystem) — you never know what surprises 15k device models can throw at you.

🔍 𝐁𝐫𝐞𝐚𝐤𝐝𝐨𝐰𝐧 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡:

• Understand the full API call flow from app start to home render. Document it in the form of diagram, use whimsical or whatever drawing tool you know and share with team.

• Figure out what really needs to be loaded upfront and what can wait.• If you’re using a splash screen, and especially custom ones with timeouts or animations — you can use that time smartly to preload essentials for the home page.

• Dive into every section of startup code.• Identify things you can defer — analytics init, payment sdk init, etc.

• Use tools like Android Profiler, macrobenchmark, baseline profiles, and Perfetto to measure where time is being spent.Here’s a great video that helped me understand Perfetto: https://www.youtube.com/watch?v=YEX26m89fco

📊 𝐎𝐧 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 & 𝐥𝐨𝐠𝐠𝐢𝐧𝐠 (𝐝𝐨𝐧’𝐭 𝐣𝐮𝐬𝐭 𝐥𝐨𝐠 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐥𝐢𝐤𝐞 𝐢𝐭’𝐬 𝐟𝐫𝐞𝐞 𝐬𝐭𝐨𝐫𝐚𝐠𝐞)

• We created custom analytic events to breakdown user journey and pushed them to the server — because that’s where we could see aggregate patterns across millions of devices. You just can’t get that scale from local logs.

• But not everything needs to hit the server. For debugging and fine-tuning, we also used local timestamp events to track certain transitions.

• This balance helped us avoid polluting backend logs with noise, while still having high-granularity visibility when we needed it.

⚙️ 𝐌𝐨𝐫𝐞 𝐍𝐨𝐭𝐞𝐬:-

Make API calls async, and always check for network race conditions.

Cache with proper invalidation. Don't rely on device state like time. Feature flag also helps.

Use tools like macrobenchmark to run startup flows multiple times on different devices — and profile each section to find hotspots.

🎯 𝐋𝐚𝐬𝐭 𝐛𝐮𝐭 𝐧𝐨𝐭 𝐥𝐞𝐚𝐬𝐭:• Don’t rush into fixing things blindly. If you're working on a large-scale app where stakes are high, take time to step back, experiment, and verify.• Always document your learnings and share with team.

When Reddit’s team discovered their app took 12 seconds to launch for p90 (90%!) users, they were shocked. With over 2 million DAUs on the Android app, that meant about 200,000 users were waiting for >12 seconds for the app to load.

Reddit's engineering team made game-changing improvements to their Android app, reducing cold start times by over 8 seconds from app launch to the Reddit feed.

Here’s how they did it:

• They audited startup tasks from start to finish and classified tasks as essential, deferrable, or removable
• The team replaced legacy tech like old work manager solutions and Rx initialization with more modern patterns
• Optimized GraphQL calls and payloads as well as the amount of networking they were doing
• Deferred non-critical work and embraced lazy loading for efficiency, including stopping pre-warming non-essential features
• Modularized code ownership for all startup tasks to maintain startup health across teams.
• Introduced robust CI checks, startup experiment checks and observability to prevent regressions.
• Constituted an advisory group for benchmarking and tooling, which helped catch and prevent regressions

Thanks to these smart optimizations, Reddit’s cold start times have been consistently stable worldwide.

How do you all currently measure and optimise startup times? Have you seen if they're worse on some devices vs others, or some countries vs others?

Is it normal that the app performance of this game is hot garbage or is that just my phone?? Navigating menus is absolutely painful