Imagine this: Your app goes viral.
Revenue is rising fast, but instead of celebrating, you are worried as your system struggles to keep up - pages lag, servers crash, and customers get frustrated.
This is a real challenge for many startups that grow quickly without a strong tech foundation.
Even big names like Zerodha and Amazon have faced serious tech hurdles. Zerodha processes over 100,000 transactions every day, but once lost crores during a trading surge due to system overload. Amazon Prime Video managed to cut its operational costs by 90% after reworking its complex infrastructure.
The lesson? Scaling too quickly with the wrong technology can lead to costly failures.
In this article, we’ll share common scaling problems and how smart tech choices help businesses grow fast and save money.
You know that your tech stack is more than just software. So let’s build it smart.
What is a Tech Stack?
A tech stack is a group of tools, programming languages, and services used to build your software product. It includes things like the backend (server-side), frontend (user interface), database, and hosting services.
Choosing the right startup tech stack is very important. A strong stack helps your product run fast and handle more users. But if your stack is weak or poorly planned, your app may crash or slow down as it grows.
Problems that Companies Face When They Scale Without Planning
1. Started Small, But Didn’t Plan for Growth
- Many companies build their product quickly to launch fast. At the start, everything works fine. But as users grow, the system starts to break, it becomes slow, unresponsive, or crashes.
2. Microservices Look Cool, But Are Not Always Right
- Some companies follow trends and build microservices early. But each service needs its own setup and team. Without proper planning, it becomes very difficult to manage.
3. Too Many Things Going On, No Full Control
- When many teams work on different parts of the app, it becomes hard to understand the full system. If one team makes a small change, it can affect other parts and cause errors. This makes the system confusing and hard to manage.
4. Costs Go Up, But Speed Goes Down
- More services mean more cloud servers and more cost. Also, services talk to each other over the internet, which takes time and slows down the app.
5. No Load Testing or Real-World Checks
- Many teams don’t check how much user load their system can handle. When real users come in big numbers, the system fails badly.
6. Features Increase, But Structure Gets Messy
- New features are added quickly without planning. This makes the code messy and hard to manage. Over time, fixing or changing anything becomes risky.
7. Team Is Small, But the System Is Overcomplicated
- A small tech team tries to manage too many services. This creates pressure, more bugs, and slow progress.
8. Users Suffer, Business Slows Down
- Slow apps, errors, and downtime make users unhappy. This reduces trust and can hurt business growth.
9. Monitoring Tools Are Missing or Weak
- Without good tracking and monitoring, teams don’t know when a service is down or slow. Problems stay hidden until users complain.
10. Poor Communication Between Teams
- In fast-growing companies, teams often work in silos. They don’t talk enough. This causes mistakes, delays, and confusion in the tech system.
11. Switching to Better Tech Becomes Hard Later
- If the wrong setup is used in the beginning, changing it later becomes a big challenge. It takes a lot of time, money, and risk to fix everything once it’s too large.
12. Security Gets Ignored During Scaling
- While rushing to handle more users, teams often forget to secure their systems. This can lead to bugs, data leaks, or hacking risks.
How to Select the Right Tech Stack That Increases Growth?
1. Start Simple, Don’t Overbuild Too Early
- In the beginning, use a monolithic structure (everything in one system). It’s easier to manage with a small team. You can add complexity later when your product grows and your team becomes bigger.
2. Move to Microservices Only When Ready
- Don’t jump to microservices right away. Start with what your product needs. If something like payments grows quickly, break that part into a microservice.
3. Test Your System With Real Load
- Before launching or during peak times, check how your app handles heavy traffic. Use load testing tools to see what breaks under pressure. Fix those weak points in advance, just like Zerodha does.
4. Use Tools That Handle Scale Better
- Use cloud tools like AWS Batch, Load Balancers, and Auto-scaling groups. These tools help your system stay fast even if 1,00,000 users come at the same time. Zerodha used such tools to handle its growing users smoothly.
5. Keep Codebase Clean and Well-Organized
- As you add more features, make sure your code stays neat. Follow good coding practices, name things properly, and write simple logic. This helps when your team grows or when you need to fix bugs quickly.
6. Monitor Everything, All the Time
- Add strong monitoring tools to track your system’s health. If something goes wrong, you get alerts early. This saves you from surprise crashes. Tools like Datadog, Prometheus, and New Relic are commonly used for this.
7. Use Caching and Queues for Speed
- For faster performance, use caching (like Redis) to store repeated data. Also, use queues (like RabbitMQ or Kafka) to manage tasks in the background. This reduces pressure on your main system and improves speed.
8. Train and Grow Your Team with the System
- As your system grows, grow your team too. Don’t let a small team handle too many services. Hire wisely, train developers, and keep clear roles so everything runs smoothly.
9. Build a Clear Roadmap for Scaling
- Before scaling, create a plan. Decide what needs to change first- database, services, servers, or team. This gives direction and avoids last-minute panic.
10. Communicate Openly During Outages or Bugs
- If something breaks, talk to your users. Share what happened and how you’re fixing it- like Zerodha does on their blog. It builds trust and keeps users calm even during issues.
11. Focus on One Problem at a Time
- Don't try to fix everything together. Pick the biggest problem- like speed or reliability and solve it properly. Then move to the next one. This keeps your team focused and avoids burnout.
12. Always Keep Users First
- Every change you make, whether in tech or team, should make life better for your users. Fast app, smooth experience, fewer bugs- these things help you grow faster and build trust.
Real Life Case Studies & Learnings
How Zerodha Handles 1 Lakh+ Trades Daily Without Crashing?
Zerodha is one of the biggest stock trading platforms in India. Every day, it handles more than 1,00,000 transactions. To manage such a large number of users and activities, Zerodha needed a strong and smart technology system.
In the beginning, simple development methods are enough. But as the company grows, the system also needs to grow. Zerodha could not depend on a single system (called monolithic), so they moved to a better structure called microservices.
Here’s how Zerodha built a system that works fast and handles heavy traffic:
- Microservices: Instead of one big system, Zerodha used small services for each task, like handling transactions, generating reports, or managing user accounts. This helps the platform stay strong even if one part has a problem.
- Pipelines and Deployment: They used automated pipelines. This means whenever the team updates something, it gets tested and deployed quickly with the help of tools like Docker.
- Auto-scaling: When many users log in at the same time (like during market opening), the system increases its power automatically by adding more servers.
- Smart Algorithms: Zerodha’s system also uses smart coding techniques to make sure everything runs fast. This includes solving time delays and keeping the platform smooth.
So, Zerodha did not just grow its users- it also improved its technology to handle that growth in the right way. This is a great example of how important it is to choose the right tech stack while scaling your business.
How Amazon Saves 90% of Costs by Rebuilding Its Video System?
The Problems: Amazon Prime Video’s team was facing a major challenge with its Video Quality Analysis (VQA) system. This tool was responsible for monitoring thousands of live video streams to detect audio and video quality issues.
However, the existing setup was built using distributed microservices and AWS serverless tools like Lambda and Step Functions.
Here’s what went wrong:
- Scaling bottlenecks: Step Functions performed too many state transitions, hitting account limits and slowing things down.
- Sky-high costs: Constant communication between services and repeated calls to S3 for storing video frames added heavy expenses.
- Not built for scale: The original tool wasn’t designed to handle such a large volume of streams.
All of this resulted in a system that worked, but wasn’t practical for large-scale usage due to high operational costs and limited scalability.
The Solution: Smart Move from Microservices to Monolith
Instead of scrapping the system completely, the Prime Video team made a smart architectural change.
Here’s what they did:
- Combined all components into a single process (monolith): This allowed all data transfers to happen in memory instead of going through S3, reducing latency and cost.
- Replaced AWS Step Functions with internal orchestration logic: This simplified the workflow and removed the dependency on state transitions that were causing scale issues.
- Deployed the new monolithic service in ECS containers: It runs as part of a broader event-driven system but focuses on efficient performance.
- Cloned the service with different detectors: Since one instance couldn’t scale endlessly, they cloned the monolith for different workloads and used a lightweight orchestrator to handle traffic.
Important note: This wasn't a traditional "monolith" in the old-fashioned sense– it was a refactored microservice running in a single container for better control, not spaghetti code.
The Results: 90% Cost Reduction and Scalable Performance
After this architectural shift, the results were impressive:
- Reduced operational costs by 90%
- Improved performance by keeping data in memory
- Enabled smooth horizontal scaling by cloning services smartly
- Simplified orchestration and deployment, making the system more manageable
This shift wasn’t just about going from microservices to monolith- it was about choosing the right approach for the job. The initial serverless architecture allowed rapid development, and the optimized monolithic service allowed efficient scaling and cost control.
Why Tech Stack Matters in Scaling?
When you first launch a product, things feel easy and smooth. But as your users grow, your tech needs grow too. If your tech stack is not ready, your app will start to break down and slow down.
- When a company is small, even a basic tech stack works well.
- But as more users join, the same tech stack may not handle the load.
- You may see problems like slow speed or app crashing.
- These issues happen because the base setup was not made for scaling.
- That’s why picking the right tech stack from the beginning is important.
- The tech stack includes server, backend, frontend, database, and system type.
- System type means whether it is monolithic or uses microservices.
- A smart tech stack helps your app grow without major problems.
- It keeps things simple, fast, and easy to manage.
- Good choices early can save time, money, and stress later.
Your tech stack is like the base of your building. If it is strong, you can build higher without fear. So always choose tools and systems that grow with your business.
Conclusion
Growing your product is exciting, but if the system is not ready, it can create big problems. Many companies make mistakes by overbuilding too early or not planning for scale properly. The smart way is to start simple, test with real users, and grow step-by-step.
Is your tech ready to scale? Let's connect! We’ll guide you to the right solution and ensure you avoid costly mistakes.
Thanks for reading till the end. See you soon in our next blog with more real and helpful content.
