Expert Insights on Startup Tech Stack Scaling
Expert Insights on Startup Tech Stack Scaling
Is Your Startup's Tech Ready to Scale? Expert Tips Inside
You want to scale, right?
That comes with more users (great!) and hence, more demands on your infrastructure (less great).
What worked great for your first 100 customers may not work for 1,000 or 10,000 users. Knowing when and how to upgrade your tech stack is crucial for your growth.
Is It Time to Scale Up?
Many indicators are available in your startup daily life. But if you start monitoring these 4, you WILL notice when it’s time to scale:
1. Slow load times: If your website or app takes more than 3 seconds to load, 40% of users will abandon it.
2. Frequent crashes or downtime: Unreliable service will quickly hurt customer trust. Aim for 99.9% uptime.
3. Running out of storage: If you have to constantly purchase more storage, you've probably outgrown your current setup.
4. Inability to handle spikes: Can your system handle a sudden surge of traffic or transactions (like a Black Friday sale)? If not, it's time to scale.
Scaling Strategies
As for many things, there’s (unfortunately) not one-choice-fits-all.
For most strategies, we can distinguish 2 types of scaling:
Vertical Scaling ("Scaling Up"), adds more power (CPU, RAM, etc.) to your existing server(s). It's the simplest approach, but has limits in terms of maximum capacity (you can’t add an infinite amount of RAM in your personal computer, it’s the same for servers). It’s good for handling increased loads, up to a certain point.
Horizontal Scaling ("Scaling Out") involves adding more servers to your infrastructure and distributing the load among them. It provides more flexibility and room for growth. Kubernetes and Docker are popular tools for managing horizontal scaling.
These tools being pretty complex, all cloud providers (AWS, GCP, Azure, Scaleway…) provide high-level tool that allow you to easily manage and automate the scaling process.
For example, AWS offers Elastic Beanstalk, which handles capacity provisioning, load balancing, and application health monitoring automatically.
Google Cloud provides Google Kubernetes Engine (GKE), a managed environment for deploying, managing, and scaling your containerized applications using Kubernetes. This abstracts away much of the complexity, making it simpler for startups to implement horizontal scaling without deep expertise in infrastructure management.
I’ve helped startups choose their tech infrastructure and build their processes for more than 15 years. If you have any questions or doubts, I offer a free 30-minute consultation to help you make the right decisions.
When it comes to handling more data, databases will also, of course, be affected.
As you scale, you may need to transition from a single database to a distributed database system. Options include:
- Sharding: Splitting your database across multiple servers
- NoSQL databases: Like MongoDB or Cassandra, designed for scalability
- NewSQL databases: Like CockroachDB or TiDB, these aim to provide the scalability of NoSQL with the consistency of SQL
Serverless architecture: With serverless, you don't manage the infrastructure at all - it automatically scales based on demand. AWS Lambda, Google Cloud Functions, and Azure Functions are leading serverless platforms. This can be very cost-effective, as you only pay for the compute time you actually use.
Content Delivery Networks (CDNs): CDNs like Cloudflare or Akamai cache your static content across a global network of servers, reducing load times for users far from your main servers.
How Can I Balance Cost and Performance?
As always, in your startup life, you need to carefully balance infrastructure costs against performance requirements.
Having more users does not necessarily having much more money to spend. Here are some tips to get the best out of your infrastucture without over-spending:
- Use cloud spot instances: These offer unused cloud capacity at huge discounts (up to 90% off)
- Right-size your instances: Don't pay for more capacity than you actually need. Use the providers monitoring tools and advices
- Take advantage of serverless: As mentioned, serverless can provide automatic scaling (up and down) while minimizing costs
- Use open-source software: Try to avoid vendor lock-in and licensing fees
Case Studies
Even if the following are now big names in the game, they once were where you’re at.
- Airbnb: Airbnb famously scaled from 50,000 to 80 million users on AWS, using Amazon ECS for orchestration
- Spotify: Spotify moved from on-premises data centers to Google Cloud as soon as in 2016, hugely improving scalability and performance
- Pokémon GO: The game's meteoric rise put intense strain on its infrastructure. The developers relied on Google Cloud to scale to over 500 million downloads
Don’t forget that scalability is not a reactive action. It needs to be in your mind right from the start, and influence your technology decisions from the start, to ensure your startup's infrastructure is always ready for the next stage.
P.S. If you need help assessing your startup's scalability needs, I offer free 30-minute consultations. Book yours now!
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