Day 5 ️: Microservices, Cost Estimation, and Engineering Trade-offs!

🎉 Welcome Back, Future Tech Architects!

You’ve been crushing it so far! Logging? ✅ Monitoring? ✅ Resilience? ✅ . Day 4 was really mind blowing. We really managed to reduce all those support tickets that were happening so far 😤. NICE WORK chad.

And just when you thought things were settling down… your founder returns with even bigger questions. As things were going good, your founder starts making technical questions…

“Hey, should we move to microservices? I heard they’re fast and scalable!”

“Also, should we switch programming languages? Is Node.js too slow?”

Uh-oh. 😏 It’s time to put on your engineering manager hat 🎩 and start thinking big-picture!

🤔 Should We Move to Microservices?

💡 Microservices are great… for the right use case! But are they the right fit for us right now?

✅ Pros of Microservices

✔️ Scalability — You can scale different parts of the app independently.
✔️ Tech Flexibility — Use different languages for different services.
✔️ Faster Deployments — Teams can push updates without affecting the whole system.

⚠️ But There’s a Catch!

🚧 Complexity — Managing services, databases, and API calls is harder.
🚧 More Infrastructure Costs — Each service needs its own resources.
🚧 Harder Debugging — A failed request might involve multiple microservices, making debugging more painful.

📌 Final Verdict?
For a startup with a small team (≤15 devs), monolithic architecture is the better choice.

Rule of thumb: If your team is small and in one location, monolith is fine.
Microservices shine when teams are large and distributed across multiple locations.

🧐 Should We Change Programming Languages?

Your founder asks:

“Is Node.js slow? Should we move to Python or Go?”

⚖️ What to Consider?

1️⃣ Raw Performance? Yes, Go is faster than Node.js. But… does that actually matter for our use case? 🤔

2️⃣ Developer Cost? It’s cheaper and easier to hire Node.js devs than Go or Rust devs.

3️⃣ Migration Cost? Switching languages = months of rewriting code. Can we afford that?

📊 Cost-Benefit Tradeoff Example

• Node.js may be slower, but cloud compute power is cheap.
• Hiring Go developers costs more.
• Migration time = months of lost development.

📌 Final Verdict?
💡 Stick with Node.js for now! Optimize later if performance becomes a real bottleneck.

Lesson: Don’t switch tech stacks just because something is “faster”. Consider total cost, hiring, and training efforts.

💰 Feature Cost Estimation: How Much Does It Really Cost?

🎭 Example: Virtual Try-On for T-Shirts 👕

Your founder wants a cool new feature where users can try on t-shirts virtually using their camera.

Sounds amazing, right? But… how much will it cost to build and run?

🧮 Step 1: Estimating API Costs

Let’s break it down:

• 10,000 visitors/day
• 10% of users try the feature → 1,000 API calls/day
• Each API call costs $0.01

📌 Monthly cost:

1000 API calls/day × $0.01 × 30 days = $300/month

Not too bad… but what if we switch to real-time video processing? 😨

🎥 Step 2: Estimating Storage Costs

If each virtual try-on video is 1MB, storing 1,000 videos/day = 1GB/day

📌 Monthly storage cost (AWS S3 example):

1000 videos/day × 30 days × 1MB = 30GB/month

💰 S3 cost for 30GB storage = ~$0.69/month (super cheap).

📌 Final Thought: The real cost isn’t storage, but API compute time and bandwidth usage!

So every new feature involves so many decision. Its important to talk in numbers and analyze cost estimation for the feature. Thinking about frequency of usage, Cost per API Calls. That brings so much data while making decision to build a feature or not, or optimize to bring the cost down if it can be.

🤝 API Contracts & Service Level Agreements (SLAs)

Now that we’re working with external APIs (payment gateways, AI services, etc.), we need clear contracts.

What is an API Contract?

It’s an agreement between our system and external services about:

• ✅ What data will be sent?
• ✅ How fast should the response be?
• ✅ What happens if it fails?

📌 Key Takeaway:
API contracts help avoid misunderstandings and ensure smooth integrations. How are you going to write the code is not as important as how you expose this code to external systems.

🏆 Final Takeaways from Day 5

✅ Microservices? Not yet! Too complex for a small startup.
✅ New language? Stick to Node.js! Optimizing later is cheaper than migrating now.
✅ Cost estimation? Always break down API & storage costs.
✅ Capacity planning? Predict server needs before launching features.
✅ API Contracts & SLAs? Essential for reliable external integrations.

See you in the next blog! 😃🎉

💬 Got questions? Add a comment or hit me up on any socials. Thankyou.