Scalability Comparison: Monolith vs Microservices
How do monoliths and microservices scale? The answer is more nuanced than the hype.
Scalability Comparison: Monolith vs Microservices
The common story is that microservices scale and monoliths do not. The truth is more nuanced.
How Monoliths Scale
You run multiple instances of the monolith behind a load balancer. Each instance handles any request. You scale horizontally by adding more instances.
Pros of Monolith Scaling
- Simple: one deployment, one set of metrics.
- No network calls between features (everything is a function call).
- Easier caching (one cache for everything).
Cons of Monolith Scaling
- You scale the whole app, even if only one feature is hot.
- A memory leak in one feature affects all instances.
- A long-running request on one instance can slow others.
How Microservices Scale
Each service scales independently. The chat service can have 10 instances while the auth service has 2. You scale only what is hot.
Pros of Microservice Scaling
- You scale only what needs it. Hot services get more instances; cold ones do not.
- Issues in one service do not affect others.
- Each service can pick the right tool (e.g., Go for a hot service, Node for the rest).
Cons of Microservice Scaling
- More deployments to manage.
- Network calls add latency and failure modes.
- Caching is harder (each service has its own cache).
When Monolith Scaling Is Enough
For most apps, a monolith behind a load balancer scales well. If your hot feature is 80% of traffic, scaling the whole app is fine. If different features have very different load patterns, microservices help.
The Takeaway
Monoliths scale by running more instances behind a load balancer. Microservices scale per service, which fits apps with very different load patterns. For most apps, a monolith scales fine. Split only the parts that need independent scaling.
Yes. You run multiple instances of the monolith behind a load balancer. For most apps, this scales well. Split into microservices only when different features have very different load patterns.
Each service scales independently. The hot service gets more instances; the cold ones do not. This fits apps where different features have very different traffic patterns.
You scale the whole app even if only one feature is hot, a memory leak in one feature affects all instances, and a long-running request on one instance can slow others.
More deployments to manage, network calls add latency and failure modes, and caching is harder because each service has its own cache.
For most apps. If your hot feature is 80% of traffic, scaling the whole app is fine. Microservices help when features have very different load patterns (e.g., chat is real-time, feed is read-heavy).
Ready to master Node.js completely?
Want to upskill yourself, crack your next interview, and get your dream job? Join our comprehensive course to dive deeper with high-quality video tutorials, solve interview questions, and a premium community.
Master Node.js
Want to upskill yourself, crack your next interview, and get your dream job? Join our comprehensive course.