Scale: Software architecture
Architecture that stays fast as you grow
In short
Kafka.id designs software for systems that have to stay fast under load. We pick the stack, shape the data so common questions are cheap to answer, add caching where it pays, and design multi-tenant SaaS so every customer's data stays separate. We run a platform like this for our own products.
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Who it is for
- Products that slow down every time traffic or data grows.
- Teams planning a SaaS product with many customers on shared servers.
- Companies about to rebuild that want the stack chosen on evidence.
What we do
- 1
Measure
We find what is slow by measuring it: query plans, response times and load tests.
- 2
Design
We write the architecture down: services, data model, caching, and how tenants are kept apart. Every choice comes with its reason and its cost.
- 3
Build the hard parts
We build or rework the pieces that carry the load, such as the data layer, search, queues and caches, with your team or for them.
- 4
Prove it
We load-test before launch and leave monitoring in place, so you can see how much headroom you have.
What you get
- An architecture document your developers can follow
- Indexes, query fixes and caching where they make a measured difference
- Tenant isolation designed in, so each customer sees only their own data
- Load test results from before and after
- Dashboards and alerts for the numbers that matter
Questions
What does multi-tenant mean?
One installation of your software serves many customers, called tenants, and each one sees only their own data. Done well, it lowers hosting costs and makes updates simple. Done badly, one bug can show a customer someone else's data, so the isolation has to be designed in from the start.
Why is our app slow when the server is not busy?
The time often goes to the database: a missing index, a query that runs once for every row, or far more data sent to the browser than the page needs. More servers do not fix these. Measuring finds them, and the fix is usually small once found.
Which stack do you use?
We often build with Go, Next.js and PostgreSQL, with Redis for caching, because they are fast, well supported and cheap to run. But we choose for your team and your load. If your developers know another stack well, that can be the better choice.
Do we need microservices?
Most products do not, at least not at first. One well-organised application is easier to run and to debug. We split a service out when there is a clear reason, such as very different load or a separate team.
Tell us what you're working on.
The brief takes about two minutes. Pick where to start:
Or email hello@kafka.id
