Building In Public

A collection of 26 posts

Building In Public Featured

How to analyze usage from your MCP Server

Since Anthropic launched Model Context Protocol (MCP), thousands of developers have built MCP Servers to connect Claude AI to their unique contexts. Here's how to monitor your MCP Servers for errors and analyze usage with standard logging handlers, Tinybird, and Grafana.

Building In Public

Behind the scenes of Tinybird's big frontend refactor

We recently refactored the Tinybird frontend. Take a look behind the scenes at how we started, the choices we made, and how we arrived at a faster and simpler app deployment.

Building In Public

JWTs for API Endpoints now in public beta!

We are launching JWTs for API Endpoints into public beta! With JWTs, you can call Tinybird APIs directly from within the browser, with no middleware or other backend components necessary.

ClickHouse

ClickHouse®️ JOINs... 100x faster

We recently introduced two pull requests to ClickHouse that significantly improve JOIN performance in common scenarios.

Product

We rebuilt our docs from scratch. It was worth it.

Building modern docs begins with a modern tech stack. Here’s how we rebuilt our documentation and what it enables us to do for our customers.

Real-time Data

Iterating terabyte-sized ClickHouse®️ tables in production

ClickHouse schema migrations can be challenging even on batch systems. But when you're streaming 100s of MB/s, it's a whole different beast. Here's how we make schema changes on a large ClickHouse table deployed across many clusters while streaming… without missing a bit.

Building In Public Featured

How to scale a real-time data platform

Tinybird is an enterprise-grade data platform with large customers processing huge amounts of data. Learn how we scale to support their use cases.

Using Tinybird for real-time marketing at Tinybird

Here's how we use Tinybird to drive the growth of Tinybird.

ClickHouse

Resolving a year-long ClickHouse®️ lock contention

Here's how we fixed a problem that had stumped us for over a year and saw a 5x performance improvement in the process.

Why iterating real-time data pipelines is so hard

"Why can't we just use Git?"

Building In Public

Killing the ProcessPoolExecutor

A story about the Python GIL, threading, and fixing code that already works.

Building In Public

Building a faster CI pipeline with Turborepo and pnpm

We made 3 big changes that have shortened our frontend CI execution time despite a massive increase in code size and test coverage.

Building In Public

How we cut our CI pipeline execution time in half

Our GitLab CI pipeline was slow and flaky. Here’s how we used telemetry data, real-time analytics, and smart k8s configuration to fix it.

Building In Public

Horizontally scaling Kafka consumers with rendezvous hashing

How we used rendezvous hashing to horizontally scale Kafka consumers to support hundreds of concurrent topics with fewer connections, thus lowering our infrastructure costs.

Building In Public

How we recreated r/place with 10 lines of SQL

Two developers built a data-intensive real-time app in half an hour.

Building In Public

Thinking in Tinybird

The best way to build a data project in Tinybird is to work backwards

Our Beliefs

The hard parts of building data systems with high concurrency

Here are 8 things to think about when you're trying to scale in realtime.

Building In Public

How to monitor Tinybird using Datadog with vector.dev

Making better observability possible with Tinybird API endpoints and vector.dev

Company

The realtime data stack. What’s next for Tinybird.

Sign up and start turning data into realtime insights, actions and business value.

Product

Tinybird is out of beta and open to everyone

Sign up and start turning data into realtime insights, actions and business value.

ClickHouse

Clickhouse, Open Source and Tinybird

We are hiring full-time Clickhouse Developers. Find out why we contribute to Open Source (ClickHouse) and why we want to contribute much more.

Product

Product design: how our SaaS integrates with git

Analytics data projects are code and code should be in a repo.

Building In Public

How we processed 12 trillion rows during Black Friday

In this post we explain the data architecture, infrastructure and how we scale our real-time analytics service with ClickHouse.

Building In Public

How We Handle Technical Incidents and Service Disruptions

Part of providing an outstanding level of service is to react quickly and professionally when things go wrong. This is an account of a recent service disruption and how we handled it.

Building In Public

Our focus on Speed

There is no good way to uncover new insights underlying terabytes of data unless you make the process of working with it tremendously rewarding and fast.