All posts tagged with streaming data


Building a SaaS product, a system to handle sensor data from an internet-connected thermostat or car, or an e-commerce store often requires handling a large stream of product usage data, or events. Managing event streams lets you view, in near real-time, how users are interacting with your SaaS app or the products on your e-commerce store; this is interesting because it lets you spot anomalies and get immediate data-driven feedback on new features. While this type of stream visualization is useful to a point, pushing events into a data warehouse lets you ask deeper questions using SQL.

In this post, we’ll show you how to build a system using Apache Kafka on Heroku to manage and visualize...

This is the first in a series of blog posts examining the evolution of web app architecture over the past 10 years. This post examines the forces that have driven the architectural changes and a high-level view of a new architecture. In future posts, we’ll zoom in to details of specific parts of the system.

The standard web application architecture suitable for many organizations has changed drastically in the past 10 years. Back in Heroku’s early days in 2008, a standard web application architecture consisted of a web process type to respond to HTTP requests, a database to persist data, and a worker process type plus Redis to manage a job queue.

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