You can now configure payment method settings from the Dashboard—no code required. We call this integration path dynamic payment methods. 

Delivering a good user experience without compromising the authoring experience required us to develop an authoring format that enables writers to express interactivity and simple page logic without mixing code and content.

While developing Markdoc, we learned how to balance interactivity, customization, and authoring productivity while undertaking a major overhaul of our documentation platform.

On Sunday, March 6, we migrated Stripe’s largest JavaScript codebase from Flow to TypeScript. In a single pull request, we converted more than 3.7 million lines of code. The next day, hundreds of engineers came in to start writing TypeScript for their projects.

Sorbet has been a crucial part of Stripe’s growth in recent years. Today, Sorbet runs over our entire Ruby codebase, currently amounting to over 15 million lines of code spread across 150,000 Ruby files. Sorbet increases productivity and fosters a collective engineering culture. Here’s why we love Sorbet.

Abstracting away the complexity of payments has driven the evolution of our APIs over the last decade. This post provides the context and conceptual frameworks behind our API design—and the milestones that led to the PaymentIntents API.

We set out to build a globe that inspires a sense of awe, invites people to explore, and conceals details for discovery. Along the way, we evaluated existing tools, designed our own solution, solved four interesting technical challenges, and improved the way we collaborate. Here’s what we learned.

Building and testing a Stripe integration can require frequent switching between the terminal, your code editor, and the Dashboard. Today, we’re excited to launch the Stripe command-line interface (CLI). It lets you interact with Stripe right from the terminal and makes it easier to build, test, and manage your integration.

Logging is one of the oldest and most ubiquitous patterns in computing. We’ve found using a slight augmentation to traditional logging immensely useful at Stripe—an idea that we call canonical log lines. It’s a simple technique: in addition to their normal log traces, requests also emit one long log line at the end that includes many of their key characteristics. Having that data colocated in single information-dense lines makes queries and aggregations over it faster to write, and faster to run.

Stripe builds economic infrastructure, and we’re designing for a global audience and market. In doing so, we carefully consider our technology and tools, organizational structure, and employee representation. Successful global organizations establish this mindset for different reasons. For some, it’s foundational—their mission, product, and addressable market crosses time zones. Others develop an international customer base, hire remote employees, or begin to open offices abroad to extend their physical presence.

Reserved instances are hard to purchase effectively. It’s easy to allocate the wrong number, and hard to predict future compute requirements over time. Deciding which and how many reserved instances to buy is a non-trivial exercise at the nexus of cloud strategy, bin packing, and capacity planning. Here's how we use AWS Reserved Instances to dynamically scale our fleet of servers and predictably forecast our cloud spend.