- Name
- Nick Schrock
- Handle
- @schrockn
We’re proud to announce 0.13.0 of Dagster. We’ve made dramatic improvements to our core APIs, completely revamped our UI, and brought renewed clarity to our mission. We’ve even refreshed our beloved logo and mascot. This release is the most significant change since the initial release of the project two years ago.
A New Core API
Our goal is for Dagster to become a durable standard for years and decades to come. To achieve that, we need a stable, elegant foundation to build upon and stand behind. We wanted to set that foundation before cutting a 1.0 release, and this release is that new foundation.
We received consistent feedback from our users that adopting Dagster dramatically increases their productivity. Dagster enables fast development cycles, early error detection, and testability. These are the bedrocks of productivity.
Ben Pleasanton, Data Software Engineer at MapboxWith Dagster, we've brought a core process that used to take days or weeks of developer time down to 1-2 hours.
Platform teams also report that Dagster empowers stakeholder teams with end-to-end ownership of their data assets, from development to monitoring. Distributed ownership increases the productivity of the entire organization.
David Wallace, Staff Data Engineer at DutchieDagster empowers my stakeholder teams to own their data assets end-to-end like no other orchestrator can.
Increasing individual and organizational productivity is critical to our mission. Our approach to achieving that outcome has been the result of incremental development, learning, and adaptation. We felt it was time to step back, synthesize those lessons, double down on those strengths, and build a new, improved core that will stand the test of time.
To that end, we’re introducing new core APIs that are a step-function increase in simplicity, power, and elegance. We’ve cut the number of concepts in the core API in half. This both eases onboarding and reduces the complexity of mature Dagster usage. It is a massive leap forward. You can read about the details in our documentation and upcoming blog posts.
A Revamped UI and Visual Language
We’ve shipped a new design system that communicates our ambition, seriousness, and unique approach, eschewing the traditional “tech blue” that dominates typical SaaS products and developer tools. Our new logo signals maturity while still remaining approachable. Our visual elements with kinetic motion over regularized patterns show how we bring order to chaos and improve productivity.
We also shipped a completely new design language in our UI to match our new brand. Data practitioners live in their operational tools and deserve responsive, well-designed UIs. Our goal is to deliver consumer-grade user experiences for data practitioners and stakeholders, matching the standard of forward-thinking productivity apps we admire like Superhuman and Linear. We also want to expand the universe of stakeholders that can successfully interact with operational tooling by making it approachable, intuitive, and easy to use.
We believe Dagster now hits that bar, setting a new standard for UX quality in data infrastructure tooling: robust, powerful, and approachable.
A Clarified Mission
We’re privileged to count innovative organizations such as GoodEggs, Prezi, Loom, goPuff, Virta Health, Unicef, VMWare, Drizly, Scale.ai, Mapbox, and Earnest Research as users and design partners. Our technology is used across the globe, from the core of Silicon Valley stalwarts’ data platforms to backing the government of the Philippines' response to COVID.
Our community spans thousands of people and hundreds of companies across numerous industries and company sizes. But everyone we speak to has one thing in common: a data platform that manages its data assets.
Data within an organization resides in dozens or hundreds of SaaS apps, operational databases, and is ingested from external sources such as the web or sensors. Ripped from its original context or system of record, software must transform this data into usable and meaningful data assets, ranging from datasets to ML models.
That’s where the data platform comes in: the tools, services, and applications that store, transform, manage, and serve data outside its original source or system of record.
A data platform is a set of tools, services, and applications that store, transform, manage, and serve data outside its original source or system of record.
An organization’s data assets drive critical decisions, all the way from strategic business decisions made by leaders to automated decisions made within their user-facing products: Will a business target the right customer segment, allowing it to survive and thrive? Does a customer qualify for a loan or not? Is a train in a mass transit system likely to be delayed?
The complexity of data platforms cannot be wished away. It has to be managed and tamed by making engineers, practitioners, and stakeholders more productive and efficient. We think that this is one of the foremost and formidable software engineering challenges of the next decade. We believe the right kind of orchestrator is at the heart of that. That is why Dagster exists. Supporting you in that journey is what we’re here for and why we come to work every day.
Dagster’s mission: to empower every organization to build a productive, scalable data platform.
Dagster’s mission is to empower every organization to build a productive, scalable data platform.
The Road Ahead
To our design partners and our community: Thank you for your trust and participation. Your feedback along the way has been invaluable to the evolution of our core APIs. Now with this release, we enter a new era of long-term stability with a 1.0 release in view and set the foundation for whole new lines of product development.
We're always happy to hear your feedback, so please reach out to us! If you have any questions, ask them in the Dagster community Slack (join here!) or start a Github discussion. If you run into any bugs, let us know with a Github issue. And if you're interested in working with us, check out our open roles!
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- Name
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- Handle
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- Handle
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