Ably provides an edge messaging service to deliver data at low latency and power live and collaborative applications on millions of simultaneously connected devices. Our platform runs tens of millions of concurrent, long-running WebSocket and HTTP streaming connections and reaches more than 300 million devices across 80 countries each month. Ably is on track to power realtime digital experiences for one billion devices per month by 2024.

We’re entering the defining decade of data. While every aspect of our lives have been changed by data in recent years, the next ten will see data rebuild the world around us. Every business, in every industry, needs a plan to adapt to this new world if they want to thrive. But how? That’s a question in the minds of data leaders, CEOs, and board members. The right approach is critical if companies want to dominate this new era. The wrong decision can spell disaster.

At a distance of a million miles from Earth, the James Webb Space Telescope is pushing the edge of data transfer capabilities. The observatory launched Dec. 25 2021 on a mission to look at the early universe, at exoplanets, and at other objects of celestial interest. But first it must pass a rigorous, months-long commissioning period to make sure that the data will get back to Earth properly. Mission managers provided an update Feb.

In this tutorial, you will learn how to use the Xcode Archive & Export for iOS step to manage your code signing assets, archives and export an.ipa.

In June, more than 200,000 people will gather at one of the most emblematic festivals in Barcelona: Primavera Sound. In addition to pleasing the visitors (which is easy considering the line-up), the organizers must ensure that the sound levels do not disturb the neighbors in the area, something complicated considering it is an open-air festival. That’s where EmmaDB comes in.

In this tutorial, you will learn how to use the Xcode Archive & Export for iOS step with a Flutter app to manage your code signing assets, archives and export an.ipa.

Data infrastructure is rapidly growing and evolving along with infrastructure for AI/ML, with the latter growing largely independent from the former. An emerging generation of AI/ML tooling emphasizes data-centric versus model-centric approaches to the ML development lifecycle. These tools recognize that data is the foundation for AI and seek to open opportunities for all data professionals to participate by eliminating the unnecessary complexity of traditional model-centric solutions.

TL;DR: To add events monitoring with Crashlytics to a Unity Android app, you’ll first need to prepare a Firebase project, then add the Firebase plugin to Unity and configure Unity to work with Firebase. Finally, you also need to update your CI/CD pipeline to support the changes. Let’s see how to integrate Firebase Crashlytics into a Unity Android app to monitor and troubleshoot errors easily!

This guide will show you how to easily add Continual as the AI layer to your modern data stack with Snowflake at the core. The intention is to provide an introduction to using Continual on Snowflake. After completing this tutorial, users are invited to try more advanced examples. We are going to demonstrate connecting Continual to Snowflake, building feature sets and models from data stored in Snowflake, and analyzing and maintaining the predictive model continuously over time.