An old airport customer of mine (whilst I worked for another company) used to pop someone next to a busy runway with a stopwatch strapped round their neck. The unfortunate person had to manually log the time aircrafts spent on the runway to measure the runway occupancy. All very archaic. Even in those days.
There’s no doubt which programming language is winning the battle for global supremacy right now. JavaScript has powered past the 12 million developers mark, and 5 million of its loyal fans (some 40%) have come aboard within the last three years. Initially thought of as merely a Java spin-out, it is now used to power everything from machine learning libraries to space exploration robots. But to truly maximize the potential of JavaScript, developers have to implement an effective testing regime.
Building a multi-region or multi-cloud environment for your applications requires a lot of attention. In a typical deployment, you would have an API gateway running close to the several application runtimes. You should enhance your deployment to support different regions in a given cloud, or in an even more distributed and hybrid scenario, multiple services running across other public clouds and on-premise environments.
When it comes to machine learning (ML) in the enterprise, there are many misconceptions about what it actually takes to effectively employ machine learning models and scale AI use cases. When many businesses start their journey into ML and AI, it’s common to place a lot of energy and focus on the coding and data science algorithms themselves.
With the speed of change in artificial intelligence (AI) and big data, podcasts are an excellent way to stay up-to-date on recent developments, new innovations, and gain exposure to experts’ personal opinions, regardless if they can be proven scientifically. Great examples of the thought-provoking topics that are perfect for a podcast’s longer-form, conversational format include the road to AGI, AI ethics and safety, and the technology’s overall impact on society.
Snowflake is delighted to share the findings of a new Forrester Consulting Total Economic Impact™ (TEI) study that examines the potential return on investment for organizations that procure Snowflake through Amazon Web Services (AWS) Marketplace and then use Snowflake as a core part of your application’s architecture. We commissioned the study in partnership with AWS.
I’m excited to announce that Kong Enterprise, our modern, scalable service connectivity platform, is now available on top cloud marketplaces, including AWS Marketplace and GovCloud (US) regions, Azure Marketplace, Google Cloud Platform, and Red Hat Marketplace!
We’re continuously releasing new capabilities to enable more people to be productive and compliant when working with Apache Kafka. Our engineers have been hard at work on a great Christmas present for our amazing community of Kafka users. Before unwrapping our latest and greatest release, here’s a sneak peak of what’s inside.
In this article we are going to explore lateral joins. "What is a lateral join?" you may ask. It's a new kind of join that allows to extract and work with the single elements found inside an array, as if the array was a normal table. Lenses 4.1 comes with a lot of new features that make your life easier when working with arrays: we introduced 6 new functions to work with arrays, better support for array literals, and lateral joins.
