We’re on a mission to simplify application deployment for developers and businesses worldwide. Our next-generation serverless platform enables you to deploy and scale AI workloads, full-stack applications, APIs, and more in seconds — without any complexity. 2024 was filled with major milestones in this journey: Autoscaling, scale to zero, new regions, faster deployments, Volumes and Snapshots, and so much more.

Over 70% of global enterprises generate, store and use their data in hybrid environments. But while hybrid cloud adds flexibility, it also introduces complexity. This often leads to customers avoiding implementation of mixed virtualization and container platforms in order to prevent additional complexity and to address talent shortages, as each platform is intricate and requires specialized skills.

In today’s dynamic digital landscape, multi-cloud strategies have become vital for organizations aiming to leverage the best of both cloud and on-premises environments. As enterprises navigate complex data-driven transformations, hybrid and multi-cloud models offer unmatched flexibility and resilience. Here’s a deep dive into why and how enterprises master multi-cloud deployments to enhance their data and AI initiatives.

As organizations shift from on-premise to cloud-based systems, they need solutions that simplify the transition and optimize data use with ease. With a staggering 89% of businesses now using cloud technology in some capacity every day, it is vital that business leaders invest in solutions that make it easy to use cloud applications and get the same or better results that they’re used to with on-prem solutions.

Snowflake is one of the top cloud data warehouses. Regardless of the many documentations available, I have personally faced issues while carrying out Snowflake CDC (Change data capture). Therefore, I thought sharing everything a data practitioner should know about this before you start would be helpful. Let’s jump right into it!

The healthcare sector is undergoing a remarkable wave of innovation, especially due to the integration of cloud computing in healthcare. From solidifying security to enhancing predictability, and improving performance, this transformation is touching every facet of the world while also supporting business transformation. The implementation of cloud computing in the healthcare sector has fundamentally transformed how medical data is generated, accessed, stored, and exchanged.

AWS re:Invent is one of my favorite trade shows. It is one of the biggest technology conferences of the year and is an opportunity to have hundreds of conversations with customers and prospects, listen to their priorities and challenges, hopes, and give them a Cloudera tote bag or a pair of orange sunglasses. What follows is a collection of just a few things I learned and observed during my week in Las Vegas.

This December has been full of pivotal serverless milestones. We've rolled out a series of major features designed to make your deployments experience smoother, faster, and more cost-effective: Let’s dive into this recap to cover everything that is new and share the resources you need to run and scale your workloads.

As a data engineer who has designed and managed ETL (Extract, Transform, Load) processes, I've witnessed firsthand the transformative impact of cloud-based solutions on data integration. Amazon Web Services (AWS) offers a suite of tools that streamline ETL workflows, enabling mid-market companies to move the big data to data stores such as Snowflake, data lake from different sources depending on use cases.