With interest in big data and cloud increasing around the same time, it wasn’t long until big data began being deployed in the cloud. Big data comes with some challenges when deployed in traditional, on-premises settings. There’s significant operational complexity, and, worst of all, scaling deployments to meet the continued exponential growth of data is difficult, time-consuming, and costly.

Thank you for your interest in the 451 Research Report, Living on the edge: A primer on hybrid cloud and edge infrastructure. You can download it here. 451 Research: Living on the edge: A primer on hybrid cloud and edge infrastructure Published Date: October 11, 2021 Introduction Without the internet, the cloud is nothing. But few of us really understand what is inside the internet. What is the so-called ‘edge’ of the internet, and why does it matter?

Interested in learning about different technologies and methodologies, such as Databricks, Amazon EMR, cloud computing and DataOps? A good place to start is reading articles that give tips, tricks, and best practices for working with these technologies. Here are some of our favorite articles from experts on cloud migration, cloud management, Spark, Databricks, Amazon EMR, and DataOps!

Spark is known for being extremely difficult to debug. But this is not all Spark’s fault. Problems in running a Spark job can be the result of problems with the infrastructure Spark is running on, inappropriate configuration of Spark, Spark issues, the currently running Spark job, other Spark jobs running at the same time – or interactions among these layers.