Azure Data Factory is a cloud-based data integration service that allows you to orchestrate and automate data movement and transformation using cloud-based data-driven workflows. It provides a cost-effective solution whenever a dependable code-free ETL tool on the cloud with numerous integrations is required. This blog will highlight how users can use Serverless360 to manage and monitor multiple Azure Data Factories with different pipelines. Azure Data Factory consists of a variety of components like.

Since being launched in 2014, the AWS Lambda service has spread fast amongst developers and cloud architects, for it is easy to use, and there is a significant cost benefit (pay-per-use basis). AWS Lambda is an Amazon Web Services serverless deployment platform that you can use in the AWS cloud environment with basically no overhead. It will save you much time and resources using Lambda for performing code tasks for websites, applications, and services running on AWS.

Fourteen billion dollars – that’s the projected global market size for serverless, which is supposed to grow by about 26 percent annually in the next few years, according to the recent Global Serverless Architecture Market report. The fast pace of adoption of serverless is hardly surprising because the technology can save significant costs for companies. It can enable them to build and deploy software and digital products without providing and maintaining any virtual or physical servers.

The cloud native revolution brought by Kubernetes has transformed the way we build and deliver software, but the world of big data has for too long been left on the side of this transformation. Thanks to many contributions from the open source community, Apache Spark integration on top of Kubernetes is now officially generally available with the recent releases this year.

Serverless reduces a lot of operational burdens, but a ������������ ������������������������ is still your responsibility 🔐 From web threats, over IAM principles to auditing and monitoring.