Operations | Monitoring | ITSM | DevOps | Cloud

For time series workloads the ability of serverless functions to scale up and down is a major advantage, especially for something like IoT devices that may have intermittent connectivity and might suddenly send data in bursts. In this type of situation, it doesn’t make sense to be paying for a server to be running 24/7 when you can use a serverless function and only pay for the compute you use.

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.