The Data Lake feature allows you to perform analytics on your data usage and prepare reports. Data Lake is a large repository that stores both structured and unstructured data. Data Lake Storage combines the scalability and cost benefits of object storage with the reliability and performance of the Big Data file system capabilities. The following illustration shows how Azure Data Lake stores all your business data and makes it available for analysis.
The goal of cloud computing is to make running a business easier and more efficient, whether it’s a small start-up or a large enterprise. Every business is unique and has different needs. To meet those needs, cloud computing providers offer a wide range of services. Cloud compute services including Virtual Machines, Containers, App Service and Serverless computing offer application development and deployment approaches if applied correctly can save time and money. Each service provides benefits as well as tradeoffs against other options. IT needs to have a good understanding of these compute services.
Virtual Machines (VM) is an emulation of a physical computer, which offers more control that comes with maintenance overhead.
Containers provide a consistent, isolated execution environment for applications. They are similar to VMs except they don’t require a guest operating system. Instead, the application and all its dependencies is packaged into a “container” and then a standard runtime environment is used to execute the app. This allows the container to start up in just a few seconds, because there’s no OS to boot and initialize. You only need the app to launch.
Serverless computing lets you run application code without creating, configuring, or maintaining a server. Each approach is optimized for specific use case. The core idea is that your application is broken into separate functions that run when triggered by some action. This is ideal for automated tasks.
The prefoliation of SaaS (Software as a Service) has made the delivery of technology for the business easier, faster and cheaper. SaaS is now a common system of record for organizations. This change has revolutionized the modern workplace and changed the traditional way of managing and securing the IT services for the organization. This shift has brought a completely new paradigm for IT teams on how to manage, secure and support this new landscape.
Organizations must understand exactly how SaaS applications operate and interact with each other. That includes understanding information that needs to be centralized and discovered and build insights on the data that is relevant to increase operational efficiencies. In order to reduce security risks and increase compliance, organizations must introduce automation where possible, and applying analytics on operational data to avoid alert fatigue.
A comprehensive data strategy including centralization, discoverability, insights, action, automation, delegation and auditability is needed to fill the gaps introduced by today’s SaaS environments and to gain the level of control and clarity that is essential for properly securing the corporate environment.