Many enterprise companies have moved at least some portion of their data or workloads into the cloud. That’s because the cloud offers fast and flexible access to the information that helps businesses run smoothly.
But what if you could turn your cloud into a platform for continual digital transformation? What if your cloud could work smarter, saving you time, money, and concern over not being ready for the next shift in digital technology?
The data landscape modernization concept of building a cloud environment offers an alternative to the lift and shift approach. Instead of simply transplanting resources into the cloud as they exist on-premise, the modernization approach focuses on building an end-to-end data platform that is secure, resilient, flexible, and scalable—and all built with cost optimization in mind.
Supercharge Your Cloud
We’re living in the age of Big Data and the concept is continually evolving. Data is the driving force behind many ongoing waves of digital transformation, and as technologists, we have to continue to find ways to innovate and build solutions that will drive educated business decisions through data and analysis.
All too many data platform cloud adoption initiatives involve lifting and shifting on-premise solutions and dropping them as-is, directly into the cloud. This is often not a forward thinking approach. Data landscape modernization focuses on building an environment that leverages PaaS. By stitching individual services together, you can build an extremely robust solution that can support a variety of use cases.
Why Optimize and Modernize?
To take full advantage of what the cloud has to offer, organizations need to stay current with technology. This isn’t always easy. Many organizations over time have built monolithic data platforms that are interwoven through a variety of applications to support day-to-day operations within the business.
The key to success is to uncover and highlight the dependencies of the data platform across the business, followed by defining a strategy and roadmap. By leveraging your strategy and roadmap, combined with the PaaS Azure has to offer, you can optimize and modernize those workloads in a phased approach.
Using tools like Azure DevOps gives you the ability to be agile in your development and release cycles. Azure DevOps has numerous built-in code-free activities available to support the creation of your deployment and release pipelines. Inherently, by adopting an agile methodology which follows your strategy and roadmap for optimization, you are now able to reduce your time to market with a very focused approach to the delivery of data services across the organization. Combine an agile methodology with the capabilities of PaaS in Azure and the total cost of ownership is greatly reduced due to limiting the amount of infrastructure. PaaS services do not require patching and upgrading, and standardizing and simplifying IT processes will help reduce operational costs.
Innovate Through Technology
Coming off of Microsoft Ignite 2019, all I can say is, “Wow!” I’m completely blown away by the growth and enhancements being made to PaaS since I first started working with them in Azure back in 2014.
Organizations around the world are committed to building the future of their business to be powered by the intelligent cloud, and Microsoft’s continued product developments prove it’s committed to investing and improving PaaS data services. These services are bringing next-gen capabilities to end users and putting the power in their hands to build innovative and leading-edge solutions.
With Microsoft’s large investments around IoT, AI, and machine learning, we are able to get an idea of where the industry is heading and you don’t want to be on the outside looking in. Now is the time more than ever that organizations need to focus on data and adopt a strategy for solving business problems. Leveraging innovative PaaS services like Azure Databricks or Azure Synapse are just the tip of the iceberg when it comes to providing the capabilities and insights needed to fuel the growth of your business.
Cost & Time Savings
By now, most organizations have heard of the Shared Responsibility Model for cloud computing. It differentiates which responsibilities are managed by the customer and which are delivered to you as a service. Typically, when building data solutions, I tend to lean towards the right two columns of the above diagram as much as possible for a variety of reasons, but mostly due to efficiencies and cost savings.
The need for analytics and use cases are ever-changing within organizations, so the ability to deliver a solution that solves business problems and provides ROI in a timely fashion is of the utmost importance. By leveraging PaaS and SaaS services, you are able to focus on solving the business problem at hand, while reducing costs and increasing the speed of development and deployment.
Not only can PaaS/SaaS services reduce your consumption cost by leveraging features like serverless or auto-scaling, but they can also free up operational costs. Your internal IT staff can now focus on critical business initiatives instead of managing and maintaining infrastructure.
With operating costs and budgets becoming tighter year over year, organizations are looking for ways to expand, improve, and grow through innovative technologies while keeping costs at a minimum. Looking past the lift-and-shift methodology and exploring modernization of the data landscape within Microsoft Azure accomplishes just that.
Interested in the latest and greatest in cloud capabilities? Read our take on the announcement of Azure Arc.