Avoid hidden data migration challenges


To thrive in today’s digital world, many businesses are adopting a cloud computing strategy. Driven by core goals such as rapid customer expansion and improved efficiency of IT spending, the C-suite’s push to adopt cloud services is no doubt also catalyzed by the report. $1 trillion in business value that he promises to unlock. Given the current state and pace of cloud adoption (smaller, non-critical workloads are scaling faster than larger, mission-critical workloads), it’s no surprise that the migration of enterprise-class workloads to the cloud remained an absolute priority for businesses in 2021 for the fifth consecutive year. Additionally, experts predict that cloud infrastructure spending will exceed 200 billion dollars This year.

With guidance coming from the top, many organizations are adopting a “cloud-first” strategy, which means that all new platforms and systems should first be considered for deployment on an architecture or platform. cloud service, and a (sometimes too) aggressive schedule is put in place to migrate all systems to the cloud.

Although a cloud-first strategy sounds attractive, executing it is difficult. When you dive into the architecture requirements, not all workloads are easily suited for a simple migration to the public cloud. An example is a legacy application that lives on an operating system that doesn’t have an adequate cloud alternative. Applications requiring fast performance (high throughput and low latency) also have unique considerations that cloud-native architectures and solutions struggle to address effectively (or at all). The back-end of these applications includes critical databases where sporadic performance or failures can spell disaster for the user experience, impacting the flow of services or causing outages that can disrupt the flow of business. As a reminder, to slow down is the new downtherefore being slow is just as unacceptable as being offline.

The grass isn’t always greener

Migratory struggles are not uncommon: Cloud Security Alliance finds that 90% of organizations have suffered from failed or interrupted data migration projects, primarily due to the complexity of moving from on-premises architectures to cloud-native environments. Even when companies successfully migrate their databases and applications to the cloud, they often find that the cloud grass isn’t any greener.

Moving data to the cloud comes with its own set of risks (posteriori/Shutterstock)

Since cloud environments rely on shared virtualized hardware architecture, hyperscalar providers throttle speed and data flow to ensure there is enough for everyone. Due to these QoS-based design limits, designed to accommodate the most common masses and workloads, large mission-critical workloads that use Oracle Where Microsoft SQL Server may not be able to achieve the high performance levels required to be useful in the cloud. Even shelling out more money to pay for higher levels of performance, cloud customers will only get a bit more speed before they max out.

The cloud certainly offers many benefits over legacy architectures, but if your most important workloads are now slow compared to how they were on-premises, the benefits are negated. This is why some companies have even resorted to off-site, i.e. moving their workloads from the cloud to a private cloud or to on-premises data centers.

According to 451 Research, 6% of organizations currently using IaaS/PaaS public cloud services have migrated to on-premises or colocation/enterprise data center environments, and 14% plan to do so within the next year. These numbers may not seem significant as a total percentage, but when you consider the class of workload involved that is repatriated (the most important critical applications) and the considerable time, effort, cost and risk spent on the initial migration to the cloud, it’s easy to understand the deep frustration of organizations that decide to repatriate and re-migrate their workloads. It’s a bad time for everyone involved, including cloud providers, who may have made promises they couldn’t keep.

Avoid repatriation and get the most out of the cloud

The cloud is here to stay and a transformative key to business innovation. Whether you’ve already started your cloud journey or have a corporate mandate to move all mission-critical workloads to the cloud, finding a way to make the public cloud work for you is essential.

By introducing a high-performance data platform into your design, you can significantly reduce migration risks by enabling robust and easy data mobility, while supporting large workloads that require fast performance, stability constant and guaranteed availability. A data platform sits between customer workloads and the underlying cloud infrastructure. Its goal is specifically to provide much faster performance and higher availability than cloud native alone. The value for customers who host their largest and most complex workloads on the cloud is that their cloud provider and a data platform can now handle these challenging workloads with ease.

To evolve in the current landscape, the question of migrating to the cloud is no longer if, but when and how, and avoiding moving mission-critical applications is not a viable option. Ultimately, detailed planning is required to migrate critical data and applications to the cloud, and success requires a watertight strategy. and the right environment, whatever the workload.

About the Author: Derek Swanson is the CTO of Silk (formerly Kaminario), where he is responsible for guiding the client-facing architectural teams, building the product roadmap, and is the organization’s lead technical evangelist. Derek has over 25 years of experience as a technology evangelist, systems architect, and data systems engineer. Prior to Silk, Derek had a distinguished career architecting, deploying, and operating enterprise-class networking, compute, and storage solutions in dozens of data centers. Derek holds a bachelor’s degree in political science and government from Brigham Young University, with a major in classical philosophy.

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