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The business cases adopted by the cloud have been developed and quantified by business leaders. Early adopters of private and public clouds have begun to see measurable results in reducing time to market, operational efficiency, and costs. As companies migrate workloads to the cloud, other benefits, such as higher scalability and higher performance, become more apparent.

According to a 2017 McKinsey report, some trends are obvious when comparing the workloads that companies choose for cloud placement. SaaS has the highest growth rate, with the highest percentage of backend support workloads, communications and collaboration solutions, and marketing and sales solutions. The public cloud is the best choice for development, testing, and Web workloads. Private clouds show the highest growth in infrastructure services and core business operations.

Continue to drive all enterprises to adopt these three cloud models (public, private, hybrid) rapidly over the next few years, achieving quantifiable financial resources and productivity. In adopting the cloud model, a detailed adoption plan must be developed to successfully address the required supporting technologies and processes, the most critical of which is to promote the participation of technology, culture, and stakeholders. In this article, we will focus on supporting technologies.

Key technologies to support cloud adoption

The best examples of enabling technologies that make cloud possible are virtualization and software-defined networking (SDN). Without these technologies, the clouds we have today would not exist. They are the core building blocks of every cloud technology. According to Wikipedia, virtualization refers to something that creates virtual (rather than physical) versions, including virtual computer hardware platforms, virtual storage devices, and virtual computer network resources.

SDN is another key driver of our ability to deal with networking and security in the cloud, and it is also a key part of implementing automated configuration and automation technologies. SD-WAN or software-defined WAN is a subset of SDN, no matter which cloud model or model they choose to adopt, it is critical to the enterprise.

SD-WAN is critical to reliability in the cloud

Even if enterprises achieve 100% cloud adoption, they still need to maintain the infrastructure to access cloud resources for enterprise users, remote offices, teleworkers, or retail sites. As part of this access, enterprises will need to monitor and define policies to ensure reliable and cost-effective access to these resources, which is an opportunity for SD-WAN to use its talents. In addition to providing reliable access by combining any form of connection from MPLS, broadband to wireless services such as 4G and LTE, SD-WAN is critical to defining business policy and security when accessing any form of cloud resources.

The first generation of SD-WAN technology allows you to bind different connection sources to ensure high availability. The second generation technology is application-centric, allowing policies to be defined and implemented according to practical applications, in-depth analysis and actual user experience monitoring. In addition to the network-only metrics (including bandwidth, latency, loss, and jitter) used by the first-generation SD-WAN, the second-generation SD-WAN makes execution and remediation decisions based on metrics that include user experience (response time, transaction throughput). For example, if the primary link reduces only one of the many services provided by Office365, the second-generation SD-WAN will take appropriate steps to automatically divert that traffic to a better-performing link based on the overall user experience. In addition to the network-only metrics (including bandwidth, latency, loss, and jitter) used by the first-generation SD-WAN, the second-generation SD-WAN makes execution and remediation decisions based on metrics that include user experience (response time, transaction throughput).

Second-generation SD-WAN is not just about automatic repair, continuous monitoring and performance evaluation of applications, and matching with SLA to deal with problems that take hours for full-time IT engineers to solve. If it is necessary to temporarily slow down less critical traffic types to ensure the necessary bandwidth or performance of business-critical functions, it can be handled automatically according to defined business policies without user intervention.

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