The pace of cloud migration will accelerate: Most companies, by now, have started the journey to the public cloud or to a hybrid cloud environment. The events of 2020 have added fuel to the fire, creating an urgency to maximize cloud usage within companies that now understand that the speed, resilience, security and universal access provided by cloud services is vital to the success of the organization.
“By the end of 2021, based on lessons learned in the pandemic, most enterprises will put a mechanism in place to accelerate their shift to cloud-centric digital infrastructure and application services twice as fast as before the pandemic,” says Rick Villars, group vice president, worldwide research at IDC. “Spending on cloud services, the hardware and software underpinning cloud services, and professional and managed services opportunities around cloud services will surpass $1 trillion in 2024.”
The progression for most companies will be to ensure customer-facing applications take priority. In the next phase of cloud migration, back-end functionality embodied in ERP-type applications will move to the cloud. The easiest and fastest way to move applications to the cloud is the simple lift-and-shift, where applications remain essentially unchanged. Companies looking to improve and optimize business processes, though, will most likely refactor, containerize, or completely re-write applications. They will turn to “cloud native” approaches to their applications.
- Artificial intelligence (AI) and machine learning (ML) will deliver business insight: Faced with the need to boost revenue, cut waste, and squeeze out more profits during a period of economic and competitive upheaval, companies will continue turning to AI and machine learning to extract business insight from the vast trove of data most collect routinely, but don’t always take advantage of.
According to a recent PwC survey of more than 1,000 executives, 25 percent of companies reported widespread adoption of AI in 2020, up from 18 percent in 2019. Another 54 percent are moving quickly toward AI. Either they have started implementing limited use cases or they are in the proof-of-concept phase and are looking to scale up. Companies report the deployment of AI is proving to be an effective response to the challenges posed by the pandemic.
Ramping up AI and ML capabilities in-house can be a daunting task, but the major hyperscale cloud providers have platforms that enable companies to perform AI and ML in the cloud. Examples include Amazon’s SageMaker, Microsoft’s Azure AI and Google’s Cloud AI.
- Edge computing will take on greater importance: For companies that can’t move to the cloud because of regulatory or data security concerns, edge computing is emerging as an attractive option. With edge computing, data processing is performed where the data is generated, which reduces latency and provides actionable intelligence in real time. Common use cases include manufacturing facilities, utilities, transportation, oil and gas, healthcare, retail and hospitality.
The global edge computing market is expected to reach $43.4 billion by 2027, fueled by an annual growth rate of nearly 40 percent, according to a report from Grand View Research.
The underpinning of edge computing is IoT, the instrumentation of devices (everything from autonomous vehicles to machines on the factory floor to a coffee machine in a fast-food restaurant) and the connectivity between the IoT sensor and the analytics platform. IoT platforms generate a vast amount of real-time data, which must be processed at the edge because it would too expensive and impractical to transmit that data to the cloud.
Cloud services providers recognize this reality and are now bringing forth specific managed service offerings for edge computing scenarios, such as Amazon’s new IoT Greengrass service that extends cloud capabilities to local devices, or Microsoft’s Azure IoT Edge.
- Platform-as-a-Service will take on added urgency: To increase the speed of business, companies are shifting to cloud platforms for application development, rather than developing apps in-house. PaaS offers a variety of benefits, including the ability to take advantage of serverless computing delivering scalability, flexibility and quicker time to develop and release new apps. Popular serverless platforms include Amazon Lambda and Micro