Cloud Migration, powered by AI, is becoming increasingly popular among enterprises seeking to improve their applications due to the growing demand for cutting-edge AI technologies. How is AI used in cloud migration? Cloud migration involves moving an organization's data, applications, and IT processes from on-premises servers to the cloud or from one cloud environment to another, and AI is used in this process to optimize cost-efficiency, enhance scalability, streamline operations, and automate the assessment and transfer of data, applications, and IT infrastructure.

According to Gartner, by 2028, cloud computing will shift from being a technology disruptor to becoming a necessary component for maintaining business competitiveness. Their research also predicts that more than 50% of enterprises will use industry cloud platforms by 2028 to accelerate their business initiatives. The CEO of Salesforce, Marc Benioff, said, “If someone asks me what cloud computing is, I try not to get bogged down with definitions. I tell them that, simply put, cloud computing is a better way to run your business.”

Migrating to the cloud offers companies many benefits, like cost efficiency. It shifts spending from capital expenditure to operational expenditure, eliminating the need to manage expensive on-premises equipment. According to Amazon, companies can cut up to 50% in costs by making proper cloud migration decisions. Apart from cost reduction, the cloud improves overall performance, increases uptime, and helps modernize workloads, reducing legacy application licensing fees. This article explores AI-driven cloud migration trends and strategies from Netflix, Airbnb, and Capital One, addressing challenges and solutions to help businesses build scalable systems, boost revenue, and stay competitive.

2024 AI Cloud Migration Trends: Enterprise Challenges and Solutions

Cloud technology adoption has surged recently and shows no signs of slowing down. While beneficial, it has also introduced challenges, particularly in software licensing. Organizations often assess application suitability, estimate costs, and create budgets during the cloud migration planning phase. However, unexpected licensing issues can inflate costs, with Deloitte's research showing licensing can consume up to 24% of IT spending. Developing a licensing mitigation strategy and optimizing the licensing portfolio before migration are key steps in solving these challenges. Integrating this strategy with the overall AI-powered cloud migration plan can also help prevent issues, control costs, and increase the likelihood of long-term success. AI accelerates cloud migration by automating application assessments, predicting costs, creating efficient migration strategies, and identifying potential issues before they arise.

Here are five more factors to consider when navigating cloud migration challenges:

• Address Concerns: Discuss and solve issues related to roles and job security. Upskill teams and highlight cloud benefits like improved performance and less downtime.
• Communicate Vision: Explain the benefits of cloud migration for the organization and its customers and how the team can contribute to success.
• Manage Expectations: Avoid overpromising savings and ROI. Focus on enhanced quality, agility, and attracting top talent.
• Implement DevSecOps: Use DevSecOps techniques to automate processes, embrace ‘zero trust,’ and ensure secure, rapid development.
• Adopt Agile Workflows: Start agile workflows before cloud migration for easy deployment and faster time-to-market, allowing regular adjustments and continual progress.

Other than the above factors, organizations are also grappling with managing cloud costs and resource constraints. In fact, optimizing cloud usage is a top priority, with many adopting hybrid and multi-cloud strategies. By using AI, organizations can continuously monitor their cloud environments to identify underutilized resources, detect unusual usage patterns, and forecast demand based on historical data. Also, AI-driven tools can automate routine maintenance tasks and optimize workload distribution across different cloud platforms.

For example, an AI model monitoring cloud usage might suggest using a hybrid cloud strategy to achieve these benefits. According to Arvind Krishna, The CEO of IBM (a cloud service provider), “Hybrid cloud is where the world is going. Containers are the preferred destination for applications. A hybrid cloud offers more value than relying on a singular public cloud. It enables organizations to drive business value across multiple clouds, on-premises, or at the edge. This includes scale, security, ease of use, flexibility of deployment, seamless experiences, and faster innovation cycles.” 

A few common trends resulting from these cloud migration challenges are that security and cost optimization tools are popular, AWS remains a leading cloud provider with Azure following closely behind, and there is a growing interest in PaaS offerings for machine learning and AI.

How Netflix Met Streaming Demand with AWS

One major reason many companies shift to the cloud and use AI is to meet the rising demand for their products or services. For example, in the early 2010s, Netflix faced challenges as it struggled to keep up with the rapid growth of its streaming service. They had a traditional IT infrastructure that included several on-premises data centers and servers. The company used these servers to host its websites, applications, and databases and store and process data. The company also had a number of content delivery networks (CDNs) that were used to deliver content to its customers around the world.

Netflix struggled with the high costs of maintaining and upgrading its hardware and software, as well as limited scalability. In 2008, a major hardware failure caused a two-day outage, prompting Netflix to reconsider its infrastructure strategy. As the demand for its streaming service grew, Netflix found it increasingly difficult to manage the growing volume of data and traffic. 

To meet the increasing demand, Netflix decided to migrate its entire IT infrastructure to the cloud using Amazon AWS. The primary goals of their cloud migration were to improve scalability, performance, and cost-efficiency. By transitioning to the cloud, Netflix aimed to streamline operations, reduce hardware and software maintenance expenses, swiftly adjust IT resources to meet fluctuating demands, optimize website and application speed, and bolster disaster recovery capabilities.

To mitigate risks, Netflix performed capacity experiments and established an enterprise license agreement with AWS. The migration began with non-customer-facing applications, like encoding movies, to test the cloud's capabilities. 

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Netflix successfully demonstrated the ability to scale by requesting 3,000 machines and receiving them within an hour, which validated the cloud's capacity and reliability. They then moved quality of service logging to AWS, leveraging Amazon S3 for storage and Elastic MapReduce (now EMR) for log analysis.

Adrian Cockcroft, former Cloud Architect at Netflix, explained the company's decision to migrate to the cloud: "We realized that availability had to be an application concern, not just an infrastructure concern. By moving to AWS, we could use low-cost cloud infrastructure and focus our resources on content and service development rather than maintaining expensive hardware."

And the result? In 2001, Netflix had fewer than half a million subscribers. By 2016, they had eight times as many streaming members as they did in 2008, and they were much more engaged. Today, it has 260.28 million paying members. Netflix has grown by nearly 13% year over year, solidifying its stronghold in the streaming industry.

How Capital One Transformed Its Operations with AWS 

Another company that used cloud migration to solve its storage-related challenges is Capital One. Founded in 1988 by Richard Fairbank, Capital One is a credit card company that has now grown into a Fortune 500 full-service commercial and retail bank with operations in multiple countries. Due to challenges in data storage and as part of their continuous innovation to bring the best services to customers, they have adopted the cloud.

Capital One’s cloud migration was backed by the need to evolve into a tech-centric organization to meet the growing demand for real-time, personalized banking experiences. By making use of AWS and big data analytics, the company aimed to transform its operations, build in-house applications, and cultivate a tech-savvy workforce to outpace industry innovation. This strategic shift extended beyond infrastructure migration to create a truly digital bank capable of delivering exceptional customer experiences. Chris Nims, The senior vice president of cloud and productivity engineering at Capital One, commented on the cloud migration and said, “Going all in on the cloud has enabled both instant provisioning of infrastructure and rapid innovation. We are able to manage data at a much larger scale and unlock the power of machine learning to deliver enhanced customer experiences.”

By eliminating infrastructure constraints and optimizing resource allocation through AI-driven cloud migration, the company has significantly increased development speed, reduced downtime, and improved disaster recovery. Capital One has cut its disaster recovery time by 70%, and it has reduced both critical incident resolution time and the number of transaction errors by 50%. This agility has fueled innovative projects like Eno, the intelligent assistant, and Capital One Shopping, which uses AWS cloud services for real-time data analysis and personalized customer interactions. The cloud's scalability proved invaluable during the COVID-19 pandemic, enabling seamless remote work for employees and uninterrupted service for customers.

This is an image of a message from Eno, Capital One’s intelligent assistant. Source

How Airbnb Overcame Scalability Issues by Migrating to AWS Cloud

An important insight for enterprise leaders is to remain open to changing their cloud provider and data store when facing scalability issues. For example, due to the immense success and service administration challenges of their original provider, Airbnb decided to migrate nearly all of its cloud computing functions to AWS. 

Pretty soon after launching, their website started to struggle under the constant stream of clients who wanted to use their services. As Airbnb started to plan out its new business venture, its leaders realized that something needed to change. Airbnb replaced its MySQL datastore with Amazon's RDS, a managed cloud-based MySQL service that simplifies database administration and ensures high performance. 

This transition has significantly improved frontend performance by isolating long-running queries and delivering better overall results compared to their previous MySQL setup. Amazon's robust infrastructure also guarantees uninterrupted background processes for payments and analytics, maintaining site speed and reliability. An Airbnb engineer, Tobi Knaup, said, “We are now well prepared for our future growth. Amazon Web Services listens to customers’ needs. If the feature does not yet exist, it probably will in a matter of months. The low cost and simplicity of its services made it a no-brainer to switch to the AWS cloud.”

Here are some of the main benefits Airbnb experienced from migrating to the AWS cloud:

• Automatic Scaling: Airbnb can now automatically scale based on the needs of its ever-increasing customer base.
• Running MySQL in the Cloud: This allowed Airbnb to reduce its management of MySQL, which had a positive impact on front-end performance.
• Focus on Safety: AWS has a strong focus on the security of its cloud, and the migration enabled Airbnb to ease its own workload without compromising security levels.
• Saving Resources: With AWS, Airbnb engineers can now free up their time and focus on what really matters - innovation.

As a result of all these benefits, today, there are over five million Airbnb hosts renting out properties all over the world. 

Ensuring Success in AI Cloud Migration: Best Practices and AI Integration

Cloud computing is evolving rapidly, with over 95% of all new digital workloads projected to be deployed on the cloud. Its future looks promising, driven by key trends such as AI integration, hybrid and multi-cloud strategies, edge computing, sustainability, and serverless architecture. AIaaS platforms are democratizing artificial intelligence, while flexible cloud management and data processing at the network edge enhance efficiency and responsiveness. Additionally, the industry is committed to reducing its environmental footprint through sustainable practices, and serverless computing streamlines development and reduces operational overhead.

While considering these future trends, enterprises must also adopt best practices for effective AI cloud migration. This includes defining clear goals and strategies, developing a detailed migration plan, choosing the right cloud platform, testing applications and workloads in the cloud environment, and training employees.

The shift to cloud computing is becoming essential for businesses, offering benefits such as cost reduction, scalability, and enhanced data analytics. Despite challenges like security and talent acquisition, AI is emerging as a crucial tool for optimizing the migration process. By leveraging AI and addressing these challenges, organizations can successfully transition to the cloud, gaining a competitive edge and unlocking new business opportunities.