Cloud computing has recently been the focus of the IT community. Traditionally, when organizations wanted to improve their computation capacity and data, they had two solutions: buy more hardware if the budget allows, or increase the efficiency of IT operations (but this restricted the potential growth of the enterprises impeded by restrictive resources).
Today, cloud computing delivers a completely different and economical approach to IT resource delivery: lease the data and processing capacity you require from a “cloud” (pool) of interconnected, shared computing systems that are managed by cloud service providers. Cloud computing advantages like agility, elasticity, availability, and cost-efficiency are already known, due to cost-saving through larger businesses of scale and flexible resource allocation schemes offered by various cloud services.
Nevertheless, the software that makes this possible must be designed specifically for the different cloud platforms presently available in the market. Though some recent software is written particularly for the cloud, many businesses want to shift their current applications to different cloud platforms. As this migration work is a new approach, it is nontrivial. Some changes are important to deal with software environment differences, for instance, programming models and data storage. In addition, many issues encompass the architecture and design, quality checks, requirements engineering, deployment options, development methods and platforms, management approaches, and security. Each of these points must be addressed when engineering cloud-based services and solutions, particularly if services are planned for use in an industrial landscape.
Cloud migration is not easy as businesses have their different concerns (high competition, tight budgets, and cyber-attacks like Ransomware) associated with it. In order to make a successful cloud move, enterprises need to be cautious about the challenges they are likely to face during their migration.
Top Five Enterprise Cloud Migration Challenges
Minimizing opex: The requirement for bandwidth traditionally means higher complexity and increase in opex. Costs driven by cloud migration involve capex for fiber, training, and deployment of additional equipment that result in more network complexity.
No downtime: Network outages can be devastating to businesses, leading to remarkable revenue loss and extensive disruption to business operations, and ultimately affecting customers’ loyalty. Average downtime costs vary throughout industries, about $90,000 per hour in the media sector to approximately $6.48 million per hour for the bigger online brokerages, as per Information Management magazine.
Secure business data: Cyber-attacks and data breaches are rapidly increasing. Cyber-attacks have caused an annual damage of about $100 billion to the US economy, making security a top priority in cloud infrastructures.
Scaling the network: Now, businesses cannot wait the traditional 45 to 60 days for service providers in order to implement a network bandwidth increase. Enterprise IT and planning teams should have the skills to develop and expand the network on-demand, and to implement real-time changes.
Boosting network performance: Cloud-based applications demand the same security and performance as those operating on local servers. They require low latency, maximum throughput, and high availability. Moreover, they should be agile to manage the requirement for dynamic bandwidth and changing network topology, encompassing connectivity to new data centers.
The different migration approaches
The challenges mentioned above can be solved with the best cloud migration approach to meet the company’s business objectives and requirements. Though there are many approaches used in the industry, below are the most accepted.
Lifting: This approach includes mapping the on-site hardware and VMs to same resource-sized cloud instances. For instance, if a front-end application server of a company has 4 CPUs, 64GB of RAM, and 512GB of local storage, they would go for a cloud instance that syncs that configuration well. The challenges with this approach are that on-site solutions are particularly over-provisioned regarding resources to cater peak loads as they lack the auto-scaling elasticity of cloud environments. This leads to higher cloud costs, which is fine if this approach is for a limited period.
Reshape: To capitalize on features of the cloud at its best, like auto-scaling, migration might be a forcing function to take time and redesign the application to be more performance oriented, while also maintaining costs. It is also the right time to re-examine technology choices, as an enterprise may replace some solutions from expensive commercial ones, to cloud-native offerings.
Spending: This third approach encompasses putting off a monolithic on-premises application, rather migrating to a SaaS solution. An instance of this is an HCM- Human Capital Management application, which is mostly a different set of code bases tied together with a relational database, moving to an offering like Workday HCM. This permits the modernization of business logic and unloads the operational responsibility of the service, moving infrastructure to the SaaS provider.
Though there are many problems and challenges to solve during cloud migration, these approaches ensure that CIOs and CSOs follow the best approach to capitalize on the benefits of the cloud migration, while lowering risks simultaneously. You can even take training like AWS training from experts to understand more about cloud and make the most of it.
I am amazed to know how cloud computing has proved to be an economical solution for computation capacity and data storage. And, the best part about this blog is it gives them enough details that I wanted to know.