Addressing the Risks of a Strategic Cloud Migration

In 2019, more and more enterprises and organizations are evaluating how existing workloads in on-premises data centers (or private clouds) should move to the cloud (public) and how they can leverage many benefits offered by public cloud services. To facilitate the requirements, we have key players in the public cloud services domain: AWS, Azure, and GCP. Currently, the kind of services and benefits offered by these public cloud companies are crucial to run digital business in focusing more on use cases than the investment made in IT infrastructure. Such investment can be in terms of manpower requirement as well for manual tasks involved in managing infrastructure.

But the roadmap to cloud migration is not as simple as it looks. The right cloud migration strategy should be in place.

Cloud Migration Risks

There is always a risk involved while moving applications that are dependent on data. Those application moves should have minimal impact. Any glitch or downtime may result in loss of customer focus on the business.

While moving applications and related data to the cloud, there should be checkpoints where application runtime has been tested in a new environment. Cloud migration becomes complicated as most of today's workloads are on virtual machines or on bare metal. This causes workload portability issues for many companies. However, many of the issues are related to the portability of applications, and data can be address due to existing services offered by public cloud vendors.

For some organizations, a cloud migration strategy is how to move sensitive information to the cloud. This problem can often arise for large organizations that collect proprietary and critical information from institutions like healthcare, finance, etc. There should be a checkpoint that will evaluate legal acts like GDPR for evaluating data sovereignty for a particular region or country.   

Use cases of IoT are rapidly growing, and this, in turn, is driving the need for having an infrastructure sensitive to latency. While moving to a cloud, an issue can come up with the support and distance of the location from where a variety of data processing requests may come. Migrating to the cloud might have an impact on some of the existing applications. Latency sensitive applications might suffer a shift in response time.

In IoT use cases, distributed cloud architecture can be an option. But there are potential pitfalls. If you move applications to a public cloud, there is a need for modifications at the code level to enable support at the distributed level.

Another big problem is vendor lock-in. Once you transfer all your workloads, if, for any reason, you plan to move to another cloud option, there might possible vendor lock-in in terms of applications settings and data services. This is a big risk while moving to the cloud, and most enterprises must evaluate test cases. So, it is recommended that to work on a small proof-of-concept (PoC) effort before migrating all your workloads to the cloud.

Containerization’s role in cloud migration

Many enterprises are choosing to go with containerization of workloads and data before or after moving to a public cloud. Some of them chose containerized microservices architecture that helps them to maintain different sub-services individually and allow reusability of those services in the main service application.

If enterprises already having their workloads on container-based systems and orchestrated with container orchestration engines like Kubernetes or Docker engine, migrating to the cloud can be significantly easier. AWS and Azure cloud offers specific assistance for Kubernetes as well as other engines that further helps in the migration process. As we know, Kubernetes is mainly characterized by the fact that workloads should be portable, be it any type of cloud or bare metal.

Summary

As time progresses, cloud migration has become a tedious task in terms of moving workloads due to the fact that the organization probably wanted to shift to container-based infrastructure. But most of the challenges are being addressed by public cloud players. Still, issues like downtime or vendor lock-in remain critical

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