Digital transformations are performed with a range of justifications. Some stem from a need to replace IT systems that have reached the end of their useful life; others from a reluctance to spend on a refresh. These companies’ often complex IT infrastructures can’t keep up with the pace of service demands. That leads to lackluster service levels for customers, and for mobile workers seeking help with creaky legacy systems and applications that often are fragile, prone to breakdowns, and neither scalable nor flexible enough to take on new service demands. In some cases, a company lacks the skills required to tend to its legacy systems, creating the risk that it will have trouble keeping them running. And, as technology vendors move their systems to cloud-enabled platforms, enterprises that have the on-premises versions of those applications eventually will find their vendors’ support withdrawn. Other companies embarking on a digital transformation seek a reset; they wish to establish a greenfield on which to build a fresh IT infrastructure for new ventures and innovative business models. Often, this happens when a company goes through a merger, acquisition, or divestiture. While these events provide a chance to start afresh computing environment, the new entity in all likelihood will be accessing existing data. This means that the new entity and its predecessors must ensure the disparate data sets, once held by parts of an organization that was together, can be managed separately.
Whatever the reason, a digital transformation will require an enterprise to shift much of its computing infrastructure from its own data centers to those operated by private or public cloud providers.
AWS cloud-based digital transformation strategy offers great opportunities:
- Reduced costs
- The chance to capitalize on far greater computational resources provided by cloud providers that run data-intensive computing chores
- Replacements for aging back-office applications
- The flexibility to ramp up or down according to business needs
- The ability to handle the enormous volumes of data coming from the Internet of Things-related digital sensors (from machines in the field, products in customers’ hands, and places of business)
- Resources to support the use of artificial intelligence and other systems that identify business opportunities, solve operational problems, and provide winning digital customer experiences.
AWS cloud is full of promise. But while straightforward in theory, the switchover of systems from a company’s data centers to the cloud must be planned carefully. If the planning isn’t sound, it will risk major disruptions to the information systems that the business depends upon every day. Thus, in the absence of considerable forethought, a company’s digital transformation initiatives are likely to falter.
Executives must focus first on what is relevant to the growth of their business, and how a cloud deployment can support that strategy.
Because a digital transformation is about the future of the business, the planning to support it should hinge on the business’s strategy. not on IT-centrist concerns. Decisions on the technology resources to support that strategy come afterward. And while it shifts systems to the cloud, the organization must keep a laser focus on those who will experience the systems that the cloud supports — both internal users and customers.
- Proof of concept: Get comfortable with AWS by experimenting with our products and services. Test out a subset of future-state AWS functionality in a risk-free sandbox environment to gain confidence in this cloud journey.
- Cloud Foundations: Define and build out the minimal set of AWS Cloud foundational components required by the Cloud journey such as Compute, Networking, Storage, Databases, cost control.
- Discovery and Planning: Perform a new transformation inventory to understand the overall complexity of your transformation. Plan for the subsequent stages of the journey
- Execution: Set up your business workload By serving customer traffic. Validate your deployment by performing integration and smoke testing.
- Testing: Validate functionality and start serving minimal traffic. A good rule of thumb is to start by splitting traffic between the legacy and the new solution -for example, you could serve 1% of traffic from the new solution and increase volume progressively.
- Optimization: Tweak telemetry and instrumentation iteratively in Cloud Monitoring base on AWS best practices.
