Phase 1
Overcoming challenges in the initial cloud migration
Most companies head into Phase 1 expecting it to be the easy part of the journey — the low foothills surrounding the mountain — and as a result, they plan for a rapid, one-size-fits-all “lift and shift” to the cloud. But this short-term view is a recipe for long-term disaster.
Explore the options below to make sure you sail through this stage.
Phase 1 can come with higher-than expected migration costs due to massive time and effort to rewrite and revalidate existing models.
Beware of discarding individual developers’ experiences, skills and preferences. When their choices are eliminated and extra work is foisted upon them because of a one-size-fits-all cloud migration approach, they will revolt.
A one-size-fits-all approach is based on the false assumption that all analytic models and workloads can be handled the same way. Batch and nonbatch workloads are entirely different beasts.
How much do these extra efforts add to the cost of moving data analytics workloads to the cloud?
According to a recent SAS and CIO.com survey, these extra efforts add 56% to the cost of moving data analytics workloads to the cloud compared with keeping them on premises.
IT departments can greatly mitigate these challenges by equipping themselves with a modern data and AI platform that provides all the tools they need in order to streamline the time, effort, cost, and risk for everyone involved.
SAS® Viya®, a modern data and AI platform, comes with two engines that make Phase 1 faster and easier.
IT departments also need to make sure their ecosystem can handle unpredictable analytics workloads. Are the proper operating guardrails in place? Cloud expertise, like that achieved with a SAS Managed Service, can help your organization navigate all of these early complexities. These experts have seen it all, having migrated hundreds of companies’ workloads to the cloud successfully.
For nonbatch workloads attached to developers, IT can use SAS Viya tools to advise developers on what SAS code doesn’t need to be rewritten. The tools can also detect which workloads are candidates for distributed computing to boost performance and lower cloud costs.
Be patient. Migrating workloads in a way that is performant can take some time for everything to stabilize and settle. You’ll get there.
Answer the question below to get custom resources suited to your stage of the cloud migration journey.
Which of the following steps is your organization most focused on?
Other great resources for this phase of the journey are linked below.
