Cloud migration has passed the tipping point, with nearly 60% of North American enterprises now relying on public cloud platforms, five times the percentage that did just five years ago. According to research by IBM’s Institute for Business Value, 98 percent of surveyed organizations plan to use multiple hybrid clouds by 2021, another sign of tremendous cloud momentum.
Despite this trend, migration to the cloud and the transformation to a hybrid multi-cloud IT operating environment is often viewed with anticipation and anxiety, and perceived as complicated. Most companies require an approach that ensures that their data migration is smooth and fast, putting pressure on the IT team managing the process. No matter how much data you want to move, there are many ways (some of them quite surprising) to actually transfer it to your preferred cloud service provide (CSP). As AWS notes, one should never underestimate the bandwidth of a semi truck filled with disks hurtling down the highway.
Leading CSPs AWS, Azure, Google and IBM each provide data migration services, and they assume that you have already decided to move to the cloud, you’re ready to transfer your data, and you have chosen your CSP. Each of them has carefully refined the process of getting your data from your on-prem servers to their cloud servers. After all, successful migration is a critical component of their customer acquisition strategies.
- ASSESS YOUR CURRENT ENVIRONMENT
However, before you sign up with any service provider to migrate to the cloud and all the features that come with it — like a multi-tier read-write cache, deduplication, pre-fetching, asynchronous write-back, and network optimizations — you must first conduct a thorough independent assessment of your existing on-prem workloads. This will save the IT operations team significant time and provide accurate cost projections.
To begin, each of your workloads must be carefully matched to an appropriate cloud instance. A pre-migration workload assessment should automatically analyze a CSP’s general purpose, memory-optimized, and CPU-optimized instance types and identify which is the most cost-effective for each of your workloads. Identifying the right instances f