As you move your systems and resources to the Cloud, your internal IT support model will also evolve. Most of the support work which used to be done by your support personnel such as accessing the infrastructure, servers, and applications in the on-premise data centers will now be performed by The Cloud provider’s support and operational staff in their data centers. This is because as you setup servers, virtual machine and applications to the Cloud on the provider’s infrastructure it becomes their responsibility to manage and maintain these servers and associated resources.
Cloud Computing is an enabler for all things which we knew how to do but we didn’t have the infrastructure or the computing resources to accomplish. With multiple Cloud providers out there including Amazon, Microsoft and Google with their global data centers and massive compute power, it is now possible for companies of all sizes from small to large enterprises to tap into that compute capacity and execute their Cloud strategy to enable their business scenarios. Certain key technologies which have gained prominence and become the industry’s buzz words lately include Cognitive Computing, Machine Learning (ML), Artificial Intelligence (AI) and Internet of Things (IoT). These core technologies are playing a big part in helping many organizations in their Digital Transformation journey.
Cloud costs and spend is going up for SMB and Enterprise customers across the board as companies initiate experiments in the Cloud to moving from experimentation to setting up and migrating production workloads. Along with this increase in Cloud investment, proportionately the Cloud spend waste is also going up. In this post we are going to outline some common Cloud utilization scenarios which may lead to cloud spend waste. Along with that we will also offer guidance and recommend some tools to optimize Cloud costs.
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