The public cloud (place intentional) was built on simplicity, elasticity and microservices. Your cloud strategy is a function of that operating model and, as you mature, you will change how, and where, you run certain workloads. It is important to remember that the cloud is an operating model, more so than a place.
While it may seem counterintuitive, when you truly understand your cloud workload, what it demands, how it behaves - it is likely time to change your strategy as to where it runs.
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You might need to train your team on more modern approaches including agile software development lifecycle and cloud-native technologies and best practices. If you aren’t seeing a faster pace of innovation from product teams using cloud, it’s often a sign that you have fundamental problems in your product and engineering Organization that are only being exacerbated by a move to cloud. It’s very possible the effort required was underestimated and the fundamental ROI calculation was overly optimistic. If you aren’t seeing cost savings from your lift and shift initiatives, it might be time to check your assumptions on how much work is required to move your company’s workloads into a cloud environment. Most cloud strategies are optimized for one of two outcomes: (1) cost savings or (2) increasing the pace of innovation. These are the key features of efficient CloudOps and represent a promising new approach for enterprises stuck in an environment of rising public cloud costs and complexity. Just as self-driving cars proactively detect traffic congestion and reroute without human intervention, we need workloads that self-adjust, with architectures that are practically invisible and touchless. But what’s increasingly clear is that IT needs a better way to manage cloud infrastructure, and that today’s CloudOps must involve more than infrastructure, operations and support. A dependable, always-on cloud infrastructure that scales to meet changing capacity needs is vital to this effort.
With workloads increasingly earmarked for deployment on private, public and/or hybrid clouds, organizational leaders face enormous pressure to get their cloud strategy right and manage distributed workloads effectively. This starts with transparency of current Cloud SLAs and consideration of downtime, flexibility and performance. In these situations, organizations inevitably look for services that can optimize their cloud spending and save money, while still delivering the agility and scale that’s necessary to achieve business results. Such lack of planning creates distributed copies of data – fueling data sprawl, impeding data control and making security and compliance more burdensome and complex. Often this happens because leaders blindly deploy or move data to a public cloud without first understanding the data’s true value to their business. Organizations are reevaluating cloud strategies when the cost savings promised by the public cloud fail to materialize - or worse, when the cost of their public cloud services rises much higher than anticipated.
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