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Multi-cloud: 5 important trends to watch
Some organizations went multi-cloud by accident, deploying applications on multiple cloud services without crafting a multi-cloud strategy. That’s changing in a hurry
4. IT teams prioritize operational consistency
Organizations that adopted multiple cloud services organically – which is perhaps a polite way of describing different teams using different services with little or no coordination or standardization – will become more consistent in how they operate these different services and environments going forward. Otherwise, teams risk the perils of running multiple clouds in disparate, non-repeatable fashion.
“As companies continue on the path toward digital transformation, it becomes more important for IT operations teams to provide ‘operational uniformity’ across diverse workloads, global footprints, and different business units at various stages of maturity,” says Bhanu Singh, SVP at OpsRamp. “IT Ops teams will need to be able to manage services consistently and evenly, regardless of the underlying legacy and multi-cloud applications, infrastructure, or platforms.”
For some, this is where DevOps culture plays a key role. Singh also sees a trend on the horizon where IT operations are delivered “as a service” across the organization from a centralized place in order to achieve uniformity across environments. “That service will need to be flexible, governed, and adaptable,” Singh says.
5. Machine learning and multi-cloud will grow together
“Big data” might no longer be quite the trendy term it was a few years back, but perhaps it’s time for a comeback: Data just keeps getting bigger.
Singh expects machine learning to play a growing role in data management and multi-cloud environments, from ingestion to analytics and more. It’s not trendy so much as necessary.
“Companies are moving deeper into multi-cloud and associated technologies like serverless and ephemeral workloads that generate data on an order of magnitude greater than anything we’ve ever seen,” Singh says. “It is impossible to operate in this environment without efficient data ingestion. This will accelerate [the] use of machine learning tools that manage data and deliver actionable insights.”
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