Industry executives and experts share their predictions for 2020. Read them in this 12th annual VMblog.com series exclusive.
By Bob Farzami, VP of Cloud Strategy,
Virtana
The Future of Cloud Management is Dynamic Resource Allocation
2019 saw more and more
businesses move away from the traditional IT infrastructure and realize the
true potential of implementing the cloud into their business strategy. Last
year for VMblog, Virtana's Tim Van Ash
predicted that as a result of the cloud becoming increasingly
mainstream, we could expect to see organizations becoming more deliberate about
their workload placement decisions, namely investing in workload analytics and
simulation capabilities as part of the overall strategy.
Currently, global
enterprises are at point where they recognize the need to transform IT
operations. These organizations are digitally transforming their on-premises
delivery and deployment platforms to a hybrid public/private cloud model and
evolving from a reactive operational model to a proactive, and eventually
autonomous, approach. To achieve this, enterprises need to transform their
method of infrastructure management for mission-critical deployments that involves
an amalgamation of big data analytics, real-time monitoring, and AI/ML
technologies. The new
method must take into account full-stack hybrid cloud visibility, application-centricity,
and web-scale operation.
To execute an
effective cloud initiative and migrate legacy applications to the cloud is a
challenge for every enterprise, no matter their size or depth of resources. With the increased usage of the
cloud comes the scrutiny of the associated costs of maintaining it; which
is why this year, our predictions focus on how enterprises can manage their
cloud investments.
According to Gartner, enterprise IT spending for
cloud-based offerings will grow faster than traditional (non-cloud) IT offerings
through 2022. However, a recent 451 Research survey found that more than half of
large enterprises worry about cloud costs on a daily basis, and 80% acknowledge
poor cloud financial management has had a negative impact on their business,
including lower quality of service due to poor resource utilization and
planning. Companies acknowledge
that cost optimization is a major element of hybrid operations, where a strong
understanding of cloud costs is necessary to consider when determining the best
execution venue.
Public cloud optimization has experienced a
significant evolution over the last few years. The first generation of cloud
optimization services focused on bill analysis, with the second generation
focusing on cross-analyzing cost with capacity. The third and current
generation encompasses the previous two generations, in addition to hybrid
infrastructure monitoring and capacity planning. This generation yields
recommendations on whether workloads would perform best on-premise or in the
cloud, depending on what is more cost effective.
In
2020 and beyond, we will see a fourth generation of public cloud optimization
emerge: dynamic resource allocation, enabled by workload automation technology
comprised of performance, capacity and cost management capabilities. In order for Gen-4 to
proliferate, security and governance issues will need to be addressed for
third-party vendors to gain the access they need to analyze workloads and
change control processes for mission critical applications. To reduce
public cloud spending while still maintaining performance, organizations will apply analytics that go
beyond performance data to include capacity and cost.
With the cloud
continuing to be a significant benefit to the enterprise, organizations will
make a point to be aware of how their cloud-based offerings are performing,
both as a resource and as a cost to the enterprise. As businesses realize the
importance of optimizing resource utilization, they will also become aware of
the impact of a firm cloud financial management strategy as well as the
importance of cloud optimization to their overall hybrid operations. The
evolution of cloud optimization will draw on its previous
generations of cost analysis and capacity planning to ultimately emphasize on the
performance and authority needed to achieve dynamic resource allocation.
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About the Author
Bob Farzami is VP of Cloud Strategy at Virtana and former CEO of
Metricly. Bob started his career as a hardware developer before taking on business
development for early stage software companies. In recent years, his interest
has been focused on the application of analytics to infrastructure management
which inspired Metricly, now known as Virtana's CloudWisdom. He lives in NYC
and spends any free time that he can find running in Central Park and spending
time with his wife and daughter.