Industry executives and experts share their predictions for 2019. Read them in this 11th annual VMblog.com series exclusive.
Contributed by Partha Seetala, CTO of Robin
2019 IT Infrastructure and DevOps predictions -- the year of Kubernetes becoming mainstream, DataOps, NVMe and Optimizing AI investments
As
enterprises looks forward to the next phase of Digital Transformation, what's
next? What's the prognosis for cloud native technologies? Where is DevOps
going? And where will we be on the AI adoption curve? What game-changing cloud
infrastructure technologies are achieving mainstream adoption? What exciting
capabilities can we expect from the fast-paced innovation and from open source?
Here are 5 key predictions that CIOs should be aware while charting the IT
journey in 2019:
- 2019 is the year of Stateful
Workloads on Kubernetes: We have
seen the emergence of nearly 50 CNCF certified
vendors providing a cloud native platform. With such broad vendor support,
we would expect to see several organizations successfully running Big Data
and Databases on Kubernetes. However, other than simple stateful apps,
organizations struggle with running complex workloads such as Cloudera,
Hortonworks, MongoDB, ElasticSearch, Splunk, Oracle, etc on Kubernetes. In
2019, the drive to reduce the complexity of running stateful applications
on Kubernetes will continue and DevOps teams will look for solutions to support
complex stateful applications.
- CIOs will recognize that Kubernetes
is not a solution, but a platform to build a solution. Kubernetes has
StatefulSets, Volumes, and many other features to ease the burden of
running stateful workloads. But you still require expertise to effectively
manage stateful services on Kubernetes. The fact is, doing so is
challenging. In 2019, we'll continue to see developments from ROBIN, OpenShift,
PKS and others who are working toward making Kubernetes a solution.
Everything from banking and financial services to healthcare to utilities
and beyond are using stateful applications and workloads. Hence, the need
will increase for a solution to the problem of running stateful workloads
on Kubernetes. Enterprises that employ a more holistic approach instead of
focusing on just storage-for-containers, StatefulSets, etc, will be better
poised to run production-quality deployments on Kubernetes.
- DataOps will become real with CIOs embracing it to take the success with
DevOps to the next level. In 2018, the DevOps mania spread as more and
more enterprises understood its benefits to reduce cycle times. A side
effect that this phenomenon created was the need to operationalize
increasing amounts of historical and real-time data. As a result, Database
as a Service and Big Data as a Service made DataOps that much more
important. Just as DevOps opened up a whole new world to application
development, DataOps was shown to yield significant improvements, reducing
time to deploy and manage data applications. In 2019, an increasing number
of data architects and teams will use new approaches and tools
incorporating containers and Kubernetes to continue along this path. DevOps
will operate hand-in-hand with DataOps. CIOs will be looking for better
solutions to manage the data pipeline that will continue to expand and
mature in 2019.
- NVMe will gain strong adoption and enterprises will view it as their new Near
Line Storage. This highly scalable storage protocol offers significantly
higher performance and lower latencies compared to legacy SAS and SATA
protocols. This not only accelerates existing applications like Big Data
and Database that require high performance, but it also enables new
applications and capabilities for real-time workload processing in the
data center and at the Edge.
- CIOs will do a reality check on AI
investments and realize that
these investments are not delivering the ROI that they had expected by 2019.
There will be increasing pressure to optimize and recalibrate these
investments. According
to the most recent Gartner Inc. annual survey of global CIOs, 35% are
now struggling to identify suitable use cases for AI. Another 37% of
organizations are still looking to define their AI strategies. AI projects
incur high CAPEX from expensive GPU hardware and the lack of proper
consolidation solutions for GPUs result in low utilization of these
resources. In 2019 CIOs will look for solutions to drive better value from
their AI investments by investing in products to maximize utilization.
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About the Author
Partha Seetala, Chief
Technology Officer
Partha Seetala joined Robin
Systems in 2015 as Chief Technology Officer, with more than 16 years of
technology and product expertise. His previous position was with Symantec's
information management business, known as Veritas, where he was Distinguished
Engineer and Senior Director of Engineering. In that capacity he conceived,
architected and led engineering teams to take multiple products from concept to
market in the scale-out storage, distributed systems, content-aware file
systems and information analytics space. He was also an adviser on
multimillion-dollar product lines including NetBackup Appliance, Cluster File
System, Veritas Cluster Server and Information Fabric. Earlier positions
include serving as architect at Kazeon Systems - later acquired by EMC - and
architect at Veritas Technologies. He holds a master's degree in Computer
Science and Engineering from the University of Minnesota.