Gaze into Splunk’s 2017 Predictions: What’s Next for Cloud, IoT, DevOps, Machine Learning and Cybersecurity
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To aid enterprises get ready for 2017, top experts in the technology have provided their insights and predictions regarding emerging trends of Splunk within the cloud, IoT, Machine Learning, and security.
The past year has been an exciting one for the Splunk partner ecosystem, and in 2017 Splunk led to even much more in store. With a focus on partners’ end-to-end experience coupled with innovative technology, the present ecosystem of Splunk Training seems to be unstoppable in 2017!
Gaze into Splunk’s Crystal Ball
What’s in store for 2017?
In 2017, Splunk is focusing even more on improving partners’ experience. Here are some items Splunk visionaries predict on the roadmap for the first half of 2017:
Building from the cloud up.
Enterprises will start to look at cloud as a primary drive for innovation. Emerging enterprises will become cloud-native and further big companies will invest additionally to embrace the cloud completely, thereby altering their core offerings.
No more cloud price wars.
2017 will see less cloud price and think big regarding agility and revolution. The competition is completely cut-off from the cloud giants regarding the price, hence, now their prime focus is to leverage at distinctive offerings to satisfy real-time needs of the end-user.
IoT and Business Analytics
Hybrid deep learning systems.
2017 will notice advancements in embedded analytics. The hybrid architectures (a mix of edge computing and cloud computing) extended via cloud-based learning platforms will lay a foundation for the next generation IoT machines. It proves to be a flexible platform for real-time analytics.
Smarter public safety.
In 2017, IoT transforms the way of response to crisis and events that endanger public safety. Receiving instantaneous data, moving objects and people among the environments will enable citizens to comprehend real-time problems to frame quicker and better decisions that ensure safety.
IoT as a data source for better business decisions.
Businesses that effectively collaborate with customers will benefit the most from this shift. Such enterprises will modify both customer experiences and business operations.
IT Operations and DevOps
Containers go big.
In 2017, container management and orchestration will emerge to the cutting edge as IT professionals experience visibility across the complete IT environment to obtain insights into the real business.
The “Shift Left” within DevSecOps strengthens.
The DevSecOps outlook will get mainstream and the traditional waterfall method will expire slowly out of the sight. By integrating accurate information security objectives, teams will acquire a top level of IT performance and construct higher secure systems.
The “appification” of machine learning.
Machine learning will befit greater accessibility and more broadly standardize IT and business activities through invisible app integration.
Predictive maintenance advances.
In 2017, enterprises will get held of machine learning to administer predictive maintenance. As speed automation ensures quick and efficient business continuity, organizations will turn to machine learning.
The Internet as a critical infrastructure.
To make sure systems stay online all the time, enterprises have started to put wider significance on understanding the need for detection of security attacks.
Machine learning, behavioral analytics, and adaptive response come front and center.
In 2017, many enterprises are looking forward to adapting an analytics-driven approach for the purpose of security that leverage analytics and an adaptive response to counter the security attacks within the multi-vendor environments.
IoT will be the new favored vector of cyber attacks.
IT or OT systems poses new challenges, instrumentation, automation and real-time monitoring and response that acquire a lot more attention.