David Linthicum of InfoWorld says, “It is time we do way with the word ‘cloud computing’ and say ‘computing’ instead”. This statement is quite significant considering it throws light on how vital cloud has become in our daily professional life. Easy to access from anywhere, anytime has made cloud computing the “go-to” solution. And it is this aspect that brings us to the Top 9 enterprise trends of 2016 and beyond.
‘Cloud native’ shapes the future – No doubt about it!
Monolithic applications will be substituted by applications built out of microservices that run in containers that boast of a variety of advantages over monolithic applications. Instead of dealing with obscure internal dependencies that makes troubleshooting a painful affair (not to forget the updating feature), the decoupled services function independently and can be monitored and managed on an independent basis.
But there is a small issue here. When you opt for microservices architecture, you end up using billions of containers that needs to be monitored on a daily basis. However, Google has come to the rescue. Last year, it introduced, the open source Kubernetes project, which distils the entire process into open source so that one can wrangle huge numbers of containers at scale. In fact, Craig McLuckie, founder of this project announced that they are building Cloud Native Computing Foundation so that Kubernetes is considered as the starting point from where an ecosystem will be build. This will ensure container scheduling, management, and orchestration for easy access and daily functioning.
Spark ‘streaming’ accelerates
Spark has dethroned Hadoop out of the spotlight. Wondering why? Spark works in small batches in big memory which in turn gives the impact of working in Real Time, unlike Hadoop that processes huge amounts of data in big batches and that too across many batches.
Top corporate companies like IBM and Cloudera are banking high on Spark while Google, Amazon and Microsoft are offering Spark as part of their public cloud services.
Developers tap into machine learning
With cloud computing you are able to go for analytics too. Moreover, they provide machine learning APIs in the cloud in addition to the presence of open source machine learning tools. With Ubiquitous machine learning developers can build applications that help to recognize patterns in huge amount of data. You can opt for fraud detection, infrastructure optimization, face recognition, medical diagnoses and web – ad serving. In other words, you name it and you can do it.
Machine learning has broken out as a separate identity that any developer can exploit. This is a boon considering the bulk of data that developers have at disposal in addition to GPU accelerators to run machine learning algorithms.
Cisco’s ACI reinvigorates SDN
SDN thrives on the concept that in the long run that hardware switches will become commoditized – one of the major reasons why SDN is an existential threat to Cisco. However, SDN adoption is limited mainly to Telco.
To overcome the threat, Cisco has introduced a new SDN scheme named as Application Centric Infrastructure that offers new operations control protocol, OpFlex, that will OpenFlow. Created with the aim to make large-scale deployments easy and effective, this scheme is channelized in a way that will distribute the control over configuration to network thereby ensuring that the admins enjoy the facility to adjust settings at a higher level depending on the application requirements.
The hybrid cloud gets real
The word “Hybrid-cloud” is often confusing. What does it actually signify? Does it mean integration between public cloud and on-premises infrastructure? Or is the integration between any two clouds?
Answers to all this and more are given by Azure Stack (for Windows Server) by Microsoft. It allows the user to duplicate Azure public cloud infrastructure (partially on a local basis). Even IBM is working towards the same goal by using hybrid public and private cloud OpenStack deployments.
Google has no hybrid cloud system so far but with its Kubernetes and the CNCF, it is just a matter of time when Google comes up with its own hybrid cloud solution.
Machine learning amps up security
There are many financial companies that use machine learning to detect fraud although there are other ways to map up security measures. Popular options include flagging network anomalies, tracking user behaviour, or detecting zero-day malware.
Although machine learning is becoming popular yet one needs to exercise caution. There are varying degree of success and many false positives. However, there is nothing to get disheartened about. Advances will be made, thanks to the Big data analytics but don’t expect miracles.
Blockchain breaks out
Although, Bitcoin does not enjoy a popular market image, Blockchain the mathematical magic behind Bitcoin is however gaining significant popularity. As per InfoWorld’s Peter Wayner more than 100 companies are resorting to Blockchain for their ID cards, secure storage, trading platforms, contract needs. You will be amazed to know that even banks are testing it out. And if the trends are anything to go by, Blockchain is here to stay.
July 27 , 2016
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