Google Cloud Conundrum: 7 Questions That Need Answering
In an effort to gain enterprise interest, Google announced changes to its cloud platform last month that would beef up machine learning and big data capabilities. Still, many questions remain about whether Google's cloud will ever be a serious enterprise contender.
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If you had asked me five years ago who the top three cloud providers in the world would be in 2016, I would have undoubtedly included Google Cloud Platform (GCP) on that list. But as things stand today, GCP has struggled to compete with Amazon AWS, Microsoft Azure, and even IBM.
What happened?
It appears that enterprises never bought into what Google was originally selling with its cloud platform. That seems like an odd statement, considering you get to use the same supporting infrastructure and platform on which all Google services run. But most enterprises weren't -- and still aren't -- ready for "the Google way."
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For example, asking developers and server administrators to abandon traditional architectures and, instead, migrate apps to the Google App Engine (a platform-as-a-service) is simply too far of a stretch. Google's other launches, such as Google Cloud Storage and Google Compute Engine, fared better than its App Engine. Still, it always seemed to me the company's offerings lacked many features and services that would appeal to enterprise customers -- and generally seemed limited when compared to other cloud players.
Last month, the company announced plans to beef up GCP with the addition of a machine learning framework for building and training custom data models using distributed learning algorithms based on TensorFlow.
Eric Schmidt, chairman of Google parent Alphabet, struck a conciliatory tone to court enterprise decision-makers at this year's Google Cloud Platform Next conference. He acknowledged that Google expected too much of companies as it moved into the cloud market with App Engine in 2008. The company didn't provide the right stepping stones into the cloud, he said. "We decided to meet you where you are, as opposed to where we think you should be," Schmidt stated at the event.
Clearly, Google wants to attract new enterprise customers. But many questions remain as to whether Google can claw its way to the top.
Here are seven questions Google must address as it courts the enterprise for its cloud platform. At this stage, Google can't simply be a "me too" service provider. It has to provide something truly unique to persuade enterprises to switch.
Once you've reviewed the challenges facing Google's cloud efforts, we'd love to hear your opinion. Do you think GCP has a shot at becoming as big -- or bigger --than AWS or Azure? Is its cloud service truly enterprise ready? Tell us what you think in the comments section below.
From the start of Google's foray into cloud computing, it seemed as if the company didn't understand -- or didn't care about -- how enterprises operated and managed their infrastructure and applications in-house. Now, we're suddenly expected to believe that Google "gets" the enterprise, and is ready to address the needs that we face on a daily basis? Should we believe it? We'll have to wait and see.
Despite all of the struggles Google has had in the cloud space, it does have loyal and happy customers. If a dramatic change in focus is going to occur within the Google cloud, it has the potential to impact and alienate the current customer base.
One thing that has always been absent from Google's cloud offerings were tools that helped enterprises efficiently run and manage legacy applications. Google's focus has been -- and likely always will be -- to move forward and stay on the cutting edge. Dealing with legacy apps is not in its DNA.
One of the biggest challenges Google faces with its strategy for the cloud is how to differentiate itself from the likes of Amazon AWS, Rackspace, and Microsoft Azure. If Google is trying to woo enterprise customers, what can it do, other than intensify a price war, to differentiate itself?
One regularly occurring theme at the GCP Next 2016 conference was a focus on delivering the most advanced machine learning and big data tools available anywhere. While machine learning as a cloud service might appeal to some enterprises, most aren't even close to being ready for these advanced tool sets. So, Google will either have to promote use-case scenarios that are relevant today, or risk the possibility that it's still thinking too many steps ahead of the enterprise.
From the very start of Google's cloud platform offerings, customers found themselves confused by marketing jargon and pricing schemes that were difficult to figure out. Simply put, Google's cloud marketing has been a mess. Enterprise customers are going to want an easy-to-understand, apples-to-apples pricing comparison -- even if that's not at all what Google wants to provide.
Google's cloud platform was built ahead of its time, and for customers who weren't ready to use it. Feeling the pressure, Google is backtracking to create an environment that is more enterprise-ready. One option for the company is to wait for enterprise customers -- and the software they utilize -- to advance to the point where they're ready for the next generation of cloud computing. By that time, though, the big concern for Google is that Amazon AWS, Microsoft Azure, and others will have developed their own next-gen clouds and migrated their healthy and happy customer base over, leaving Google's GCP out in the cold.
Google's cloud platform was built ahead of its time, and for customers who weren't ready to use it. Feeling the pressure, Google is backtracking to create an environment that is more enterprise-ready. One option for the company is to wait for enterprise customers -- and the software they utilize -- to advance to the point where they're ready for the next generation of cloud computing. By that time, though, the big concern for Google is that Amazon AWS, Microsoft Azure, and others will have developed their own next-gen clouds and migrated their healthy and happy customer base over, leaving Google's GCP out in the cold.
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