When it isn't crawling and ranking billions of webpages, Google is busy enhancing its cloud computing services. Known as Google Cloud Platform, the search engine giant offers a a variety of different cloud products, ranging from basic cloud storage to Docker environments, content delivery networks (CDN), speech API and more. The Mountain View company is attempting to push the envelope even further, however, as it recently unveiled its cloud computing strategy for the future.
At Google Cloud Platform Next – the company's annual conference for cloud-computing professionals – the Big G revealed its vision for cloud computing: to leverage the power of machine learning and artificial intelligence (AI) so users can “teach” computers.
“Instead of programming a computer you teach it what it [Google’s cloud] wants to know and it learns to give you what you want,” explained Eric Schmidt, software engineer and executive chairman of Google's Alphabet, Inc.
So, how does it plan to accomplish this goal? Google will reportedly use its data center, which is responsible for housing approximately 85% of the world's searches, with open-source software in a cloud environment. Google has already invested $10 billion in equipment last year – a number that's expected to grow even higher in the months and years to come. It has also used open-source software to build Google Maps, Gmail, and other services for its one billion plus users.
Machine Learning and Serverless Architectures
As noted in an article by Forbes, Google has been clearing a path for machine learning, transitioning its efforts from big data analytics to deep learning. This was confirmed at the Google Cloud Platform Next conference, during which Schmidt made several predictions about the future of Google and its cloud services. Schmidt said he believes that machine learning is on the rise, and that it will be the driving force behind technical innovations in the future.
Schmidt also predicted that NoOps will become mainstream, and that serverless architectures will become increasingly popular. A serverless architecture would essentially work by dynamically identifying the infrastructure needs of the system, allocating the necessary resources based on this information. The most obvious benefit of a serverless architecture is efficiency. Since it only uses the resources required for the application or task, it would run more efficiently and cost less to operate.
Google is hoping that it can simplify the otherwise complex and highly technical nature of machine learning so that it can used in real-world applications. If machine learning is integrated into an API call system, for instance, developers could produce apps and programs with greater ease. It's doubtful that we'll see an API for Google's machine learning processes anytime soon, but this is certainly a service that you'll want to keep your eyes peeled for.
Will NoOps become mainstream for Google? Schmidt seems to think so. Not to be confused with DevOps, NoOps is the term used to describe an increased usage and efficiency of communication between developers and infrastructure operations professionals. When speaking at the Google Cloud Platform Next conference, Schmidt said he predicts that developers will shift their attention to Google's premium, more advanced cloud services in the future. And as such, there will be less of a demand for designing, scripting, etc.
Another trend that we'll likely see in the future for Google's cloud computing services is an increased emphasis on security. If you asked ten different IT professionals what their greatest concern is for cloud computing, most of them would probably agree it's cyber threats. Cloud networks are particularly vulnerable to intrusion given their inherit, interconnected nature.
But Google has already taken great strides to protect its cloud users' data from unauthorized use and access. For starters, it uses SSL encryption by default. It also uses a multi-layered security model with its data centers, featuring safeguards like electronic access cards, vehicle access barriers, perimeter fencing, metal detectors, biometrics and more.
Google's Cloud Headaches
But even Google has experienced some technical hurdles in its efforts to revolutionize the cloud computing market. Earlier this month, Google announced that it would be reimbursing users of its Compute Engine up to 25% of their monthly charged due to a temporarily outage. Lasting roughly 18 minutes, the outage affected instances of Compute Engine across all regions. Granted, 18 minutes of downtime may seem insignificant, but for large-scale companies and organizations, it be devastating.
An apology was published on the official Google Cloud Platform status page shortly after the outage, explaining what happened while informing users that they would be reimbursed. The problem was triggered when engineers removed a GCE IP block from the network and programmed the system to use the new configuration. Google's network configuration management software then detected an inconsistency in the new configuration, promoting the outage.
The outage did not affect Google App Engine, Google Cloud Storage, or other non-Compute Engine services.
“By itself, this sort of change was harmless and had been performed previously without incident. However, on this occasion our network configuration management software detected an inconsistency in the newly supplied configuration,” explained Google VP of engineer Benjamin Treynor Sloss.
The world of cloud computing is changing – and changing fast. Just a decade ago, not many people would have even recognized the phrase “cloud computing.” Today, the vast majority of organizations use some type of cloud-based service. And with the global cloud services market expected to grow at 16.5% annually, there's no end in sight for cloud computing.
You can keep up with all of the latest news surrounding Google's cloud services by following the official Cloud Platform Blog at https://cloudplatform.googleblog.com/.
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