Forecast: It’s getting cloudy out there

From clouds with machine-learning capabilities to the rise of the intercloud — where a cloud incorporates numerous cloud platforms, even from competitors — there’s plenty of movement in this space. Here’s a look at what’s next for cloud computing.


Cloud computing has arrived. So what happens with Google Cloud Platform, Microsoft Azure and other providers could significantly affect your approach to network management. After all, the infrastructure linking businesses and users to applications and data offsite is crucial.

So what’s new in the cloud? A few noteworthy updates:

Hand-wringing over GitLab’s decision to leave cloud

The IT industry practically gasped when computer-code app provider GitLab said earlier this month that it would no longer use the cloud for data storage — “roughly equivalent to ‘man bites dog’ in the tech blogosphere,” as Fortune put it. But the news shouldn’t shock. It’s simply an indication the cloud isn’t suited to every application.

In GitLab’s case, the cloud system wasn’t fast enough when it came to retrieving customers’ data, slowing work down for the company and its clients. The organization decided to build its own storage system. GitLab CEO Sid Sijbrandij told Fortune the company would still use the cloud for other workloads, “but we have a very specific need for a massive file system and right now the best way to do that is to have our own hardware.”

Google invests to make cloud smarter

Google is boosting its cloud machine-learning capabilities, betting that more and more organizations will need to identify and react to patterns in data. (Machine learning recognizes patterns and then adjusts its approach to the task based on what it sees.)

The company recently convened a workgroup to create cloud machine-learning applications. The firm also introduced some new machine-learning technologies, such as the Google Cloud Jobs API, an application-programming interface that gives job boards, career sites and other HR-focused organizations the ability to use Google’s machine-learning systems to find and recommend job candidates.

And it’s slotting powerful hardware into its cloud computers: beginning in 2017, users will be able to access specialized graphics processing units to crunch through machine-learning workloads more quickly.

Cloud adoption continues to rise

By 2018, organizations will run relatively little of their technology on premises. Well over half of that infrastructure will operate in the cloud, according to the 2016 Cloud Computing Survey, published by global IT market-watch firm IDG.

We’re talking important workloads here: almost three-quarters of survey respondents said they already use the cloud for storage as a service, or plan to soon; 59 per cent pointed to disaster recovery as a prime cloud app; 53 per cent are or plan to use the cloud for communications.

Intercloud concept takes hold

The IT industry usually considers the cloud as a service offered by competing providers. But what if those providers worked together? That’s the idea of the intercloud, a cloud incorporating numerous cloud platforms. The concept paves the way for individual providers to access infrastructure from competitors. The goal: ensure customers get the capacity they need, regardless of the computing power they require.

The notion seems to be gaining traction. BaishanCloud, a Chinese cloud-management services provider, has introduced a cloud linkage service to deliver cloud resources from any and all cloud systems. “We’re targeting a market in the post-cloud era,” said vice-president Eddie Zhao in an interview with chinadaily.com.cn. He said cloud providers have to integrate their platforms “to fuel more cloud demand from traditional industries.”

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