Google has initiated a complete cloud assault at its San Francisco cloud conference this week, detailing a number of Google Cloud Platform services that play on the strengths of its infrastructure benefits to take on public cloud rival Amazon Web Services (AWS).
Under the leadership of new Cloud head Diane Greene, who is founder and ex-CEO of VMware, Google’s Cloud Platform announcements go hand in hand with its recently revealed global data centre expansion.
“In the last year, cloud has gone from being the untrusted option to being seen as a more secure option for many companies,” wrote Brian Stevens, vice president of product management for Google Cloud Platform.
“We know that compliance, support and integration with existing IT investments is critical for businesses trying to use public cloud services to accelerate into new markets. So what is Google doing to help?”
First up, Google has revamped its Stackdriver IT monitoring tool. Google bought the Massachusetts-based company, also named Stackdriver, back in 2014.
At that time, the firm was mostly dedicated to providing an AWS cloud monitoring service. Under Google’s ownership, Stackdriver (currently in beta) will still serve to monitor AWS services for IT teams, but also obviously works with Google’s Cloud Platform.
“We’re excited to introduce Google Stackdriver, a unified monitoring, logging and diagnostics service that makes ops easier, whether you’re running applications on Google Cloud Platform (GCP), Amazon Web Services (AWS), or a combination of the two,” said Google.
“Stackdriver is the first service to include rich dashboards, uptime monitoring, alerting, log analysis, tracing, error reporting and production debugging, across GCP and AWS, in a single, unified offering.”
Next up is Google’s new machine learning platform, which hopes to entice developers to the service.
Google’s been working on machine learning for more than a decade now, and has been drip-feeding its machine intelligence services to consumers for the past few years. You can see it in action in Google Photos and Gmail’s ‘smart reply’.
“Today we’ve taken a major stride forward with the announcement of a new product family: Cloud Machine Learning,” said Google.
“Cloud Machine Learning will take machine learning mainstream, giving data scientists and developers a way to build a new class of intelligent applications. It provides access to the same technologies that power Google Now, Google Photos and voice recognition in Google Search as easy to use REST APIs. It enables you to build powerful Machine Learning models on your data using the open-source TensorFlow machine learning library.”
Google’s also released a bunch of pre-trained machine learning models, like the Google Translate API and the Google Cloud Speech API, ready for developers straight away.
Google further buffed up its big data and analytics offerings, adding new services and capabilities to its Cloud Dataproc and managed Apache Hadoop and Apache Spark services.
New features for BigQuery include long term storage options that cut the price of storage in half after 90 days, automatic table partitions, and a new capacitor storage engine that claims to speed up queries by up to ten times.
There was also a number of new hybrid partnerships announced with Splunk, BMC, and Tenable.
Google said it wants to expand its IT ops capabilities, along with ensuring security and compliance for customers usig these services in conjunction with Google Cloud Platform:
“Integration with rich third-party ops solutions is important for customers, and we know that many of you are already using these tools to manage hybrid operations in private and public clouds.”
These announcements aim to differentiate Google from Amazon Web Services, and compete with partner-friendly rivals like IBM and Microsoft and their hybrid cloud offerings.
On the infrastructure side of things, Google said it has improved the flexibility of both its cross-cloud interconnect and intra-cloud network options, boosting the support of workload portability across hybrid cloud environments, apparently.
“From advancements in machine learning and containers, to better ways to monitor, manage and secure cloud workloads, we’re taking big steps forward to change how businesses compute,” said Stevens.
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