The most compelling case for adopting
the Google Cloud Platform is that it is the same infrastructure that powers
Google's own services, which attract well over a billion users daily. This was
the case presented by company executives at last week's Google Next event in
San Francisco – "get on the Cloud… now", said Eric Schmidt, Executive
Chairman of Alphabet, Google's parent; "Cloud is the most exciting thing
happening in IT", said Diane Greene, SVP of Google Cloud.
Direct revenue comparisons between
leading companies are a bit tricky, but many analysts place the Google Cloud
Platform at No.4 behind Amazon Web Services, Microsoft Azure and IBM in the
U.S. market. Over the past three years, Google invested $29.4 billion for its
infrastructure, according to Urs Hölzle, SVP, Technical Infrastructure for
Google Cloud, on everything from efficient data centres to customised servers,
customised networking gear and specialised ASICs for machine learning.
Google operates what it believes to
be the largest global network, carrying anywhere from 25% to 40% of all
Internet traffic. Google's backbone interconnects directly with nearly every
ISP and its private network has a point of presence in 182 countries, while the
company is investing heavily in ultra-high-capacity submarine cables.
The argument goes that by moving to
the Google Cloud Platform (GCP), enterprise customers move directly into the
fast lane of the Internet, putting their applications one hop away from any end-user
ISP they need to reach with less latency and fewer hand-offs. Two example of
satisfied GCP customers that Google likes to cite are Pokemon Go and Snap Chat,
both of which took a compelling application and brought it to global scale by
riding the Google infrastructure.
One question is, does the Google
global network give its Google Cloud Platform a decisive edge over its rivals?
Clearly all the big players are racing to scale out their infrastructure as
quickly as possible, but Google is striving to take it one step further – to
develop core technologies in hardware and software that other companies later
follow. Examples include containers, noSQL, serverless, Kubernetes, Map Reduce,
TensorFlow, and more recently its horizontally-scalable Cloud Spanner database
synchronisation service, which uses atomic-clocks running in every Google data
centre.
Highlights of Google's initiatives
include:
·
New data centres: three
new GCP regions - California, Montreal and the Netherlands - bringing the total
number of Google Cloud regions to six, and the company anticipates more than 17
locations in the future. The new regions will feature a minimum of three zones,
benefit from Google's global, private fibre network and offer a complement of
GCP services.
·
GCP the first public
cloud provider to run Intel Skylake, a custom Xeon chip for compute-heavy
workloads and a larger range of VM memory and CPU options. GCP is doubling the
number of vCPUs that can run in an instance from 32 to 64 and offering up to
416 Gbytes of memory. GCP is also adding GPU instances. Google and Intel are
collaborating in other areas as well, including hybrid cloud orchestration,
security, machine and deep learning, and IoT edge-to-cloud solutions; Intel is
also a backer of Google’s Tensor Flow and Kubernetes open source initiatives.
·
Google Cloud Functions:
a completely serverless environment and the smallest unit of compute offered by
GCP; it is able to spin up a single function and spin it back down instantly,
so billing occurs only while the function is executing, metered to the nearest
one hundred milliseconds.
·
Free services: a new
free tier to the GCP that provides limited access to Google Compute Engine (1
f1-micro instance per month in U.S. regions and 30 Gbyte-months HDD), Google
Cloud Storage (5 Gbytes a month), Google Pub/Sub (10 Gbytes of messages a month),
and Google Cloud Functions (two million invocations per month).
·
Lower prices for GCE: 5%
price drop in the U.S., 4.9% drop in Europe; 8% drop in Japan.
·
Google BigQuery data
analytics service, including automated data movement from select Google applications,
such as Adsense, DoubleClick and YouTube, directly into BigQuery.
·
Titan: a custom
security chip codenamed Titan that operates at the BIOS level; Intel is also
introducing new security tools to keep customer data secure. The chip
authenticates the hardware and services running on each server.
·
Project Kubo toolset: a
joint effort with Pivotal for packaging and managing software in a Kubernetes
environment.
·
Engineering support
plans ranging from $100 per user per month to $1,500 per user per month with a
15-minute response time.
·
Data loss prevention
API to guard information inside the Google Cloud.
The Google Next event provided a
number of sessions for looking over the horizon. In a 'fireside chat', Marc
Andreesen and Vint Cerf speculated on the arrival of quantum computing and
neural networking/machine learning services on the public clouds. Both
possibilities are likely to augment current public cloud computing models
rather than replace them. The types of applications could vary. For instance, a
cloud-based quantum computing service might be employed to finally secure
communications.
Google is also betting big that the
cloud is the ideal platform for AI. Fei-fei Li, Chief Scientist for Cloud AI
and ML at Google, observed that a few self-driving cars can put considerable
data into the cloud. What happens when there are millions of such vehicles?
Building on ramps for AI is the next step with API and SDKs that draw new
applications onto Google's TensorFlow platform. The company discusses this in
terms of 'democratising' AI, which means making sure its algorithms and cloud
analytic systems become widely available before others move into this space.
A final differentiator for GCP is
that Google is the largest corporate purchaser of renewal energy. In 2017, the
company is on track to reach 100% renewal power for its global data centres and
offices. One hopes that others will catch up soon.
