Technalysis Research
Previous Columns

June 25, 2020
Look Out, Here Comes 5G, Phase 2

June 25, 2020
How Will 5G Networks Get Faster? Densification

June 16, 2020
5G Complexity Makes Testing Critical

May 19, 2020
New Chip Advancements Highlight 5G Momentum

May 5, 2020
IBM Brings Open Hybrid Cloud Strategy to 5G and the Edge

April 29, 2020
New WiFi 6E Standard Brings 5G-Related Technologies to Local Area Wireless

April 15, 2020
Microsoft’s New Azure Edge Zones Highlights Opportunity to Combine 5G and Edge Computing

April 9, 2020
Samsung Breaks $500 Barrier for 5G Smartphones with New A Series

March 30, 2020
Microsoft Purchase of Affirmed Networks Highlights 5G Focus Shifting to Infrastructure

March 24, 2020
Spectrum-Sharing Technologies like CBRS Key to More Robust Wireless Networks

March 10, 2020
Major Chip Vendors Driving Revolutionary Changes in 5G Infrastructure

February 27, 2020
CBRS vs. C-Band: Making Sense of Mid-Band 5G

February 18, 2020
5G Latency Improvements Are Still Lagging

February 13, 2020
T-Mobile, Sprint Merger Likely to Bolster US Competitiveness for 5G

February 11, 2020
Samsung S20+ And Ultra Launch Finally Brings “Full 5G” to Market

February 3, 2020
The Top 5 Fallacies About 5G

January 9, 2020
CES Previews What to Expect from 5G in 2020

2019 Forbes Columns

Forbes Columns
TECHnalysis Research president Bob O'Donnell writes a regular column in Forbes and those columns are posted here and archived on this site.

July 14, 2020
Google Redefines Multi-Cloud Computing

By Bob O'Donnell

Ask any IT professional or tech industry observer to name the top trends they see, and you would inevitably hear many variations on the theme of cloud computing. In particular, the phrase multi-cloud computing is likely to pop up.

At its simplest level, multi-cloud computing simply means that a company is choosing to use several different public cloud vendors, such as Google’s GCP, Amazon’s AWS, Microsoft’s Azure, etc. Companies often choose this approach to avoid vendor lock-in, provide redundancy, and help deal with data sovereignty issues where certain data has to be stored in a given country for legal or regulatory purposes (and not every cloud provider has data centers in every region).

In addition, certain cloud providers have developed expertise in specific areas and companies are choosing to run workloads with these providers to take advantage of those unique capabilities. In fact, a study on Hybrid and Multi-Cloud Computing trends that was based on a survey of over 600 US-based cloud computing professionals published by TECHnalysis Research earlier this year clearly highlighted that trend.

Even in those specialized situations, however, it’s typically been an entirely separate dataset, application and workload that’s run in those different environments. With one of the many announcements that Google Cloud CEO Thomas Kurian made at the debut of their multi-week Google Cloud Next virtual event, it’s clear that Google is looking to expand the definition of multi-cloud. Specifically, Google announced a new offering that works across multiple datasets and workloads running on several different providers. The new BigQuery Omni capability lets companies leverage Google’s deep heritage in search and querying to run its unique analytics capabilities across data stored in Google Cloud, AWS, and, later this year, Azure.

At a high level, BigQuery Omni essentially enables a macro-level grouping of multiple cloud platforms, workloads and datasets under a single level of control, all while leveraging one of the widely acknowledged strengths that Google has on its competition. This federated, multi-cloud, data analytics architecture is exactly the kind of clever and aggressive move that’s helping Google start to win the kinds of big-name customers that the company also highlighted at this year’s Cloud Next, including 5G carriers Telefonica, Vodaphone, and now Verizon, as well as Deutsche Bank, Renault, Fox Sports, and others.

One of the key benefits of how BigQuery Omni works is that Google code runs natively on the different cloud platforms and accesses data locally from the storage resources within those platforms, thereby avoiding the expensive and time-consuming process of transferring data across platforms (otherwise known as data egress). Plus, the BigQuery Omni offering is structured such that users can utilize the same basic BigQuery interface (running on GCP) to create the SQL commands necessary to query the databases, and then those requests are computed locally within each environment. The results from multiple sources can then all be transferred back to a single pane-of-glass UI for easier analysis or stored within each platform to avoid any cross-cloud move of data.

Part of the reason this is all possible is that, since its inception over 10 years ago as a Google internal tool, BigQuery, with its Dremel query engine, has separated the compute elements from the storage elements. That architecture wasn’t originally built with multi-cloud computing in mind, but by combining it with Google Anthos’ ability to run or transfer workloads across different cloud platforms through an abstraction layer, the company was able to create a solution that essentially treats different cloud platforms as if they were different regions within a single platform.

The idea of turning multi-cloud computing into an extended version of a single cloud platform—which BigQuery Omni does—seems to offer a number of interesting benefits. First, from a user’s perspective, this meta-platform concept provides a consistent way to access multiple data sets across multiple platforms, all through a single interface. More importantly, it opens up the idea of thinking about cloud computing resources overall in a significantly more flexible manner. It’s not difficult to imagine, for example, that Google (or other cloud providers) could create other types of multi-platform solutions that let them leverage some of their unique IP. Using new types of machine learning or neural network training algorithms across multiple datasets stored in multiple locations, for instance, could be an interesting new option.

The bottom line is that by leveraging both its BigQuery and Anthos assets, Google has put together an intriguing new twist on multi-cloud computing. Offerings like BigQuery Omni have the potential to open up the cloud world to new types of unified macro-level meta-platform offerings that, ironically, can further break down the walls that exist between the different cloud platforms at the same time. It remains to be seen how effective they prove to be in the real world, but conceptually it breaks some interesting new ground.

Disclosure: TECHnalysis Research is a tech industry market research and consulting firm and, like all companies in that field, works with many technology vendors as clients, some of whom may be listed in this article.

Here’s a link to the original column:

Forbes columnist Bob O'Donnell is the president and chief analyst of TECHnalysis Research, a market research and consulting firm that provides strategic consulting and market research services to the technology industry and professional financial community.