The 10 Hottest Google Cloud, Workspace Tools Of 2023 (So Far)

CRN breaks down the 10 hottest new Google Cloud and Workspace products launched in 2023 so far, with the majority based around AI.

If Google Cloud’s innovation strategy in 2023 could be summed up in two words, it would be: artificial intelligence.

The nearly $30 billion Mountain View, Calif.-based cloud giant unleashed a slew of new AI and generative AI products, tools and services across its portfolio—spanning from Google Workspace to Vertex AI.

“Seven years into our journey as an AI-first company, we’re at an exciting inflection point,” said Google CEO Sundar Pichai in May. “We have an opportunity to make AI even more helpful for people, for businesses, for communities, for everyone. We’ve been applying AI to make our products radically more helpful for a while. With generative AI, we’re taking the next step.”

[Related: The 10 Coolest New AWS Tools Of 2023 (So Far)]

Google Cloud And Workspace AI

Although Google Cloud did enhance some of its flagship products this year, such as BigQuery, the vast majority of big new Google and Workspace tools came in the form of AI.

AI was top of mind for Google in 2023 for both Pichai and Google Cloud CEO Thomas Kurian, specifically around generative AI and Workspace.

“Developers and businesses can now try new APIs and products that make it easy, safe and scalable to start building with Google’s best AI models through Google Cloud and a new prototyping environment called MakerSuite,” said Kurian in March. “In Google Workspace, we’re introducing new features that help people harness the power of generative AI to create, connect and collaborate.”

CRN breaks down the 10 hottest Google Cloud and Workspace new tools launched in 2023 so far that are important for channel partners, customers and Google’s future in AI.

* Duet AI For Google Workspace

* Generative AI App Builder

* BigQuery Revamped

* Gmail Gets Generative AI

* Google MakerSuite

* PaLM API

* Built With Google Cloud AI

* Duet AI for Google Cloud

* Vertex AI

* RaMP Deck

Mark Haranas is an assistant news editor and longtime journalist now covering cloud, multicloud, software, SaaS and channel partners at CRN. He speaks with world-renown CEOs and IT experts as well as covering breaking news and live events while also managing several CRN reporters. He can be reached at mharanas@thechannelcompany.com.

Google Cloud and Salesforce team up to bolster AI offerings

Salesforce and Google Cloud are teaming up to help businesses leverage data and AI via a new strategic partnership.

Announced this morning, the partnership will allow companies to use their data along with custom machine learning models to anticipate their customer’s needs, execs from Google and Salesforce said. The tie-up spans products and services including Google’s BigQuery tooling, Salesforce’s Data Cloud and Vertex AI, Google’s fully managed AI platform.

“This really allows us to democratize AI so that customers get choice on which AI they want to use,” David Schmaier, Salesforce’s chief product officer, told TechCrunch in a phone interview.

It’s the second such major partnership between Google and Salesforce in recent years. The first, inked in 2017, was largely analytics- and big data-focused. The companies subsequently expanded that original agreement, deepening their data sharing collaborations and building AI-infused customer service experience and marketing tools.

The move makes sense for Salesforce on its journey to reposition itself as a “data company.” Over the past several months, Salesforce has introduced new generative AI tools, including EinsteinGPT, an AI assistant for customer relationship management (CRM) tasks like drafting emails, and SlackGPT, which answers natural language questions about a company’s Slack content, servers and channels.

Salesforce is also investing in the broader generative AI ecosystem, no doubt hoping to sniff out the next hit that might bolster its expanding product portfolio. Salesforce Ventures, the company’s corporate investment arm, this March launched a $250 million fund aimed at what it calls “responsible” generative AI startups.

As for Google, the renewed partnership with Salesforce puts its big data analytics and AI services front and center — which isn’t insignificant considering Salesforce’s customer base of over 150,000 organizations.

Google Cloud’s arguably in a position of strength, having just two months ago reported its first profitable quarter. At the same time, the company remains third in the U.S. cloud infrastructure market, behind Amazon and Microsoft.

“From our point of view, this partnership brings two very large ecosystems of data together and makes it much simpler and easier for customers to get value,” Google Cloud CEO Thomas Kurian told TechCrunch in an interview.

In terms of what the new strategic partnership will accomplish concretely, Google and Salesforce plan to launch an integration between Data Cloud — which is essentially a sophisticated data integration layer — and BigQuery that’ll enable companies to more easily create unified profiles of customers. The integration will provide companies with access across portions of Google and Salesforce’s platforms and clouds, akin to having their data housed in a single location.

Elsewhere, new connectors between Data Cloud and Vertex AI will allow companies to bring any AI models they’ve trained or fine-tuned in Vertex across the Salesforce platform. Companies will be able to train and retrain models on customer data from Salesforce, ostensibly streamlining the model development process.

How might companies actually use the new integrations and connectors? Salesforce provided a few examples in a memo ahead of today’s announcement.

A fashion retailer, for example, could connect CRM data like customer purchase history and service interactions with non-CRM data, such as social media sentiment, to deploy a custom AI model that predicts a customer’s likelihood to buy certain types of clothing based on the data. Or a financial institution could combine CRM and non-CRM data with an AI model to anticipate a customer’s spending habits and investment preferences.

So, will Google and Salesforce customers actually bite? That’s the perennial question. But Kurian and Schmaier seemed confident in the robustness of the new cross-platform offerings.

“Our general view is, these AI models are going to get richer and richer and much more sophisticated,” Kurian said. “The result that we’re trying to enable is productivity and efficiency for people doing work, and then, secondly, integrating all the information to make better decisions.”

The Data Cloud and Google Vertex AI integration will be in pilot starting July 2023 and generally available in October 2023, Google and Salesforce say. As for the Data Cloud and BigQuery integration, it’ll enter pilot in October 2023 and GA in February 2024.

Google Cloud Expands Cloud Interconnect Portfolio and Enhances Networking Capabilities

Recently Google Cloud announced a significant expansion of its Cloud Interconnect portfolio by unveiling Cross-Cloud Interconnect. The new offering enables organizations to connect any public cloud with Google Cloud securely and efficiently, allowing seamless application deployment across multiple clouds and simplified SaaS networking in a multicloud environment.

Connecting and securing distributed environments has posed challenges for cloud infrastructure teams. Configurations often involve complex setups, dedicated hardware, and time-consuming operational processes. With the Cross-Cloud Interconnect offering, Google aims to simplify these processes by minimizing hardware requirements, reducing overhead, and providing a secure, high-performance network for connecting any public cloud like Microsoft Azure, AWS, and Alibaba with Google Cloud.

The offering is available in 10 Gbps or 100 Gbps options and does not require new hardware. In addition, it has the same features as Cloud Interconnect and is backed with an SLA (99.99%). According to the company, customers with multicloud environments can leverage Cross-Cloud Interconnect to enable the following:

Source: https://cloud.google.com/blog/products/networking/announcing-google-cloud-cross-cloud-interconnect

Alongside the introduction of Cross-Cloud Interconnect, Google Cloud enhanced its Private Service Connect offering. Private Service Connect enables the creation of private and secure connections from virtual private clouds (VPCs) to Google Cloud, partner services, or custom services, simplifying network configuration for published services and SaaS applications. The recent enhancements include support for Cross-Cloud Interconnect, automated service connection policies, and expanded access for on-premises and multi-cloud clients.

In addition to these advancements, Google Cloud has strengthened its Cloud Interconnect capabilities with new encryption options, improved performance, and enhanced network resiliency. Features like MACsec for Cloud Interconnect provide point-to-point line-rate L2 encryption, ensuring secure communications between customers and Google Cloud, and HA VPN over Interconnect provides IPSec encryption to protect communications between a customer’s on-prem VPN gateway and the HA VPN gateway in Google Cloud.

In addition, bidirectional forwarding detection expedites the detection of link failures, enabling prompt traffic rerouting in case of path outages, and 9K MTU support (in preview) allows large packet sizes to deliver higher throughput over Interconnect offerings. Moreover, BGP enhancements (in preview) include support for custom-learned routes and increased prefix scale, further optimizing networking operations.

Several cloud providers offer similar services to Google Cloud Interconnect. For example, Azure ExpressRoute provides a private and dedicated connection between an organization's on-premises infrastructure and Azure cloud services. It offers secure and reliable connectivity with high bandwidth and low latency options. Furthermore, it allows connectivity with other clouds. Another example is AWS Direct Connect, which enables organizations to establish a dedicated network connection between their on-premises data centers and AWS, bypassing the public internet.