An Inside Perspective: Key Takeaways from Google Cloud Next 2019
Google unveiled several game-changing technologies at Google Cloud Next 2019 that are sure to catapult the company to new heights in its quest to position itself as a perennial leader in today’s cloud platform market. Google Cloud already powers many of the world’s leading enterprises and startups and is now poised to disrupt the status quo with its latest innovations.
Our team at Solstice sent developers and architects to Google Cloud Next to discover, share, connect, and most importantly, learn. Below are six key takeaways we see emerging from the conference.
1. Raising the bar with game-changing multi-cloud capabilities
As hybrid cloud continues to evolve, it makes sense that containers would be part of the future. To that end, one of the more noteworthy takeaways at this year’s Next 2019 conference was the announcement that Google will extend its market-leading Google Kubernetes Engine (GKE) offering to enterprise data centers in an on-premise hybrid cloud service that will run on existing enterprise servers.
Perhaps more surprising was the revelation that the service offering will also be available to run on any of the major public clouds including Amazon Web Services (AWS) and Microsoft Azure — and can be managed from a common user interface (GKE currently manages the distributed infrastructure running on Google Cloud on-premise data centers). The move underscores Google’s commitment to having hybrid/multi-cloud configurations, giving enterprises more options to deploy and manage their applications on any cloud.
Google is one of the first cloud providers to launch a multi-cloud platform. The first-of-its-kind offering is certain to garner wide appeal — and for a good reason. Google promises Anthos to simply work out-of-the-box with little configuration needed. Multi-cloud capabilities are unique in the industry and could well be the break-through product Google needs to effectively gain market share in the enterprise cloud market currently dominated by Amazon (31.5 percent) and Microsoft (13.5 percent).
2. Streamlining management of containerized workloads
While service mesh offers an attractive option for microservices environments, it can also have more complex operational requirements as it expands. Google’s integration of Istio service mesh into GKE helps address this issue, offering a way to integrate microservices, secure them, and aggregate log data while providing an additional abstraction layer.
Google recently announced updates to GKE (GKE Advanced), which extends these capabilities, enabling security (mTLS), monitoring, tracing and advanced routing without having to rewrite code. Integration with Stackdriver, Google Cloud’s logging and monitoring service, helps to further ease management tasks. The result: enhanced visibility and security while making design and development with containerized workloads easier.
The advanced edition builds upon Google’s unique insights from running a complex container infrastructure internally for years. Istio currently only supports the Kubernetes container orchestration service, though the plan is to support other environments in the future.
3. Accelerating development speed with Cloud Code plugins
Writing cloud-native applications can present some unique challenges for developers. The launch of Cloud Code, a set of plugins for popular development environments like IntelliJ and Visual Studio Code, is designed to help ease that burden. The goal here is to provide developers with all of the necessary tools to build cloud-native applications — all without having to deal with tedious configuration work that is typically required.
Using Cloud Code, developers can simply write their applications like before, but then package them as cloud-native apps and ship them to a Kubernetes cluster for testing or production. Advantages include faster development in local and remote clusters and easier deployment and debugging in Kubernetes.
While some features of the plugins support Google Cloud services, (such as dependency management and automatic library) Cloud Code is explicitly designed to work with Kubernetes, no matter your provider. In fact, the plugins include tools for designing new Kubernetes clusters on competitor services like Azure and AWS.4. Lowering the barrier to entry for AI
AI and machine learning are key focal points for all big cloud providers, but the development experience leaves considerable room for improvement. At Next 2019, Google showcased its artificial intelligence prowess with a number of AI announcements. Most prominent was Google’s new AI platform, which offers an end-to-end solution that allows developers to go from ingesting data to training and testing their models, to putting them into production.
Having comprehensive solutions is clearly a major step forward here and opens up the promise of machine learning to a wider range of potential users. We believe that this platform will be widely adopted and sought after as Google continues to expand and simplify access and add pre-trained models that will help enterprises meet their unique AI skill level requirements.
5. Driving digital transformation
Google continues to democratize artificial intelligence and bring the benefits of AI to its platform with simple and approachable APIs. Document Understanding AI is a good example. The solution uses machine learning on a scalable cloud-based platform to help businesses efficiently analyze documents, unlock new insights and improve decision making.
Automating, validating and archiving documents from multiple sources into one cloud-based system helps minimize risk and reduces errors common with manual data entry. Document Understanding AI allows you to take advantage of insights and knowledge in your unstructured documents, making this information available to your business applications and users while saving you time, money, and labor in the process.
From our perspective, Document Understanding AI will help pave the way for enterprises to uncover a treasure trove of knowledge and insights while helping to improve accuracy, governance and compliance.
6. Elevating the customer experience
On the customer experience front, Google and Salesforce announced the integration of Dialogflow Enterprise Edition with the Salesfore Einstein platform — coming two years after forming its strategic partnership. The objective is to help enterprises automate normal repetitive customer service inquiries and enhance the customer experience regardless of whether the customer is engaging with an agent, a bot, or a combination of the two.
The integration will extend the functionality of Einstein and open new capabilities for businesses, freeing agents to focus their energy on resolving more complex cases and accelerating resolution. The announcement also opens the door to additional opportunities between Google Contact Center AI and Salesforce’s Service Cloud, with the potential for new functionality resulting from the extensive feature set and robust capabilities inherent in Contact Center AI.
Raising the stakes
Google’s latest innovations underscore the efforts the company is putting into the cloud, specifically around AI as well as open source tools for fast, efficient deployments, easy management, and optimum performance. Meanwhile, Google continues to push the envelope on technology development, continuing to up the ante while seeking new areas of differentiation and additional opportunities to capture market share.
This post was co-authored by Brian Kim, Daher Alfawares and Adam Haag.