Google NEXT 2019 Recap

Brendan Doohan
Jun 28 · 4 min read

From April 9th through the 11th, Google Cloud Platform celebrated its 11th birthday with the Google NEXT Conference in San Francisco. This was my first Google NEXT Conference, so I wasn’t sure what to expect. What I experienced was a mind-bending mix of exciting product announcements, informative breakout sessions, and inspiring demos. I also got to meet some of my Google heroes, including Coursera instructor Lak Lakshmanan and Emma Haruka Iwao, the Guinness World Record holder for most-calculated digits of pi. Most exciting was the slew of new GCP services and features announced at Google NEXT. The new releases underscored GCP’s investments in containerization, machine learning, and managed database services.


It was clear from the conference that Google is focused on leveraging the power of pipelines on GCP. To this end, the most exciting announcement of the conference was Anthos, an application management platform that provides a consistent development and operations experience for cloud and on-prem environments. Essentially, Anthos is a container management platform based on Kubernetes that allows deployment and management of clusters. You can enforce security standards, deploy applications, and configure management workflows using a configuration-as-code approach. Anthos is ideal for clients looking to develop software that will run on multi-cloud and/or hybrid cloud environments. (Source:

GCP also announced the release of Cloud Run, which is a managed, serverless compute platform that allows you to create and run stateless containers through HTTP requests. Cloud Run takes care of infrastructure management, so you can focus on building applications. It is built on Knative — a Kubernetes-based platform — allowing you to run containers either fully managed with Cloud Run, or in a Google Kubernetes Engine cluster with Cloud Run on GKE. Cloud Run is great if you’re looking to develop pipelines quickly on GCP. (Source:

In addition to the emergence of containerization, point-and-click pipeline solutions, such as Alteryx and Qlik, have become more and more in demand. These solutions enable users to import, wrangle, and connect data in manageable pipelines. GCP has tossed its hat into this ring with the announcement of Cloud Data Fusion (“CDF”). CDF is a fully managed, cloud native data integration service designed for quickly building and managing data pipelines. It has a nice graphical interface that will enable business users, developers, and data scientists to easily and reliably build data solutions. (Source:


From an analytics perspective, GCP has been working to supplement the popular BigQuery interface with machine learning capabilities (BigQuery ML) and Data Studio visualizations. GCP extended this effort by announcing the launch of BigQuery BI Engine (“BQBI”). BQBI is a fast, in-memory analysis service that allows you to analyze data stored in BigQuery. It plays nice with other Google tools like Google Data Studio. You can now build rich, interactive dashboards and reports in Data Studio without compromising performance. (Source:

GCP increased its already robust machine learning and artificial intelligence offerings by announcing AutoML Tables (“AML”). AML is a supervised learning service that allows users to train a machine learning model with example data. It uses tabular data to train a machine learning model to make predictions on new data. You can use the same input features to build multiple kinds of models just by changing the target. For example, you could build two models with the same input features being used to predict two targets. This offering is great for clients who need predictive models but who may not have the machine learning skillsets needed to create, tune, and maintain models. (Source:


In the past, you could run Microsoft SQL Server on GCP by hosting it on a Compute Engine instance. However, this required you to manage the installation, implementing patches and updates yourself. GCP increased its offering in this space by launching a Managed SQL Server. You can now run managed SQL Server images on Google Compute Engine, giving users the continuity as they scale up their operations (

Security and privacy have always been top priorities of GCP, e.g. encrypting data at rest and in flight by default. GCP doubled down on its security offerings by announcing the launch of Cloud Security Command Center (Cloud SCC). Cloud SCC is a security and data risk database for GCP. It provides asset inventory, discovery, search, and management while also helping security teams gather data, identify threats, and act on them before they result in business damage or loss. With this tool, security teams can answer questions like “Which cloud storage buckets contain PII?”. Cloud SCC is ideal for clients with a large GCP footprint who need to manage access, security and data privacy. (Source:


Google NEXT was a great experience! The main takeaway from the conference was that Google is looking to triple its GCP capabilities in the next 2–3 years. This will likely entail continued growth in the number of GCP products and services. Please visit us at if you would like to discuss how your company can use GCP.

Slalom Technology

Thought leadership from technologists at Slalom.

Brendan Doohan

Written by

Slalom Technology

Thought leadership from technologists at Slalom.