Google Cloud Platform

While most developer resources are focused on a limited set of projects, there is a large set of mission critical processes that still need attention.

Learn how to build production ML workflows that are scalable, serverless, and reproducible; and support monitoring, continuous training, artifact management, collaboration, and more.

Serverless allows you to write code without worrying about infrastructure or scaling. Go is perfect for cloud applications because of its efficiency, portability, and fast learning curve.

More data will be generated in the 2016 elections than any other election cycle in history.

Aja Hammerly (@the_thagomizer) demonstrates how to view audit logs on Google Cloud Platform.

Cost Control → goo.gle/3sOKrOJ In this episode of VM End-to-End, Developer Advocate Carter Morgan sits down with Developer Advocate Brian Dorsey to talk about VMs.

Time management is hard, and most of us struggle.

Your production release pipeline might have a number of stages for experimentation, validation, testing, approval, and release, but the integrations and operations of environments is tricky.

Getting Started |

Here to bring you the latest news in the Cloud is Debi Cabrera. • Visual UI for STT API → goo.gle/3LBV3tt • Pub/Sub Lite Updates → goo.gle/3oFMCTL • Free Cloud Training → goo.

Google Container Builder is a tool for building application containers in the cloud, using Google’s resources.

In this episode of Stack Chat, Tony Walker, Public Cloud Engineering from Two Sigma, shares how the company builds its data pipeline with the combination of GCP technologies and the company’s own

Aja Hammerly (@the_thagomizer) shows you how you can use exclusion filters in Stackdriver Logging to reduce log waste and noise.

Time series data is conducive to the growth of a company but you want the best performance when collecting these field data.

In this episode of Eyes on Enterprise, Stephanie Wong invites Brian Dorsey, Compute Developer Advocate, to talk about where to run your workloads on Google Cloud.

Watch an overview of Google Cloud’s approach to implementing AI Principles into well-known products.

HPC Cloud services built on the latest Intel architecture, Skylake Xeon processor, are now powering Google compute engine and can serve as your next-generation HPC platform.

The next answers to the mysteries of life and discovery of disease treatments have never felt more attainable with these no-cost solutions to run AlphaFold on Vertex AI.

In this session, Steve Niemitz from Twitter will present how they use Cloud Bigtable to power their advertiser analytics systems.

If your system's security has been breached, what can you do to stop this attack and not make the situation worse?

SRE Workbook chapter on alerting on SLOs → goo.gle/2UdHEBD Blog post → goo.gle/32KbK0V Error budget burn rate is a measure of how fast, relative to your SLO, your service consumes

Update (July 31): New version with slides and demo added. This session highlights a newly released project from the Go team that supports developing applications for the open cloud.

Kotlin is a versatile language that can be used for both frontends and backends. This talk will show you how you can quickly create Kotlin backends that can serve RESTful endpoints using popular

In this episode of AI Adventures, Yufeng Guo uses AI Platform Custom Containers to show you how to run custom training jobs on Google Cloud using Docker containers.

Google owns and operates the largest, highest-performing global cloud network.

Compute Engine offers a wide spectrum of instance types to match your compute needs.

Code Sample → goo.gle/3CqEn2g BigQuery APIs → goo.gle/3FhSUir Using the BigQuery Google Apps Script Service → goo.gle/3ouiTMJ Connecting BigQuery to Google Sheets with Apps