We celebrated National Cyber Security Awareness Month.
Cyber attacks constantly evolve, and we build automatic protections into our products to keep people safe. That’s part of the puzzle, with another big piece being what you can do to keep your accounts protected. We introduced some best practices for password management, 2019 edition, to offer tips on developing good habits around passwords. Plus, we explored some best practices around two-factor authentication (2FA) when using Google Cloud. And finally, we made the new USB-C Titan Security Keys available for everyone in the U.S.
Students of cloud can explore new cloud 101 trainings.
New trainings came out in October, designed to tackle a few of the big questions that come up when businesses are first moving their applications and data into cloud services. One big decision is whether to use Google Compute Engine or Google Kubernetes Engine (GKE). Compute Engine is more similar to how businesses have been operating their technology systems, while GKE is a newer type of technology. The trainings can help explain the hows and whys of using and setting up each of the options.
We explored tech accessibility for Disability Awareness Month.
Accessibility isn’t just about physical spaces—it also matters that apps, online content and digital tools are inclusive of all users. So during Disability Awareness Month, we explored some of the Chromebook’s accessibility features, like the Select-to-speak text reader, the ChromeVox built-in screen reader, dictation tools and more. G Suite also comes with built-in accessibility features that make it easy to add closed captioning to your presentations, use voice typing tools and more.
We heard a story about jobs and tech changing together.
Changes at work can be hard, but can also result in great things. Lots of our engineering teams follow a model, developed here, called Site Reliability Engineering (SRE). It’s a methodology that helps teams build services that are reliable for users and that take the human element of technology into account—so IT teams on call can work harmoniously without getting burned out. This story describes how the Google team in charge of the network moved to this model. It involved changing the roles of team members so they can now do fewer repetitive tasks and more of the work to solve bigger problems.
Machine learning gets better at seeing moving images.
At Google Cloud, customers use our AI Building Blocks to get started easily with machine learning without requiring AI expertise. Recent updates to our vision products offer even more ways get insights from images and video. Customers use AutoML Vision to create models that are specific to their domain, so that they can get important information from images. AutoML Vision Edge, which runs ML models for devices like sensors, now detects objects in addition to classifying images. Plus, a new feature in AutoML Video means models can be trained to track objects in videos—useful for things like traffic management or sports analytics. In addition, a new feature in the Video Intelligence API can detect, track and recognize logos of popular businesses and organizations.
APIs took center stage.
APIs are interfaces that enable different software programs to communicate with one another—think of how you can sign in to one app on your phone with the login credentials from another. As you might imagine, these APIs are pretty important in our interconnected world, and there are quite a lot of them out there. API management, then, is its own important area of using modern technology—it’s how organizations secure, analyze, and expose APIs in ways that make it easy for developers to build on them. Google Cloud’s API management platform, Apigee, was once again recognized a leader in the 2019 Gartner Magic Quadrant for Full Lifecycle API Management. This report is often used by our customers as a reliable evaluation tool.
That’s a wrap for October. Keep up on cloud on our blog, and we’ll see you next month.
