Google Cloud Platform (GCP) is a suite of cloud computing services for deploying, managing, and monitoring applications. A critical part of deploying reliable applications is securing your infrastructure. Google Cloud Audit Logs record the who, where, and when for activity within your environment, providing a breadcrumb trail that administrators can use to monitor access and detect potential threats across your resources (e.g., storage buckets, databases, service accounts, virtual machines).

APIs are stable, until they aren’t. We talk about that often at Bearer. If you control the APIs, it gets easier, but with third-party APIs and integrations it can be more difficult to predict when an outage or incident is about to happen.

In under five years time, Kubernetes has become the default method for deploying and managing cloud applications, a remarkably fast adoption rate for any enterprise technology. Amongst other things, Kubernetes’s power lies in its ability to map compute resources to the needs of services in the current infrastructure paradigm. But how does this tool work when faced with the new infrastructure layer that is blockchain? Can the two technologies be used in conjunction?

Machine learning (ML) used to be a tool limited to specialized developers and dedicated teams. Now, thanks to many web service providers and approachable tooling, your applications can use pre-build learning models and machine learning techniques the same way you would use any web service API. This is a quick way to test out and benefit from machine learning without having to invest in artificial intelligence, building your own learning models, or shaping your application around ML.

This guide explains how to get started with any Google API, such as Google Maps, Google Calendar, Youtube, or Google Sheets. Google's APIs can allow your application to integrate with Google services on the web or in a native application. There are three types of credentials for Google APIs.