If you do not care about how much money you spend on your Google Cloud project then this post won’t be interesting to you. If you do, you might find the information below useful. Google Cloud documentation gives examples of the automated cost control responses. It describes an option to send a notification message to PubSub in addition to the email each time the billing budget alert is triggered. The specific example that stops the usage shows a Cloud Function (code in NodeJS and Python) that disables the billing account on the project.

Last updated: August 12, 2024. Everyone today heard or read about GenAI, ChatGPT and other AI things. There are a lot of terminology, abbreviations and other clever words. I found myself troubled to remember all of them. So I decided to write down my definitions for each of these terms. TL;DR; If you are familiar with AI terminology, you might want to stop reading this post here. For the rest of the readers, welcome to my personalized thesaurus of GenAI terminology.

This article surveys various health checks in Google Cloud. If you want to learn more, leave your preferences in the feedback form. Generally speaking, a health check is a function or a method to indicate a general state (a.k.a. health) of the underlying service. Some products elaborate the definition of “general state” to be something particular, such as the ability of the service to respond to requests. Health checks are an important instrument of service observability.

Google Cloud lets you run Kubernetes in three flavors: Vanilla is when you do all on your own. This is also the quickest “lift and shift” strategy to migrate your cluster to cloud. Essentially it is just a group of virtual machines that run on Google Compute Engine (GCE). Managed that shifts administration and maintenance tasks from DevOps teams to the cloud service. See Google Kubernetes Engine (GKE) Standard cluster architecture and Autopilot for more details.

You may have seen this notice when opening SLOs Overview in Cloud Console. This notice announces a recent change in the way of defining services for Cloud Monitoring. Before the change, Cloud Monitoring automatically discovered services that were provisioned in AppEngine, Cloud Run or GKE. These services were automatically populated in the Services Overview dashboard. After the change, all services in the Services Overview dashboard have to be created explicitly. To simplify this task, when defining a new service in UI you are presented with a list of candidates that is built based on the auto-discovered services.

Google Cloud supports service monitoring by defining and tracking SLO of the services based on their metrics that are ingested to Google Cloud. This support greatly simplifies implementing SRE practices for services that are deployed to Google Cloud or that store telemetry data there. To make it even more simple to developers, the service monitoring is able to automatically detect many types of managed services and supports predefined availability and latency SLI definitions for them.

I wanted to introduce a support for “series” ‒ an ordered collection of posts about the same topic. For example, this post is the 4th post in the series “Getting Started with Hugo”. And I wanted to enable navigation between different posts from the same series instead of just going to “next” or “previous” post in the blog. I looked on internet and found many articles about how to do it using Hugo.

Hosting After a brief review of the selected Hugo settings, let’s review the decisions about hosting. I used only two criteria when I was choosing hosting for my blog website: Convenience – the service should be simple to use, allow automation, to have both CLI and Web interface and, ideally, familiar Costs – it should be cheap or, ideally, it should be free The choice for the website source code management was straightforward.

Almost all customizations for Hugo websites can be done using configuration. The configuration is stored in the single place the hugo.yaml file at the root folder of the website. Hugo comes with the hugo.toml (TOML) but I prefer to use YAML for my configurations. Hugo also supports JSON if you like it more. Documentation is nice and descriptive. I found several guidelines about what should be included into the config file.

I often (re-)use the same laptop to work in different projects that have to be committed to Github under different identities. By “identities” I do not mean different Github accounts. I sign my commits with SSH key registered at Github to emails that are associated with my Github account. Different types of projects are supposed to sign with different emails and keys. I could call git config... each time or maintain multiple .