Video-Tutorials

3 Tricks for Network Debugging on Google Cloud Platform

In this video, we look at three unusual tricks for debugging networking on Google Cloud. These are in addition to the normal network visibility tools, like packet mirroring and the Cloud Ops suite. Specifically, we look at Connectivity Tests, the Cloud Shell, and HTTP HTTPS Echo (on Cloud Run).

Address and Entities Validation (Google Maps/Places APIs)

Dive into the world of Address Validation and enrichment with Google Maps APIs. In this tutorial, we’ll explore the Address Validation API and how to use it with the Google Cloud Console and Cloud Shell IDE. Learn how to make API calls, analyze response structures, and gather valuable information for a seamless user experience in your applications. As a bonus, we’ll also delve into the Places API to enrich address data even further.

Automatische GitHub-Freigaben mit GitHub-Aktionen

GitHub Releases helfen Benutzern, die neuesten Versionen einer Bibliothek oder Anwendung schnell zu verstehen - welche Versionen das sind und welche Änderungen sie enthalten. Die Erstellung eines GitHub Releases kann mit einem einfachen GitHub Actions-Workflow automatisiert werden, sodass die Versionierung und die Änderungsprotokolle einen minimalen Entwickleraufwand erfordern. In diesem Video besprechen und demonstrieren wir die automatisierte Erstellung von GitHub Releases.

Cloud-Based Development Environments with Google Cloud

In this video, we review the two options for platformized, cloud-based IDEs in Google Clouds. Namely, we demonstrate, compare, and contrast Cloud Shell IDE and Cloud Workstations.

Kontinuierliche Bereitstellung von statischen Websites mit GitHub und Cloudflare

Gemeinsam bieten GitHub und Cloudflare eine einfache und kostengünstige Möglichkeit, eine statische Website bereitzustellen und zu verwalten. In diesem Video veröffentlichen wir eine neue Website im öffentlichen Internet und richten Konfigurationen ein, damit unsere Website automatisch aktualisiert wird, wenn es neue Code-Commits gibt.

Create an API that Executes Templated Bash Scripts

In this video, we use an open source project to create an API that runs bashscripts. For this setup, we only need a service like Cloud Run (or a similar Docker environment like Kubernetes), a Dockerfile, a simple YAML configuration, and our bash/shell script. We use HTTP request properties as bash script arguments, and can layer on security measures like Bearer tokens for authorization.

Create and Run OAuth2-Secured Websites (Docker and Cloud Run)

In this video, we review how to build and deploy a static website (HTML, CSS, and client-side JavaScript) using the OAuth2 Proxy project, Docker, and Cloud Run. Google Cloud Platform is used for the OAuth2 provider, but the architecture can be easily adapted to other providers like GitHub or Keycloak.

Easily Run a Website with HTML, CSS, and Client-Side JavaScript on Google Cloud

In this video, we setup Google Cloud Platform resources to host/serve a static website (HTML, CSS, and client-side JavaScript). The setup is simple, yet performant and secure. The performance is facilitated by Cloud CDN, which caches website files closer to users. The security is enabled by a minimal cloud resources setup, tightly-controlled configurations, and HTTPS website encryption.

Establishing and Debugging Windows Connections in Google Cloud Platform

RDP and SSH are common connection protocols for accessing Windows VMs running on Google Cloud Platform. In this video, we establish and debug these connections.

Sofortige Analyseanwendung mit AWS Kinesis, AWS Redshift und Retool

AWS Kinesis, AWS Redshift und Retool bieten eine hervorragende Grundlage für einfache Analyse-/Intelligenz-/Metrik-Anwendungen. In diesem Lernprogramm befassen wir uns mit der manuellen Erstellung der erforderlichen Ressourcen und der Terraform-basierten Bereitstellung.

Getting Started with Image Text Extraction (Google Cloud)

In this video, we demonstrate how to quickly get started with image text extraction, using the respective ML API from Google Cloud. If you have an existing Google Cloud project, you begin experimenting with the API in less than a minute or two.

Helm + Kubernetes Install of Argo Workflows and Argo Events

In this video, we setup Argo Workflows and Argo Events on a Kubernetes cluster. While we leverage Google Kubernetes Engine (GKE) in this video, the same approach is relatively portable to other Kubernetes environments, like on Amazon Web Services (EKS on AWS). By including load balancing, SSL certificates, and web application firewall in the installation, we get a more solid and secure setup.

Helm Repo with GitHub Actions and Google Cloud (Serverless)

In this video, we setup a Helm repository using only serverless networking and storage services on Google Cloud. We include Google-managed SSL certificates and a custom DNS domain name, for a professional HTTPS repository endpoint. GitHub Actions will give us workflow automation that creates, updates, and manages the Helm repository.

Intro to Advanced Routing with Cloud Load Balancers

In this video, we’ll explore a few advanced routing examples, on Google Cloud Load Balancing. We’ll also share a reusable pattern for backing load balancers with test Cloud Run services. While this video focuses on hosts, URI paths, headers, HTTPS, SSL certificates, routing, rewrites, and redirects, the demonstrated concepts should be relatively portable to other load balancing situations.

Introduction to CDN Cache Configuration on Google Cloud

In this video, we walk through CDN cache configurations like: cache mode, time to lives, serve while stale, cache security, negative caching, and header-based bypasses. This is presented alongside explanations and diagrams to clarify the concepts.

Kubernetes Ingresses & Gateway API: Strengths and Limitations

In this video, we explore popular options for exposing workloads in Google Kubernetes Engine (although the concepts are relatively portable to other Kubernetes environments). The examples are chosen to demonstrate and contrast: cluster-local ingresses, cloud-native ingresses, and the new Gateway API. More broadly, the demonstrated use cases, domains/certs, and evaluated options are selected based on their applicability and popularity for real production scenarios.

Open Source Kubernetes Networking (Nginx + Cert Manager)

In this video, we establish a foundation for Kubernetes web service/application networking, using Nginx Ingress and Cert Manager. This dynamic duo gives us a lot of flexibility, yet has the robustness to handle high traffic production use cases. Much of the networking is backed by Google Cloud Platform: Cloud Load Balancing, Google Kubernetes Engine, and Cloud DNS. However, the demonstrated approach is highly portable to other cloud environments.

PaLM 2 Text/Chat - Getting Started (Google Cloud Vertex AI)

Join us as we explore Google’s new generative AI Model Garden, focusing on the revolutionary PaLM 2 models for text and chat!

This video guides you through the Vertex AI Model Garden, its various open-source models, and the powerful PaLM APIs for text and chat. We demonstrate how to interact with these models, create context for requests, save prompts, and even provide Python code for you to replicate the process.

Private Python Package Artifact Registry with Google Cloud

In this video, we setup a private PyPI-like private Python artifact repository, using Google Cloud’s Artifact Registry service. From building the package and publishing it, to installing, importing, and using it, we demonstrate the full end-to-end process. With this setup, teams can securely manage their shared libraries and better promote code reuse.

Running Nginx on Kubernetes via Ingress-Nginx

In this video, we setup the Nginx ingress controller on a Kubernetes cluster, which then gives us an ingress class for exposing applications to external users and services. We demonstrate the setup with Google Cloud Platform (GCP). Specifically, we use Google Kubernetes Engine (GKE), However, the demonstrated setup process should be quite portable to other Kubernetes environments like Amazon Kubernetes Service (AKS).

Running Python Functions in SQL (BigQuery Example)

BigQuery Remote Functions allows us to run data processing logic, using languages like Python, Golang (Go), Javascript, and Java. Specifically, BigQuery will call a Google Cloud Function when the remote function is built into any normal BigQuery SQL query. This pattern not only enables complex algorithms in BigQuery data processing, but can also democratize algorithms and specialized processing, such that non-programers can use the logic (via SQL). The setup is simple, serverless, and secure.

S3/GCS/MinIO Buckets as Kubernetes Persistent Volume Storage

Any S3-API-compatible storage can be used as a persistent volume in Kubernetes, if we use the Linux Foundation’s Datashim project. While this is not a general substitute for traditional disks and file systems, it does enable interesting architectures, cheap cloud-native storage, and a clean way to access bucket-based data, configurations, and code.

Set Up a File Server (HTTPS and SFTP) on Kubernetes

In this video, we setup an HTTPS+SFTP file server on Kubernetes (Google Kubernetes Engine, on Google Cloud Platform). The demonstrated use case is a file server with public, browser-based read access and secure, SSH-key-based write access. The setup is easily customizable to other use cases and cloud environments.

Setting Up Jupyter Notebooks on Google Cloud Platform

In this video, we set up a Jupyter Notebook on Google Cloud Platform. For a clean, secure, and integrated setup, we leverage the Vertex AI Workbench service and a custom service account.