Argo CD Links Title Link Argo CD Up and Running https://www.youtube.com/watch?v=yATHNHLWj-M GitOps Best Practices 2025 https://www.youtube.com/watch?v=mlYW54JEoqg

1. Create machines # Create 1 controle plane and 1 worker machine in your infrastructure of choice. # This example is for AWS Ubuntu 22.04 (replace with own amis, sgids, sids) # Create control plane instance aws ec2 run-instances \ --image-id ami-04a5bacc58328233d \ --count 1 \ --instance-type m5.large \

Welcome to the Architecting on Kubernetes class. This notes contain a lot of supporting material from public sources that will further improve your understanding of Kubernetes and the corresponding tools. https://medium.com/nerd-for-tech/11th-dec-2024-openais-kubernetes-outage-explained-27c60e620bc3?utm_source=chatgpt.com "11th Dec 2024 — OpenAI Outage (ChatGPT) Explained: Kubernetes Clusters ..." https://www.portainer.io/blog/when-kubernetes-fails-reflections-on-the-openai-outage?utm_source=chatgpt.com "When Kubernetes Fails: Reflections on the OpenAI Outage - Portainer" https://grafana.com/blog/2022/08/31/how-adding-kubernetes-label-selectors-caused-an-outage-in-grafana-cloud-logs-and-how-we-resolved-it/?utm_source=chatgpt.com "How adding Kubernetes label selectors caused an outage in Grafana Cloud ..." https://docs.google.com/spreadsheets/d/1zCqaQWHu21zDCniuIb3GW8KJTvgPdCbzH2imxnXFuyw?utm_source=chatgpt.com "Kubernetes Failures Analyzed - Google Docs" Books https://www.redhat.com/cms/managed-files/cm-oreilly-kubernetes-patterns-ebook-f19824-201910-en.pdf https://www.wolf.university/learninghelm/ebook/learninghelm.pdf

Question 1 What is Calico's primary function as a Container Network Interface (CNI) in Kubernetes? [ ] A) Manage container orchestration [ ] B) Provide network connectivity and security policy between pods [ ] C) Monitor cluster performance [ ] D) Distribute container workloads across nodes Show Answer Correct Answer: B) Provide network connectivity and security policy between pods

Here are some essential commands for configuring and managing etcd in a Kubernetes cluster: Adjust the endpoints, certificate paths, and IP addresses according to your specific cluster configuration. Check etcd version: ETCDCTL_API=3 etcdctl --endpoints=https://127.0.0.1:2379 \ --cacert=/etc/kubernetes/pki/etcd/ca.crt \ --cert=/etc/kubernetes/pki/etcd/server.crt \ --key=/etc/kubernetes/pki/etcd/server.key \

Welcome to the MLOps Engineering on AWS. This document contains useful links to complement our April 2025 training. AI Services on AWS Title Link Amazon SageMaker https://www.youtube.com/watch?v=5ZN-90fi3II Amazon Bedrock

SageMaker Clarify Bias Metrics Acronym Name Description CI Class Imbalance Measures imbalance between positive and negative labels.

Welcome to the Generative AI Essentials on AWS. This document contains useful links to complement our April 2025 training. Useful Links Title Link AWS GenAI Keynote 2024 https://www.youtube.com/watch?v=qGzYTg5FIA4 AWS Use Cases

1. sagemaker.algorithm Purpose: Provides functionality for working with algorithmic estimators in SageMaker. Enables users to use built-in algorithms for common ML tasks. Allows packaging custom algorithms for reuse. Supports algorithm validation and registration in the marketplace. Facilitates algorithm selection and tuning. Key Submodules: algorithm_estimator - Classes for training with algorithm resources algorithm_spec - Algorithm specification utilities metadata_properties - Metadata processing components metric_definitions - ML metric definition helpers

SageMaker Studio SageMaker Studio is an integrated development environment (IDE) for machine learning that enables developers to build, train, and deploy models from a single web-based interface. It provides a unified experience for the entire machine learning workflow, from data preparation to deployment. Studio offers collaboration features that allow teams to share notebooks, models, and resources. It includes built-in support for popular frameworks and tools like TensorFlow, PyTorch, and Jupyter. Studio also enables customization through container images and lifecycle configurations to meet specific development requirements. CreateApp: Creates an application within a SageMaker domain, such as JupyterLab, Code Editor, or other supported apps. The app is associated with either a user profile or a shared space. This resource manages the lifecycle of individual applications that users interact with. CreateAppImageConfig: Creates a configuration for a custom container image that can be used with SageMaker Studio applications. This configuration defines settings such as kernel specifications and file system access. The image config enables customization of the development environment for specific project requirements. CreateDomain: Creates a SageMaker domain, which is the primary organizational unit for SageMaker Studio that shares settings and resources. A domain contains user profiles, apps, and can be configured with specific security and networking settings. Domains provide organizational boundaries for ML workloads within an AWS account. CreateImage: Creates a custom container image definition that can be used with SageMaker Studio applications. The image definition includes the ECR image URI and metadata about the image. This resource enables teams to use specialized environments with specific dependencies and tools. CreateImageVersion: Creates a new version of an existing custom container image for SageMaker Studio. Each version is associated with a specific ECR image tag or digest. Version management allows for controlled updates to development environments while maintaining backward compatibility. CreatePresignedDomainUrl: Creates a pre-signed URL for accessing a user's SageMaker Studio environment. The URL provides secure, temporary access to Studio without requiring AWS console login. This enables simplified sharing of Studio access for specific users or scenarios. CreateSpace: Creates a shared collaborative space within a SageMaker domain that multiple users can access. Spaces allow teams to collaborate on projects using shared compute resources and storage. This resource promotes team-based workflows where multiple users need to work on the same ML projects.

Section 1 Question 1 What is the core principle of GitOps? [ ] A) Git repository is the single source of truth for declarative infrastructure [ ] B) Everything must be manually approved before deployment [ ] C) Developers must have direct access to production environments [ ] D) All infrastructure changes require separate CI/CD pipelines Show Answer

Welcome to the AWS Discovery Days - Generative AI. This document contains useful links to complement our January 2025 Discovery Day. Follow me on LinkedIn: https://www.linkedin.com/in/gekart/ Useful Links Title Link AWS GenAI Keynote 2024 https://www.youtube.com/watch?v=qGzYTg5FIA4

Welcome to the Architecting on OpenShift class. This note contain supporting material from public sources that will further improve your understanding of OpenShift / Kubernetes and the corresponding tools. Books https://www.redhat.com/cms/managed-files/cm-oreilly-kubernetes-patterns-ebook-f19824-201910-en.pdf https://www.manning.com/books/kubernetes-in-action-second-edition Kubernetes in 2023 https://www.youtube.com/watch?v=kGrpLKNi4ZI Installation

Books Title Link Pro Git book https://github.com/progit/progit2/releases/download/2.1.375/progit.pdf git cheat sheet https://training.github.com/downloads/github-git-cheat-sheet.pdf

Welcome to the Building Batch Data Analytics Solutions on AWS class. This will be used as supporting material that you can take with you. EMR Title Link Deep Dive and Best Practices https://www.youtube.com/watch?v=dU40df0Suoo

Welcome to the Planning and Designing Databases on AWS class. This will be used as supporting material above and beyond Redshift that you can take with you. RDS Title Link Performance Insights https://aws.amazon.com/de/blogs/database/set-alarms-on-performance-insights-metrics-using-amazon-cloudwatch/

Welcome to the Architecting on AWS class. This material will be used as supporting material that you can take with you. Cloud Adoption Framework (CAF) Title Link CAF Overview https://aws.amazon.com/professional-services/CAF/?nc1=h_ls

Welcome to the Developing on AWS class. This will be used as supporting material that you can take with you. AWS CDK https://www.youtube.com/watch?v=ZWCvNFUN-sU https://www.youtube.com/watch?v=1ps0Wh19MHQ https://cdkworkshop.com Code Guru https://www.youtube.com/watch?v=4DXZQ9ZOdVw

Welcome to The Machine Learning Pipeline class. This will be used as supporting material that you can take with you. Exam Readiness Workshop https://www.aws.training/Details/eLearning?id=42183 https://medium.com/@adam.dejans/my-path-to-passing-the-aws-machine-learning-certification-e8fc45ad7762 Machine Learning Title

Themenspeicher VIM Softwareverwaltung Pakete Repositories / git Patching Service-Architekturen mit Docker Compose abbilden Docker in Docker und DNS ElasticSearch offizielles Image