AirGap_zusammen_neu.pdf

Test Infra project walkthrough and project description. Areas for improvement.

The document outlines 5 steps to set up a container pipeline: 1. Use versioning and container registries like GitHub, Docker, and private registries to manage code versions and container images. 2. Use an orchestration engine like Kubernetes to manage and orchestrate container processes. Common options are AWS EKS, GCP GKE, and Oracle OKE. 3. Provision the Kubernetes cluster using scripts or Terraform on cloud infrastructure like OCI. 4. Implement container pipelines using tools like Oracle Container Pipelines to automate building, testing, and deploying containers. 5. Use Helm to package and deploy Kubernetes applications and integrate it into the CI/CD pipeline

This document discusses Dockerizing OpenStack high availability services. It begins by outlining existing challenges with OpenStack HA including complex configuration, scaling complexity, and lack of automation/visibility. It then discusses how Docker can help by allowing applications and dependencies to be packaged in lightweight containers, improving scaling, density, flexibility and reducing overhead. The document provides an example of running OpenStack services like Nova API in Docker containers for improved HA and manageability. It discusses sharing images in a private Docker registry and orchestrating container management.

This document discusses lightweight virtualization and Docker. It provides an overview of lightweight virtualization technology and how it isolates processes and limits resource usage. Docker is introduced as an open source project that provides a simple way to create and manage lightweight virtual machines called containers. Baidu's BAE platform chose to use Docker due to its ease of use and ability to avoid limitations of sandbox-based platforms while providing resource isolation and constraints. The document also discusses Docker developments, such as integration with Red Hat and solutions to issues regarding security and hardware support.

My cloud native security talk I gave at Innotech Austin 2018. I cover container and Kubernetes security topics, security features in Kubernetes, including opensource projects you will want to consider while building and maintaining cloud native applications.

3 years ago, Meetic chose to rebuild it's backend architecture using microservices and an event driven strategy. As we where moving along our old legacy application, testing features became gradually a pain, especially when those features rely on multiple changes across multiple components. Whatever the number of application you manage, unit testing is easy, as well as functional testing on a microservice. A good gherkin framework and a set of docker container can do the job. The real challenge is set in end-to-end testing even more when a feature can involve up to 60 different components. To solve that issue, Meetic is building a Kubernetes strategy around testing. To do such a thing we need to : - Be able to generate a docker container for each pull-request on any component of the stack - Be able to create a full testing environment in the simplest way - Be able to launch automated test on this newly created environment - Have a clean-up process to destroy testing environment after tests To separate the various testing environment, we chose to use Kubernetes Namespaces each containing a variant of the Meetic stack. But when it comes to Kubernetes, managing multiple namespaces can be hard. Yaml configuration files need to be shared in a way that each people / automated job can access to them and modify them without impacting others. This is typically why Meetic chose to develop it's own tool to manage namespace through a cli tool, or a REST API on which we can plug a friendly UI. In this talk we will tell you the story of our CI/CD evolution to satisfy the need to create a docker container for each new pull request. And we will show you how to make end-to-end testing easier using Blackbeard, the tool we developed to handle the need to manage namespaces inspired by Helm.

Docker EE 2.0 provides choice, security, and agility for container deployments. It offers more than just containers and orchestration, including lifecycle management, governance, and security features. Docker EE can deploy applications on Linux and Windows across on-premises and cloud infrastructure. It supports both Docker Swarm and Kubernetes orchestrators. Security features include image scanning, role-based access control, and audit logging to secure the software supply chain. Docker EE aims to provide a unified platform for both traditional and microservices applications.

An overview on docker and container technology behind it. Lastly, we discuss few tools that might come handy when dealing with large number of containers management.

They provide the workload isolation and security advantages of VMs. but at the same time maintain the speed of deployment and usability of containers.by using kata containers, instead of namespace, small virtual machines are created on the kernel and be strongly isolated. The technology of Kata Containers is based on KVM hypervisor. That’s why the level of isolation is equivalent to typical hypervisors. This session will focus on a live production phase when choosing kata instead of docker, and why they are preferable Although containers provides software-level isolation of resources, the kernel needs to be shared. That’s why the isolation level in terms of security is not so high when compared with hypervisors.This learns to shift from Docker as the de facto standard to Kata containers and learn how to obtain higherl level of security

Production Grade Edge Computing on Kubernetes Presentation at Open Source Summit Europe October 2018

The document discusses securing a Kubernetes cluster from multiple layers of risk. It covers securing the infrastructure layer by limiting access and exposure, the control plane layer by enabling TLS and RBAC, the workload layer using pod security policies and network policies, the container runtime layer with tools like Kata Containers, the user misconfiguration layer by avoiding defaults and validating configurations, and useful security tools. The presenter then provides contact information for potential job opportunities.

Container adoption is on the rise across companies of every size and industry. While containerization is a new and exciting paradigm, it brings with it some of the same technical and organizational issues that security teams have always faced. This presentation will dive into a selection of these familiar issues and suggested solutions to help security teams get a better handle on containers and keep up with the deployment pace that DevOps requires. Check out the Denver Chapter of OWASP! meetup.com/denver-owasp and our annual conference www.snowfroc.com

The document provides an overview of Kubernetes concepts including pods, deployments, services, ingress, volumes, and configmaps. It explains that pods are the smallest deployable units that can contain one or more containers running applications. Deployments help manage and scale replicated applications, while services expose pods to other pods or external clients. Ingress manages external access to services. Volumes provide shared storage within a pod. Configmaps and secrets allow injecting configuration and credentials into applications.

Lightweight virtualization uses container technology to isolate processes and their resources through namespaces and cgroups. Docker is a container management system that provides lightweight virtualization. Baidu chose Docker for its BAE platform because containers provide better isolation than sandboxes with fewer restrictions and lower costs. Docker meets BAE's needs but was improved with additional security and resource constraints for its PAAS platform.

This document provides an overview of Container as a Service (CaaS) with Docker. It discusses key concepts like Docker containers, images, and orchestration tools. It also covers DevOps practices like continuous delivery that are enabled by Docker. Specific topics covered include Docker networking, volumes, and orchestration with Docker Swarm and compose files. Examples are provided of building and deploying Java applications with Docker, including Spring Boot apps, Java EE apps, and using Docker for builds. Security features of Docker like content trust and scanning are summarized. The document concludes by discussing Docker use cases across different industries and how Docker enables critical transformations around cloud, DevOps, and application modernization.

This Slide Presented in May 2019 at the "Cluster and Grid Computing" course at the "Iran University Of Science at Technology" by me.

Docker allows building portable software that can run anywhere by packaging an application and its dependencies in a standardized unit called a container. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes can replicate containers, provide load balancing, coordinate updates between containers, and ensure availability. Defining applications as Kubernetes resources allows them to be deployed and updated easily across a cluster.

k6 is an open source load testing tool that was acquired by Grafana in 2021. It allows teams to test reliability before problems impact users by simulating user traffic to applications and services. The k6-operator allows running distributed k6 tests on Kubernetes and integrates k6 into developer workflows. It provides many options for configuring and scaling tests through JavaScript scripts.

This document discusses extending kubectl functionality through plugins. It introduces kubectl plugins and Krew, a plugin manager for kubectl. It covers developing and publishing plugins, including writing plugins in any language, creating a krew manifest, and automating plugin updates through GitHub actions.

This document discusses enhancing data protection workflows with Kanister and Argo Workflows. It begins with discussing the need for data protection of stateful workloads on Kubernetes and challenges with current approaches. It then provides an overview of Kanister, an open source tool for application-level data protection on Kubernetes. Kanister uses custom resources and functions to abstract away complex data protection workflows. It also works with Argo Workflows to scale parallel data operations. The document concludes with a demo of using Kanister's CSI functions to create and restore snapshots and scaling snapshots with Argo Workflows.

This document discusses 10 common fallacies in platform engineering. It begins by introducing the speaker and topic, which are 10 fallacies seen in platform engineering and how to mitigate them. Some of the fallacies discussed include prioritizing the wrong procedures, relying only on visualizations, trying to replace all tools at once, providing too much freedom without constraints, and trying to compete directly with large cloud providers. The goal of platform engineering is to standardize processes and reduce cognitive load on developers and operations teams.