#how to deploy docker image in openshift

[hawkstack]

🚀 Container Adoption Boot Camp for Developers: Fast-Track Your Journey into Containerization

In today’s DevOps-driven world, containerization is no longer a buzzword—it’s a fundamental skill for modern developers. Whether you're building microservices, deploying to Kubernetes, or simply looking to streamline your development workflow, containers are at the heart of it all.

That’s why we created the Container Adoption Boot Camp for Developers—a focused, hands-on training program designed to take you from container curious to container confident.

🧠 Why Containers Matter for Developers

Containers bring consistency, speed, and scalability to your development and deployment process. Imagine a world where:

Your app works exactly the same on your machine as it does in staging or production.

You can spin up dev environments in seconds.

You can ship features faster with fewer bugs.

That’s the power of containerization—and our boot camp helps you unlock it.

🎯 What You’ll Learn

Our boot camp is developer-first and practical by design. Here’s a taste of what we cover:

✅ Container Fundamentals

What are containers? Why do they matter?

Images vs containers vs registries

Comparison: Docker vs Podman

✅ Building Your First Container

Creating and optimizing Dockerfiles

Managing multi-stage builds

Environment variables and configuration strategies

✅ Running Containers in Development

Volume mounting, debugging, hot-reloading

Using Compose for multi-container applications

✅ Secure & Efficient Images

Best practices for lightweight and secure containers

Image scanning and vulnerability detection

✅ From Dev to Prod

Building container workflows into your CI/CD pipeline

Tagging strategies, automated builds, and registries

✅ Intro to Kubernetes & OpenShift

How your containers scale in production

Developer experience on OpenShift with odo, kubectl, and oc

🔧 Hands-On, Lab-Focused Learning

This isn’t just theory. Every module includes real-world labs using tools like:

Podman/Docker

Buildah & Skopeo

GitHub Actions / GitLab CI

OpenShift Developer Sandbox (or your preferred cloud)

You’ll walk away with reusable templates, code samples, and a fully containerized project of your own.

👨‍💻 Who Should Join?

This boot camp is ideal for:

Developers looking to adopt DevOps practices

Backend engineers exploring microservices

Full-stack developers deploying to cloud platforms

Anyone working in a container-based environment (Kubernetes, OpenShift, EKS, GKE, etc.)

Whether you're new to containers or looking to refine your skills, we’ve got you covered.

🏁 Get Started with HawkStack

At HawkStack Technologies, we bridge the gap between training and real-world implementation. Our Container Adoption Boot Camp is crafted by certified professionals with deep industry experience, ensuring you don’t just learn—you apply.

📅 Next cohort starts soon 📍 Live online + lab access 💬 Mentorship + post-training support

👉 Contact us to reserve your spot or schedule a custom boot camp for your team - www.hawkstack.com

Ready to take the leap into containerization? Let’s build something great—one container at a time. 🧱💻🚢

[ellcrys]

ok I just want to take a moment to rant bc the bug fix I’d been chasing down since monday that I finally just resolved was resolved with. get this. A VERSION UPDATE. A LIBRARY VERSION UPDATE. *muffled screaming into the endless void*

so what was happening. was that the jblas library I was using for handling complex matrices in my java program was throwing a fucking hissy fit when I deployed it via openshift in a dockerized container. In some ways, I understand why it would throw a fit because docker containers only come with the barest minimum of software installed and you mostly have to do all the installing of what your program needs by yourself. so ok. no biggie. my program runs locally but doesn’t run in docker: this makes sense. the docker container is probably just missing the libgfortran3 library that was likely preinstalled on my local machine. which means I’ll just update the dockerfile (which tells docker how to build the docker image/container) with instructions on how to install libgfortran3. problem solved. right? WRONG.

lo and behold, the bane of my existence for the past 3 days. this was the error that made me realize I needed to manually install libgfortran3, so I was pretty confident installing the missing library would fix my issue. WELL. turns out. it in fact didn’t. so now I’m chasing down why.

some forums suggested specifying the tmp directory as a jvm option or making sure the libgfortran library is on the LD_LIBRARY_PATH but basically nothing I tried was working so now I’m sitting here thinking: it probably really is just the libgfortran version. I think I legitimately need version 3 and not versions 4 or 5. because that’s what 90% of the solutions I was seeing was suggesting.

BUT! fuck me I guess because the docker image OS is RHEL which means I have to use the yum repo to install software (I mean I guess I could have installed it with the legit no kidding .rpm package but that’s a whole nother saga I didn’t want to have to go down), and the yum repo had already expired libgfortran version 3. :/ It only had versions 4 and 5, and I was like, well that doesn’t help me!

anyways so now I’m talking with IT trying to get their help to find a version of libgfortran3 I can install when. I FIND THIS ELUSIVE LINK. and at the very very bottom is THIS LINK.

Turns out. 1.2.4 is in fact not the latest version of jblas according to the github project page (on the jblas website it claims that 1.2.4 is the current verison ugh). And according to the issue opened at the link above, version 1.2.5 should fix the libgfortran3 issue.

and I think it did?! because when I updated the library version in my project and redeployed it, the app was able to run without crashing on the libgfortran3 error.

sometimes the bug fix is as easy as updating a fucking version number. but it takes you 3 days to realize that’s the fix. or at least a fix. I was mentally preparing myself to go down the .rpm route but boy am I glad I don’t have to now.

anyways tl;dr: WEBSITES ARE STUPID AND LIKELY OUTDATED AND YOU SHOULD ALWAYS CHECK THE SOURCE CODE PAGE FOR THE LATEST MOST UP TO DATE INFORMATION.

[codecraftshop]

Deploy application in openshift using container images

Deploy application in openshift using container images

#openshift #containerimages #openshift # openshift4 #containerization

Deploy container app using OpenShift Container Platform running on-premises,openshift deploy docker image cli,openshift deploy docker image command line,how to deploy docker image in openshift,how to deploy image in openshift,deploy image in openshift,deploy…

[computingpostcom]

How can I create a single Ubuntu Pod in a Kubernetes or OpenShift cluster?. In Kubernetes a Pod is a group of one or more containers, with shared storage/network resources, and a specification for how to run the containers. When a Pod running a single container you can think of a it as a wrapper around a single container. Kubernetes manages Pods rather than managing the containers directly. In this tutorial we will look at how you can deploy an Ubuntu Pod in Kubernetes or OpenShift cluster. This can be for Debug purposes or just testing network connectivity to other Pods and Services in the namespace. Since Pods are designed as relatively ephemeral and disposable entities you should never run Production container workloads by creating Pods directly.  Instead, create them using workload resources such as Deployment. We will create a sleep container from Ubuntu docker image using latest tag. Below is the Pod creation YAML contents. $ vim ubuntu-pod.yaml apiVersion: v1 kind: Pod metadata: name: ubuntu labels: app: ubuntu spec: containers: - name: ubuntu image: ubuntu:latest command: ["/bin/sleep", "3650d"] imagePullPolicy: IfNotPresent restartPolicy: Always Then apply the file created using kubectl command: kubectl apply -f ubuntu-pod.yaml You can run below kubectl commands to deploy the Pod in the current namespace: cat

[swarnalata31techiio]

A brief overview of Jenkins X

What is Jenkins X?

Jenkins X is an open-source solution that provides automatic seamless integration and continuous distribution (CI / CD) and automated testing tools for cloud-native applications in Cubernet. It supports all major cloud platforms such as AWS, Google Cloud, IBM Cloud, Microsoft Azure, Red Hat OpenShift, and Pivotal. Jenkins X is a Jenkins sub-project (more on this later) and employs automation, DevOps best practices and tooling to accelerate development and improve overall CI / CD.  

Features of Jenkins X

Automated CI /CD:

Jenkins X offers a sleek jx command-line tool, which allows Jenkins X to be installed inside an existing or new Kubernetes cluster, import projects, and bootstrap new applications. Additionally, Jenkins X creates pipelines for the project automatically.

Environment Promotion via GitOps:

Jenkins X allows for the creation of different virtual environments for development, staging, and production, etc. using the Kubernetes Namespaces. Every environment gets its specific configuration, list of versioned applications and configurations stored in the Git repository. You can automatically promote new versions of applications between these environments if you follow GitOps practices. Moreover, you can also promote code from one environment to another manually and change or configure new environments as needed.

Extensions:

It is quite possible to create extensions to Jenkins X. An extension is nothing but a code that runs at specific times in the CI/CD process. You can also provide code through an extension that runs when the extension is installed, uninstalled, as well as before and after each pipeline.

Serverless Jenkins:

Instead of running the Jenkins web application, which continually consumes a lot of CPU and memory resources, you can run Jenkins only when you need it. During the past year, the Jenkins community has created a version of Jenkins that can run classic Jenkins pipelines via the command line with the configuration defined by code instead of the usual HTML forms.

Preview Environments:

Though the preview environment can be created manually, Jenkins X automatically creates Preview Environments for each pull request. This provides a chance to see the effect of changes before merging them. Also, Jenkins X adds a comment to the Pull Request with a link for the preview for team members.

How Jenkins X works?

The developer commits and pushes the change to the project’s Git repository.

JX is notified and runs the project’s pipeline in a Docker image. This includes the project’s language and supporting frameworks.

The project pipeline builds, tests, and pushes the project’s Helm chart to Chart Museum and its Docker image to the registry.

The project pipeline creates a PR with changes needed to add the project to the staging environment.

Jenkins X automatically merges the PR to Master.

Jenkins X is notified and runs the staging pipeline.

The staging pipeline runs Helm, which deploys the environment, pulling Helm charts from Chart Museum and Docker images from the Docker registry. Kubernetes creates the project’s resources, typically a pod, service, and ingress.

[bestwallartdesign]

What Are The Best Devops Tools That Should Be Used In 2022?

Actually, that's a marketing stunt let me rephrase that by saying what are the best tools for developers and operators and everything in between in 2022 and you can call it devops  I split them into different categories so let me read the list and that's ids terminals shell packaging Kubernetes distribution serverless Github progressive delivery infrastructures code programming language cloud logging monitoring deployment security dashboards pipelines and workflows service mesh and backups I will not go into much details about each of those tools that would take hours but I will provide the links to videos or descriptions or useful information about each of the tools in this blog. If you want to see a  link to the home page of the tool or some useful information let's get going.

Let's start with ids the tool you should be using the absolute winner in all aspects is visual studio code it is open source it is free it has a massive community massive amount of plugins there is nothing you cannot do with visual studio code so ids clear winner visual studio code that's what you should be using next are terminals, unlike many others that recommend an item or this or different terminals I recommend you use a terminal that is baked into visual studio code it's absolutely awesome you cannot go wrong and you have everything in one place you write your code you write your manifest you do whatever you're doing and you have a terminal baked in using the terminal in visual studio code there is no need to use an external terminal shell the best shell you can use you will feel at home and it features some really great things.

Experience if you're using windows then install wsl or windows subsystem for Linux and then install ssh and of my ssh next packaging how do we package applications today that's containers containers containers actually we do not packages containers we package container images that are a standard now it doesn't matter whether you're deploying to Kubernetes whether you're deploying directly to docker whether you're using serverless even most serverless today solutions allow you to run containers that means that you must and pay attention that didn't say should you must package your applications as container images with few exceptions if you're creating clips or desktop applications then package it whatever is the native for that operating system that's the only exception everything else container images doesn't matter where you're deploying it and how should you build those container images you should be building it with docker desktop docker.

if you're building locally and you shouldn't be building locally if you're building through some cicd pipelines so whichever other means that it's outside of your laptop use kubernetes is the best solution to build container images today next in line kubernetes distribution or service or platform which one should you use and that depends where you're running your stuff if it's in cloud use whatever your provider is offering you're most likely not going to change the provider because of kubernetes service but if you're indifferent and you can choose any provider to run your kubernetes clusters then gke google kubernetes engine is the best choice it is ahead of everybody else that difference is probably not sufficient for you to change your provider but if you're undecided where to run it then google cloud is the place but if you're using on-prem servers then probably the best solution is launcher unless you have very strict and complicated security requirements then you should go with upper shift if you want operational simplicity and simplicity in any form or way then go with launcher if you have tight security needs then openshift is the thing finally if you want to run kubernetes cluster locally then it's k3d k3d is the best way to run kubernetes cluster locally you can run a single cluster multi-cluster single node multi-node and it's lightning fast it takes couple of seconds to create a cluster and it uses minimal amount of resources it's awesome try it out serverless and that really depends what type of serverless you want if you want functions as a service aws lambda is the way to go they were probably the first ones to start at least among big providers and they are leading that area but only for functions as a service.

If you wanted containers as a service type of serverless and i think you should want containers as a service anyways if you want containers as a service flavor of serverless then google cloud run is the best option in the market today finally if you would like to run serverless on-prem then k native which is actually the engine behind the google cloud run anyways k native is the way to go if you want to run serverless workloads in your own clusters on-prem githubs and here i do not have a clear recommendation because both argo cd and flux are awesome they have some differences there are some weaknesses pros and cons for each and they cannot make up my mind both of them are awesome and it's like arms race you know cold war as soon as one gets a cool feature the other one gets it as well and then the circle continues both of them are more or less equally good you cannot go wrong with either progressive delivery is in a similar situation you can use algorithms or flagger you're probably going to choose one or the other depending on which github solution you chose because argo rollouts works very well with dargo cd flagger works exceptionally well with the flux and you cannot go wrong with either you're most likely going to choose the one that belongs to the same family as the github's tool that you choose previously infrastructure is code has two winners in this case one is terraform terraform is the leader of the market it has the biggest community it is stable it exists for a long time and everybody is using it you cannot go wrong with terraform but if you want to get a glimpse of the future of potential future we don't know the future but potential future with additional features especially if you want something that is closer to kubernetes that is closer to the ecosystem of kubernetes then you should go with crossplane.

In my case i'm combining both i'm still having most of my workloads in terraform and then transitioning slowly to cross plane when that makes sense for programming languages it depends really what you're doing if you're working on a front end and i it's javascript there is nothing else in the world everything is javascript don't even bother looking for something else for everything else go is the way to go that that rhymes right go is the way to go excellent go is the language that everybody is using today i mean not everybody minority of us are using go but it is increasing in polarity greatly especially if you're working on microservices or smaller applications footprint of go is very small it is lightning fast just try it out if you haven't already if for no other reason you should put go on your curriculum because it's all the hype and for a very good reason it has its problems every language has its problems but you should use it even if that's only for hobby projects next inline cloud which provider should be using i cannot answer the question aws is great azure is great google cloud is great if you want to save money at the expense of the catalog of the offers and the stability and whatsoever then go with linux or digitalocean personally when i can choose and i have to choose then i go with google cloud as for logging solutions if you're in cloud go with whatever your cloud provider is giving you as long as that is not too expensive for your budget.

If you have to choose something else something outside of the offering of your cloud use logs is awesome it's very similar to prometus it works well it has low memory and cpu footprint if you're choosing your own solution instead of going with whatever provider is giving you lockheed is the way to go for monitoring it's prometheus you have to have promote use even if you choose something else you will have to have prometheus on top of that something else for a simple reason that many of the tools frameworks applications what's or not are assuming that you're using promit use from it you see is the de facto standard and you will use it even if you already decided to use something else because it is unavoidable and it's awesome at the same time for deployment mechanisms packaging templating i have two i cannot make up my mind i use customize and i use helm and you should probably combine both because they have different strengths and weaknesses if you're an operator and you're not tasked to empower developers then customize is a better choice no doubt now if you want to simplify lives of developers who are not very proficient with kubernetes then helm is the easiest option for them it will not be easiest for you but for them yes next in line is security for scanning you sneak sneak is a clear winner at least today for governance legal requirements compliance and similar subjects i recommend opa gatekeeper it is the best choice we have today even though that market is bound to explode and we will see many new solutions coming very very soon next in line are dashboards and this was the easiest one for me to pick k9s use k9s especially if you like terminals it's absolutely awesome try it out k9s is the best dashboard at least when kubernetes is concerned for pipelines and workflows it really depends on how much work you want to invest in it yourself if you want to roll up your sleeves and set it up yourself it's either argo workflows combined with argo events or tecton combined with a few other things they are hand-in-hand there are pros and cons for each but right now there is no clear winner so it's either argo workflows combined with events or tactile with few other additional tools among the tools that require you to set them up properly there is no competition those are the two choices you have now.

If you want not to think much about pipelines but just go with the minimal effort everything integrated what's or not then i recommend code rush now i need to put a disclaimer here i worked in code fresh until a week ago and you might easily see that i'm too subjective and that might be true i try not to be but you never know serious mesh service mesh is in a similar situation like infrastructure is code most of the implementations are with these two today easter is the de facto standard but i believe that we are moving towards slinkerty being the dominant player for a couple of reasons the main one being that it is independently managed it is in the cncf foundation and nobody really owns it on top of that linker d is more lightweight it is easier to learn it doesn't have all the features of youtube but you likely do not need the features that are missing anyway finally linkedin is based on smi or service mesh interface and that means that you will be able to switch from linker d to something else if you choose to do so in the future easter has its own interface it is incompatible with anything else finally the last category i have is backups and if you're using kubernetes and everybody is using kubernetes today right use valero it is the best option we have today to create backups it works amazingly well as long as you're using kubernetes.

If you're not using Kubernetes then just zip it up and put it on a tape as we were doing a long long time ago that was the list of the recommendation of the tools platforms frameworks whatsoever that you should be using in 2022 i will make a similar blog in the future and i expect you to tell me a couple of things which categories did i miss what would you like me to include in the next blog of this kind what are the points you do not agree with me let's discuss it i might be wrong most of the time I'm wrong so please let me know if you disagree about any of the tools or categories that i mentioned we are done, Cloud now technologies ranked as top three devops services company in usa.Cloud now technologies devops service delivery at high velocity with cost savings through accelerated software deployment.

[dmroyankita]

What is Kubernetes?

Kubernetes (also known as k8s or “kube”) is an open source container orchestration platform that automates many of the manual processes involved in deploying, managing, and scaling containerized applications.

 In other words, you can cluster together groups of hosts running Linux containers, and Kubernetes helps you easily and efficiently manage those clusters.

 Kubernetes clusters can span hosts across on-premise, public, private, or hybrid clouds. For this reason, Kubernetes is an ideal platform for hosting cloud-native applications that require rapid scaling, like real-time data streaming through Apache Kafka.

 Kubernetes was originally developed and designed by engineers at Google. Google was one of the early contributors to Linux container technology and has talked publicly about how everything at Google runs in containers. (This is the technology behind Google’s cloud services.)

 Google generates more than 2 billion container deployments a week, all powered by its internal platform, Borg. Borg was the predecessor to Kubernetes, and the lessons learned from developing Borg over the years became the primary influence behind much of Kubernetes technology.

 Fun fact: The 7 spokes in the Kubernetes logo refer to the project’s original name, “Project Seven of Nine.”

 Red Hat was one of the first companies to work with Google on Kubernetes, even prior to launch, and has become the 2nd leading contributor to the Kubernetes upstream project. Google donated the Kubernetes project to the newly formed Cloud Native Computing Foundation (CNCF) in 2015.

 Get an introduction to enterprise Kubernetes

What can you do with Kubernetes?

 The primary advantage of using Kubernetes in your environment, especially if you are optimizing app dev for the cloud, is that it gives you the platform to schedule and run containers on clusters of physical or virtual machines (VMs).

 More broadly, it helps you fully implement and rely on a container-based infrastructure in production environments. And because Kubernetes is all about automation of operational tasks, you can do many of the same things other application platforms or management systems let you do—but for your containers.

 Developers can also create cloud-native apps with Kubernetes as a runtime platform by using Kubernetes patterns. Patterns are the tools a Kubernetes developer needs to build container-based applications and services.

 With Kubernetes you can:

 Orchestrate containers across multiple hosts.

Make better use of hardware to maximize resources needed to run your enterprise apps.

Control and automate application deployments and updates.

Mount and add storage to run stateful apps.

Scale containerized applications and their resources on the fly.

Declaratively manage services, which guarantees the deployed applications are always running the way you intended them to run.

Health-check and self-heal your apps with autoplacement, autorestart, autoreplication, and autoscaling.

However, Kubernetes relies on other projects to fully provide these orchestrated services. With the addition of other open source projects, you can fully realize the power of Kubernetes. These necessary pieces include (among others):

 Registry, through projects like Atomic Registry or Docker Registry

Networking, through projects like OpenvSwitch and intelligent edge routing

Telemetry, through projects such as Kibana, Hawkular, and Elastic

Security, through projects like LDAP, SELinux, RBAC, and OAUTH with multitenancy layers

Automation, with the addition of Ansible playbooks for installation and cluster life cycle management

Services, through a rich catalog of popular app patterns

Get an introduction to Linux containers and container orchestration technology. In this on-demand course, you’ll learn about containerizing applications and services, testing them using Docker, and deploying them on a Kubernetes cluster using Red Hat® OpenShift®.

 Start the free training course

Learn to speak Kubernetes

As is the case with most technologies, language specific to Kubernetes can act as a barrier to entry. Let's break down some of the more common terms to help you better understand Kubernetes.

 Master: The machine that controls Kubernetes nodes. This is where all task assignments originate.

 Node: These machines perform the requested, assigned tasks. The Kubernetes master controls them.

 Pod: A group of one or more containers deployed to a single node. All containers in a pod share an IP address, IPC, hostname, and other resources. Pods abstract network and storage from the underlying container. This lets you move containers around the cluster more easily.

 Replication controller: This controls how many identical copies of a pod should be running somewhere on the cluster.

 Service: This decouples work definitions from the pods. Kubernetes service proxies automatically get service requests to the right pod—no matter where it moves in the cluster or even if it’s been replaced.

 Kubelet: This service runs on nodes, reads the container manifests, and ensures the defined containers are started and running.

 kubectl: The command line configuration tool for Kubernetes.

 How does Kubernetes work?

Kubernetes diagram

A working Kubernetes deployment is called a cluster. You can visualize a Kubernetes cluster as two parts: the control plane, which consists of the master node or nodes, and the compute machines, or worker nodes.

 Worker nodes run pods, which are made up of containers. Each node is its own Linux® environment, and could be either a physical or virtual machine.

 The master node is responsible for maintaining the desired state of the cluster, such as which applications are running and which container images they use. Worker nodes actually run the applications and workloads.

 Kubernetes runs on top of an operating system (Red Hat® Enterprise Linux®, for example) and interacts with pods of containers running on the nodes.

 The Kubernetes master node takes the commands from an administrator (or DevOps team) and relays those instructions to the subservient nodes.

 This handoff works with a multitude of services to automatically decide which node is best suited for the task. It then allocates resources and assigns the pods in that node to fulfill the requested work.

 The desired state of a Kubernetes cluster defines which applications or other workloads should be running, along with which images they use, which resources should be made available to them, and other such configuration details.

 From an infrastructure point of view, there is little change to how you manage containers. Your control over containers just happens at a higher level, giving you better control without the need to micromanage each separate container or node.

 Some work is necessary, but it’s mostly a matter of assigning a Kubernetes master, defining nodes, and defining pods.

 Where you run Kubernetes is up to you. This can be on bare metal servers, virtual machines, public cloud providers, private clouds, and hybrid cloud environments. One of Kubernetes’ key advantages is it works on many different kinds of infrastructure.

 Learn about the other components of a Kubernetes architecture

What about Docker?

Docker can be used as a container runtime that Kubernetes orchestrates. When Kubernetes schedules a pod to a node, the kubelet on that node will instruct Docker to launch the specified containers.

 The kubelet then continuously collects the status of those containers from Docker and aggregates that information in the master. Docker pulls containers onto that node and starts and stops those containers.

 The difference when using Kubernetes with Docker is that an automated system asks Docker to do those things instead of the admin doing so manually on all nodes for all containers.

 Why do you need Kubernetes?

Kubernetes can help you deliver and manage containerized, legacy, and cloud-native apps, as well as those being refactored into microservices.

 In order to meet changing business needs, your development team needs to be able to rapidly build new applications and services. Cloud-native development starts with microservices in containers, which enables faster development and makes it easier to transform and optimize existing applications.

 Production apps span multiple containers, and those containers must be deployed across multiple server hosts. Kubernetes gives you the orchestration and management capabilities required to deploy containers, at scale, for these workloads.

 Kubernetes orchestration allows you to build application services that span multiple containers, schedule those containers across a cluster, scale those containers, and manage the health of those containers over time. With Kubernetes you can take effective steps toward better IT security.

 Kubernetes also needs to integrate with networking, storage, security, telemetry, and other services to provide a comprehensive container infrastructure.

 Kubernetes explained - diagram

Once you scale this to a production environment and multiple applications, it's clear that you need multiple, colocated containers working together to deliver the individual services.

 Linux containers give your microservice-based apps an ideal application deployment unit and self-contained execution environment. And microservices in containers make it easier to orchestrate services, including storage, networking, and security.

 This significantly multiplies the number of containers in your environment, and as those containers accumulate, the complexity also grows.

 Kubernetes fixes a lot of common problems with container proliferation by sorting containers together into ”pods.” Pods add a layer of abstraction to grouped containers, which helps you schedule workloads and provide necessary services—like networking and storage—to those containers.

 Other parts of Kubernetes help you balance loads across these pods and ensure you have the right number of containers running to support your workloads.

 With the right implementation of Kubernetes—and with the help of other open source projects like Atomic Registry, Open vSwitch, heapster, OAuth, and SELinux— you can orchestrate all parts of your container infrastructure.

 Use case: Building a cloud platform to offer innovative banking services

Emirates NBD, one of the largest banks in the United Arab Emirates (UAE), needed a scalable, resilient foundation for digital innovation. The bank struggled with slow provisioning and a complex IT environment. Setting up a server could take 2 months, while making changes to large, monolithic applications took more than 6 months.

 Using Red Hat OpenShift Container Platform for container orchestration, integration, and management, the bank created Sahab, the first private cloud run at scale by a bank in the Middle East. Sahab provides applications, systems, and other resources for end-to-end development—from provisioning to production—through an as-a-Service model.

 With its new platform, Emirates NBD improved collaboration between internal teams and with partners using application programming interfaces (APIs) and microservices. And by adopting agile and DevOps development practices, the bank reduced app launch and update cycles.

 Read the full case study

Support a DevOps approach with Kubernetes

Developing modern applications requires different processes than the approaches of the past. DevOps speeds up how an idea goes from development to deployment.

 At its core, DevOps relies on automating routine operational tasks and standardizing environments across an app’s lifecycle. Containers support a unified environment for development, delivery, and automation, and make it easier to move apps between development, testing, and production environments.

 A major outcome of implementing DevOps is a continuous integration and continuous deployment pipeline (CI/CD). CI/CD helps you deliver apps to customers frequently and validate software quality with minimal human intervention.

 Managing the lifecycle of containers with Kubernetes alongside a DevOps approach helps to align software development and IT operations to support a CI/CD pipeline.

 With the right platforms, both inside and outside the container, you can best take advantage of the culture and process changes you’ve implemented.

 Learn more about how to implement a DevOps approach

Using Kubernetes in production

Kubernetes is open source and as such, there’s not a formalized support structure around that technology—at least not one you’d trust your business to run on.[Source]-https://www.redhat.com/en/topics/containers/what-is-kubernetes

Basic & Advanced Kubernetes Certification using cloud computing, AWS, Docker etc. in Mumbai. Advanced Containers Domain is used for 25 hours Kubernetes Training.

[faizrashis1995]

What is Kubernetes?

The primary advantage of using Kubernetes in your environment, especially if you are optimizing app dev for the cloud, is that it gives you the platform to schedule and run containers on clusters of physical or virtual machines (VMs).

 More broadly, it helps you fully implement and rely on a container-based infrastructure in production environments. And because Kubernetes is all about automation of operational tasks, you can do many of the same things other application platforms or management systems let you do—but for your containers.

 Developers can also create cloud-native apps with Kubernetes as a runtime platform by using Kubernetes patterns. Patterns are the tools a Kubernetes developer needs to build container-based applications and services.

 With Kubernetes you can:

 Orchestrate containers across multiple hosts.

Make better use of hardware to maximize resources needed to run your enterprise apps.

Control and automate application deployments and updates.

Mount and add storage to run stateful apps.

Scale containerized applications and their resources on the fly.

Declaratively manage services, which guarantees the deployed applications are always running the way you intended them to run.

Health-check and self-heal your apps with autoplacement, autorestart, autoreplication, and autoscaling.

However, Kubernetes relies on other projects to fully provide these orchestrated services. With the addition of other open source projects, you can fully realize the power of Kubernetes. These necessary pieces include (among others):

 Registry, through projects like Atomic Registry or Docker Registry

Networking, through projects like OpenvSwitch and intelligent edge routing

Telemetry, through projects such as Kibana, Hawkular, and Elastic

Security, through projects like LDAP, SELinux, RBAC, and OAUTH with multitenancy layers

Automation, with the addition of Ansible playbooks for installation and cluster life cycle management

Services, through a rich catalog of popular app patterns

Get an introduction to Linux containers and container orchestration technology. In this on-demand course, you’ll learn about containerizing applications and services, testing them using Docker, and deploying them on a Kubernetes cluster using Red Hat® OpenShift®.

 Start the free training course

Learn to speak Kubernetes

As is the case with most technologies, language specific to Kubernetes can act as a barrier to entry. Let's break down some of the more common terms to help you better understand Kubernetes.

 Master: The machine that controls Kubernetes nodes. This is where all task assignments originate.

 Node: These machines perform the requested, assigned tasks. The Kubernetes master controls them.

 Pod: A group of one or more containers deployed to a single node. All containers in a pod share an IP address, IPC, hostname, and other resources. Pods abstract network and storage from the underlying container. This lets you move containers around the cluster more easily.

 Replication controller: This controls how many identical copies of a pod should be running somewhere on the cluster.

 Service: This decouples work definitions from the pods. Kubernetes service proxies automatically get service requests to the right pod—no matter where it moves in the cluster or even if it’s been replaced.

 Kubelet: This service runs on nodes, reads the container manifests, and ensures the defined containers are started and running.

 kubectl: The command line configuration tool for Kubernetes.

 How does Kubernetes work?

Kubernetes diagram

A working Kubernetes deployment is called a cluster. You can visualize a Kubernetes cluster as two parts: the control plane, which consists of the master node or nodes, and the compute machines, or worker nodes.

 Worker nodes run pods, which are made up of containers. Each node is its own Linux® environment, and could be either a physical or virtual machine.

 The master node is responsible for maintaining the desired state of the cluster, such as which applications are running and which container images they use. Worker nodes actually run the applications and workloads.

 Kubernetes runs on top of an operating system (Red Hat® Enterprise Linux®, for example) and interacts with pods of containers running on the nodes.

 The Kubernetes master node takes the commands from an administrator (or DevOps team) and relays those instructions to the subservient nodes.

 This handoff works with a multitude of services to automatically decide which node is best suited for the task. It then allocates resources and assigns the pods in that node to fulfill the requested work.

 The desired state of a Kubernetes cluster defines which applications or other workloads should be running, along with which images they use, which resources should be made available to them, and other such configuration details.

 From an infrastructure point of view, there is little change to how you manage containers. Your control over containers just happens at a higher level, giving you better control without the need to micromanage each separate container or node.

 Some work is necessary, but it’s mostly a matter of assigning a Kubernetes master, defining nodes, and defining pods.

 Where you run Kubernetes is up to you. This can be on bare metal servers, virtual machines, public cloud providers, private clouds, and hybrid cloud environments. One of Kubernetes’ key advantages is it works on many different kinds of infrastructure.

 Learn about the other components of a Kubernetes architecture

What about Docker?

Docker can be used as a container runtime that Kubernetes orchestrates. When Kubernetes schedules a pod to a node, the kubelet on that node will instruct Docker to launch the specified containers.

 The kubelet then continuously collects the status of those containers from Docker and aggregates that information in the master. Docker pulls containers onto that node and starts and stops those containers.

 The difference when using Kubernetes with Docker is that an automated system asks Docker to do those things instead of the admin doing so manually on all nodes for all containers.

 Why do you need Kubernetes?

Kubernetes can help you deliver and manage containerized, legacy, and cloud-native apps, as well as those being refactored into microservices.

 In order to meet changing business needs, your development team needs to be able to rapidly build new applications and services. Cloud-native development starts with microservices in containers, which enables faster development and makes it easier to transform and optimize existing applications.

 Production apps span multiple containers, and those containers must be deployed across multiple server hosts. Kubernetes gives you the orchestration and management capabilities required to deploy containers, at scale, for these workloads.

 Kubernetes orchestration allows you to build application services that span multiple containers, schedule those containers across a cluster, scale those containers, and manage the health of those containers over time. With Kubernetes you can take effective steps toward better IT security.

 Kubernetes also needs to integrate with networking, storage, security, telemetry, and other services to provide a comprehensive container infrastructure.

 Kubernetes explained - diagram

Once you scale this to a production environment and multiple applications, it's clear that you need multiple, colocated containers working together to deliver the individual services.

 Linux containers give your microservice-based apps an ideal application deployment unit and self-contained execution environment. And microservices in containers make it easier to orchestrate services, including storage, networking, and security.

 This significantly multiplies the number of containers in your environment, and as those containers accumulate, the complexity also grows.

 Kubernetes fixes a lot of common problems with container proliferation by sorting containers together into ”pods.” Pods add a layer of abstraction to grouped containers, which helps you schedule workloads and provide necessary services—like networking and storage—to those containers.

 Other parts of Kubernetes help you balance loads across these pods and ensure you have the right number of containers running to support your workloads.

 With the right implementation of Kubernetes—and with the help of other open source projects like Atomic Registry, Open vSwitch, heapster, OAuth, and SELinux— you can orchestrate all parts of your container infrastructure.

 Use case: Building a cloud platform to offer innovative banking services

Emirates NBD, one of the largest banks in the United Arab Emirates (UAE), needed a scalable, resilient foundation for digital innovation. The bank struggled with slow provisioning and a complex IT environment. Setting up a server could take 2 months, while making changes to large, monolithic applications took more than 6 months.

 Using Red Hat OpenShift Container Platform for container orchestration, integration, and management, the bank created Sahab, the first private cloud run at scale by a bank in the Middle East. Sahab provides applications, systems, and other resources for end-to-end development—from provisioning to production—through an as-a-Service model.

 With its new platform, Emirates NBD improved collaboration between internal teams and with partners using application programming interfaces (APIs) and microservices. And by adopting agile and DevOps development practices, the bank reduced app launch and update cycles.

 Read the full case study

Support a DevOps approach with Kubernetes

Developing modern applications requires different processes than the approaches of the past. DevOps speeds up how an idea goes from development to deployment.

 At its core, DevOps relies on automating routine operational tasks and standardizing environments across an app’s lifecycle. Containers support a unified environment for development, delivery, and automation, and make it easier to move apps between development, testing, and production environments.

 A major outcome of implementing DevOps is a continuous integration and continuous deployment pipeline (CI/CD). CI/CD helps you deliver apps to customers frequently and validate software quality with minimal human intervention.

 Managing the lifecycle of containers with Kubernetes alongside a DevOps approach helps to align software development and IT operations to support a CI/CD pipeline.

 With the right platforms, both inside and outside the container, you can best take advantage of the culture and process changes you’ve implemented.[Source]-https://www.redhat.com/en/topics/containers/what-is-kubernetes

 Basic & Advanced Kubernetes Certification using cloud computing, AWS, Docker etc. in Mumbai. Advanced Containers Domain is used for 25 hours Kubernetes Training.

[isearchgoood]

December 02, 2019 at 10:00PM - AWS Solutions Architect Certification Bundle (97% discount) Ashraf

AWS Solutions Architect Certification Bundle (97% discount) Hurry Offer Only Last For HoursSometime. Don't ever forget to share this post on Your Social media to be the first to tell your firends. This is not a fake stuff its real.

With cloud computing, applications need to move around efficiently and run almost anywhere. In this course, you’ll learn how to create containerized applications with Docker that are lightweight and portable. You’ll get a comprehensive understanding of the subject and learn how to develop your own Docker containers.

Access 13 lectures & 4 hours of content 24/7

Install Docker on standard Linux or specialized container operating systems

Set up a private Docker Registry or use OpenShift Registry

Create, run, & investigate Docker images and containers

Pull & push containers between local systems and Docker registries

Integrate Docker containers w/ host networking and storage

Orchestrate multiple containers into complex applications with Kubernetes

Build a Docker container to simplify application deployment

Launch a containerized application in OpenShift

In this training, you’ll be introduced to some of the motivations behind microservices and how to properly containerize web applications using Docker. You’ll also get a quick overview of how Docker registries can help to store artifacts from your built images. Ultimately, by course’s end, you’ll have a strong understanding of modern containerized applications and microservices and how systems like Docker and Kubernetes can benefit them.

Access 9 lectures & 2 hours of content 24/7

Begin designing your web apps as microservices

Use Docker to containerize your microservices

Leverage modern Docker orchestration tools to aid in both developing & deploying your applications

Use Google’s container orchestration platform Kubernetes

Interpret the modern DevOps & container orchestration landscape

This course first covers the basics and rapid deployment capabilities of AWS to build a knowledge foundation for individuals who are brand new to cloud computing and AWS. You will explore the methods that AWS uses to secure its cloud services. You will learn how you, as an AWS customer, can have the most secure cloud solution possible for a wide variety of implementation scenarios. This course delves into the flexibility and agility needed to implement the most applicable security controls for your business functions in the AWS environment by deploying varying degrees of restrictive access to environments based on data sensitivity.

Access 10 lectures & 6.5 hours of content 24/7

Apply security concepts, models, & services in an AWS environment

Manage user account credentials & deploy AWS Identity and Access Management (IAM) to manage access to AWS services and resources securely

Protect your network through best practices using NACLs & security groups, as well as the security offered by AWS Web Application Firewall (WAF) and AWS Shield

Protect your data w/ IPsec, AWS Certificate Manager, AWS Key Management Services (KMS), AWS CloudHSM, & other key management approaches

Ensure that your AWS environment is secure through logging, monitoring, auditing, & reporting services available in AWS

This introduction to the leading cloud provider, Amazon Web Services (AWS), provides a solid foundational understanding of the AWS infrastructure-as-a-service products. You’ll cover concepts necessary to understand cloud computing platforms, working with virtual machines, storage in the cloud, security, high availability, and more. This course is a good secondary resource to help you study for the AWS Solutions Architect exam.

Access 11 lectures & 6 hours of content 24/7

Get an overview of AWS

Explore security, networking, & computing in AWS

Cover storage & databases in AWS

Understand developer & management tools

This course was specifically developed to help you pass the latest edition of the AWS Certified Solutions Architect Associate exam. This certification is ideal for anyone in a solutions architect or similar technical role. You’ll cover all the key areas addressed in the exam and review a number of use cases designed to help you gain an intellectual framework with which to formulate the correct answers.

Access 15 lectures & 6.5 hours of content 24/7

Design AWS environments to be highly-available, fault-tolerant, & self-healing

Design for cost, security, & performance

Leverage automation within AWS

Prepare for the AWS Certified Solutions Architect exam

This course is designed to help you understand Amazon Web Services at a high level, introduce you to cloud computing concepts and key AWS services, and prepare you for the AWS Certified Cloud Practitioner exam.

Access 9 lectures & 7 hours of content 24/7

Study to pass the Cloud Practitioner Certification exam

Cover fundamental concepts of AWS

Explore basic & advanced core services

Understand security in AWS, service pricing, cost management, & more

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[asrarmukadamworld-blog]

10 Free Courses to Learn Docker for Programmers

Here is my list of some of the best, free courses to learn Docker in 2019. They are an excellent resource for both beginners and experienced developers.

 1. Docker Essentials

 If you have heard all the buzz around Docker and containers and are wondering what they are and how to get started using them, then this course is for you.

 In this course, you will learn how to install Docker, configure it for use on your local system, clone and work with Docker images, instantiate containers, mount host volumes, redirect ports and understand how to manage images and containers.

After completing the course you should be able to implement containers in your projects/environment while having a firm understanding of their use cases, both for and against.

In short, one of the best course for developers and DevOps Engineers who want to learn basics, like what Docker containers are and how to use them in their environment.

 2. Understanding Docker and using it for Selenium Automation

 This is another good course to learn and understand the basics of Docker while automating Selenium test cases for your project.

The course is specially designed for DevOps engineers, automation guys, testers, and developers.

The course is divided into three main parts: Introduction of Docker, Docker Compose, and Selenium Grid with Docker.

 The three sections are independent of each other and you can learn than in parallel or switch back and forth.

   3. Docker for Beginners

 This is one of the best sources to learn the big picture of Docker and containerization. If you know a little bit about virtualization, networking, and cloud computing, then you can join this course.

 It provides a good introduction to current software development trend and what problems Docker solves.

In short, this is a good course for Software and IT architects, Programmers, IT administrator and anyone who want to understand the role of Docker in current world application development.

4. Containers 101

 Docker and containers are a whole new way of developing and delivering applications and IT infrastructure.

 This course will cover Docker and containers, container registries, container orchestration, understand if this will work for the enterprise, and how to prepare yourself for it.

In short, a good course for anyone who wants to get up to speed with containers and Docker.

 5. Docker Swarm: Native Docker Clustering

 Managing Docker at scale is the next challenge facing IT. This course, Docker Swarm: Native Docker Clustering will teach you everything you need to know about Docker Swarm, the native solution for managing Docker environments at scale.

 It’s a good course for Developers, Networking Teams, DevOps Engineers, and Networking infrastructure teams.

This was a paid course earlier on Udemy, but it’s free for a limited time. Join this course before it becomes paid again.

6. Docker Course Made for Developers

 Whether or not you’re a Developer, anyone who works with code or servers will boost their productivity with Docker’s open app-building platform.

 In this course, you will learn how to use the Docker products, like Docker Toolbox, Docker Client, Docker Machine, Docker Compose, Kinematic, and Docker Cloud.

You will also learn how to work with images and containers, how to get your project running, and how to push it to the cloud, among other important lessons.

7. Docker on Windows 10 and Server 2016

 If you are thinking to learn how to use Docker on Windows 10 and Windows Server 2016 then this is the right course for you.

 In this course, you will understand what Docker On Windows is all about and how Docker on Windows is the same as Linux Containers.

You will also learn Hyper-V, namespace isolation and server containers in depth.

8. Deploying Containerized Applications Technical Overview

 Docker has become the de facto standard for defining and running containers in the Linux operating system. Kubernetes is Red Hat’s choice for container orchestration.

 OpenShift, built upon Docker, Kubernetes, and other open source software projects, provides Platform-as-a-Service (PaaS) for the ultimate in deploying applications within containers.

This is an Official Red Hat course about containers using Docker running on Red Hat Enterprise Linux.

In this course, Jim Rigsbee, a curriculum architect for Red Hat Training, will introduce you to container technology using Docker running on Red Hat Enterprise Linux

 9. Docker Deep Dive

 As the title suggests this is a great course to learn Docker in depth. It provides a good experience for core Docker technologies, including the Docker Engine, Images, Containers, Registries, Networking, Storage, and more.

 You will also learn theory and all concepts are clearly demonstrated on the command line.

And the best part of this course is that no prior knowledge of Docker or Linux is required.

10. Docker and Containers

 In this course, you’ll learn how this is going to impact you as an individual as well as the teams and organizations you work for.

This course will cover Docker and containers, container registries, container orchestration, whether this stuff is for the enterprise, and how to prepare yourself for it.

 These two courses from Pluralsight are not really free; you need a Pluarlsight membership to get this course, and monthly membership costs around $29 and annual membership cost around $299.

 I know, we all love free stuff, but you will not only get access to this course but over 5000 courses as well, so it’s definitely the money well spent.

I have an annual membership because I have to learn a lot of new stuff all the times. Even if you are not a member, you can get this course for free by signing a free trial. Pluralsight provides 10-day free trial with no obligation.

That’s all about some of the free Docker container courses for Java developers. It’s one of the essential skill if you are developing a mobile application or web application hence, I suggest every application developer learn Docker in 2019. You will not only learn an essential skill but also take your career to the next level, given the high demand for Docker specialist and developer who knows Docker.

[Source] https://hackernoon.com/10-free-courses-to-learn-docker-for-programmers-and-devops-engineers-7ff2781fd6e0

Beginners & Advanced level Docker Training Course in Mumbai. Asterix Solution's 25 Hour Docker Training gives broad hands-on practicals

[codecraftshop]

Deploy application in openshift using container images#openshift #containerimages #openshift # openshift4 #containerization Deploy container app using OpenShift Container Platform running on-premises,openshift deploy docker image cli,openshift deploy docker image command line,how to deploy docker image in openshift,how to deploy image in openshift,deploy image in openshift,deploy image into openshift,Deploy application in openshift using container images,openshift container platform,openshift tutorial,red hat openshift,openshift,kubernetes,openshift 4,red hat,redhat openshift online https://www.youtube.com/channel/UCnIp4tLcBJ0XbtKbE2ITrwA?sub_confirmation=1&app=desktop About: 00:00 Deploy application in openshift using container images In this course we will learn about deploying an application from container images to openshift / openshift 4 online cluster in different ways. First method is to use the webconsole to deploy application using docker container images. Second way is to login through OC openshift cluster command line tool for windows and through oc command we can deploy the container image to openshift cluster. Openshift/ Openshift4 a cloud based container to build deploy test our application on cloud. In the next videos we will explore Openshift4 in detail. Commands Used: Image to be deployed: openshiftkatacoda/blog-django-py oc get all -o name :-This will return all the resources we have in the project oc describe route/blog-django-py :-This will give us the details of the route that has been created. Through this route or url we can access the application externally. oc get all --selector app=blog-django-py -o name :-This will select only the resources with the label app=blog-django-py . By default openshift automatically applies the label app=blog-django-py to all the resources of the application. oc delete all --selector app=blog-django-py :-This will delete the application and the related resources having label app= app=blog-django-py oc get all -o name :-This get the list of all the available resources. oc new-app --search openshiftkatacoda/blog-django-py oc new-app openshiftkatacoda/blog-django-py :-This command will create / deploy the image in openshift container. oc new-app openshiftkatacoda/blog-django-py -o name blog :-This command will create / deploy the image in openshift container with custom name oc expose service/blog-django-py :-This will expose the service to the external world so that it can be accessed globally. oc get route/blog-django-py --- this will give the url of the application that we have deployed. certification,OpenShift workflow,openshift tutorial,ci cd pipeline,ci cd devops,openshift container platform,ci cd openshift,openshift installation,Getting Started with OpenShift,OpenShift for the Absolute Beginners,Get started with RedHat OpenShift https://www.facebook.com/codecraftshop/ https://t.me/codecraftshop/ Please do like and subscribe to my you tube channel "CODECRAFTSHOP" Follow us on facebook | instagram | twitter at @CODECRAFTSHOP . -~-~~-~~~-~~-~- Please watch: "Install hyperv on windows 10 - how to install, setup & enable hyper v on windows hyper-v" https://www.youtube.com/watch?v=KooTCqf07wk -~-~~-~~~-~~-~-

[computingpostcom]

Project Quay is a scalable container image registry that enables you to build, organize, distribute, and deploy containers. With Quay you can create image repositories, perform image vulnerability scanning and robust access controls. We had covered installation of Quay on a Linux distribution using Docker. How To Setup Red Hat Quay Registry on CentOS / RHEL / Ubuntu In this guide, we will review how you can deploy Quay container registry on OpenShift Container Platform using Operator. The operator we’ll use is provided in the Operators Hub. If you don’t have an OpenShift / OKD cluster running and would like to try this article, checkout our guides below. Setup Local OpenShift 4.x Cluster with CodeReady Containers How to Setup OpenShift Origin (OKD) 3.11 on Ubuntu How To run Local Openshift Cluster with Minishift The Project Quay is made up of several core components. Database: Used by Red Hat Quay as its primary metadata storage (not for image storage). Redis (key, value store): Stores live builder logs and the Red Hat Quay tutorial. Quay (container registry): Runs the quay container as a service, consisting of several components in the pod. Clair: Scans container images for vulnerabilities and suggests fixes. Step 1: Create new project for Project Quay Let’s begin by creating a new project for Quay registry. $ oc new-project quay-enterprise Now using project "quay-enterprise" on server "https://api.crc.testing:6443". ..... You can also create a Project from OpenShift Web console. Click create button and confirm the project is created and running. Step 2: Install Red Hat Quay Setup Operator The Red Hat Quay Setup Operator provides a simple method to deploy and manage a Red Hat Quay cluster. Login to the OpenShift console and select Operators → OperatorHub: Select the Red Hat Quay Operator. Select Install then Operator Subscription page will appear. Choose the following then select Subscribe: Installation Mode: Select a specific namespace to install to Update Channel: Choose the update channel (only one may be available) Approval Strategy: Choose to approve automatic or manual updates Step 3: Deploy a Red Hat Quay ecosystem Certain credentials are required for Accessing Quay.io registry. Create a new file with below details. $ vim docker_quay.json "auths": "quay.io": "auth": "cmVkaGF0K3F1YXk6TzgxV1NIUlNKUjE0VUFaQks1NEdRSEpTMFAxVjRDTFdBSlYxWDJDNFNEN0tPNTlDUTlOM1JFMTI2MTJYVTFIUg==", "email": "" Then create a secret on OpenShift that will be used. oc project quay-enterprise oc create secret generic redhat-pull-secret --from-file=".dockerconfigjson=docker_quay.json" --type='kubernetes.io/dockerconfigjson' Create Quay Superuser credentials secret: oc create secret generic quay-admin \ --from-literal=superuser-username=quayadmin \ --from-literal=superuser-password=StrongAdminPassword \ --from-literal=superuser-email=admin@example.com Where: quayadmin is the Quay admin username StrongAdminPassword is the password for admin user admin@example.com is the email of Admin user to be created Create Quay Configuration Secret A dedicated deployment of Quay Enterprise is used to manage the configuration of Quay. Access to the configuration interface is secured and requires authentication in order for access. oc create secret generic quay-config --from-literal=config-app-password=StrongPassword Replace StrongPassword with your desired password. Create Database credentials secret – PostgreSQL oc create secret generic postgres-creds \ --from-literal=database-username=quay \ --from-literal=database-password=StrongUserPassword \ --from-literal=database-root-password=StrongRootPassword \ --from-literal=database-name=quay These are the credentials for accessing the database server: quay – Database and DB username StrongUserPassword – quay DB user password StrongRootPassword – root user database password

Create Redis Password Credential By default, the operator managed Redis instance is deployed without a password. A password can be specified by creating a secret containing the password in the key password. oc create secret generic redis-password --from-literal=password=StrongRedisPassword Create Quay Ecosystem Deployment Manifest My Red Hat Quay ecosystem configuration file looks like below apiVersion: redhatcop.redhat.io/v1alpha1 kind: QuayEcosystem metadata: name: quay-ecosystem spec: clair: enabled: true imagePullSecretName: redhat-pull-secret updateInterval: "60m" quay: imagePullSecretName: redhat-pull-secret superuserCredentialsSecretName: quay-admin configSecretName: quay-config deploymentStrategy: RollingUpdate skipSetup: false redis: credentialsSecretName: redis-password database: volumeSize: 10Gi credentialsSecretName: postgres-creds registryStorage: persistentVolumeSize: 20Gi persistentVolumeAccessModes: - ReadWriteMany livenessProbe: initialDelaySeconds: 120 httpGet: path: /health/instance port: 8443 scheme: HTTPS readinessProbe: initialDelaySeconds: 10 httpGet: path: /health/instance port: 8443 scheme: HTTPS Modify it to fit you use case. When done apply the configuration: oc apply -f quay-ecosystem.yaml Using Custom SSL Certificates If you want to use custom SSL certificates with Quay, you need to create a secret with the key and the certificate: oc create secret generic custom-quay-ssl \ --from-file=ssl.key=example.key \ --from-file=ssl.cert=example.crt Then modify your Ecosystem file to use the custom certificate secret: quay: imagePullSecretName: redhat-pull-secret sslCertificatesSecretName: custom-quay-ssl ....... Wait for few minutes then confirm deployment: $ oc get deployments NAME READY UP-TO-DATE AVAILABLE AGE quay-ecosystem-clair 1/1 1 1 2m35s quay-ecosystem-clair-postgresql 1/1 1 1 2m57s quay-ecosystem-quay 1/1 1 1 3m45s quay-ecosystem-quay-postgresql 1/1 1 1 5m8s quay-ecosystem-redis 1/1 1 1 5m57s quay-operator 1/1 1 1 70m $ oc get svc NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE quay-ecosystem-clair ClusterIP 172.30.66.1 6060/TCP,6061/TCP 4m quay-ecosystem-clair-postgresql ClusterIP 172.30.10.126 5432/TCP 3m58s quay-ecosystem-quay ClusterIP 172.30.47.147 443/TCP 5m38s quay-ecosystem-quay-postgresql ClusterIP 172.30.196.61 5432/TCP 6m15s quay-ecosystem-redis ClusterIP 172.30.48.112 6379/TCP 6m58s quay-operator-metrics ClusterIP 172.30.81.233 8383/TCP,8686/TCP 70m Running pods in the project: $ oc get pods NAME READY STATUS RESTARTS AGE quay-ecosystem-clair-84b4d77654-cjwcr 1/1 Running 0 2m57s quay-ecosystem-clair-postgresql-7c47b5955-qbc4s 1/1 Running 0 3m23s quay-ecosystem-quay-66584ccbdb-8szts 1/1 Running 0 4m8s quay-ecosystem-quay-postgresql-74bf8db7f8-vnrx9 1/1 Running 0 5m34s quay-ecosystem-redis-7dcd5c58d6-p7xkn 1/1 Running 0 6m23s quay-operator-764c99dcdb-k44cq 1/1 Running 0 70m Step 4: Access Quay Dashboard Get a route URL for deployed Quay: $ oc get route quay-ecosystem-quay quay-ecosystem-quay-quay-enterprise.apps.example.com quay-ecosystem-quay 8443 passthrough/Redirect None

Open the URL on the machine with access to the cluster domain. Use the credentials you configured to login to Quay registry. And there you have it. You now have Quay registry running on OpenShift using Operators. Refer to below documentations for more help. Quay Operator Github Page Red Hat Quay documentation Project Quay Documentation

[abckidstvyara]

The Red Hat Linux distribution is turning 25 years old this week. What started as one of the earliest Linux distributions is now the most successful open-source company, and its success was a catalyst for others to follow its model. Today’s open-source world is very different from those heady days in the mid-1990s when Linux looked to be challenging Microsoft’s dominance on the desktop, but Red Hat is still going strong.

To put all of this into perspective, I sat down with the company’s current CEO (and former Delta Air Lines COO) Jim Whitehurst to talk about the past, present and future of the company, and open-source software in general. Whitehurst took the Red Hat CEO position 10 years ago, so while he wasn’t there in the earliest days, he definitely witnessed the evolution of open source in the enterprise, which is now more widespread than every.

“Ten years ago, open source at the time was really focused on offering viable alternatives to traditional software,” he told me. “We were selling layers of technology to replace existing technology. […] At the time, it was open source showing that we can build open-source tech at lower cost. The value proposition was that it was cheaper.”

At the time, he argues, the market was about replacing Windows with Linux or IBM’s WebSphere with JBoss. And that defined Red Hat’s role in the ecosystem, too, which was less about technological information than about packaging. “For Red Hat, we started off taking these open-source projects and making them usable for traditional enterprises,” said Whitehurst.

Jim Whitehurst, Red Hat president and CEO (photo by Joan Cros/NurPhoto via Getty Images)

About five or six ago, something changed, though. Large corporations, including Google and Facebook, started open sourcing their own projects because they didn’t look at some of the infrastructure technologies they opened up as competitive advantages. Instead, having them out in the open allowed them to profit from the ecosystems that formed around that. “The biggest part is it’s not just Google and Facebook finding religion,” said Whitehurst. “The social tech around open source made it easy to make projects happen. Companies got credit for that.”

He also noted that developers now look at their open-source contributions as part of their resumé. With an increasingly mobile workforce that regularly moves between jobs, companies that want to compete for talent are almost forced to open source at least some of the technologies that don’t give them a competitive advantage.

As the open-source ecosystem evolved, so did Red Hat. As enterprises started to understand the value of open source (and stopped being afraid of it), Red Hat shifted from simply talking to potential customers about savings to how open source can help them drive innovation. “We’ve gone from being commeditizers to being innovators. The tech we are driving is now driving net new innovation,” explained Whitehurst. “We are now not going in to talk about saving money but to help drive innovation inside a company.”

Over the last few years, that included making acquisitions to help drive this innovation. In 2015, Red Hat bought IT automation service Ansible, for example, and last month, the company closed its acquisition of CoreOS, one of the larger independent players in the Kubernetes container ecosystem — all while staying true to its open-source root.

There is only so much innovation you can do around a Linux distribution, though, and as a public company, Red Hat also had to look beyond that core business and build on it to better serve its customers. In part, that’s what drove the company to launch services like OpenShift, for example, a container platform that sits on top of Red Hat Enterprise Linux and — not unlike the original Linux distribution — integrates technologies like Docker and Kubernetes and makes them more easily usable inside an enterprise.

The reason for that? “I believe that containers will be the primary way that applications will be built, deployed and managed,” he told me, and argued that his company, especially after the CoreOS acquisition, is now a leader in both containers and Kubernetes. “When you think about the importance of containers to the future of IT, it’s a clear value for us and for our customers.”

The other major open-source project Red Hat is betting on is OpenStack. That may come as a bit of a surprise, given that popular opinion in the last year or so has shifted against the massive project that wants to give enterprises an open source on-premise alternative to AWS and other cloud providers. “There was a sense among big enterprise tech companies that OpenStack was going to be their savior from Amazon,” Whitehurst said. “But even OpenStack, flawlessly executed, put you where Amazon was five years ago. If you’re Cisco or HP or any of those big OEMs, you’ll say that OpenStack was a disappointment. But from our view as a software company, we are seeing good traction.”

Because OpenStack is especially popular among telcos, Whitehurst believes it will play a major role in the shift to 5G. “When we are talking to telcos, […] we are very confident that OpenStack will be the platform for 5G rollouts.”

With OpenShift and OpenStack, Red Hat believes that it has covered both the future of application development and the infrastructure on which those applications will run. Looking a bit further ahead, though, Whitehurst also noted that the company is starting to look at how it can use artificial intelligence and machine learning to make its own products smarter and more secure, but also at how it can use its technologies to enable edge computing. “Now that large enterprises are also contributing to open source, we have a virtually unlimited amount of material to bring our knowledge to,” he said.

[dalepwithchari]

Red Hat looks beyond Linux

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The Red Hat Linux distribution is turning 25 years old this week. What started as one of the earliest Linux distributions is now the most successful open-source company, and its success was a catalyst for others to follow its model. Today’s open-source world is very different from those heady days in the mid-1990s when Linux looked to be challenging Microsoft’s dominance on the desktop, but Red Hat is still going strong.

To put all of this into perspective, I sat down with the company’s current CEO (and former Delta Air Lines COO) Jim Whitehurst to talk about the past, present and future of the company, and open-source software in general. Whitehurst took the Red Hat CEO position 10 years ago, so while he wasn’t there in the earliest days, he definitely witnessed the evolution of open source in the enterprise, which is now more widespread than every.

“Ten years ago, open source at the time was really focused on offering viable alternatives to traditional software,” he told me. “We were selling layers of technology to replace existing technology. At the time, it was open source showing that we can build open-source tech at lower cost. The value proposition was that it was cheaper.”

At the time, he argues, the market was about replacing Windows with Linux or IBM’s WebSphere with JBoss. And that defined Red Hat’s role in the ecosystem, too, which was less about technological information than about packaging. “For Red Hat, we started off taking these open-source projects and making them usable for traditional enterprises,” said Whitehurst.

Jim Whitehurst, Red Hat president and CEO (photo by Joan Cros/NurPhoto via Getty Images)

About five or six ago, something changed, though. Large corporations, including Google and Facebook, started open sourcing their own projects because they didn’t look at some of the infrastructure technologies they opened up as competitive advantages. Instead, having them out in the open allowed them to profit from the ecosystems that formed around that. “The biggest part is it’s not just Google and Facebook finding religion,” said Whitehurst. “The social tech around open source made it easy to make projects happen. Companies got credit for that.”

He also noted that developers now look at their open-source contributions as part of their resumé. With an increasingly mobile workforce that regularly moves between jobs, companies that want to compete for talent are almost forced to open source at least some of the technologies that don’t give them a competitive advantage.

As the open-source ecosystem evolved, so did Red Hat. As enterprises started to understand the value of open source (and stopped being afraid of it), Red Hat shifted from simply talking to potential customers about savings to how open source can help them drive innovation. “We’ve gone from being commeditizers to being innovators. The tech we are driving is now driving net new innovation,” explained Whitehurst. “We are now not going in to talk about saving money but to help drive innovation inside a company.”

Over the last few years, that included making acquisitions to help drive this innovation. In 2015, Red Hat bought IT automation service Ansible, for example, and last month, the company closed its acquisition of CoreOS, one of the larger independent players in the Kubernetes container ecosystem — all while staying true to its open-source root.

There is only so much innovation you can do around a Linux distribution, though, and as a public company, Red Hat also had to look beyond that core business and build on it to better serve its customers. In part, that’s what drove the company to launch services like OpenShift, for example, a container platform that sits on top of Red Hat Enterprise Linux and — not unlike the original Linux distribution — integrates technologies like Docker and Kubernetes and makes them more easily usable inside an enterprise.

The reason for that? “I believe that containers will be the primary way that applications will be built, deployed and managed,” he told me, and argued that his company, especially after the CoreOS acquisition, is now a leader in both containers and Kubernetes. “When you think about the importance of containers to the future of IT, it’s a clear value for us and for our customers.”

The other major open-source project Red Hat is betting on is OpenStack . That may come as a bit of a surprise, given that popular opinion in the last year or so has shifted against the massive project that wants to give enterprises an open source on-premise alternative to AWS and other cloud providers. “There was a sense among big enterprise tech companies that OpenStack was going to be their savior from Amazon,” Whitehurst said. “But even OpenStack, flawlessly executed, put you where Amazon was five years ago. If you’re Cisco or HP or any of those big OEMs, you’ll say that OpenStack was a disappointment. But from our view as a software company, we are seeing good traction.”

Because OpenStack is especially popular among telcos, Whitehurst believes it will play a major role in the shift to 5G. “When we are talking to telcos, we are very confident that OpenStack will be the platform for 5G rollouts.”

With OpenShift and OpenStack, Red Hat believes that it has covered both the future of application development and the infrastructure on which those applications will run. Looking a bit further ahead, though, Whitehurst also noted that the company is starting to look at how it can use artificial intelligence and machine learning to make its own products smarter and more secure, but also at how it can use its technologies to enable edge computing. “Now that large enterprises are also contributing to open source, we have a virtually unlimited amount of material to bring our knowledge to,” he said.

  [Read More …]

Red Hat looks beyond Linux

[jamesmcphee30]

Running Non-Root Containers On Openshift

In this blog post we see how a Bitnami non-root Dockerfile looks like by checking the Bitnami Nginx Docker image. As an example of how the non-root containers can be used, we go through how to deploy Ghost on Openshift. Finally, we will cover some of the issues we faced while moving all of these containers to non-root containers

from martinos https://www.linux.com/news/running-non-root-containers-openshift

[codecraftshop]

Deploy application in openshift using container imagesOpenshift 4 is latest devops technology which can benefit the enterprise in a lot of ways. Build development and deployment can be automated using Openshift 4 platform. Features for autoscaling , microservices architecture and lot more features. So please like watch subscribe my channel for the latest videos. #Deploy #application #openshift #container #images #openshift # openshift4 #containerization #cloud #online #container #kubernetes #docker #automation #redhatopenshift #openshifttutorial #openshiftonline, Deploy container app using OpenShift Container Platform running on-premises,how to deploy node js application in openshift,openshift deploy docker image cli,openshift deploy docker image command line,how to deploy docker image in openshift,how to deploy image in openshift,deploy image in openshift,deploy image into openshift,Deploy application in openshift using container images,openshift container platform,openshift tutorial,red hat openshift,openshift,kubernetes https://www.youtube.com/channel/UCnIp4tLcBJ0XbtKbE2ITrwA?sub_confirmation=1&app=desktop About: 00:00 Deploy application in openshift using container images In this course we will learn about deploying an application from container images to openshift / openshift 4 online cluster in different ways. First method is to use the webconsole to deploy application using docker container images. Second way is to login through OC openshift cluster command line tool for windows and through oc command we can deploy the container image to openshift cluster. Openshift/ Openshift4 a cloud based container to build deploy test our application on cloud. In the next videos we will explore Openshift4 in detail. Commands Used: Image to be deployed: openshiftkatacoda/blog-django-py oc get all -o name :-This will return all the resources we have in the project oc describe route/blog-django-py :-This will give us the details of the route that has been created. Through this route or url we can access the application externally. oc get all --selector app=blog-django-py -o name :-This will select only the resources with the label app=blog-django-py . By default openshift automatically applies the label app=blog-django-py to all the resources of the application. oc delete all --selector app=blog-django-py :-This will delete the application and the related resources having label app= app=blog-django-py oc get all -o name :-This get the list of all the available resources. oc new-app --search openshiftkatacoda/blog-django-py oc new-app openshiftkatacoda/blog-django-py :-This command will create / deploy the image in openshift container. oc new-app openshiftkatacoda/blog-django-py -o name blog :-This command will create / deploy the image in openshift container with custom name oc expose service/blog-django-py :-This will expose the service to the external world so that it can be accessed globally. oc get route/blog-django-py --- this will give the url of the application that we have deployed. certification,OpenShift workflow,openshift tutorial,ci cd pipeline,ci cd devops,openshift container platform,ci cd openshift,openshift installation,Getting Started with OpenShift,OpenShift for the Absolute Beginners,Get started with RedHat OpenShift https://www.facebook.com/codecraftshop/ https://t.me/codecraftshop/ Please do like and subscribe to my you tube channel "CODECRAFTSHOP" Follow us on facebook | instagram | twitter at @CODECRAFTSHOP . -~-~~-~~~-~~-~- Please watch: "Install hyperv on windows 10 - how to install, setup & enable hyper v on windows hyper-v" https://www.youtube.com/watch?v=KooTCqf07wk -~-~~-~~~-~~-~-