#openshift origin

[timothyvalihora]

Governance Without Boundaries - CP4D and Red Hat Integration

The rising complexity of hybrid and multi-cloud environments calls for stronger and more unified data governance. When systems operate in isolation, they introduce risks, make compliance harder, and slow down decision-making. As digital ecosystems expand, consistent governance across infrastructure becomes more than a goal, it becomes a necessity. A cohesive strategy helps maintain control as platforms and regions scale together.

IBM Cloud Pak for Data (CP4D), working alongside Red Hat OpenShift, offers a container-based platform that addresses these challenges head-on. That setup makes it easier to scale governance consistently, no matter the environment. With container orchestration in place, governance rules stay enforced regardless of where the data lives. This alignment helps prevent policy drift and supports data integrity in high-compliance sectors.

Watson Knowledge Catalog (WKC) sits at the heart of CP4D’s governance tools, offering features for data discovery, classification, and controlled access. WKC lets teams organize assets, apply consistent metadata, and manage permissions across hybrid or multi-cloud systems. Centralized oversight reduces complexity and brings transparency to how data is used. It also facilitates collaboration by giving teams a shared framework for managing data responsibilities.

Red Hat OpenShift brings added flexibility by letting services like data lineage, cataloging, and enforcement run in modular, scalable containers. These components adjust to different workloads and grow as demand increases. That level of adaptability is key for teams managing dynamic operations across multiple functions. This flexibility ensures governance processes can evolve alongside changing application architectures.

Kubernetes, which powers OpenShift’s orchestration, takes on governance operations through automated workload scheduling and smart resource use. Its automation ensures steady performance while still meeting privacy and audit standards. By handling deployment and scaling behind the scenes, it reduces the burden on IT teams. With fewer manual tasks, organizations can focus more on long-term strategy.

A global business responding to data subject access requests (DSARs) across different jurisdictions can use CP4D to streamline the entire process. These built-in tools support compliant responses under GDPR, CCPA, and other regulatory frameworks. Faster identification and retrieval of relevant data helps reduce penalties while improving public trust.

CP4D’s tools for discovering and classifying data work across formats, from real-time streams to long-term storage. They help organizations identify sensitive content, apply safeguards, and stay aligned with privacy rules. Automation cuts down on human error and reinforces sound data handling practices. As data volumes grow, these automated capabilities help maintain performance and consistency.

Lineage tracking offers a clear view of how data moves through DevOps workflows and analytics pipelines. By following its origin, transformation, and application, teams can trace issues, confirm quality, and document compliance. CP4D’s built-in tools make it easier to maintain trust in how data is handled across environments.

Tight integration with enterprise identity and access management (IAM) systems strengthens governance through precise controls. It ensures only the right people have access to sensitive data, aligning with internal security frameworks. Centralized identity systems also simplify onboarding, access changes, and audit trails.

When governance tools are built into the data lifecycle from the beginning, compliance becomes part of the system. It is not something added later. This helps avoid retroactive fixes and supports responsible practices from day one. Governance shifts from a task to a foundation of how data is managed.

As regulations multiply and workloads shift, scalable governance is no longer a luxury. It is a requirement. Open, container-driven architectures give organizations the flexibility to meet evolving standards, secure their data, and adapt quickly.

[hawskstack]

Enterprise Kubernetes Storage With Red Hat OpenShift Data Foundation

In today’s enterprise IT environments, the adoption of containerized applications has grown exponentially. While Kubernetes simplifies application deployment and orchestration, it poses a unique challenge when it comes to managing persistent data. Stateless workloads may scale with ease, but stateful applications require a robust, scalable, and resilient storage backend — and that’s where Red Hat OpenShift Data Foundation (ODF) plays a critical role.

🌐 Why Enterprise Kubernetes Storage Matters

Kubernetes was originally designed for stateless applications. However, modern enterprise applications — databases, analytics engines, monitoring tools — often need to store data persistently. Enterprises require:

High availability

Scalable performance

Data protection and recovery

Multi-cloud and hybrid-cloud compatibility

Standard storage solutions often fall short in a dynamic, containerized environment. That’s why a storage platform designed for Kubernetes, within Kubernetes, is crucial.

🔧 What is Red Hat OpenShift Data Foundation?

Red Hat OpenShift Data Foundation is a Kubernetes-native, software-defined storage solution integrated with Red Hat OpenShift. It provides:

Block, file, and object storage

Dynamic provisioning for persistent volumes

Built-in data replication, encryption, and disaster recovery

Unified management across hybrid cloud environments

ODF is built on Ceph, a battle-tested distributed storage system, and uses Rook to orchestrate storage on Kubernetes.

Key Capabilities

1. Persistent Storage for Containers

ODF provides dynamic, persistent storage for stateful workloads like PostgreSQL, MongoDB, Kafka, and more, enabling them to run natively on OpenShift.

2. Multi-Access and Multi-Tenancy

Supports file sharing between pods and secure data isolation between applications or business units.

3. Elastic Scalability

Storage scales with compute, ensuring performance and capacity grow as application needs increase.

4. Built-in Data Services

Includes snapshotting, backup and restore, mirroring, and encryption, all critical for enterprise-grade reliability.

Integration with OpenShift

ODF integrates seamlessly into the OpenShift Console, offering a native, operator-based deployment model. Storage is provisioned and managed using familiar Kubernetes APIs and Custom Resources, reducing the learning curve for DevOps teams.

🔐 Enterprise Benefits

Operational Consistency: Unified storage and platform management

Security and Compliance: End-to-end encryption and audit logging

Hybrid Cloud Ready: Runs consistently across on-premises, AWS, Azure, or any cloud

Cost Efficiency: Optimize storage usage through intelligent tiering and compression

✅ Use Cases

Running databases in Kubernetes

Storing logs and monitoring data

AI/ML workloads needing high-throughput file storage

Object storage for backups or media repositories

📈 Conclusion

Enterprise Kubernetes storage is no longer optional — it’s essential. As businesses migrate more critical workloads to Kubernetes, solutions like Red Hat OpenShift Data Foundation provide the performance, flexibility, and resilience needed to support stateful applications at scale.

ODF helps bridge the gap between traditional storage models and cloud-native innovation — making it a strategic asset for any organization investing in OpenShift and modern application architectures.

For more info, Kindly follow: Hawkstack Technologies

[qcsdclabs]

Red Hat Enterprise Linux

Red Hat Linux was one of the most popular Linux distributions (distros) for both servers and desktops before it was discontinued. It played a key role in the development of Linux as a mainstream operating system. Here's a breakdown of Red Hat Linux and its modern successor:

1. Red Hat Linux (1994–2004):

Initial Release: Red Hat Linux was first released in 1994 by Red Hat, Inc., founded by Marc Ewing and Bob Young. It became one of the most widely used distributions, known for its stability and reliability, which made it popular in enterprise environments.

Package Management: It used the Red Hat Package Manager (RPM) format for installing and managing software, which became one of the most common package management systems in the Linux world.

Discontinuation: Red Hat discontinued Red Hat Linux in 2004, transitioning to a more enterprise-focused distribution—Red Hat Enterprise Linux (RHEL).

2. Red Hat Enterprise Linux (RHEL):

Enterprise-Focused: RHEL was launched to focus on businesses and large organizations. It is a paid, subscription-based Linux distribution that offers long-term support, regular security updates, and extensive hardware certification.

Key Features:

Stability: RHEL is designed for mission-critical environments, ensuring a stable platform for servers, databases, and applications.

Security: Features like SELinux (Security-Enhanced Linux) provide an additional layer of security for enterprise environments.

Long-Term Support: Each major version of RHEL is supported for around 10 years (with 5 years of full support and 5 years of maintenance support).

Software Repositories: RHEL includes official repositories containing enterprise-grade software and has commercial support from Red Hat.

RHEL vs. Fedora vs. CentOS:

Fedora: This is the upstream, community-driven version that serves as a testing ground for RHEL features.

CentOS: CentOS was originally a free, community-supported clone of RHEL. However, Red Hat shifted its focus in late 2020 to CentOS Stream, which serves as a rolling-release version that is positioned between Fedora and RHEL.

3. Modern Usage:

RHEL is widely used in enterprise environments, especially for web servers, application servers, cloud computing, and more. Red Hat also offers a variety of tools and services around RHEL, including automation, containerization (via OpenShift), and Kubernetes support.

4. Red Hat's Role in the Linux Ecosystem:

Open Source Commitment: Red Hat has been a significant contributor to the open-source community, funding many projects and sponsoring key development initiatives.

Acquisition by IBM: In 2019, IBM acquired Red Hat for $34 billion, further strengthening Red Hat's position as a leader in enterprise Linux solutions.

5. Alternatives:

Other Linux Distros: While Red Hat (and its enterprise variants) is quite popular, there are many alternatives such as Ubuntu, Debian, SUSE, and Arch Linux, each with different goals, community support, and use cases.

for more details please visit 

www.qcsdclabs.com, 

www.hawkstack.com

[qcsdslabs]

Why Choose OpenShift Virtualization for Your Enterprise Applications?

In today’s fast-evolving IT landscape, organizations are continuously seeking solutions that bridge the gap between traditional virtualization and modern container-based application deployments. OpenShift Virtualization emerges as a game-changer, enabling enterprises to run and manage both virtual machines (VMs) and containers seamlessly within a single platform. Here’s why OpenShift Virtualization stands out as the ideal choice for your enterprise applications:

1. Unified Platform for Hybrid Workloads

OpenShift Virtualization integrates virtual machines and containers into one cohesive environment. This eliminates the need for separate infrastructure management tools, simplifying operations and reducing overhead. Enterprises can modernize their applications at their own pace, running VMs alongside containerized workloads without disruption.

Example:

An enterprise with legacy applications running on VMs can migrate to OpenShift Virtualization, enabling gradual modernization by containerizing parts of their workload while still maintaining the original VM environment.

2. Enhanced Operational Efficiency

By consolidating VMs and containers within OpenShift, IT teams can leverage the same CI/CD pipelines, monitoring tools, and automation workflows across all workloads. This consistency streamlines processes, minimizes human error, and accelerates application delivery.

Key Features:

Unified monitoring using OpenShift's built-in tools.

Centralized lifecycle management for VMs and containers.

3. Improved Resource Utilization

OpenShift Virtualization optimizes resource allocation by using Kubernetes-native scheduling for both VMs and containers. This ensures better utilization of compute and storage resources, reducing costs while maintaining performance.

Example:

Instead of over-provisioning for VM workloads, enterprises can dynamically allocate resources based on real-time demand, preventing wastage.

4. Flexibility for Legacy and Modern Applications

Not all enterprise applications are ready to be containerized. OpenShift Virtualization allows businesses to continue running their legacy applications in VMs while exploring modernization strategies. This dual capability ensures business continuity and future readiness.

Real-World Scenario:

A financial services company with critical applications running on legacy systems can use OpenShift Virtualization to maintain operations while developing new containerized microservices.

5. Seamless Migration to Cloud-Native Architectures

OpenShift Virtualization provides tools for migrating existing VMs into the OpenShift environment. This paves the way for organizations to adopt cloud-native practices without the immediate need for a complete rewrite of their applications.

Migration Tools:

KubeVirt for VM integration.

Import/export utilities for moving VMs into OpenShift.

6. Simplified Hybrid Cloud Management

For enterprises operating in hybrid cloud environments, OpenShift Virtualization offers consistent management and deployment practices across on-premises and cloud platforms. This consistency reduces complexity and ensures predictable performance.

7. Enterprise-Grade Security

Security remains a top concern for enterprises. OpenShift Virtualization extends OpenShift’s robust security model to VMs, ensuring:

Isolation between workloads.

Role-based access control (RBAC).

Integrated compliance and auditing capabilities.

8. Cost Savings

By consolidating workloads and leveraging Kubernetes’ dynamic resource allocation, OpenShift Virtualization helps enterprises reduce hardware and licensing costs associated with traditional virtualization platforms.

Conclusion

OpenShift Virtualization is more than just a tool for running VMs within OpenShift. It’s a comprehensive solution that empowers enterprises to bridge their past and future, combining the stability of traditional virtualization with the agility of containerization. By choosing OpenShift Virtualization, businesses can simplify their IT operations, optimize resource usage, and accelerate their journey toward digital transformation.

Whether you’re managing legacy applications, exploring cloud-native architectures, or striving to enhance operational efficiency, OpenShift Virtualization offers the flexibility and innovation your enterprise needs. It’s not just a platform—it’s the cornerstone of modern enterprise IT.

For more information  visit: https://www.hawkstack.com/

[fromdevcom]

In today’s modern software development world, container orchestration has become an essential practice. Imagine containers as tiny, self-contained boxes holding your application and all it needs to run; lightweight, portable, and ready to go on any system. However, managing a swarm of these containers can quickly turn into chaos. That's where container orchestration comes in to assist you. In this article, let’s explore the world of container orchestration. What Is Container Orchestration? Container orchestration refers to the automated management of containerized applications. It involves deploying, managing, scaling, and networking containers to ensure applications run smoothly and efficiently across various environments. As organizations adopt microservices architecture and move towards cloud-native applications, container orchestration becomes crucial in handling the complexity of deploying and maintaining numerous container instances. Key Functions of Container Orchestration Deployment: Automating the deployment of containers across multiple hosts. Scaling: Adjusting the number of running containers based on current load and demand. Load balancing: Distributing traffic across containers to ensure optimal performance. Networking: Managing the network configurations to allow containers to communicate with each other. Health monitoring: Continuously checking the status of containers and replacing or restarting failed ones. Configuration management: Keeping the container configurations consistent across different environments. Why Container Orchestration Is Important? Efficiency and Resource Optimization Container orchestration takes the guesswork out of resource allocation. By automating deployment and scaling, it makes sure your containers get exactly what they need, no more, no less. As a result, it keeps your hardware working efficiently and saves you money on wasted resources. Consistency and Reliability Orchestration tools ensure that containers are consistently configured and deployed, reducing the risk of errors and improving the reliability of applications. Simplified Management Managing a large number of containers manually is impractical. Orchestration tools simplify this process by providing a unified interface to control, monitor, and manage the entire lifecycle of containers. Leading Container Orchestration Tools Kubernetes Kubernetes is the most widely used container orchestration platform. Originally developed by Google and now maintained by the Cloud Native Computing Foundation (CNCF), Kubernetes offers a comprehensive set of features for deploying, scaling, and managing containerized applications. Docker Swarm Docker Swarm is Docker's native clustering and orchestration tool. It integrates seamlessly with Docker and is known for its simplicity and ease of use. Apache Mesos Apache Mesos is a distributed systems kernel that can manage resources across a cluster of machines. It supports various frameworks, including Kubernetes, for container orchestration. OpenShift OpenShift is an enterprise-grade Kubernetes distribution by Red Hat. It offers additional features for developers and IT operations teams to manage the application lifecycle. Best Practices for Container Orchestration Design for Scalability Design your applications to scale effortlessly. Imagine adding more containers as easily as stacking building blocks which means keeping your app components independent and relying on external storage for data sharing. Implement Robust Monitoring and Logging Keep a close eye on your containerized applications' health. Tools like Prometheus, Grafana, and the ELK Stack act like high-tech flashlights, illuminating performance and helping you identify any issues before they become monsters under the bed. Automate Deployment Pipelines Integrate continuous integration and continuous deployment (CI/CD) pipelines with your orchestration platform.

This ensures rapid and consistent deployment of code changes, freeing you up to focus on more strategic battles. Secure Your Containers Security is vital in container orchestration. Implement best practices such as using minimal base images, regularly updating images, running containers with the least privileges, and employing runtime security tools. Manage Configuration and Secrets Securely Use orchestration tools' built-in features for managing configuration and secrets. For example, Kubernetes ConfigMaps and Secrets allow you to decouple configuration artifacts from image content to keep your containerized applications portable. Regularly Update and Patch Your Orchestration Tools Stay current with updates and patches for your orchestration tools to benefit from the latest features and security fixes. Regular maintenance reduces the risk of vulnerabilities and improves system stability.

[govindhtech]

KServe Providers Serve NIMble Cloud & Data Centre Inference

It’s going to get easier than ever to implement generative AI in the workplace.

NVIDIA NIM, an array of microservices for generative AI inference, will integrate with KServe, an open-source programme that automates the deployment of AI models at the scale of cloud computing applications.

Because of this combination, generative AI can be implemented similarly to other large-scale enterprise applications. Additionally, it opens up NIM to a broad audience via platforms from other businesses, including Red Hat, Canonical, and Nutanix.

NVIDIA’s solutions are now available to clients, ecosystem partners, and the open-source community thanks to the integration of NIM on KServe. With a single API call via NIM, all of them may benefit from the security, performance, and support of the NVIDIA AI Enterprise software platform – the current programming equivalent of a push button.

AI provisioning on Kubernetes

Originally, KServe was a part of Kubeflow, an open-source machine learning toolkit built on top of Kubernetes, an open-source software containerisation system that holds all the components of big distributed systems.

KServe was created as Kubeflow’s work on AI inference grew, and it eventually developed into its own open-source project.

The KServe software is currently used by numerous organisations, including AWS, Bloomberg, Canonical, Cisco, Hewlett Packard Enterprise,as IBM, Red Hat, Zillow, and NVIDIA. Several organisations have contributed to and used the software.

Behind the Scenes With KServe

In essence, KServe is a Kubernetes addon that uses AI inference like a potent cloud app. It runs with optimal performance, adheres to a common protocol, and supports TensorFlow, Scikit-learn, PyTorch, and XGBoost without requiring users to be familiar with the specifics of those AI frameworks.

These days, with the rapid emergence of new large language models (LLMs), the software is very helpful.

KServe makes it simple for users to switch between models to see which one best meets their requirements. Additionally, a KServe feature known as “canary rollouts” automates the process of meticulously validating and progressively releasing an updated model into production when one is available.

GPU autoscaling is an additional feature that effectively controls model deployment in response to fluctuations in service demand, resulting in optimal user and service provider experiences.

KServe API

With the convenience of NVIDIA NIM, the goodness of KServe will now be accessible.

All the complexity is handled by a single API request when using NIM. Whether their application is running in their data centre or on a remote cloud service, enterprise IT administrators receive the metrics they need to make sure it is operating as efficiently and effectively as possible. This is true even if they decide to switch up the AI models they’re employing.

With NIM, IT workers may alter their organization’s operations and become experts in generative AI. For this reason, numerous businesses are implementing NIM microservices, including Foxconn and ServiceNow.

Numerous Kubernetes Platforms are Rideable by NIM

Users will be able to access NIM on numerous corporate platforms, including Red Hat’s OpenShift AI, Canonical’s Charmed KubeFlow and Charmed Kubernetes, Nutanix GPT-in-a-Box 2.0, and many more, because of its interaction with KServe.

Contributing to KServe, Yuan Tang is a principal software engineer at Red Hat. “Red Hat and NVIDIA are making open source AI deployment easier for enterprises “Tang said.The Red Hat-NVIDIA partnership will simplify open source AI adoption for organisations, he said. By upgrading KServe and adding NIM support to Red Hat OpenShift AI, they can simplify Red Hat clients’ access to NVIDIA’s generative AI platform.

“NVIDIA NIM inference microservices will enable consistent, scalable, secure, high-performance generative AI applications from the cloud to the edge.with Nutanix GPT-in-a-Box 2.0,” stated Debojyoti Dutta, vice president of engineering at Nutanix, whose team also contributes to KServe and Kubeflow.

Andreea Munteanu, MLOps product manager at Canonical, stated, “We’re happy to offer NIM through Charmed Kubernetes and Charmed Kubeflow as a company that also contributes significantly to KServe.” “Their combined efforts will enable users to fully leverage the potential of generative AI, with optimal performance, ease of use, and efficiency.”

NIM benefits dozens of other software companies just by virtue of their use of KServe in their product offerings.

Contributing to the Open-Source Community

Regarding the KServe project, NVIDIA has extensive experience. NVIDIA Triton Inference Server uses KServe’s Open Inference Protocol, as mentioned in a recent technical blog. This allows users to execute several AI models concurrently across multiple GPUs, frameworks, and operating modes.

NVIDIA concentrates on use cases with KServe that entail executing a single AI model concurrently across numerous GPUs.

NVIDIA intends to actively contribute to KServe as part of the NIM integration, expanding on its portfolio of contributions to open-source software, which already includes TensorRT-LLM and Triton. In addition, NVIDIA actively participates in the Cloud Native Computing Foundation, which promotes open-source software for several initiatives, including generative AI.

Using the Llama 3 8B or Llama 3 70B LLM models, try the NIM API in the NVIDIA API Catalogue right now. NIM is being used by hundreds of NVIDIA partners throughout the globe to implement generative AI.

Read more on Govindhtech.com

[akrnd085]

OpenShift vs Kubernetes: A Detailed Comparison

When it comes to managing and organizing containerized applications there are two platforms that have emerged. Kubernetes and OpenShift. Both platforms share the goal of simplifying deployment, scaling and operational aspects of application containers. However there are differences between them. This article offers a comparison of OpenShift vs Kubernetes highlighting their features, variations and ideal use cases.

What is Kubernetes? Kubernetes (often referred to as K8s) is an open source platform designed for orchestrating containers. It automates tasks such as deploying, scaling and managing containerized applications. Originally developed by Google and later donated to the Cloud Native Computing Foundation (CNCF) Kubernetes has now become the accepted industry standard for container management.

Key Features of Kubernetes Pods: Within the Kubernetes ecosystem, pods serve as the units for deploying applications. They encapsulate one or multiple containers.

Service Discovery and Load Balancing: With Kubernetes containers can be exposed through DNS names or IP addresses. Additionally it has the capability to distribute network traffic across instances in case a container experiences traffic.

Storage Orchestration: The platform seamlessly integrates with storage systems such as on premises or public cloud providers based on user preferences.

Automated. Rollbacks: Kubernetes facilitates rolling updates while also providing a mechanism to revert back to versions when necessary.

What is OpenShift? OpenShift, developed by Red Hat, is a container platform based on Kubernetes that provides an approach to creating, deploying and managing applications in a cloud environment. It enhances the capabilities of Kubernetes by incorporating features and tools that contribute to an integrated and user-friendly platform.

Key Features of OpenShift Tools for Developers and Operations: OpenShift offers an array of tools that cater to the needs of both developers and system administrators.

Enterprise Level Security: It incorporates security features that make it suitable for industries with regulations.

Seamless Developer Experience: OpenShift includes a built in integration/ deployment (CI/CD) pipeline, source to image (S2I) functionality, as well as support for various development frameworks.

Service Mesh and Serverless Capabilities: It supports integration with Istio based service mesh. Offers Knative, for serverless application development.

Comparison; OpenShift, vs Kubernetes 1. Installation and Setup: Kubernetes can be set up manually. Using tools such as kubeadm, Minikube or Kubespray.

OpenShift offers an installer that simplifies the setup process for complex enterprise environments.

2. User Interface: Kubernetes primarily relies on the command line interface although it does provide a web based dashboard.

OpenShift features a comprehensive and user-friendly web console.

3. Security: Kubernetes provides security features and relies on third party tools for advanced security requirements.

OpenShift offers enhanced security with built in features like Security Enhanced Linux (SELinux) and stricter default policies.

4. CI/CD Integration: Kubernetes requires tools for CI/CD integration.

OpenShift has an integrated CI/CD pipeline making it more convenient for DevOps practices.

5. Pricing: Kubernetes is open source. Requires investment in infrastructure and expertise.

OpenShift is a product with subscription based pricing.

6. Community and Support; Kubernetes has a community, with support.

OpenShift is backed by Red Hat with enterprise level support.

7. Extensibility: Kubernetes: It has an ecosystem of plugins and add ons making it highly adaptable.

OpenShift:It builds upon Kubernetes. Brings its own set of tools and features.

Use Cases Kubernetes:

It is well suited for organizations seeking a container orchestration platform, with community support.

It works best for businesses that possess the technical know-how to effectively manage and scale Kubernetes clusters.

OpenShift:

It serves as a choice for enterprises that require a container solution accompanied by integrated developer tools and enhanced security measures.

Particularly favored by regulated industries like finance and healthcare where security and compliance are of utmost importance.

Conclusion Both Kubernetes and OpenShift offer capabilities for container orchestration. While Kubernetes offers flexibility along with a community, OpenShift presents an integrated enterprise-ready solution. Upgrading Kubernetes from version 1.21 to 1.22 involves upgrading the control plane and worker nodes separately. By following the steps outlined in this guide, you can ensure a smooth and error-free upgrade process. The selection between the two depends on the requirements, expertise, and organizational context.

Example Code Snippet: Deploying an App on Kubernetes

apiVersion: v1

kind: Pod

metadata:

name: myapp-pod

labels:

app: myapp

spec:

containers:

- name: myapp-container

image: myapp:1.0 This YAML file is an example of deploying a simple application on Kubernetes. It defines a Pod with a single container running ‘myapp’.

In conclusion, both OpenShift vs Kubernetes offer robust solutions for container orchestration, each with its unique strengths and use cases. The choice between them should be based on organizational requirements, infrastructure, and the level of desired security and integration.

[venatrixnetwork-blog]

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[euteh]

How to create a project with OpenShift Origin

How to create a project with OpenShift Origin

With the OpenShift Origin web console, creating new projects and adding users to the project is quite simple.

How to create a project with OpenShift Origin With the OpenShift Origin web console, creating new projects and adding users to the project is quite simple.

If you’ve deployed OpenShift Origin (see How to Install OpenShift Origin on Ubuntu 18.04),…

[thewalrushole]

Distributed Wireless

A bunch of wireless access points running 802.11r in a bridged network, based on linux, hostapd, ect.

Objectives:

- distributed, redundant, optimised, converged coverage

Hardware:

Raspberry Pi 3B is ok for testing supporting either spectrum (2.4 or 5.0) in ht mode

SBC with dual concurrent radios to test .. Wally’s Communications DR6018 and DR6018-S V02

OS:

DD-WRT ( I really should revisit this, but seems like bloatware

Ubuntu server for ARM seems like a better option

Build:

apt-get install rfkill hostapd bridge-utils cpufrequtils dnsmasq htop lldpd sshpass wireless-tools 

remove snap from ubuntu

Netplan

Don’t need to configure wlan interfaces into the bridge hostapd will do this, loopback is a /32 from within the bridge lan range (linux is crap at strict routing so this will actually work), loopback duplicated on all AP’s for distributed DHCP, DNSMasq, ect

       version: 2

       renderer: networkd

       ethernets:

               eth0:

                       dhcp4: false

                       dhcp6: false

               lo:

                       match:

                               name: lo

                       addresses:

                               - 192.168.200.251/32

       bridges:

               br0:

                       dhcp4: false

                       dhcp6: false

                       addresses:

                               - 192.168.200.201/24

                       gateway4: 192.168.200.250

                       interfaces:

                               - eth0

Hostapd

country_code=NZ

interface=wlan0

bridge=br0

ssid=ssid here

auth_algs=1

macaddr_acl=0

ignore_broadcast_ssid=0

wpa=2

wpa_passphrase=password here

wpa_key_mgmt=WPA-PSK

wpa_pairwise=TKIP

rsn_pairwise=CCMP

hw_mode=a

wmm_enabled=1

iapp_interface=br0

okc=1

ieee80211n=1

require_ht=1

ht_capab=[MAX-AMSDU-3839][HT40+][SHORT-GI-20][SHORT-GI-40][DSSS_CCK-40]

ieee80211ac=1

ieee80211ac=1

require_vht=1

ieee80211d=0

ieee80211h=0

vht_capab=[SHORT-GI-80][SU-BEAMFORMEE]

vht_oper_chwidth=1

channel=36

#vht_oper_centr_freq_seq_idx=42

disassoc_low_ack=1

multicast_to_unicast=1

#proxy_arp=1

#rssi_reject_assoc_rssi=-75

#rssi_ignore_probe_request=-75

rssi_reject_assoc_timeout=10

mobility_domain=a1b2

nas_identifier=b827eb3b638c

r0_key_lifetime=10000

r1_key_holder=b827eb3b638c

reassociation_deadline=1000

#ft_over_ds=1

r0kh=ff:ff:ff:ff:ff:ff * 00112233445566778899aabbccddeeff

DNSMasq

port=53

domain-needed

resolv-file=/etc/resolv.dns

strict-order

server=/200.168.192.in-addr.arpa/192.168.200.250

address=/double-click.net/127.0.0.1

ipset=/yahoo.com/google.com/vpn,search

server=192.168.200.250@br0

interface=br0

Thinks to do

Docker and Openshift Origin

Salt Stack package and configuration management

sshd authentication allow non privilege users during startup/shutdown

pretty sure if I set the radius interface and nas identifier it will control which interface hostapd used for broadcast

cluster DHCP and DNSMasq if required

Clean up and format this blog

TCP multipath dual ip uplinks

wireless backhaul backup

QoS/WMM

build standard vlan on bridge interface (management lan, user, security ect)

build mutiple SSID to vlan

something like vrf to ensure segmentation of SSID/VLANS

Manage all this via salt.. and look into dbus remote send

move to WPA3 or Radius or something more secure

Zigbee and BT....

Wifi spectrum management (channel management/switching)

RF location services

DHCP PXE boot for future management of zigbee ect.

802.11ac dongle, onboard 5ghz radio and antenna are weak switched to 2.4(g) 

Do I

local cluster/bind9 <--> local dnsmasq 

local cluster/bind isc-dhcp-server <--> local dnsmasq

Why, bind9 able to look up root no fowarder required, and local entries for windows ect, but dnsmasq for fast caching .. is it overkill, bind9 is supposed to cache too in ram, but we want this highly available and fast

Same for dhcp fast/redundancy

References / Reading

http://www.routereflector.com/2016/11/working-with-vrf-on-linux/

https://www.raspberrypi.org/documentation/configuration/wireless/access-point-bridged.md

http://ftp.gwdg.de/pub/linux/linux-magazin/listings/raspberry-pi-geek.com/04/AccessPoint/Listing04.txt

https://www.linux.com/topic/networking/advanced-dnsmasq-tips-and-tricks/

[arunsinghus-blog]

Openshift Interview Questions

Openshift Interview Questions For Freshers & Experienced

OpenShift Origin, likewise referred to since August 2018 as OKD (Origin Community Distribution) is the upstream network venture utilized in OpenShift Online, OpenShift Dedicated, and OpenShift Container Platform. ... Root gives an open source application compartment stage.

read the some new things like openshift programming for new invention , 

continue for read Openshift interview question 

[codecraftshop]

Deploy jenkins on openshift cluster - deploy jenkins on openshift | openshift#deploy #jenkins #openshift #deployjenkinsonopenshift #jenkinsonopenshift deploy jenkins on openshift,deploy jenkins x on openshift,install jenkins on openshift,deploying jenkins on openshift part 2,deploy jenkins on openshift origin,deploy jenkins on openshift cluster,demo jenkins ci cd on openshift,how to deploy jenkins in openshift,jenkins pipeline tutorial for beginners,openshift,jenkins,fedora,cloud,deployments,pipeline,openshift origin,redhat,container platform,redhat container platform,docker,container https://www.youtube.com/channel/UCnIp4tLcBJ0XbtKbE2ITrwA?sub_confirmation=1&app=desktop About: 00:00 Deploy Jenkins on Openshift cluster - deploy jenkins on openshift - Install Jenkins on Openshift In this course we will learn about deploy jenkins on openshift cluster. How to access jenkins installed on openshift cluster. deploy jenkins on openshift cluster - Red Hat is the world's leading provider of enterprise open source solutions, including high-performing Linux, cloud, container, and Kubernetes technologies. deploy jenkins on openshift origin - Continuous Integration (CI) is a development practice that requires developers to integrate code into a shared repository several times a day Openshift/ Openshift4 a cloud based container to build deploy test our application on cloud. In the next videos we will explore Openshift4 in detail. 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 .

[venatrix191-blog]

Use the power of kubernetes with Openshift Origin

Get the most modern and powerful Openshift OKD subscription with VENATRIX.

OpenShift Origin / OKD is an open source cloud development Platform as a Service (PaaS). This cloud-based platform allows developers to create, test and run their applications and deploy them to the cloud.

Automate the Build, Deployment and Management of your Applications with openshift Origin Platform.

OpenShift is suitable for any application, language, infrastructure, and industry. Using OpenShift helps developers to use their resources more efficiently and flexible, improve monitoring and maintenance, harden the applications security and overall make the developer experience a lot better. Venatrix’s OpenShift Services are infrastructure independent and therefore any industry can benefit from it.

What is openshift Origin?

Red Hat OpenShift Origin is a multifaceted, open source container application platform from Red Hat Inc. for the development, deployment and management of applications. OpenShift Origin Best vps hosting container Platform can deploy on a public, private or hybrid cloud that helps to deploy the applications with the use of Docker containers. It is built on top of Kubernetes and gives you tools like a web console and CLI to manage features like load balancing and horizontal scaling. It simplifies operations and development for cloud native applications.

Red Hat OpenShift Origin Container Platform helps the organization develop, deploy, and manage existing and container-based apps seamlessly across physical, virtual, and public cloud infrastructures. Its built on proven open source technologies and helps application development and IT operations teams modernize applications, deliver new services, and accelerate development processes.

Developers can quickly and easily create applications and deploy them. With S2I (Source-to-Image), a developer can even deploy his code without needing to create a container first. Operators can leverage placement and policy to orchestrate environments that meet their best practices. It makes the development and operations work fluently together when combining them in a single platform. It deploys Docker containers, it gives the ability to run multiple languages, frameworks and databases on the same platform. Easily deploy microservices written in Java, Python, PHP or other languages.

[innovationgreys]

Luxcorerender reality 4.3

#LUXCORERENDER REALITY 4.3 SOFTWARE#

While Kubernetes isn’t going to run on IBM i, and IBM i isn’t going to morph into a version of Linux, the platforms can still work closely together, especially with OpenShift running directly on Power (although Merlin also will run on Red Shift on X86. Google, which created the Borg workload and container scheduler, the origination of Kubernetes, to simplify the massive workloads running in its cloud datacenters, and which open sourced a layer of Borg as Kubernetes in 2014, didn’t develop Kubernetes to be able to run on other operating systems – not Windows, not Unix, and certainly not IBM i. What’s more, all Kubernetes runs on Linux, which makes Merlin a Linux app at the end of the day. In fact, it runs only in containers managed by Kubernetes, and the only Kubernetes distribution it supports is IBM’s own Red Hat OpenShift.

#LUXCORERENDER REALITY 4.3 SOFTWARE#

Instead of making this software all native, Big Blue wants it to run in the same modern manner in which the wider IT world runs stuff, which means containers. Merlin is also unique in how IBM chose to deliver it. And in the future, Merlin will have even more goodies, including possibly an app catalog, PTF management, security capabilities, and more integrations with tools from third-party vendors. It’s a framework, if you will, that today includes a Web-based IDE, connectors for Git and Jenkins, and impact analysis and code conversion software OEMed from ARCAD Software. For starters, it isn’t a modernization tool per se, but more like a collection of tools that allow IBM i customers to begin developing IBM i applications using modern DevOps methods. Merlin is a different sort of product than what IBM typically ships. Just like IBM i had to become more like Unix and Windows Server, in many ways, to survive. One of the questions has to do with IBM i’s relationship with Linux, and whether it will have to be become more like Linux to survive. The recent launch of Merlin, a Linux-based collection of tools for creating next-gen IBM i applications, has raised questions about the future of IBM i.

Will IBM i Become More Like Linux? - IT Jungle.