OpenShift

OpenShift | findAIList | findAIList

Use Cases

Automated Application Deployments with CI/CD

Reduces manual effort and errors in application deployment processes, accelerating release cycles.

VIEW EXECUTION STEPS

Step 1: Define a CI/CD pipeline using OpenShift Pipelines.

Step 2: Configure the pipeline to build and test application code.

Step 3: Integrate the pipeline with a Git repository for automated triggers.

Step 4: Deploy the application to OpenShift environments upon successful builds.

Modernizing Legacy Applications

Enables organizations to migrate and modernize existing applications to a containerized environment, improving scalability and maintainability.

VIEW EXECUTION STEPS

Step 1: Containerize the legacy application using Docker.

Step 2: Deploy the containerized application to OpenShift.

Step 3: Expose the application through OpenShift services.

Step 4: Monitor and manage the application using OpenShift tools.

Building and Deploying Microservices

Facilitates the development and deployment of microservices-based applications, improving application agility and scalability.

VIEW EXECUTION STEPS

Step 1: Design the microservices architecture.

Step 2: Develop individual microservices using appropriate technologies.

Step 3: Containerize each microservice using Docker.

Step 4: Deploy the microservices to OpenShift and manage them using Service Mesh.

Deploying AI/ML Models

Streamlines the deployment and management of AI/ML models, enabling organizations to quickly leverage AI in their applications.

VIEW EXECUTION STEPS

Step 1: Train and package the AI/ML model.

Step 2: Containerize the model using Docker.

Step 3: Deploy the model to OpenShift using OpenShift AI.

Step 4: Expose the model as a service and integrate it with applications.

Edge Computing Deployments

Enables organizations to deploy applications closer to the data source, reducing latency and improving performance for edge computing use cases.

VIEW EXECUTION STEPS

Step 1: Design the edge computing architecture.

Step 2: Containerize the application for edge deployment.

Step 3: Deploy the application to OpenShift clusters at the edge.

Step 4: Manage and monitor the application using OpenShift's centralized management tools.

Alternative Tools

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Netlify

The Composable Web Platform for High-Performance Digital Experiences.

Freemium

From $19/mo

Automated CI/CD deployments

Edge-side compute and logic execution

Data orchestration via GraphQL

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Vultr

The AI-first Global Cloud Platform, offering a broad array of AMD and NVIDIA GPUs to virtual CPUs.

Paid

From $0.06/mo

AI Model Training

AI Inference

Cloud Computing

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Cloud Native Now (formerly MediaOps)

Cloud Native Now delivers news, webinars, and podcasts focused on cloud-native development, platforms, networking, and security.

Developer

Free

View Pricing

Stay updated on the latest cloud-native news and trends.

Learn about cloud-native development best practices.

Explore cloud-native platform options.

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Golem Network

Golem Network is a decentralized platform that allows users to share and access computing power.

Developer

Freemium

View Pricing

Share unused computing resources on the network.

Access computing power for rendering tasks.

Utilize computing resources for AI model training.

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KITTI Dataset

KITTI Dataset provides a suite of real-world computer vision benchmarks for autonomous driving research and development.

Developer

Free

View Pricing

Evaluating stereo vision algorithms

Benchmarking optical flow methods

Assessing visual odometry techniques

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Kapa.ai

Kapa.ai builds accurate AI agents from your technical documentation and other sources, enabling deployment across support, documentation, and internal teams.

Developer

Freemium

From $29/mo

Connect to existing documentation sources

Deploy AI chatbot across multiple platforms

Provide grounded answers based on documentation

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K9s

K9s is a terminal-based UI to interact with and manage Kubernetes clusters in real-time.

Developer

Free

View Pricing

Monitor Kubernetes resource status in real-time

Manage Kubernetes deployments

View and interact with container logs

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k3d

k3d is a lightweight Kubernetes distribution focused on providing a fast, simple, and local Kubernetes experience for development and testing.

Developer

Free

View Pricing

Create local Kubernetes clusters

Manage local Kubernetes clusters

Test Kubernetes deployments locally

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About OpenShift

Core Capabilities

Main Tasks

Build containerized applications

Deploy applications to Kubernetes clusters

Manage and scale applications

Automate deployments with CI/CD pipelines

Monitor application health and performance

Secure applications with built-in security features

Key Features

Source-to-Image (S2I)

OpenShift Pipelines

Operator Lifecycle Manager (OLM)

Service Mesh

Knative

Use Cases

Automated Application Deployments with CI/CD

Modernizing Legacy Applications

Building and Deploying Microservices

Deploying AI/ML Models

Edge Computing Deployments

Quick Start Guide

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Cons

Frequently Asked Questions

Reviews & Ratings

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Developer Sandbox

Red Hat OpenShift Dedicated

Specs

Core Tasks

Categories

Alternative Tools

Netlify

Vultr

Cloud Native Now (formerly MediaOps)

Golem Network

KITTI Dataset

Kapa.ai

K9s

k3d

Data Interface