Jozu Integrations

Docker takes away repetitive, mundane configuration tasks and is used throughout the development lifecycle for fast, easy and portable application development, desktop and cloud. Docker’s comprehensive end-to-end platform includes UIs, CLIs, APIs and security that are engineered to work together across the entire application delivery lifecycle. Get a head start on your coding by leveraging Docker images to efficiently develop your own unique applications on Windows and Mac. Create your multi-container application using Docker Compose. Integrate with your favorite tools throughout your development pipeline, Docker works with all development tools you use including VS Code, CircleCI and GitHub. Package applications as portable container images to run in any environment consistently from on-premises Kubernetes to AWS ECS, Azure ACI, Google GKE and more. Leverage Docker Trusted Content, including Docker Official Images and images from Docker Verified Publishers.

Run advanced apps on a secured and managed Kubernetes service. GKE is an enterprise-grade platform for containerized applications, including stateful and stateless, AI and ML, Linux and Windows, complex and simple web apps, API, and backend services. Leverage industry-first features like four-way auto-scaling and no-stress management. Optimize GPU and TPU provisioning, use integrated developer tools, and get multi-cluster support from SREs. Start quickly with single-click clusters. Leverage a high-availability control plane including multi-zonal and regional clusters. Eliminate operational overhead with auto-repair, auto-upgrade, and release channels. Secure by default, including vulnerability scanning of container images and data encryption. Integrated Cloud Monitoring with infrastructure, application, and Kubernetes-specific views. Speed up app development without sacrificing security.

Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google, combined with best-of-breed ideas and practices from the community. Designed on the same principles that allows Google to run billions of containers a week, Kubernetes can scale without increasing your ops team. Whether testing locally or running a global enterprise, Kubernetes flexibility grows with you to deliver your applications consistently and easily no matter how complex your need is. Kubernetes is open source giving you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you effortlessly move workloads to where it matters to you.

The Kubernetes platform for big ideas. Empower developers to innovate and ship faster with the leading hybrid cloud, enterprise container platform. Red Hat OpenShift offers automated installation, upgrades, and lifecycle management throughout the container stack—the operating system, Kubernetes and cluster services, and applications—on any cloud. Red Hat OpenShift helps teams build with speed, agility, confidence, and choice. Code in production mode anywhere you choose to build. Get back to doing work that matters. Red Hat OpenShift is focused on security at every level of the container stack and throughout the application lifecycle. It includes long-term, enterprise support from one of the leading Kubernetes contributors and open source software companies. Support the most demanding workloads including AI/ML, Java, data analytics, databases, and more. Automate deployment and life-cycle management with our vast ecosystem of technology partners.

GitLab is a complete DevOps platform. With GitLab, you get a complete CI/CD toolchain out-of-the-box. One interface. One conversation. One permission model. GitLab is a complete DevOps platform, delivered as a single application, fundamentally changing the way Development, Security, and Ops teams collaborate. GitLab helps teams accelerate software delivery from weeks to minutes, reduce development costs, and reduce the risk of application vulnerabilities while increasing developer productivity. Source code management enables coordination, sharing and collaboration across the entire software development team. Track and merge branches, audit changes and enable concurrent work, to accelerate software delivery. Review code, discuss changes, share knowledge, and identify defects in code among distributed teams via asynchronous review and commenting. Automate, track and report code reviews.

The leading open source automation server, Jenkins provides hundreds of plugins to support building, deploying and automating any project. As an extensible automation server, Jenkins can be used as a simple CI server or turned into the continuous delivery hub for any project. Jenkins is a self-contained Java-based program, ready to run out-of-the-box, with packages for Windows, Linux, macOS and other Unix-like operating systems. Jenkins can be easily set up and configured via its web interface, which includes on-the-fly error checks and built-in help. With hundreds of plugins in the Update Center, Jenkins integrates with practically every tool in the continuous integration and continuous delivery toolchain. Jenkins can be extended via its plugin architecture, providing nearly infinite possibilities for what Jenkins can do. Jenkins can easily distribute work across multiple machines, helping drive builds, tests and deployments across multiple platforms faster.

The Industry Standard Universal Binary Repository Manager. Supports all major package types (over 27 and growing) such as Maven, npm, Python, NuGet, Gradle, Go, and Helm including Kubernetes and Docker as well as integration with leading CI servers and DevOps tools that you already use. Additional functionalities include: - High Availability that scales to infinity with active/active clustering of your DevOps environment and scales as business grows - On-Prem, Cloud, Hybrid, or Multi-Cloud Solution - De Facto Kubernetes Registry managing application packages, operating system’s component dependencies, open source libraries, Docker containers, and Helm charts with full visibility of all dependencies. Compatible with a growing list of Kubernetes cluster providers.

CNCF Harbor is an open-source project that enhances container registry capabilities with a focus on security and compliance. It builds upon basic registry functionality by offering features such as vulnerability scanning to identify known security weaknesses in images, role-based access control for granular image access management, image signing to ensure authenticity and prevent tampering, and replication for efficient syncing of images across multiple other registries. Harbor strengthens the security of the image management process. It can be particularly beneficial for organizations that prioritize security and compliance in their containerized environments. However, users should be aware that setting up and maintaining Harbor can require additional effort and expertise compared to simpler container registries. 

Hugging Face is a leading platform for AI and machine learning, offering a vast hub for models, datasets, and tools for natural language processing (NLP) and beyond. The platform supports a wide range of applications, from text, image, and audio to 3D data analysis. Hugging Face fosters collaboration among researchers, developers, and companies by providing open-source tools like Transformers, Diffusers, and Tokenizers. It enables users to build, share, and access pre-trained models, accelerating AI development for a variety of industries.

Model Context Protocol (MCP) is an open protocol designed to standardize how applications provide context to large language models (LLMs). It acts as a universal connector, similar to a USB-C port, allowing LLMs to seamlessly integrate with various data sources and tools. MCP supports a client-server architecture, enabling programs (clients) to interact with lightweight servers that expose specific capabilities. With growing pre-built integrations and flexibility to switch between LLM vendors, MCP helps users build complex workflows and AI agents while ensuring secure data management within their infrastructure.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.

Sonatype Nexus Repository is a robust binary repository manager designed to store, manage, and distribute open-source components, dependencies, and artifacts across the software development lifecycle (SDLC). It supports over 20 formats, including Maven, npm, PyPI, and Docker, allowing for seamless integration with build tools and CI/CD pipelines. With advanced features like high availability, disaster recovery, and scalability across cloud platforms, Nexus Repository ensures secure and efficient management of your software artifacts. The platform enhances collaboration, automates workflows, and improves visibility into your software supply chain, helping teams manage dependencies and improve software quality.

The fully managed Azure Kubernetes Service (AKS) makes deploying and managing containerized applications easy. It offers serverless Kubernetes, an integrated continuous integration and continuous delivery (CI/CD) experience, and enterprise-grade security and governance. Unite your development and operations teams on a single platform to rapidly build, deliver, and scale applications with confidence. Elastic provisioning of additional capacity without the need to manage the infrastructure. Add event-driven autoscaling and triggers through KEDA. Faster end-to-end development experience with Azure Dev Spaces including integration with Visual Studio Code Kubernetes tools, Azure DevOps, and Azure Monitor. Advanced identity and access management using Azure Active Directory, and dynamic rules enforcement across multiple clusters with Azure Policy. Available in more regions than any other cloud providers.

Amazon Elastic Kubernetes Service (Amazon EKS) is a fully managed Kubernetes service. Customers such as Intel, Snap, Intuit, GoDaddy, and Autodesk trust EKS to run their most sensitive and mission-critical applications because of its security, reliability, and scalability. EKS is the best place to run Kubernetes for several reasons. First, you can choose to run your EKS clusters using AWS Fargate, which is serverless compute for containers. Fargate removes the need to provision and manage servers, lets you specify and pay for resources per application, and improves security through application isolation by design. Second, EKS is deeply integrated with services such as Amazon CloudWatch, Auto Scaling Groups, AWS Identity and Access Management (IAM), and Amazon Virtual Private Cloud (VPC), providing you a seamless experience to monitor, scale, and load-balance your applications.

Microservices, containers and Kubernetes help to free apps from infrastructure, enabling them to work independently and run anywhere. With VMware Tanzu, you can make the most of these cloud native patterns, automate the delivery of containerized workloads, and proactively manage apps in production. It’s all about freeing developers to do their thing: build great apps. Adding Kubernetes to your infrastructure doesn’t have to add complexity. With VMware Tanzu, you can ready your infrastructure for modern apps with consistent, conformant Kubernetes everywhere. Provide a self-service, compliant experience for developers that clears their path to production. Then centrally manage, govern and observe all clusters and apps across clouds. It’s that simple.

MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.

Easily store, share, and deploy your container software anywhere. Push container images to Amazon ECR without installing or scaling infrastructure, and pull images using any management tool. Share and download images securely over Hypertext Transfer Protocol Secure (HTTPS) with automatic encryption and access controls. Access and distribute your images faster, reduce download times, and improve availability using a scalable, durable architecture. Amazon ECR is a fully managed container registry offering high-performance hosting, so you can reliably deploy application images and artifacts anywhere. Meet your organization’s image compliance security requirements using insights from common vulnerabilities and exposures (CVEs) and the Common Vulnerability Scoring System (CVSS). Publish containerized applications with a single command and easily integrate your self-managed environments.

The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow. Kubeflow provides a custom TensorFlow training job operator that you can use to train your ML model. In particular, Kubeflow's job operator can handle distributed TensorFlow training jobs. Configure the training controller to use CPUs or GPUs and to suit various cluster sizes. Kubeflow includes services to create and manage interactive Jupyter notebooks. You can customize your notebook deployment and your compute resources to suit your data science needs. Experiment with your workflows locally, then deploy them to a cloud when you're ready.

GitHub Actions is a powerful automation tool that enables developers to streamline their software workflows directly within GitHub. It allows teams to build, test, and deploy code automatically using CI/CD pipelines triggered by events such as code pushes or pull requests. With support for multiple programming languages and environments, developers can run workflows across Linux, macOS, and Windows. GitHub Actions also provides hosted and self-hosted runners for flexible execution. It simplifies repetitive tasks like code reviews, issue management, and deployment processes. With real-time logs and built-in secret management, it ensures transparency and security. Overall, GitHub Actions helps teams automate development processes and deliver software faster.