Originally developed by DeployHub, Ortelius was created to provide a means to automate configuration at the application level. It also provides a central catalog of services that makes it easier to consume and deploy services across clusters that also tracks application versions and dependencies as updates to services are made.

DeployHub CEO Tracy Ragan said Ortelius is now being donated to the CD Foundation, an arm of the Linux Foundation, which is working to create de facto continuous delivery standards. As such, Ortelius will benefit from contributions from other members of the consortium that includes Google, CloudBees, CircleCI, JFrog, IBM, GitLab, Netflix and DeployHub.

The core CF Foundation projects are the open source Jenkins continuous integration/continuous delivery (CI/CD) platform; Jenkins X, an open source CI/CD solution on Kubernetes; Spinnaker, an open source CD platform; and the Tekton specification for building CI/CD components.

Ortelius already integrates with CD orchestration tools and deployment tools such as Helm, Ansible and Spinnaker. The opportunity now is to address the entire application development life cycle of cloud-native applications using a GitOps methodology, said Ragan.

While in theory the rise of Kubernetes should make it easier to automate CD processes across multiple platforms, Ragan noted that in practice there are still substantial differences between instances of Kubernetes that will require tools to automate the rollout of microservices across multiple clusters. Ortelius allows IT teams to logically manage groups for microservices as a single entity in much the same way IT teams manage monolithic applications as a single entity, she said.

Ragan also noted that not all microservices are of equal value, so different approaches to managing them are required based on the number of dependencies they have and the value of the microservices to the business. As it becomes apparent IT teams will soon be managing perhaps thousands of microservices, the need for a standard approach that integrates with multiple CD platforms becomes more acute. In fact, she said, IT teams are approaching a new era when chaos engineering principles will need to be applied to the management of microservices.

Longer-term, Ragan said Ortelius will also make it feasible to employ machine learning algorithms to provide predictive analytics that can be used to optimize the microservices environment. That capability eventually will provide a critical capability for managing microservices at scale. It may also serve to further the adoption of best CD practices that thus far have proven elusive to achieve in IT environments where each platform has unique attributes that make automating application delivery challenging regardless of what type of application is involved.

In the meantime, IT organizations are being invited to contribute to the Ortelius project, now that it’s part of the CD Foundation. The more contributions that are made, the sooner the Ortelius platform graduates, which can’t come soon enough for many organizations that have already invested in microservices.

IBM Corp. said today it’s hoping to provide a standardized solution for developers to create and deploy machine learning models in production and make them portable to any cloud platform.

To do so, it said it’s open-sourcing the Kubeflow machine learning platform on Tekton, a continuous integration/continuous development platform developed by Google LLC. It’s popular with developers who use Kubernetes to manage containerized applications, which can run unchanged across many computing environments.

IBM said it created Kubeflow Pipelines on Tekton in response to the need for a more reliable solution for deploying, monitoring and governing machine learning models in production on any cloud platform. That’s important, IBM says, because hybrid cloud models are rapidly becoming the norm for many enterprises that want to take advantage of the benefits of running their most critical business applications across distributed computing environments.

One of the main complaints of data science and application development and delivery teams is the difficulty of creating portable machine learning models that can run on any cloud, Animesh Singh, IBM’s chief architect of data and AI open source, and Trent Gray-Donald, a distinguished engineer in AI, said in a blog post. They cite problems such as manual handoffs, frantic monitoring and loose governance, which can cause big delays in the deployment of new models.

IBM’s response to this has been to double down on Machine Learning Operations, or MLOps, which refers to a practice for collaboration and communication between data scientists and operations professionals to help manage production ML lifecycles.

IBM has since adopted Kubeflow Pipelines as the basis of its MLOps. Kubeflow is a machine learning platform that’s focused on distributed training, hyperparameter optimization, production model serving and management. Singh and Gray-Donald said Kubeflow was chosen primarily for its ability to tap into the Kubernetes ecosystem, which makes it compatible with containers and gives it greater scalability.

Kubeflow Pipelines also uses the Python interconnected that’s familiar to many developers for defining and deploying Pipelines. That enables metadata collection and lineage tracking of ML models.

Now, IBM has decided to open-source a revamped version of Kubeflow Pipelines especially for Tekton, which is an open-source project that provides a framework to create cloud-native continuous integration/continuous deployment pipelines quickly. With Tekton, developers can build, test, and deploy CI/CD pipelines across multiple cloud providers or on-premises systems by abstracting away the underlying implementation details.

“The decision to adopt Kubeflow Pipelines on our side came with an internal requirement to redesign Kubeflow Pipelines to run on top of Tekton,” Singh and Gray-Donald said.

Available today, the new Kubeflow Pipelines on Tekton provides Kubernetes-style resources for developers to declare CI/CD pipelines. It also introduces several new Custom Resource Definitions such as Task, Pipeline, TaskRun and PipelineRun.

In addition, IBM has created OpenShift Pipelines based on Tekton for its Red Hat OpenShift platform. That’s used to automate the building, testing and deployment of containerized applications for on-premises and public cloud platforms.

“Within IBM, we have standardized on Tekton as a cloud CI/CD engine, and OpenShift Pipelines is based on Tekton,” Singh and Gray-Donald said.

IBM is also planning to add to its stack with the coming launch of Watson AI Platform Pipelines. That will provide features that make it even easier for developers to build ML pipelines with a drag-and-drop canvas, pipeline components registry and production-grade logging. It will also provide better governance capabilities via integrations with IBM Watson Studio, Watson AutoAI, Watson Knowledge Catalog and others.

IBM has recently announced the beta availability of a new serverless compute service called IBM Cloud Code Engine. The service is a managed serverless platform that runs containerized workloads, for example web apps, micro-services, event-driven functions and batch jobs.

A follow up article describes the use cases and the open source technologies used to build Code Engine, including Knative, the Kubernetes-based platform to deploy and manage serverless workloads, the service mesh Istio, and Tekton, the framework for creating continuous integration and delivery (CI/CD) systems. Cong Nguyen, developer advocate at IBM, tweets:

IBM emphasises the open source layers and the portability of the platform, explaining that while it offers a simplified user experience, developers can still fully customize the Kubernetes data model or reuse existing deployment scripts on Code Engine.

Depending on the load, Code Engine automatically scales the containers, including scaling to zero when no requests are active. A container image is not a prerequisite to use the service: Code Engine can bundle the source-code from a Git repository with a supported runtime environment, what IBM calls a “buildpack”, and generate the container. A guide on how to do it is available in the IBM Cloud Design Engineer Gitbook.

The About IBM Cloud Code Engine covers the main concepts, names and terminology used on the platform. The first tutorial provided by IBM shows how to build a visual recognition platform, using Code Engine and the Cloud CLI.

Harald Uebele, developer advocate at IBM Germany, wrote a detailed article on in his personal blog on how to run containers serverless on Code Engine, highlighting the use cases where the new platform should excel:

While Christophe Boulangé, Cloud Director at BNP Paribas, labels it the “FaaS next-generation” other developers question the advantages against other existing offers: “What is the strongest part of this solution against AWS lambda, or Cloud Functions from GCP?”

The Linux Foundation Releases Jenkins Essentials Course (LFS267)

The Linux Foundation, in collaboration with the Continuous Delivery Foundation (CDF), announced the availability of LFS267 – Jenkins Essentials, a new training course targeting DevOps engineers, Quality Assurance personnel, Site Reliability Engineers (SREs), software developers, and architects who want to deepen their expertise with Jenkins for CI/CD workflows.

Why Jenkins Still Matters

Jenkins is an open-source automation server that offers hundreds of plugins supporting the building, deploying, and automation of virtually any software project. First released in 2004, Jenkins has maintained its position as one of the most widely adopted CI servers in the world. Its extensibility and large community make it a common choice for teams building CI/CD pipelines at scale.

What You Will Learn in LFS267

The course covers a broad range of practical, production-relevant Jenkins skills. By the end of the course, students will be able to:

• Deploy Jenkins on Kubernetes — set up and manage Jenkins within a Kubernetes cluster for containerized workloads.
• Automate Jenkins installation with IaC — apply Infrastructure-as-Code principles to provision and configure Jenkins reliably.
• Configure a highly available Jenkins server — architect Jenkins for resilience and uptime in production environments.
• Scale with static and dynamic build agents — expand Jenkins infrastructure horizontally to handle varying build loads.
• Automate routine tasks via CLI and REST API — script and automate common Jenkins administration and job management tasks.
• Implement fine-grained security controls — secure Jenkins jobs and resources with role-based access and security policies.
• Set up effective CI/CD feedback loops — integrate notifications and reporting so teams get actionable build feedback quickly.
• Build complex multi-branch pipelines — create pipelines that mirror real-world branching strategies and release flows.
• Automate pull request workflows with GitOps — integrate Jenkins with Git repositories to trigger and validate PRs automatically.

These competencies map directly to SRE, DevOps engineer, and release engineer roles.

Prerequisites

Before enrolling in LFS267, students should have a working familiarity with Jenkins, Kubernetes, and Docker. Those who are new to any of these technologies can first complete free introductory courses from The Linux Foundation:

• Introduction to Jenkins (LFS167x)
• Introduction to Cloud Infrastructure Technologies
• Introduction to Kubernetes

About the Course Authors

LFS267 was developed by Himanshu Gautam and Deepika Gautam, co-founders of Aplima Inc., a CI/CD solutions provider.

Himanshu Gautam is an author, trainer, speaker, and software engineer with over 20 years of industry experience. He focuses on cloud-native architecture and DevOps practices, and has also authored the CI/CD with Jenkins X course (LFS268) for the Linux Foundation.

Deepika Gautam is an author, trainer, speaker, and DevOps evangelist with nearly two decades of software industry experience. She specializes in implementing DevOps toolchains across multi-cloud environments and authored the Introduction to Jenkins course (LFS167x).

About the Continuous Delivery Foundation

The Continuous Delivery Foundation (CDF) is a vendor-neutral organization under the Linux Foundation that works to establish best practices for software delivery automation, promote adoption of CD tooling, and encourage collaboration across the ecosystem. The CDF hosts several prominent open-source projects including Jenkins, Jenkins X, Tekton, and Spinnaker.

About the Linux Foundation

Founded in 2000, the Linux Foundation supports open-source collaboration across software, standards, data, and hardware. It is home to critical infrastructure projects including Linux, Kubernetes, and Node.js, and is supported by more than 1,000 member organizations worldwide.

Linux Foundation Releases Jenkins Essentials Training Course (LFS267)

The Linux Foundation, in collaboration with the Continuous Delivery Foundation (CDF), announced the availability of a new instructor-developed training course: LFS267 – Jenkins Essentials. The course targets DevOps engineers, Quality Assurance (QA) professionals, Site Reliability Engineers (SREs), software developers, and architects who want to build practical expertise with Jenkins for continuous integration and continuous delivery (CI/CD) workflows.

Why Jenkins Still Matters

Jenkins is an open-source automation server that has been a cornerstone of software delivery pipelines since its inception in 2004. With hundreds of plugins covering build, test, deploy, and notification workflows, it remains one of the most widely adopted CI servers in the industry. As organizations migrate workloads to Kubernetes and adopt GitOps practices, the need to operate Jenkins at scale—and to integrate it cleanly into cloud-native environments—has grown significantly.

What You Will Learn in LFS267

The course is structured to take learners from foundational Jenkins operations through advanced, production-grade configurations. Key topics include:

• Running Jenkins on Kubernetes – deploying and managing Jenkins controller and agents inside a Kubernetes cluster.
• Infrastructure-as-Code (IaC) automation – automating Jenkins installation and configuration using IaC principles to eliminate manual, error-prone setup.
• High availability – architecting a highly available Jenkins environment to minimize downtime.
• Scaling with static and dynamic agents – leveraging both pre-provisioned static build agents and on-demand dynamic agents to match workload requirements.
• CLI and REST API automation – scripting routine Jenkins administrative tasks to reduce toil.
• Fine-grained security controls – implementing role-based access and job-level security to protect CI/CD pipelines.
• Effective CI/CD feedback loops – configuring notifications and reporting so teams get actionable build and test feedback quickly.
• Multi-branch pipelines – building complex, real-world pipelines that handle feature branches, release branches, and hotfixes simultaneously.
• GitOps-driven pull request workflows – automating PR validation and merge gates using GitOps principles.

Together, these skills map directly to SRE, DevOps engineer, and release engineer job responsibilities.

Prerequisites

Students should arrive with a working understanding of Jenkins, Kubernetes, and Docker before enrolling. If you need to fill gaps in any of those areas, the Linux Foundation offers free introductory courses that can serve as on-ramps:

• Introduction to Jenkins (LFS167x) – free foundational Jenkins course.
• Introduction to Cloud Infrastructure Technologies – covers core cloud and container concepts.
• Introduction to Kubernetes – covers Kubernetes fundamentals needed to follow the cluster-deployment labs.

Course Authors

LFS267 was developed by Himanshu Gautam and Deepika Gautam, co-founders of Aplima Inc., a CI/CD solutions provider.

Himanshu brings more than 20 years of software engineering experience. He is a practitioner focused on cloud-native architecture and DevOps culture, and also authored the CI/CD with Jenkins X (LFS268) course for the Linux Foundation.

Deepika has nearly two decades of software industry experience specializing in DevOps toolchain implementation across multi-cloud environments. She authored the Introduction to Jenkins (LFS167x) course.

Pricing and Access

At the time of announcement, LFS267 was priced at $299, which includes unlimited access to all course content and hands-on labs for one year. The course was available to enroll immediately upon announcement.

Note: Pricing and availability may have changed since the original October 2020 announcement. Check the Linux Foundation Training catalog for current details.

About the Linux Foundation and the Continuous Delivery Foundation

Founded in 2000, the Linux Foundation is a nonprofit organization that hosts collaborative development of critical open-source infrastructure, including Linux, Kubernetes, and Node.js, and is supported by more than 1,000 member organizations.

The Continuous Delivery Foundation (CDF) is a vendor-neutral, Linux Foundation-hosted organization dedicated to improving software delivery through security and speed. The CDF stewards some of the fastest-growing CD projects, including Jenkins, Jenkins X, Tekton, and Spinnaker, and drives best-practice education and cross-project collaboration across the CD ecosystem.