May 2018 Summaries

This week featured a webinar with Oren Rubin, Founder of Testim, discussing how machine learning and Kubernetes pipelines can simplify the process of creating scalable UI tests as part of a software delivery pipeline. The session, led by Rubin and Dan Garfield, explored the challenges and advantages of UI and end-to-end testing, highlighting how machine learning can enhance these processes. The webinar included a demonstration and a live Q&A session, with a recorded version available for those who missed it. Participants were encouraged to engage further by scheduling one-on-one sessions or demos with Testim and to explore implementing Testim in a Codefresh pipeline, with YAML configuration details provided to facilitate integration and result parsing.

In a recent webinar, Testim's Founder, Oren Rubin, alongside Kubernaut Dan Garfield, discussed how machine learning and Kubernetes pipelines can simplify the process of creating scalable UI tests within software delivery pipelines. The session addressed two major challenges: establishing a suitable environment and developing tests that can be effectively scaled. Participants were introduced to the benefits and challenges of UI and end-to-end testing, with practical demonstrations and a live Q&A segment enhancing the learning experience. For those unable to attend, a recording of the webinar is available, and further resources such as a slide deck and one-on-one consultations are offered.

In a recent webinar, Stef Arnold from SUSE CaaS Platform and Josh Dolitsky from Codefresh discussed enhancing the delivery of Kubernetes-based applications using Helm and ChartMuseum, two open-source tools. They demonstrated how Helm can be utilized to package applications into charts, which are deployable collections of Kubernetes files, and subsequently release these charts to ChartMuseum, which functions as an artifact repository for Helm charts. The session was recorded for those who missed it, and additional resources such as the slide deck are available, with options for scheduling one-on-one consultations or signing up for a Codefresh account for newcomers.

Codefresh has introduced Managed Helm Repositories for all accounts, leveraging ChartMuseum, an open-source Helm repository server, to offer customers an integrated solution for storing and distributing Helm charts both within and outside the Codefresh platform. This development acknowledges the contributions from the Kubernetes open-source community and allows users to manage their Helm repositories through their Account Settings by linking to a default repository named CF_HELM_DEFAULT. Users can utilize token-based authentication for chart uploads via the ChartMuseum helm-push plugin, requiring them to generate a Codefresh API Token and configure their environment accordingly. The new feature supports various Helm CLI commands, including a push command for uploading charts, as part of its aim to enhance the Helm-based CI/CD workflow. Users are encouraged to explore additional features through the documentation and are invited to provide feedback or suggestions for further improvements.

Codefresh is actively enhancing its Container Native CI/CD platform, introducing innovative features as highlighted in a recent live webinar by CTO Oleg Verhovsky. The webinar showcased the latest product additions and improvements, with video recordings available for viewing. Individuals interested in learning more or having questions can schedule a one-on-one session, and those new to Codefresh are invited to sign up for an account to get started.

The blog post delves into the process of running Deployment Verification Tests on Docker's Example Voting App using Selenium and PyTest within a Kubernetes Helm Release, building on the groundwork laid in the first part of the series titled "The Perfect Pipeline." It outlines steps such as creating a Dockerfile for a Test Docker image, setting up a Codefresh pipeline with added build steps, and integrating Selenium Hub with Chrome and Firefox to conduct tests across multiple browsers. The process involves annotating Docker image metadata with test results and uploading PyTest HTML reports to an S3 bucket, ensuring the pipeline is equipped with the necessary environment variables and access credentials. The post also mentions future plans to address Helm Chart Management using Codefresh's embedded Chart Museum, offering a comprehensive guide for users to enhance their CI/CD workflows with Codefresh.