November - 2023
We hope you guys had a wonderful Thanksgiving! We are eternally grateful to our employees, teams, and customers who have contributed to evolving Ozone over the years to where we stand now with their efforts and insights!
Over the previous month, we have been busy with a few more feature additions and enhancements for the 1.2.18 release of Ozone. Here’s a summary:
Deployment Verification: Ozone integrates across monitoring tool stacks to ingest data like events, logs, metrics, and APM (Application Performance Monitoring) to identify and flag anomalies and later automate rollbacks in case the pre-defined threshold is breached. In this release, we have optimized the dashboard to provide more real-time insights into irregularities while allowing for a custom threshold setup post in which a rollback or an alert has to be triggered.
Native Integration for Triggering External CI Pipelines: In the new release, Ozone natively integrates with Jenkins. With our task catalog and the Ozone pipeline studio, this means that external pipelines from Jenkins can be triggered within Ozone in a low-code/no-code approach. In ArgoCD-derived solutions, this is typically achieved by an incoming webhook. With our native support for Jenkins pipelines, you can trigger them and observe logs from within Ozone. This makes it useful for large-scale organizations, which typically take time to migrate to a next-generation CI/CD solution.
Ozone-AI for Pipeline Conversions and Migrations: As you may already know, Ozone leverages the Tekton framework to provide reusable task and pipeline templates for enterprises. Being the world’s first platform to make Tekton accessible, the team has taken a step further in making migrations to Tekton more streamlined with the Ozone AI engine. There are two main use cases under this:
Automating pipeline conversions to Tekton with LLM: This new feature of Ozone automates the conversion of existing Jenkins pipelines into reusable Tekton pipelines within minutes, making migrations to Tekton a piece of cake. It leverages large language models (LLMs) which are fine-tuned using proprietary and open-source data to optimize these legacy to Tekton pipeline conversions. As of this release, support is for Jenkins pipeline conversions and later, this will be extended to GitLab and Azure DevOps pipelines.
Intelligent Prompt-driven Tekton Pipeline Generation: This feature of Ozone AI gives a whole new meaning to “low-code/no-code” DevOps. As the name suggests, users can simply ask the AI engine to “create a pipeline that deploys XYZ workload to the attached AKS cluster,” and they will instantly be presented with a Tekton YAML for the pipeline. Users can then save the pipeline or customize it if needed on the Ozone Pipeline Studio - A drag-and-drop pipeline configurator, and run the pipeline. By inputting just their use cases in simple English, Ozone enables smart reusable pipeline generation on the go, enabling teams to re-focus on what matters, while the platform does what it does best: automating CI/CD end-to-end with intelligence.
Click here for a detailed demo of Ozone AI in action!
Enhancements:
Cluster attach: Once a cluster is attached, the cluster status sync has been optimized along with other scenarios where clusters are a dependency.
Standardized in-app messages: In order to provide better context on the errors and their causes, the in-app toaster messages have been tweaked for better message delivery.
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