Operate First Data Science Community Meetup 18

[aakankshaduggal]

Title Build AIOps tools using Operate First

Short Description Want to learn how to accelerate your development of AI applications on the hybrid cloud? In this workshop, we introduce you to Operate First, an open cloud platform that provides cloud services and applications that support data scientists. We will walk you through the process of building a simple AIOps tool from scratch on the Operate First cloud and learn how to move your AI workloads to the cloud by implementing an end-to-end ML tool.

We start by learning how to collect data from an open CI/CD data source, use Jupyterlab and its extensions to manage dependencies, and run jupyter notebooks. We will learn how to perform automated, repeatable experiments using Elyra and Kubeflow Pipelines, create and deploy machine learning modes on OpenShift using Seldon and visualize results on a Superset dashboard.

By the end of this workshop, you will have an idea of how to build a simple AIOps tool on the cloud that can support your CI/CD processes. You will learn how to get started with, build data science tools, or onboard your existing projects on the Operate First cloud.

Presentation Day Date of the meetup

Presenter(s) @aakankshaduggal @suppathak

Actionable Items (Following actions would be carried out by the Organizers of the Operate First Data Science Community Meetup)

• [x] Add the topic and description to the agenda.
• [x] Send an invite via email using the email template and a tweet through the Operate First twitter account by adding a PR to operate-first-twitter.
• [x] Present the talk in Operate First Data Science Meetup. Follow the format and record the meetup.
• [ ] Edit the video recording of the Meetup and upload the video recording to Operate First YouTube channel.
• [ ] Send out meetup recording via email using the email template and tweet through Operate First twitter by adding a PR to operate-first-twitter.

[sesheta]

Issues go stale after 90d of inactivity. Mark the issue as fresh with /remove-lifecycle stale. Stale issues rot after an additional 30d of inactivity and eventually close.

If this issue is safe to close now please do so with /close.

/lifecycle stale

[sesheta]

Stale issues rot after 30d of inactivity. Mark the issue as fresh with /remove-lifecycle rotten. Rotten issues close after an additional 30d of inactivity.

If this issue is safe to close now please do so with /close.

/lifecycle rotten

[sesheta]

Rotten issues close after 30d of inactivity. Reopen the issue with /reopen. Mark the issue as fresh with /remove-lifecycle rotten.

/close

[sesheta]

@sesheta: Closing this issue.

In response to [this](https://github.com/operate-first/operate-first-data-science-community/issues/120#issuecomment-1385834126): >Rotten issues close after 30d of inactivity. >Reopen the issue with `/reopen`. >Mark the issue as fresh with `/remove-lifecycle rotten`. > >/close Instructions for interacting with me using PR comments are available [here](https://git.k8s.io/community/contributors/guide/pull-requests.md). If you have questions or suggestions related to my behavior, please file an issue against the [kubernetes/test-infra](https://github.com/kubernetes/test-infra/issues/new?title=Prow%20issue:) repository.