Daniel Hinojosa

Gitops: From Commit to Deploy

Join us for a hands-on workshop, GitOps: From Commit to Deploy, where you’ll explore the entire lifecycle of modern application deployment using GitOps principles.

We’ll begin by committing an application to GitHub and watching as your code is automatically built through Continuous Integration (CI) and undergoes rigorous unit and integration tests. Once your application passes these tests, we’ll build container images that encapsulate your work, making it portable, secure, and deployment-ready. Next, we’ll push these images to a container registry preparing for deployment

Next, you will learn how to sync your application in a staging Kubernetes cluster using ArgoCD (CD), a powerful tool that automates and streamlines the deployment process. Finally, we’ll demonstrate a canary deployment in a production environment with ArgoCD, allowing for safe, gradual rollouts that minimize risk.

By the end of this workshop, you’ll have practical experience with the tools and techniques that perform GitOps deployments, so you can take this information and set up your deployments at work.

• Creating Your Application
• Running Locally
• Proper Commits
• Security Scans
• Safe Image Creation
• Image Publishing
• ArgoCD and Syncing
• Canary Deployments

Gitops: From Commit to Deploy

Join us for a hands-on workshop, GitOps: From Commit to Deploy, where you’ll explore the entire lifecycle of modern application deployment using GitOps principles.

We’ll begin by committing an application to GitHub and watching as your code is automatically built through Continuous Integration (CI) and undergoes rigorous unit and integration tests. Once your application passes these tests, we’ll build container images that encapsulate your work, making it portable, secure, and deployment-ready. Next, we’ll push these images to a container registry preparing for deployment

Next, you will learn how to sync your application in a staging Kubernetes cluster using ArgoCD (CD), a powerful tool that automates and streamlines the deployment process. Finally, we’ll demonstrate a canary deployment in a production environment with ArgoCD, allowing for safe, gradual rollouts that minimize risk.

By the end of this workshop, you’ll have practical experience with the tools and techniques that perform GitOps deployments, so you can take this information and set up your deployments at work.

• Creating Your Application
• Running Locally
• Proper Commits
• Security Scans
• Safe Image Creation
• Image Publishing
• ArgoCD and Syncing
• Canary Deployments

The Fine Art of Canary Deployments

Canary Deployments are the last ingredient of any Continuous Delivery or Continuous Deployment rollout. A canary deployment is a deployment strategy that releases an application or service incrementally to a subset of users. All infrastructure in a target environment is updated in small phases (e.g., 2%, 25%, 75%, 100%). This control makes a canary release the lowest risk-prone compared to all other deployment strategies, like the blue-green strategy. If you need to back out of a production deployment quickly without much disruption, then canary deployments may be an excellent practice to set up.

We will treat this talk like a recipe so that you can set up a canary in your work environment.

• Continuous Integration, Continuous Delivery,
• Continuous Deployment Overview
• You can perform this anywhere: Cloud instances or Kubernetes
• What is Canary? What are some of the strategies you can use?
• What CD Frameworks perform Canary Deployments?
• How do you perform metrics? Are things going too slow or too fast?
• How do you back out if this rollout is not performing as well as it should?
• Can you perform canary deployments without a CD framework? Perhaps something native to Kubernetes?
• Performing using Spinnaker, Argo, Istio
• Conclusion

MLOps Half Day Workshop

MLOps is a mix of Machine Learning and Operations. It is the new frontier for those interested in or knowledgeable about both of these disciplines. MLOps supports the operationalization of machine learning models developed by data scientists and delivers the model for processing via streaming or batch operations. Operationalizing Machine Learning Models is nurturing your data from notebook to deployment through pipelines.

In this workshop, we will describe the processes:

• Model Development
• Model Packaging
• Model Deployment
• Model Cataloging
• Model Monitoring
• Model Maintenance

Some of the technologies we will discover include:

• Airflow, Kubeflow, MLFlow
• Prometheus & Grafana
• TensorFlow, XGBoost,
• Serving
• Hyperparameter Tuning

Our exercises will include running and understanding MLFlow.

MLOps Half Day Workshop

MLOps is a mix of Machine Learning and Operations. It is the new frontier for those interested in or knowledgeable about both of these disciplines. MLOps supports the operationalization of machine learning models developed by data scientists and delivers the model for processing via streaming or batch operations. Operationalizing Machine Learning Models is nurturing your data from notebook to deployment through pipelines.

In this workshop, we will describe the processes:

• Model Development
• Model Packaging
• Model Deployment
• Model Cataloging
• Model Monitoring
• Model Maintenance

Some of the technologies we will discover include:

• Airflow, Kubeflow, MLFlow
• Prometheus & Grafana
• TensorFlow, XGBoost,
• Serving
• Hyperparameter Tuning

Our exercises will include running and understanding MLFlow.