The challenge with Machine Learning (ML) models is productionizing. It requires data ingestion, data preparation, model training, model deployment, and monitoring.Adopting MLOps practices is similar to DevOps practices. In MLOps, the workload changes, but some core principles like automation, continuous integration/continuous deployment (CI/CD), and monitoring. Taking DevOps practices, I will discuss the similarities and differences in adopting MLOps practices.In this talk, Chinmay takes a production use case to scale ML models to 2 million+ daily requests. It leverages Google Cloud's (GCP) infrastructure to use its GPU and other services. This talk will help you draw similarities between DevOps and MLOps as a DevOps practitioner and help you learn how to run Machine Learning models at the production scale with best practices.

Ever wish you could test your whole cloud app without touching the cloud? I’ll show you how to validate your serverless pipeline from start to finish, right on your laptop using LocalStack. Join our Slack community and start shipping with confidence.

Bring your tests to CI/CD with GitHub Actions! In this episode, we’ll show how to integrate LocalStack into your workflow, so your tests run automatically on every push without touching real AWS resources.Whether you're testing Lambda, DynamoDB, S3, or beyond LocalStack makes it possible to run everything locally, even in your CI workflows.🔗 Read the companion blog post: https://blog.localstack.cloud/automate-your-tests-with-github-actions-and-localstack/

Building and debugging cloud-native applications often involves slow CI/CD pipelines, hard-to-reproduce bugs, and the need for costly shared environments. LocalStack offers a better way — letting developers simulate real AWS services entirely on their local machine.In this presentation, Kiah Imani gives a hands-on walkthrough of building and testing AWS workflows locally with LocalStack. From Lambda functions to S3 pre-signed uploads and SNS/SQS pipelines, you'll see how to prototype, debug, and iterate on cloud-native apps without ever deploying to the cloud.### Resources- S3: https://docs.localstack.cloud/aws/services/s3/- Lambda: https://docs.localstack.cloud/aws/services/lambda/- SQS: https://docs.localstack.cloud/aws/services/sqs/- SNS: https://docs.localstack.cloud/aws/services/sns/- Repo: https://github.com/localstack-samples/sample-serverless-image-resizer-s3-lambda/