This is a hands-on guide with Python example code that walks through the deployment of an ML-based search API using a simple 3-step approach. The article provides a deployment strategy applicable to most machine learning solutions, and the example code is available on GitHub.
• Continuous Integration (CI) and Continuous Deployment (CD) pipelines for Machine Learning (ML) applications
• Importance of CI/CD in ML lifecycle
• Designing CI/CD pipelines for ML models
• Automating model training, deployment, and monitoring
• Overview of tools and platforms used for CI/CD in ML
This blog post compares Ansible and Terraform, two popular tools in the DevOps world, and discusses how they can be used together for a more efficient and comprehensive approach to infrastructure management. It also includes a video walk-through and requirements for a demo example where Terraform and Ansible are combined to create an AWS EC2 instance and deploy a Docker engine on it with Ansible, followed by launching a Jenkins container.
Create standalone with Splunk Free license
Splunk Free is the totally free version of Splunk software. The Free license lets you index up to 500 MB per day and will never expire.
Execute the following to bring up a Splunk Free standalone environment:
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