Giskard

Remove the bottlenecks in application development, so administrators and other non-technical users can configure, test, and release apps faster, more reliability, and with less interruption to users. Our AppOps platform automates the entire development lifecycle for low-code applications giving administrators easy to use tools for change management, version control, regression testing, and reference data deployment. Speed through release management by automating tedious reference data deployments between Salesforce orgs. Our templates make managing even the most complex, relational data sets a breeze. So you can deploy faster than you can say change set. Sometimes small changes have unexpected consequences. Not to worry; we’ve got you covered with automated regression testing. Find and fix bugs—before they’re introduced in production. Keep your apps running smoothly and roll out new features with certainty.

Using Amazon SageMaker Pipelines, you can create ML workflows with an easy-to-use Python SDK, and then visualize and manage your workflow using Amazon SageMaker Studio. You can be more efficient and scale faster by storing and reusing the workflow steps you create in SageMaker Pipelines. You can also get started quickly with built-in templates to build, test, register, and deploy models so you can get started with CI/CD in your ML environment quickly. Many customers have hundreds of workflows, each with a different version of the same model. With the SageMaker Pipelines model registry, you can track these versions in a central repository where it is easy to choose the right model for deployment based on your business requirements. You can use SageMaker Studio to browse and discover models, or you can access them through the SageMaker Python SDK.