Code Intelligence announced a new feature to CI Sense, a scalable fuzzing platform for continuous testing.
Iterative launched Machine Learning Engineering Management (MLEM) – an open source model deployment and registry tool that uses an organization’s existing Git infrastructure and workflows.
MLEM bridges the gap between ML engineers and DevOps teams. DevOps teams can easily understand the underlying frameworks and libraries a model uses and automate deployment into a one-step process for production services and apps.
“Iterative enables customers to treat AI models as just another type of software artifact,” said Sriram Subramanian, research director, AI/ ML Lifecycle Management Software, IDC. “The ability to build ML model registries using Git infrastructure and DevOps principles allows models to get into production faster.”
MLEM is a core building block for a Git-based ML model registry, together with other Iterative tools, like GTO and DVC. A model registry stores and versions trained ML models. Model registries greatly simplify the task of tracking models as they move through the ML lifecycle, from training to production deployments and ultimately retirement.
“Model registries simplify tracking models moving through the ML lifecycle by storing and versioning trained models, but organizations building these registries end up with two different tech stacks for machine learning models and software development,” said Dmitry Petrov, co-founder and CEO of Iterative. “MLEM as a building block for model registries uses Git and traditional CI/CD tools, aligning ML and software teams so they can get models into production faster.”
With Iterative tools, organizations can build a ML model registry based on software development tools and best practices. This means Git acts as a central source of truth for models, eliminating the need for external tools specific to machine learning. All information around a model including which are in production, development, or deprecated, can all be viewed in Git.
MLEM’s modular nature fits into any organization’s software development workflows based on Git and CI/CD, without engineers having to transition to a separate machine learning deployment and registry tool. This allows teams to use a similar process across both ML models and applications for deployment, eliminating duplication in processes and code. Teams are then able build a model registry in hours rather than days.
MLEM promotes a comprehensive machine learning model lifecycle management workflow using a GitOps-based approach. Software development and MLOps teams can then be aligned, using the same tools to speed the time it takes a model to get from development to production.
Industry News
WSO2 is adding new capabilities for WSO2 API Manager, WSO2 API Platform for Kubernetes (WSO2 APK), and WSO2 Micro Integrator.
OpenText™ announced a solution to long-standing open source intake challenges, OpenText Debricked Open Source Select.
ThreatX has extended its Runtime API and Application Protection (RAAP) offering to provide always-active API security from development to runtime, spanning vulnerability detection at Dev phase to protection at SecOps phase of the software lifecycle.
Canonical announced the release of Ubuntu 24.04 LTS, codenamed “Noble Numbat.”
JFrog announced a new machine learning (ML) lifecycle integration between JFrog Artifactory and MLflow, an open source software platform originally developed by Databricks.
Copado announced the general availability of Test Copilot, the AI-powered test creation assistant.
SmartBear has added no-code test automation powered by GenAI to its Zephyr Scale, the solution that delivers scalable, performant test management inside Jira.
Opsera announced that two new patents have been issued for its Unified DevOps Platform, now totaling nine patents issued for the cloud-native DevOps Platform.
mabl announced the addition of mobile application testing to its platform.
Spectro Cloud announced the achievement of a new Amazon Web Services (AWS) Competency designation.
GitLab announced the general availability of GitLab Duo Chat.
SmartBear announced a new version of its API design and documentation tool, SwaggerHub, integrating Stoplight’s API open source tools.
Red Hat announced updates to Red Hat Trusted Software Supply Chain.
Tricentis announced the latest update to the company’s AI offerings with the launch of Tricentis Copilot, a suite of solutions leveraging generative AI to enhance productivity throughout the entire testing lifecycle.