Last week, Docker announced more than 1,000 Docker Hardened Images as free, open-source software that, when combined with Anaconda's AI Catalyst and other development technologies, can help overcome hurdles in building secure and scalable AI applications, Anaconda CEO David DeSanto told CRN.
Docker's recent move to make more than 1,000 containers Docker Hardened Images free and open source software represents a major step forward in its efforts to accelerate AI software development and secure the software development supply chain.
This is what David DeSanto, CEO of data science and AI development platform provider Anaconda, a leading Docker partner, said: CRN The newly open-sourced Docker container image, combined with Anaconda's own products, promises to be a breakthrough in AI development.
“One of the most difficult things developers face is knowing whether they are using safe and reliable components. As a former software developer, I can relate to that. The explosion of AI development and other events that have occurred over the past decade has made it even more difficult. That's why it's important for developers to have a reliable starting point,” said DeSanto (pictured).
[Related: Anaconda Looks To Speed AI Development Tasks With New Offering]
“For us, [the Docker move] “As a way to continually reach out to developers and help them build secure AI-native applications from trusted sources (like Docker and Anaconda),” the CEO said.
Despite the frenzy in AI software development in recent years, DeSanto says 80% of AI projects never make it into production. (According to an August MIT Media Lab report, only about 5% of generative AI pilot projects go into production and achieve measurable value.)
Much of the problem, DeSanto said, is that developers lack safe and reliable components such as models and containers. This slows down AI development projects, especially during the prototyping phase, as developers have to deal with vulnerabilities and meet stringent data governance, security, and sovereignty requirements.
Docker is a leading provider of cloud and AI-native development tools. Launched earlier this year, Docker Hardened Images (DHI) are pre-configured containers hardened with built-in security measures to help protect the software development “supply chain,” or the cycle of software applications from early stages of development to prototyping and operational production.
Last week, Docker announced that it is making its catalog of over 1,000 Docker Hardened images free and fully open source under the Apache 2.0 license. Docker said the move will ensure that developers, software maintainers, hobbyists, development teams, governments and organizations “can use, share and build on DHI with clear rights and no hidden restrictions.”
(Images are available from the Docker Hub website. According to Docker, enterprises with unique requirements such as customization, compliance with regulated industries, and faster patching can purchase Docker's DHI Enterprise. DHI Extended Lifecycle Support extends beyond the end of upstream support.)
Anaconda is a leading company in the open source software development space with a focus on the Python programming language. Anaconda's Miniconda is the company's free installer for Conda packages and environment manager for Python, and is a standard part of Docker images.
Earlier this month, Anaconda applied its strategy to provide the world of AI development with open source development capabilities combined with data security, governance, and compliance with the debut of its AI Catalyst suite of development tools for building, deploying, and managing AI applications.
At the core of AI Catalyst is a set of curated open source AI models selected and vetted by Anaconda, along with risk profiles and other documentation.
Anaconda and Docker partnership
The Anaconda and Docker partnership allows developers to combine Anaconda's development environment management capabilities with Docker containers to accelerate software development and ensure portability of AI and data science applications.
“When you look at our partnership with Docker, it's about helping people start that journey. The hardest part of the AI journey is having an environment that you know can scale,” DeSanto said.
The CEO said one of the biggest challenges when moving an application from prototype to production is meeting an organization's security trust model.
“There is still some resistance to safely deploying AI into production. Through partnerships, we need to understand what this can do for our users.” [with Docker]get it [developers] We use Docker-hardened images that meet security team requirements, allowing you to develop on a trusted base that you know will be accepted in production. It also speeds development by reducing the time required to configure the environment to get started and subsequently troubleshoot the application.
DeSanto said the integration of Anaconda and Docker, as well as Anaconda and Nvidia GPUs, “gives us a truly secure stack from application to hardware.”
He pointed out that the Anaconda environment has 50 million users (and 2 million community contributors). “From that framework, we're now enabling those 50 million users to build more secure AI workloads faster as part of our partnership, and potentially reaching even more users beyond that 50 million.” [developers] They are also trying this, but have not discovered Anaconda yet. ”
The partnership between Anaconda and Docker will also benefit solution providers and ISVs who develop applications for their customers, helping them build AI software that is scalable, meets security requirements, and avoids “potential backlash between infrastructure teams and developers,” DeSanto said.
“For us, we want to help people build what we call trusted AI workloads at scale,” the CEO said, summarizing Anaconda's intentions for 2026. “Another thing we're focused on is how we can further speed up development. And the last part is just being secure by design. We're looking at how we can give people more governance and control so they can work within trusted guardrails and get their jobs done,” he said, pointing to recent AI. Activation of catalyst.
