Mongodb Inc. expands beyond its database roots and aims to be one of the most awful challenges faced by many corporate IT organizations, outdated legacy applications.
At the Mongodb.local New York City event today, the company announced its MongoDB application modernization platform. It is an artificial intelligence-driven approach to convert decades-old applications into modern, scalable services. The platform combines tools, structured modernization methodology and human expertise to combine technical debt, $1.52 trillion issues, and a consortium of software quality estimated in 2022. MongoDB said that AMP practices can reduce the modernization timeline by up to two-thirds.
“Legacy applications are the leading blockers that are slowing down innovation,” said Shilpa Kolhar, senior vice president of application modernization at Mongodb. “Making the simplest changes is extremely dangerous. No developers are familiar with these older applications and old stacks.”
The company said AMP is the culmination of over two years of development and customer testing. The platform supports not only database layers, but also full application stacks that include outdated frameworks, vulnerable runtime environments, and undocumented stored procedures.
“AMP covers the entire modernization lifecycle,” says Kolhar. “By combining AI-powered tools, methodologies and modernization expertise, businesses can quickly convert Mongod's latest scalable services than traditional approaches, helping businesses 10 times faster.”
Mongodb said Lombard Odier & Co Ltd., a bank of Switzerland, a 200-year-old private bank, has reduced transition testing time from three days to three hours. Australia's Bendigo and Adelaide Bank Limited reported that the development time required to move core banking applications from relational databases to Mongodobu Atlas was reduced by 90%.
It's not a black box
Kolhar said AMP is not a “black box” that sends old code to large language models. “That doesn't work,” she said. “Actual applications have a large, complex codebase that AI cannot handle correctly and efficiently directly. This tool allows you to break this issue into small chunks using interactive, automated processes.”
Ben Cefalo, senior vice president at Mongodb and head of Core Products and Atlas Foundational Services, says the database has become the “source of agent memory and truth” for intelligent systems. “The database is the source of memory and truth for agents, and it works consistently over multiple cycles and even coordinates with other agents,” he said.
Cefalo is an AI-friendly solution for MongoDB's JavaScript notation-based document model, integrated with Vector and Text Search, as it is AI-friendly, and therefore consistent with the language model and AI framework consume and emit data. “If you ask AI what an ideal database would look like in this agent world, you'll see that it's very similar to Mongodb,” he said.
Photo: Robert Hoff/Silicon Angle
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