Harness has enhanced its AI capabilities in the DevOps platform, enabling users to create pipelines using plain language while adhering to corporate standards. The AI will analyze logs, correlate errors, recommend fixes, and automatically apply them if approved. It allows the creation of policies deployed as code using the Rego programming language within DevSecOps. The platform dynamically selects AI models based on use cases and is supported by the Model Context Protocol. A recent survey indicates that 41% of DevOps teams anticipate the use of generative AI tools in coding activities.
Harness AI extends its capabilities to allow users to create pipelines using plain language, adhering to corporate standards, and analyzing pipeline logs for error correlation.
The platform utilizes AI agents and large language models, dynamically selecting between Anthropic Claude 3.7 Sonnet or OpenAI GPT4.0 based on use cases and internal benchmarking.
It enables the deployment of policies as code using the Rego programming language, facilitating a streamlined approach to DevSecOps workflows.
According to a Futurum Group survey, 41% of respondents believe generative AI tools will be crucial for generating, reviewing, and testing code in the future.
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