2023年2月20日

DevOps.com Logz。io集成ChatGPT与可观测平台Logz。io首席技术官Asaf Yigal表示，该公司已经将ChatGPT与其现有的人工智能引擎(称为认知洞察)集成在一起，该引擎应用机器学习算法来识别预示潜在关键IT问题的异常。他补充说，随着进一步的进步，该公司预计能够添加其他生成式人工智能功能。Logz。io Open 360平台基于开源的OpenSearch、Prometheus和Jaeger软件，该公司将这些软件注入了机器学习算法。与ChatGPT的集成是通过OpenAI提供的应用程序编程接口(API)实现的。Yigal说，总的目标是利用人工智能来发现DevOps团队需要关注的最相关的问题，而无需搜索大量的日志、跟踪和度量数据。Yial指出，生成式人工智能平台解决了当今DevOps团队收集更多数据时产生的基本认知负载问题。Yigal说，DevOps团队收集的数据越多，就越难确定it环境中发生了什么。 He added that generative AI platforms make it possible to analyze massive amounts of data at a scale that isn’t otherwise achievable. AI tools should make it possible to manage IT at a level of scale that eliminates many of the low-level data engineering and analytics tasks that previously required manual effort from a DevOps engineering team. It’s not clear how many other DevOps tools and platforms will be invoking generative AI capabilities in the months ahead, but DevOps teams should assume that large language models will soon be augmenting DevOps teams in ways that previously would have been thought unlikely. For example, discovering vulnerabilities in software running in production environments is about to become trivial as artificial intelligence (AI) platforms such as ChatGPT evolve. A generative AI platform can identify code vulnerabilities in much the same way as a traditional scanning tool. An AI platform, however, could theoretically monitor code repositories and scan them for vulnerabilities as updates and commits are being made in real-time. DevOps teams should be able to use generative AI platforms to discover and remediate these issues before code is deployed in a production environment. It’s just as probable bad actors will use the same platform to achieve the same goal, so from that perspective, many DevOps teams will now find themselves in an AI arms race to improve DevSecOps workflows. There are still lots of issues to be worked out in terms of the overall accuracy of generative AI platforms, but they will only become more intelligent as processors continue to advance. The issue now will be determining precisely where the man-machine interface for DevOps teams is today and in the future. Recent Posts By Mike Vizard