{"id":55875,"date":"2024-10-22T13:56:16","date_gmt":"2024-10-22T17:56:16","guid":{"rendered":"https:\/\/sdtimes.com\/?p=55875"},"modified":"2024-10-22T13:56:16","modified_gmt":"2024-10-22T17:56:16","slug":"report-how-ai-platform-engineering-and-developer-experience-are-impacting-engineering-performance","status":"publish","type":"post","link":"https:\/\/sdtimes.com\/devops\/report-how-ai-platform-engineering-and-developer-experience-are-impacting-engineering-performance\/","title":{"rendered":"Report: How AI, platform engineering, and developer experience are impacting engineering performance"},"content":{"rendered":"

Google Cloud is revealing the results of its <\/span>10th annual DORA report<\/span><\/a>, which was designed to create industry benchmarks to give engineering teams a sense of how they are performing in relation to their peers.\u00a0<\/span><\/p>\n

DORA includes four key metrics for measuring delivery performance: lead time for changes, deployment frequency, change fail rate, and failed deployment recovery time. \u201cDORA\u2019s four key metrics, introduced in 2013, have become the industry standard for measuring software delivery performance,\u201d Nathen Harvey, DORA lead and developer advocate at Google Cloud, and Derek DeBellis, senior quantitative UX researcher at Google, wrote in a <\/span>blog post<\/span><\/a>.\u00a0<\/span><\/p>\n

This year, the report highlights the impact of AI, the growth of platform engineering, and the importance of developer experience.\u00a0<\/span><\/p>\n

Impact of AI<\/b><\/h5>\n

When it comes to AI, 75.9% of respondents said they used AI for at least one of their daily tasks, the most popular being generating code, summarizing information, and getting explanations of their code.\u00a0<\/span><\/p>\n

Some key benefits of AI included a 7.5% increase in documentation quality, a 3.4% increase in code quality, and a 3.1% increase in code review speed. The negatives of AI adoption were a decrease in delivery throughput by 1.5% and a 7.2% reduction in delivery stability. Additionally 39% of respondents had little to no trust in AI-generated code.<\/span><\/p>\n

Google Cloud\u2019s recommendations in this area include orienting AI adoption strategies around empowering employees and eliminating unwanted tasks, establishing clear AI use guidelines, and encouraging continuous exploration of AI tools.\u00a0<\/span><\/p>\n

Growth of platform engineering<\/b><\/h5>\n

Platform engineering has seen significant adoption because it increases productivity for developers.\u00a0<\/span><\/p>\n

The report found that this practice is currently most prevalent in larger companies, which signals that it is effective in managing complex development environments, Google Cloud explained.<\/span><\/p>\n

The research also noted that companies might see an initial decrease in engineering team performance when a platform is first implemented, which will go away as improvements are made and the platform evolves.\u00a0<\/span><\/p>\n

In order to see optimal results, companies should center their platform engineering strategy around user-centric design, developer independence, and a product-oriented approach.\u00a0<\/span><\/p>\n

Developer experience remains key<\/b><\/h5>\n

And finally, the third major theme of the report was the importance of developer experience. A healthy developer culture can help reduce burnout, increase productivity, and increase job satisfaction. These claims are nothing new, but still held true in this year\u2019s report.\u00a0<\/span><\/p>\n

The \u201cmove fast and constantly pivot\u201d approach was found to negatively affect developer well-being and performance, even when paired with strong leadership, comprehensive documentation, and a user-centric approach.\u00a0<\/span><\/p>\n

\u201cThe key takeaway from the decade of research is that software development success hinges not just on technical prowess but also on fostering a supportive culture, prioritizing user needs, and focusing on developer experience,\u201d the company wrote.\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Google Cloud is revealing the results of its 10th annual DORA report, which was designed to create industry benchmarks to give engineering teams a sense of how they are performing in relation to their peers.\u00a0 DORA includes four key metrics for measuring delivery performance: lead time for changes, deployment frequency, change fail rate, and failed … continue reading<\/a><\/p>\n","protected":false},"author":752,"featured_media":55876,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"cybocfi_hide_featured_image":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[1],"tags":[11009,7724],"coauthors":[11687],"acf":[],"yoast_head":"\nReport: How AI, platform engineering, and developer experience are impacting engineering performance - SD Times<\/title>\n<meta name=\"description\" content=\"The DORA report creates industry benchmarks to give engineering teams a sense of how they are performing in relation to their peers.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sdtimes.com\/devops\/report-how-ai-platform-engineering-and-developer-experience-are-impacting-engineering-performance\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Report: How AI, platform engineering, and developer experience are impacting engineering performance - 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