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🔥 Product Hunt Spotlight: Railtown AI’s powerful error resolution feature pinpoints and fixes issues in real-time. Save hours of dev time and focus on what matters most—building great products better, faster. Our root cause analysis feature allows team to stay on top of all new error, map an error to an environment and buckets similar errors. Check us out on Product Hunt! https://lnkd.in/gvqksjC6 #AI #DevOps #RailtownAI

🚀 Elevate your approach to AI-driven code generation with LLaMA 3! In my latest blog post, I break down how to fine-tune key parameters like `max_tokens` and `temperature` to consistently produce reliable, standard-compliant code. Perfect for developers looking to integrate generative AI into their workflow. Check it out here:https://lnkd.in/g-HRWDbn #AI #CodeGeneration #LLaMA3 #DevOps #TechInnovation

On today's Techstrong Gang episode, Michael Vizard, Mitch Ashley, and special guest Tracy Bannon discuss how AI is about to transform DevOps workflows before discussing the revival of internal developer portals (IDPs). Then, the gang turns its attention to the obsession some organizations have with “golden templates,” which might not go over so well with application developers who prize flexibility. Watch the episode here: https://lnkd.in/eAxJDqj3 Listen here: https://lnkd.in/eMAFnADa #AI #DevOps #platformengineering #softwareengineering

Time for the soapbox - software is fluid, not fixed. Concepts like “golden templates” and “gold masters” are long outdated. Let’s not set up #platformengineering to fail with inflexible models of software. And AI must move beyond the individual to teamwork, collaboration and workflows. Comment below with your thoughts. Techstrong Gang is a fantastic forum to share, discuss and debate with people smarter than yourself.

Google's 2024 DORA Report presents a complex view of AI's role in DevOps 👇 While 81% of organizations have adopted AI, only 39.2% of respondents fully trust it. AI's potential to improve productivity and code quality is clear, but there's still skepticism, especially regarding AI-generated code. This highlights a need for cautious integration, as AI’s impact can vary—boosting some metrics like focus and satisfaction, but potentially slowing meaningful work. AI isn’t a one-size-fits-all solution but rather a powerful tool that requires careful and informed use. #AIDevelopment #PlatformEngineering #GenerativeAI #AIandDevOps

Using an AI Assistant to Read Tool Documentation @matthias / #docker #container - This ongoing Docker Labs GenAI series explores the exciting space of AI developer tools.At Docker, we believe there is a vast scope to explore, openly and without the hype.We will share our explorations and collaborate with the developer community in real-time.Although developers have adopted autocomplete tooling like GitHub Copilot and use chat, there is significant potential for AI tools to assist with more specific tasks https://lnkd.in/eMtPyDF3

"Security needs AI to help you find multiple needles in huge haystacks, very quickly". We heard from Jimmy Xu, Field CTO at Cycode at our recent webinar, on why ASPM platforms are the perfect co-pilot for developers pushing code quicker than ever before. 🎥 You can watch the full conversation on the impact of AI on application security here - https://shorturl.at/IwsZt #aspm #developersecurity #DevOps #AI

I'm super excited to share a sneak peek of v0 of an interesting feature we've been building at deployment.io :-). It's a foundation for a lot of other things to come. #buildinpublic #devops #ai #genai

The 2024 DORA report has some 🤯 findings! It rethinks throughput and stability, questions the impact of AI on software delivery, and suggests maybe coding isn't the bottleneck after all. 🔗https://hubs.li/Q02-RS6f0 via Rachel Stephens @rstephensme RedMonk #DevOps #AI

This article talks about MLOps, why it is needed, the challenges of MLOps, the tools available, and how MLOps pipelines work. Read it Here: https://lnkd.in/dqxCRwt5 #IPSpecialist #MLOps #MachineLearning #AI #DataScience #DevOps #ArtificialIntelligence #DataEngineering #ModelDeployment #DataOps #ModelManagement #MachineLearningEngineering #AIEngineering #MLLifecycle #DataPipeline #MLInfrastructure #ModelMonitoring #MLDeployment #ContinuousIntegration #ContinuousDeployment #ModelOps #DataEngineering #MLWorkflow #AIInfrastructure #MLModels #ModelLifecycle #DataOps #ModelMonitoring #AIIntegration #ModelTraining #AIEngineering