Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Azure SRE Agentで運用は楽になるのか?

Azure SRE Agentで運用は楽になるのか?

Discover how AI Agents, Azure SRE, and Foundry are transforming the future of IT operations—where human intervention is rapidly evolving. In this session, Kazushi Kamegawa (Microsoft MVP) explores the impact of Large Language Models (LLMs) on requirements definition, coding, testing, troubleshooting, and cybersecurity. Learn practical insights on leveraging AI-powered agents, the latest Azure SRE Agent preview, and strategies for thriving in an era where automation and intelligence reshape the workplace. Is the age of “human-free” operations coming? Find out how to stay ahead and make AI work for you!

Avatar for KAMEGAWA Kazushi

KAMEGAWA Kazushi

August 29, 2025
Tweet

More Decks by KAMEGAWA Kazushi

Other Decks in Programming

Transcript

  1. AIを使った開発前にやること XユーザーのSam Altmanさん: 「Most users should like GPT-5 better soon;

    the change is rolling out over the next day. The real solution here remains letting users customize ChatGPT's style much more. We are working that!」 / X
  2. 価格 Price component Description Calculation basis Price per AAU Price

    per flow Baseline, fixed cost (Always-on flow) Always-on flow: The agent continuously monitors and learns in the background, incurring ongoing charges. 1 AAU X 4 per hour per agent ¥14.850 ¥59.398 per hour per agent Usage-based, variable cost (Active flow) Active flow: When issues are detected, the agent triggers AI responses like incident resolution or scaling. Billing applies only while these tasks run. 1 AAU X 0.25 per second per agent task ¥14.850 ¥3.713 per second per agent task SRE Agent - Pricing | Microsoft Azure