SKILL BENCHMARK

Generative AI for Site Reliability Engineering with Azure Competency (Intermediate Level)

  • 13m
  • 13 questions
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Generative AI for Site Reliability Engineering with Azure Competency is an intermediate-level benchmark that evaluates your knowledge of how advanced generative AI (GenAI) models can enhance site reliability engineering (SRE). You will be assessed on your skills in deploying generative AI models from the Azure AI catalog, testing their integration with SRE applications, and configuring these models for scalability and efficiency in Azure Kubernetes Service (AKS). A learner who scores high on this benchmark demonstrates the skills needed to utilize generative AI to support and optimize SRE operations, including deploying AI-driven tools, implementing backoff mechanisms, fine-tuning models in Azure OpenAI Studio, and configuring log analytics for monitoring and performance evaluation.

Topics covered

  • assess the suitability of advanced generative AI models for enhancing SRE practices using Azure
  • configure a log analytics workspace and diagnostics settings to enable analytics for generative AI resources
  • deploy advanced generative AI models from Azure AI model catalog
  • deploy reliable and scalable apps that integrate generative AI on Azure Kubernetes Service (AKS)
  • employ robust testing and responsible deployment strategies to ensure reliability of advanced generative AI applications
  • evaluate a generative AI model using Azure AI Studio’s evaluation feature
  • identify site reliability engineering (SRE) principles and practices that are used to ensure the reliability and availability of software systems
  • identify SRE tools and platforms that incorporate advanced generative AI capabilities for enhanced incident management and monitoring
  • improve site reliability by implementing a backoff mechanism to avoid rate limiting errors in generative AI applications
  • optimize and fine-tune advanced generative AI models
  • outline the use of advanced generative AI techniques such as generative adversarial networks (GANs), variational autoencoders (VAEs), and autoregressive models
  • provide an overview of generative AI and SRE advancements with a focus on how Azure based technologies can adapt and innovate in the space
  • support SRE operations by providing an AI chatbot customized to answer questions regarding SRE best practices