Generative Development Framework
GDF.ai
  • Intro to GDF-FSE
    • Generative AI, Large Language Models, ChatGPT?
    • Knowledge Areas
    • Access a Chat Based LLM
    • Why GDF?
    • Expectations
  • Limitations
  • Prompting
    • Prompt Patterns
    • Prompt Context
    • Prompt Stores
    • Prompt Operators
    • Prompt Chaining
  • Security
    • Protecting Data
    • Protecting Application Security
    • Protecting Intellectual Property
    • Protection Stores
    • AI Security Assessments and Penetration Testing
    • Social Engineering Testing with AI
  • Subject Knowledge Areas
    • Ideation
      • Identifying a Problem Statement
      • Plan and Prioritize Features
      • Develop User Stories
      • Requirement Gathering
      • Ideation Prompting
      • Ideation Template
    • Specification
      • Specifying Languages
      • Specifying Libraries
      • Specifying Project Structures
      • Specify Schemas
      • Specifying Elements
      • Specifying API Specs
    • Generation
      • Generating UI Elements
      • Generating Mock Data
      • Generating Schemas
      • Generating Parsers
      • Generating Databases
      • Generate Functions
      • Generate APIs
      • Generate Diagrams
      • Generating Documentation
    • Transformation
      • Converting Languages
      • Converting Libraries
    • Replacement
      • Replacing Functions
      • Replacing Data Types
    • Integration
      • Connecting UI Components
      • Connecting UI to Backend
      • Connecting Multiple Services Together
      • Connecting Cloud Infrastructure (AWS)
    • Separation
      • Abstraction
      • Model View Controller (MVC)
    • Consolidation
      • Combining UI Elements
      • Deduplicating Code Fragments
    • Templating
      • Layouts
      • Schemas
      • Project Structures
      • Content Management Systems
    • Visualization
      • General Styling
      • Visual Referencing
      • Visual Variations
    • Verification
      • Test Classes
      • Logging and Monitoring
      • Automated Testing
      • Synthetic Monitoring
    • Implementation
      • Infrastructure
      • DevOps / Deployment
    • Optimization
      • General Optimization
      • Performance Monitoring
      • Code Review
  • Guidance
    • Business Process
    • Regulatory Guidance
  • Generative Pipelines
  • Troubleshooting
    • Client Side Troubleshooting
    • Server Side Troubleshooting
    • Troubleshooting with AI
    • Documentation
    • Infrastructure Engineering
  • Terminology
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  1. Troubleshooting

Infrastructure Engineering

Understanding infrastructure engineering regarding generative AI

There are multiple cloud platforms available such as Microsoft Azure, Amazon Web Service (AWS), Google Cloud, Digital Ocean, and many others. Each platform has their own way to log, report, and monitor issues. Use generative AI to quickly see how to troubleshoot a given platform or read through documentation to figure out what needs to be done.

Below we go over a short example of using AWS CloudWatch to troubleshoot issues. CloudWatch is a logging service by provided by AWS that has native integrations into many AWS services that allow you to quickly troubleshoot issues with services such as EC2, API Gateway, and S3.

Using AWS CloudWatch to Troubleshoot Infrastructure Issues

  1. Logging:

    • Access the AWS Management Console or use the AWS CLI to create and manage CloudWatch Log Groups and Log Streams.

    • Configure your AWS resources (e.g., EC2 instances, Lambda functions) to send logs to Amazon CloudWatch.

    • Set up log retention policies to control how long logs are stored in CloudWatch.

  2. Log queries:

    • Open the Amazon CloudWatch console and navigate to the "Logs Insights" section.

    • Select the desired Log Group and start writing custom queries using the CloudWatch Logs Query Language.

    • Use the built-in query editor to write, test, and save your queries.

    • Visualize your log data by creating custom charts and dashboards.

  3. Monitoring and alerting:

    • In the AWS Management Console, navigate to the "CloudWatch" section.

    • Create CloudWatch Alarms to monitor specific metrics for your AWS resources.

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Last updated 3 months ago

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