> For the complete documentation index, see [llms.txt](https://docs.gdf.ai/gdf-full-stack-engineering/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.gdf.ai/gdf-full-stack-engineering/troubleshooting/infrastructure-engineering.md).

# Infrastructure Engineering

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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