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- Updated pyproject.toml to use latest versions of boto3, botocore, awscli, and agentcore packages - Merged main branch changes with conflict resolution - Restructured README.md to follow template format with overview, prerequisites, setup, and execution sections - Created detailed documentation structure in docs/ folder with specialized content files - Updated package dependencies to use version constraints instead of local wheel files - Removed production-specific language and focused on demo/sample implementation - Added comprehensive documentation covering agents, configuration, deployment, and development
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Example Use Cases
Investigating Pod Failures
sre-agent --prompt "Our database pods are crash looping in production"
The agents collaborate to check pod status, analyze events, examine memory usage trends, and provide remediation steps.
Diagnosing Performance Issues
sre-agent --prompt "API response times have degraded 3x in the last hour"
The system correlates metrics across multiple dimensions to identify latency sources and configuration issues.
Interactive Troubleshooting Session
sre-agent --interactive
👤 You: We're seeing intermittent 502 errors from the payment service
🤖 Multi-Agent System: Investigating intermittent 502 errors...
👤 You: What's causing the queue buildup?
🤖 Multi-Agent System: Analyzing payment queue patterns...
Interactive mode allows multi-turn conversations for complex investigations.
Proactive Monitoring
# Morning health check
sre-agent --prompt "Perform a comprehensive health check of all production services"
# Capacity planning
sre-agent --prompt "Analyze resource utilization trends and predict when we'll need to scale"
# Security audit
sre-agent --prompt "Check for any suspicious patterns in authentication logs"
Examples of proactive monitoring and health check queries.