Quarterly Engineering System Performance & Reliability Review

Track and analyze key system performance metrics, reliability indicators, and infrastructure health to ensure optimal service delivery, identify potential issues, and maintain high availability standards. Focus on uptime, response times, error rates, and system resource utilization across our technology stack.

Report Objective

Monitor and evaluate system performance, reliability, and infrastructure health across all production environments. Track key metrics including system availability, response times, error rates, and resource utilization to maintain service level agreements (SLAs) and identify areas requiring optimization or intervention.

System Availability & Reliability

Line chart showing uptime percentage and incident counts

Questions to Consider:

2024-10-012024-11-012024-12-01date99.9099.95100.00sum(uptime_percentage)How is System Uptime Trending Over the Quarter?System uptime remains consistently high with 99.95% average, showing minor fluctuations

  • Are there any concerning trends in system availability?

  • How do uptime variations correlate with deployment schedules?

  • What is our performance against SLA commitments?

  • How has the distribution of incident severity changed?

  • Are there patterns in incident occurrence by severity level?

  • What is our mean time to resolution by severity?

P3P2P4P1severity_level0510152025sum(incident_count)What is the Distribution of Incidents by Severity?Majority of incidents are P3/P4, with minimal critical P1 occurrences

Performance Metrics

Bar charts displaying response times and error rates by service

Questions to Consider:

api-gatewayauth-servicepayment-serviceuser-serviceservice_name0200040006000sum(response_time_ms)How are Service Response Times Distributed?API Gateway shows highest average response time at 250ms

  • Which services are experiencing performance degradation?

  • How do response times vary during peak usage?

  • Are there specific endpoints causing delays?

  • Are there patterns in error rate spikes?

  • Which services show concerning error trends?

  • How do error rates correlate with deployment times?

2024-10-01 00:002024-11-01 00:002024-12-01 00:00timestamp0.00%0.05%0.10%0.15%0.20%0.25%sum(error_rate) vs. service_nameWhat are the Error Rates Across Services?Overall error rates remain below 0.2% threshold across services

Resource Utilization

Line charts showing CPU, memory, and storage utilization trends

Questions to Consider:

2024-10-01 00:002024-11-01 00:002024-12-01 00:00timestamp404550cpu_utilizationHow is Resource Utilization Trending?CPU and memory utilization show steady increase, averaging 45% and 60% respectively

  • Are we approaching any resource capacity limits?

  • How effective is our current auto-scaling?

  • What is our projected resource needs based on growth?

Areas for Additional Investigation