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Book Description

For companies such as Amazon, Dropbox, and Gremlin, the term high severity incident (SEV) signifies drops in network availability, product feature issues, data loss, revenue loss, and security risks. These high-impact bugs occur when coding, automation, testing, and other engineering practices create issues that eventually reach the customer—issues that can exist without detection for hours, days, weeks, and even years.

With this in-depth ebook, SREs, SRE managers, VPs of engineering, and CTOs will learn powerful methods for reducing MTTD through incident classification and leveling, tooling, monitoring, KPI metrics, alerting, observability, and chaos engineering. The authors share real-life experiences to explain how they achieved MTTD reduction results for companies including Gremlin, LinkedIn, Twitter, Amazon Web Services, Fuzzbox, and Samba TV.

This ebook dives into:

  • Incident classification: SEV descriptions and levels, and SEV and time-to-detection (TTD) timelines
  • Organization-wide critical service monitoring, including key dashboards and KPI metrics emails
  • Service ownership and metrics for organizations maintaining a microservice architecture
  • Effective on-call principles for site reliability engineers, including rotation structure, alert threshold maintenance, and escalation practices
  • Chaos engineering practices to identify random and unpredictable behavior in your system
  • Monitoring and metrics to detect incidents caused by self-healing systems
  • Creating a high-reliability culture by listening to people in your organization

Table of Contents

  1. Reducing Mean Time to Detection for High-Severity Incidents
    1. Introduction
    2. Step 0: Incident Classification
      1. SEV Descriptions and Levels
      2. The SEV Timeline
      3. The TTD Timeline
    3. Step 1: Organization-Wide Critical-Service Monitoring
      1. Critical-Service Dashboard
      2. High-Level Service Dashboards
    4. Critical-Service KPI Metrics Emails
      1. Critical-Service KPI Emails
      2. Daily Service-Specific KPI Email: A Database Example
    5. Step 2: Service Ownership and Metrics
      1. The Role of Services in SEVs
      2. Service Alerting Configuration
    6. Step 3: On-Call Principles
      1. On-Call Schedules
      2. On-Call Alerting
    7. Step 4: Chaos Engineering
    8. Step 5: Detecting Incidents Caused by Self-Healing Systems
    9. Step 6: Listening to Your People and Creating a High-Reliability Culture
    10. Conclusion
    11. Further Reading on Reducing MTTD for High-Severity Incidents
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