LOGGING, MONITORING, AND OBSERVABILITY IN GOOGLE CLOUD

What you'll learn

This three-day instructor-led course teaches participants techniques for monitoring, troubleshooting, and improving infrastructure and application performance in Google Cloud. Guided by the principles of Site Reliability Engineering (SRE), and using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage.

Who's this course for?

  • Cloud architects, administrators, and SysOps personnel
  • Cloud developers and DevOps personnel

To get the most out of this course, participants should have:

  • Completion of Google Cloud Platform Fundamentals: Core Infrastructure or equivalent experience
  • Basic scripting or coding familiarity
  • Proficiency with command-line tools and Linux operating system environments

Course Content

  • Understand the purpose and capabilities of Google Cloud operations-focused components: Logging, Monitoring, Error Reporting, and Service Monitoring
  • Understand the purpose and capabilities of Google Cloud application performance management focused components: Debugger, Trace, and Profiler
  • Construct a monitoring base on the four golden signals: latency, traffic, errors, and saturation
  • Measure customer pain with SLIs
  • Define critical performance measures
  • Create and use SLOs and SLAs
  • Achieve developer and operation harmony with error budgets
  • Develop alerting strategies
  • Define alerting policies
  • Add notification channels
  • Identify types of alerts and common uses for each
  • Construct and alert on resource groups
  • Manage alerting policies programmatically
  • Choose best practice monitoring project architectures
  • Differentiate Cloud IAM roles for monitoring
  • Use the default dashboards appropriately
  • Build custom dashboards to show resource consumption and application load
  • Define uptime checks to track aliveness and latency
  • Integrate logging and monitoring agents into Compute Engine VMs and images
  • Enable and utilize Kubernetes Monitoring
  • Extend and clarify Kubernetes monitoring with Prometheus
  • Expose custom metrics through code, and with the help of OpenCensus
  • Identify and choose among resource tagging approaches
  • Define log sinks (inclusion filters) and exclusion filters
  • Create metrics based on logs
  • Define custom metrics
  • Link application errors to Logging using Error Reporting
  • Export logs to BigQuery
  • Collect and analyze VPC Flow logs and Firewall Rules logs
  • Enable and monitor Packet Mirroring
  • Explain the capabilities of Network Intelligence Center
  • Use Admin Activity audit logs to track changes to the configuration or metadata of resources
  • Use Data Access audit logs to track accesses or changes to user-provided resource data
  • Use System Event audit logs to track GCP administrative actions
  • Define incident management roles and communication channels
  • Mitigate incident impact
  • Troubleshoot root causes
  • Resolve incidents
  • Document incidents in a post-mortem process
  • Debug production code to correct code defects
  • Trace latency through layers of service interaction to eliminate performance bottlenecks
  • Profile and identify resource-intensive functions in an application
  • Analyze resource utilization cust for monitoring related components within Google Cloud
  • Implement best practices for controlling the cost of monitoring within Google Cloud

Upcoming Schedule

Daniel King

As an experienced technologist Daniel has built a career in consulting, teaching and inspiring others to be enthusiastic about emerging technology adoption. He’s always been fascinated by what comes next and often speaks on a range of subjects engaging with developers and executives via conferences, meetups and summits around the world.

Course Details

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