Logging, Monitoring and Observability in Google Cloud

This course teaches participants the following skills:

• Plan and implement a well-architected logging and monitoring infrastructure
• Define Service Level Indicators (SLIs) and Service Level Objectives (SLOs)
• Create effective monitoring dashboards and alerts
• Monitor, troubleshoot, and improve Google Cloud infrastructure
• Analyze and export Google Cloud audit logs
• Find production code defects, identify bottlenecks, and improve performance
• Optimize monitoring costs

This class is intended for the following participants:

• 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

Module 1: Introduction to Google Cloud Monitoring Tools

• Understand the purpose and capabilities of Google Cloud
• 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

Module 2: Avoiding Customer Pain

• 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

Module 3: Alerting Policies

• 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

Module 4: Monitoring Critical Systems

• 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

Module 5: Configuring Google Cloud Services for Observability

• 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

Module 6: Advanced Logging and Anaylsis

• 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

Module 7: Monitoring Network Security and Audit Logs

• 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

Module 8: Managing Incidents

• Define incident management roles and communication channels
• Mitigate incident impact
• Troubleshoot root causes
• Resolve incidents
• Document incidents in a post-mortem process

Module 9: Investigating Application Performance Issues

• 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

Module 10: the Costs of Monitoring

• Analyze resource utilization cost for monitoring related components within Google Cloud
• Implement best practices for controlling the cost of monitoring within Google Cloud