Logging, Monitoring, and Observability in Google
Logging, Monitoring and Observability in Google Cloud 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.
Objetivos
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
Cloud computing
Disponible en formato e-learning
Disponible en formato presencial
Disponible en formato a distancia
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Subvención disponible
A través de Fundae, cumpliendo requisitos.
Duración
15 horas
- Dificultad 50%
- Nivel alcanzado 80%
Dirigido a
This class is intended for the following participants:
Cloud architects, administrators, and SysOps personnel Cloud developers and DevOps personnel.
Conocimientos requeridos
To get the most out of this course, participants should have:
Google Cloud Platform Fundamentals: Core Infrastructure or equivalent experience
Basic scripting or coding familiarity
Proficiency with command-line tools and Linux operating system environments
Temario
Module 1: Introduction to Google Cloud Monitoring Tools
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.
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 Analysis
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: Optimizing 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.
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