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1 2 3 4 5 › 18
Logging, Monitoring, and Observability in Google Cloud
GOOGLE PROFESSIONAL PROFESSIONAL DEVOPS ENGINEER CLOUD, IOT, Kubernetes, artificialintelligence, machinelearning, bigdata, deeplearning, bigquery, monitoring, logging, observability
NewCondition € 2000.00
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DURATION
3 days
DESCRIPTION
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.
OBJECTIVES
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
AUDIENCE
This class is intended for the following participants:
Cloud architects, administrators, and SysOps personnel
Cloud developers and DevOps personnel
PREREQUISITES
To get the most out of this course, participants should have:
Google Cloud Platform Fundamentals: Core Infrastructure or equivalent experience
Basic scripting or coding ability
Proficiency with command-line tools and Linux operating system environments
TOPICS
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 cust for monitoring related components
within Google Cloud
Implement best practices for controlling the cost of monitoring within
Google Cloud
3 days
DESCRIPTION
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.
OBJECTIVES
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
AUDIENCE
This class is intended for the following participants:
Cloud architects, administrators, and SysOps personnel
Cloud developers and DevOps personnel
PREREQUISITES
To get the most out of this course, participants should have:
Google Cloud Platform Fundamentals: Core Infrastructure or equivalent experience
Basic scripting or coding ability
Proficiency with command-line tools and Linux operating system environments
TOPICS
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 cust for monitoring related components
within Google Cloud
Implement best practices for controlling the cost of monitoring within
Google Cloud
