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Part_4.md
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Monitoring, Managing, and Maximizing Google Cloud Operations (GCP DevOps Engineer Track Part 4)
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===============================================================================================
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### Introduction
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#### About the Course and Learning Path
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Make better software, faster
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#### Milestone: Getting Started
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### Understanding Operations in Context
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#### Section Introduction
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#### What Is Ops?
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- GCP Defined
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- _"Monitor, troubleshoot, and improve application performance on your Google Cloud Environment"_
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- Logging Management
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- Gather Logs, metrics and traces everywhere
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- Audit, Platform, User logs
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- Export, Discard, Ingest
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- Error Reporting
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- So much data, How do you pick out the important indicators?
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- A centralized error management interface that shows current & past errors
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- Identify your app's top or new errors at a glance, in a dedicated dashboard
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- Shows the error details such as time chart, occurences, affected user count, first- and last- seen dates as well as a cleaned exception stack trace
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- Across-the-board Monitoring
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- Dashboards for built-in and customizable visualisations
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- Monitoring Features
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- Visual Dashboards
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- Health Monitoring
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- Associate uptime checks with URLs, groups, or resources (e.g. instances and load balancers)
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- Service Monitoring
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- Set, monitor and alert your teams as needed based on Service Level Objectives (SLO's)
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- SRE Tracking
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- Monitoring is critical for SRE
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- Google Cloud Monitoring enables the quick and easy development of SLIs and SLOs
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- Pinpoint SLI's and develop and SLO on top of it
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- Operational Management
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- Debugging
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- Inspects the state of your application at any code location in production without stopping or slowing down requests
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- Latency Management
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- Provides latency sampling and reporting for App Engine, including latency distributions and per-URL statistics
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- Performance Management
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- Offers continuous profiling of resource consumption in your production applications along with cost management
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- Security Management
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- With audit logs, you have near real-time user activity visibility across all your applications on Google Cloud
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**What is Ops: Key Takeaways**
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- Ops Defined: Watch, learn and fix
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- Primary services: Monitoring and Logging
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- Monitoring dashboads for all metrics, including health and services (SLOs)
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- Logs can be exported, discarded, or ingested
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- SRE depends on ops
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- Error alerting pinpoints problems, quickly
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Scratch:
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- Metric query and tracing analysis
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- Establish performance and reliability indicators
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- Trigger alerts and error reporting
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- Logging Features
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- Error Reporting
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- SRE Tracking (SLI/SLO)
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- Performance Management
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#### Clarifying the Stackdriver/Operations Connection
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- 2012 - Stackdriver Created
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- 2014 - Stackdriver Acquired by Google
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- 2016 - Stackdriver Released: Expanded version of Stackdriver with log analysis and hybrid cloud support is made generally available
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- 2020 - Stackdriver Integrated: Google fully integrates all Stackdriver functionality into the GCP platform and drops name
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**Cloud Monitoring, CLoud Logging, Cloud Trace, Cloud Profiler, Cloud Debugger, Cloud Audit Logs** (formerly all called Stackdriver <service>)
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"StackDriver" lives on - in the exam only
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Integration + Upgrades
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- Complete UI Integrations
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- All of Stackdrivers functionality - and more - is now integrated into the Google Cloud console
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- Dashboard API
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- New API added to allow creation and sharing of dashoards across projects
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- Log Retention Increased
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- Logs can now be retained for up to **10 years** and you have control over the time specified
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- Metrics Enhancement
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- In Cloud Monitoring, metrics are kept up to 24 months, and writing metrics has been increased to a 10-second granularity (write out metrics every 10 seconds)
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- Advanced Alert Routing
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- Alerts can now be routed to independent systems that support Cloud Pub/Sub
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#### Operations and SRE: How Do They Relate?
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- Lots of questions in Exam on SRE
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What is SRE? - _"SRE is what happens when a software engineer is tasked with what used to be called operations"_ (Founder Google SRE Team)
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**Pillars of DevOps**
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- Accept failure as normal:
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- Try to anticipate, but...
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- Incidents bound to occur
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- Failures help team learn
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- No-fault postmortems & SLOs:
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- No two failures the same
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- Track incidents (SLIs)
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- Map to Objectives (SLOs)
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- Implement gradual change:
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- Small updates are better
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- Easier to review
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- Easier to rollback
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- Reduce costs of failures:
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- Limited "canary" rollouts
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- Impact fewest users
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- Automate where possible
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- Measure everything:
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- Critical guage of sucess
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- CI/CD needs full monitoring
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- Synthetic, proactive monitoring
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- Measure toil and reliability:
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- Key to SLOs and SLAs
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- Reduce toil, up engineering
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- Monitor all over time
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<hr style="height:2px;border-width:0;color:gray;background-color:gray">
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SLI: _"A carefully defined <u>quantitative</u> measure of some aspect of the level of service that is provided"_
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SLIs are metrics over time - specific to a user journey such as request/response, data processing, or storage - that show how well a service is doing
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Example SLIs:
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- Request Latency: How long it takes to return a response to a request
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- Failure Rate: A fractice of all rates recevied: (unsuccessful requests/all requests)
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- Batch Throughput - Proportion of time = data processing rate > than a threshold
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**Commit to Memory - Google's 4x Golden Signals!**
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- Latency
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- The time is takes for your service to fulfill a request
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- Errors
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- The rate at which your service fails
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- Traffic
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- How much demand is directed at your service
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- Saturation
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- A measure of how close to fully utilized the services' resources are
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> **LETS**
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<hr style="height:2px;border-width:0;color:gray;background-color:gray">
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SLO: _"Service level objectives (SLOs) specify a target level for the reliability of your service"_ - The site reliability workbook
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SLOs are tied to you SLIs
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- Measured by SLLI
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- Can be a single target value or range of values
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- SLIs <= SLO
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- or
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- (lower bound <= SLI <= upper bound) = SLO
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- Common SLOs: 99.5%, 99.9%, 99.99% (4x 9's)
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SLI - Metric over time which detail the health of a service
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- example: `Site homepage latency requests < 300ms over last 5 minutes @ 95% percentile`
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SLO - Agreed-upon bounds how often SLIs must be met
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- example: `95% percentile homepage SLI will suceed 99.9% of the time over the next year`
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Phases of Service Lifetime
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SRE's are involved in the architecture and design phase, but really hit their stride in the "Limited Availability" (operations) phase. This phase typically includes the alpha/beta phases, and provides SRE's great opportunity to:
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- Measure and track SLIs (Measuring increasing performance)
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- Evaluate reliability
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- Define SLOs
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- Build capacity models
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- Establish incident response, shared with dev team
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General Availability Phase
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- After Production Readiness Review passed
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- SREs handle majority of op work
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- Incident responses
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- Track operational load and SLOs
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**Ops & SRE: Key Takeaways**
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- SRE: Operations from a software engineer
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- Many shared pillars between DevOps/SRE
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- SLIs are quantitative metrics over time
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- Remember the 4x Google Golden Signals (LETS)
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- SLOs are a target objective for reliability
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- SLIs are lower then SLO - or - in-between upper and lower bound
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- SREs are most active in limited availability and general availability phases
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#### Operation Services at a Glance
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#### Section Review
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#### Milestone: The Weight of the World (Teamwork, Not Superheroes)
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Monitoring Your Operations
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Section Introduction
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Cloud Monitoring Concepts
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Monitoring Workspaces Concepts
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Monitoring Workspaces
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Perspective: Workspaces in Context
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What Are Metrics?
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Exploring Workspace and Metrics
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Monitoring Agent Concepts
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Installing the Monitoring Agent
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Collecting Monitoring Agent Metrics
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Integration with Monitoring API
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Create Dashboards with Command Line
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GKE Metrics
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Perspective: What's Up, Doc?
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Uptime Checks
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Establishing Human-Actionable and Automated Alerts
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Section Review
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Milestone: Spies Everywhere! (Check Those Vitals!)
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Hands-On Lab:
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Install and Configure Monitoring Agent with Google Cloud Monitoring
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Logging Activities
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Section Introduction
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Cloud Logging Fundamentals
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Log Types and Mechanics
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Cloud Logging Tour
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Logging Agent Concepts
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Install Logging Agent and Collect Agent Logs
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Logging Filters
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Hands-On with Advanced Filters
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VPC Flow Logs
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Firewall Logs
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VPC Flow Logs and Firewall Logs Demo
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Routing and Exporting Logs
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Export Logs to BigQuery
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Logs-Based Metrics
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Section Review
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Milestone: Let the Record Show
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Hands-On Lab:
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Install and Configure Logging Agent on Google Cloud
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SRE and Alerting Policies
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SLOs and Alerting Strategy
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Service Monitoring
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Milestone: Come Together, Right Now, SRE
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Optimize Performance with Trace/Profiler
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Section Introduction
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What the Services Do and Why They Matter
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Tracking Latency with Cloud Trace
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Accessing the Cloud Trace APIs
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Setting Up Your App with Cloud Profiler
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Analyzing Cloud Profiler Data
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Section Review
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Milestone: It All Adds Up!
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Hands-On Lab:
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Discovering Latency with Google Cloud Trace
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Identifying Application Errors with Debug/Error Reporting
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Section Introduction
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Troubleshooting with Cloud Debugger
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Establishing Error Reporting for Your App
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Managing Errors and Handling Notifications
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Section Review
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Milestone: Come Together - Reprise (Debug Is De Solution)
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Hands-On Lab:
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Correcting Code with Cloud Debugger
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Course Conclusion
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Milestone: Are We There, Yet?
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landscape
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Practice Exam / Quiz:
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Google Certified Professional Cloud DevOps Engineer Exam Prep
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