GOOGLE CLOUD
Architecting with Google Cloud Design and Process
This course features a combination of lectures, design activities, and hands-on labs to show you how to use proven design patterns on Google Cloud to build highly reliable and efficient solutions and operate deployments that are highly available and cost-effective. This course was created for those who have already completed the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine course.
Apply a tool set of questions, techniques and design considerations
Define application requirements and express them objectively as KPIs, SLO's and SLI's
Decompose application requirements to find the right microservice boundaries
Leverage Google Cloud developer tools to set up modern, automated deployment pipelines
Choose the appropriate Google Cloud Storage services based on application requirements
Architect cloud and hybrid networks
Implement reliable, scalable, resilient applications balancing key performance metrics with cost
Choose the right Google Cloud deployment services for your applications
Secure cloud applications, data and infrastructure
Monitor service level objectives and costs using Stackdriver tools
Intermediate
2 x 8 hour sessions
Delivered in English
Have completed Architecting with Google Compute Engine, Architecting with Google Kubernetes Engine, or have equivalent experience
Have basic proficiency with command-line tools and Linux operating system environments
Have systems operations experience, including deploying and managing applications, either on-premises or in a public cloud environment
Cloud Solutions Architects, Site Reliability Engineers, Systems Operations professionals, DevOps Engineers, IT managers
Individuals using Google Cloud to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud
Describe users in terms of roles and personas
Write qualitative requirements with user stories
Write quantitative requirements using key performance indicators (KPIs)
Evaluate KPIs using SLOs and SLIs
Determine the quality of application requirements using SMART criteria
Decompose monolithic applications into microservices
Recognize appropriate microservice boundaries
Architect stateful and stateless services to optimize scalability and reliability
Implement services using 12-factor best practices
Build loosely-coupled services by implementing a well-designed REST architecture
Design consistent, standard RESTful service APIs
Automate service deployment using CI/CD pipelines
Leverage Cloud Source Repositories for source and version control
Automate builds with Google Cloud Build and build triggers
Manage container images with Google Container Registry
Create infrastructure with code using Deployment Manager and Terraform
Choose the appropriate Google Cloud data storage service based use case, durability, availability, scalability and cost
Storage binary data with Cloud Storage
Store relational data using Cloud SQL and Spanner
Store NoSQL data using Firestore and BigTable
Cache data for fast access using Memorystore
Build a data warehouse using BigQuery
Design VPC networks to optimize for cost, security and performance
Configure global and regional load balancers to provide access to services
Leverage Cloud CDN to provide lower latency and decrease network egress
Evaluate network architecture using the Network Intelligence Center
Connect networks using peering and VPNs
Create hybrid networks between Google Cloud and on-premises data centers
Choose the appropriate Google Cloud deployment service for your applications
Configure scalable, resilient infrastructure using Instance Templates and Groups
Orchestrate microservice deployments using Kubernetes and GKE
Leverage App Engine for a completely automated platform as a service (PaaS)
Create serverless applications using Google Cloud Functions
Design services to meet requirements for availability, durability and scalability
Implement fault tolerant systems by avoiding single points of failure, correlated failures and cascading failures
Avoid overload failures the the circuit breaker and truncated exponential backoff design patterns
Design resilient data storage with lazy deletion
Analyze disaster scenarios and plan for disaster recovery using cost/risk
Design secure systems using best-practices like separation of concerns, principle of least privilege and regular audits
Leverage Google Cloud Security Command Center to help identify vulnerabilities
Simplify cloud governance using or organization policies and folders
Secure people using IAM roles, Identity Aware Proxy and Identity Platform
Manage the access and authorization of resources by machines and processes using service accounts
Secure networks with with private IPs, firewalls and Google Cloud private access
Mitigate DDoS attacks by leveraging Cloud DNS and Cloud Armor
Manage new service versions using rolling updates, blue-green deployments and canary releases
Forecast, monitor and optimize service cost using the Google Cloud pricing calculator, billing reports and by analyzing billing data
Observe if your services are meeting their SLOs using Stackdriver Monitoring and Dashboards
Use Uptime Checks to determine service availability
Respond to service outages using Stackdriver Alerts
Ref: T-GCPIDP-I -01
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