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GCP - Cloud Architect Cloud Infrastructure (GCP Fundamentals: Core…

- - - - Is binary large-object store
      - High performance, internet-scale
      - Simple administration (does not require capacity management)
    - - is a managed RDBMS
      - Offers MySQL and PostgreSQL (Beta) as a service
      - Automatic replication
      - Scaling
        
        Vertical (read and write)
        
        Horizontal (read)
      - Cloud SQL can be used with other GCP services
    - - is a Horizontally scalable RDBMS
      - Managed instances with high availability
    - - is a horizontally scalable NoSQL Document DB
    - - is managed NoSQL wide column
      - Ideal for storing large amounts of data with very low latency (for terabyte Applications)
      - Accessed using HBase API
      - Native compatibility with big data, Hadoop ecosystems
  - - - Why use containers?
        
        Consistency
        
        Loose coupling
        
        Workload migration
        
        Agility
    - - is a PaaS for building scalable applications
      - Standard Environment
        Example
        
        Easily deploy your applications
        
        Autoscale workloads
        
        Free daily quota
        
        Usage based pricing
        
        Requirements
        
        No writing to local files
        
        All rquests time out at 60s
        
        Limits on third-party software
      - Flexible Environment
        
        Build and deploy containerized apps with a click
    - - Runtime environment
        
        App Engine Flexible
        
        Kubernetes
        
        Compute Engine
      - Clients
        
        Android
        
        IOS
        
        Javascript
  - - - is managed Hadoop
        
        Fast, easy, managed way to run
        
        Create clusters in 90 seconds or less
        
        Scale clusters up and down
        
        Why use ?
        
        Easily migrate on-premises Hadoop jobs to the cloud
        
        Save money with preemptible instances
        
        Use spark Machine Learning (MLlib) to run classification algorithms
    - - offers managed data pipelines
        
        Processes data using Computer Engine
        
        Clusters are sized for you
        
        Automated scaling, no instance provisioning required
        
        Why use?
        
        ETL pipelines
        
        Data analysis
    - - is a fully managed data warehouse
        
        Provides near real-time interactive analysis of massive datasets
        
        No cluster maintenance is required
        
        you only pay for storage and processing used
        
        Automatic discount for long-term data storage
    - - is scalable, reliable messaging
        
        Supports many-tomany asynchronous messaging
        
        Application components make push/pull subscriptions to topics
        
        Include support for offline consumers
        
        Why use?
        
        Building block for data ingestion in Dataflow, IOT, Marketing Analystics
        
        Fundation for Dataflow streaming
        
        Push notifications for cloud-based applications
        
        Connect applications across GCP (push /pull between Compute Engine and App Engine)
    - - offers interactive data exploration
        
        Interactive tool for large-scale data exploration, transformation, analysis and visualization
        
        Integrated with Jupyter
        
        Easily deploy models to BigQuery
        
        Analyze data in BigQuery, Compute Engine, and Cloud Storage
    - - Cloud Vision API
      - Cloud Speech API
      - Cloud Natural Language API
      - Cloud Translattion API
      - Cloud Video Intelligence API (Beta)
- - - - Temporary Compute Engine VM
      - Command-line access to the instance via a browser
      - 5 GB of persistent disk storage ($HOME dir)
      - Pre-installed Cloud SDK and other tools
      - gcloud: for working with Google Compute Engine and many GCP services
      - gsutil: for working with Cloud Storage
      - kubectl: for working with Google Container Engine and Kubernetes
      - bq: for working with BigQuery
      - Language support for Java, Go, Python, Node.js, PHP, and Ruby
      - Web preview functionality
      - Built-in authorization for access to resources and instances
  - - - Associates objects and services with billing
      - Contains networks (quota max 5)
    - - Has no IP address range
      - Is global and spans all available regions
      - Contains subnetworks
      - Can be of type default, auto mode or custom mode -> "one custom, always custom"
    - - Services have 2 IP: Internal and External IP
        Details
      - DNS Resolution for internal addresses
        Details
      - Alias IP ranges
        Details
      - DNS Resolution for external addresses
        Details
    - - A route is a mapping of an IP range to a destination
      - Firewall parameters
    - - Availability
      - Globalization
      - Cross-project VPC
      - Management separation
      - Bastion host isolation
      - NAT gateway host isolation
  - - - Linux: SSH
        
        SSH from console, CloudShell via SDK
        
        Requires firewall rule to allow tcp:22
      - Windows: RDP
        
        Requires setting the Windows password
        
        Requires firewall rule to allow tcp:3389
        
        RDP clients:
        
        Chrome extension
        
        MS Windows RDP client
        
        Powershell terminal
    - - Moving an instance to a new zone
      - Snapshots
      - Resize persistent disk
- - - - Primitive Roles
        
        Owner
        
        Editor
        
        Viewer
        
        Billing administrator
      - Curated roles
      - Custom roles
    - - Users
      - Service Accounts
        
        User-Created
        
        Built-in
        
        Google APIs
  - - - Classes
        and
        Decision chart
        
        Multi-Regional
        
        Nearline
        
        Coldline
        
        Regional
      - Data Import
        
        Storage Transfer Service
        
        Google Transfer Appliance
        
        Offline Media Import
  - - - Monitors multi-cloud: GCP and AWS
      - Identify trends and prevent issues
      - Reduce monitoring overhead
      - Improve signal-to-noise