Szkolenia HPE

Cel szkolenia szkolenie zdalne - dlearning

kod: HG7G2S | wersja: v5

This course is for administrators who want to learn about the installation, upgrade, system management, network integration and other tasks required to effectively administer HPE Ezmeral Container Platform 5.3. Hands-on labs are included.

Course objectives

  • Understand all architecture components of the HPE Ezmeral Container Platform 5.3
  • Understand all basic administration concepts of the HPE Ezmeral Container Platform 5.3, including installation, tenant management, user management and maintenance
  • Understand application development to cluster handling
  • Learn how HPE Ezmeral Container Platform integrates with existing IT infrastructure and integration with MapR
  • Understand monitoring and alerting services in HPE Ezmeral Container Platform

Audience

Hadoop administrators, system administrators, network administrators, IT managers

Plan szkolenia Rozwiń listę

  • Introduction
    • Introduction
    • Learning objectives review
    • Course schedule review
    • HPE Ezmeral Container Platform architecture overview
    • Control plane/management overview
    • Network architecture overview
    • Handling distributed stateful app
    • Storage architecture overview
  • HPE Ezmeral Container Platform Packaging—Install, Upgrade
    • Requirement gathering and planning
    • Installation/deployment
    • Airgap support
    • License
    • Upgrade
  • HPE Ezmeral Container Platform Multi-Tenancy
    • Multi-tenancy
    • Tenant management
  • HPE Ezmeral Container Platform User Role
    • User roles
    • User authentication
    • RBAC: Role binding (authorization)
    • Session management
  • HPE Ezmeral Container Platform Storage
    • Overall storage architecture
    • Ephemeral storage
    • Tenant share
    • HDFS
    • Application persistent storage
    • FS mount/DTap management
    • MapR management
    • MapR Integration
    • MapR terminology
    • MapR services
    • HPE Ezmeral Container Platform and MapR integration
    • MapR Control System (MCS)
    • MapR user accounts
  • HPE Ezmeral Container Platform Application
    • Complex stateful application deployment
    • Anatomy of Kubedirector application
    • Application lifecycle
    • Kubedirector operator
  • HPE Ezmeral Container Platform Monitoring and Alerting
    • Kubernetes cluster service monitoring
    • Dashboard monitoring
    • Usage monitoring
    • Monitoring architecture
    • HPE Ezmeral Container Platform usage monitoring tools
    • Kibana: UI visualization
    • Collecting container node storage usage
    • Elasticsearch monitoring logs
    • Elasticsearch common tasks
    • Best practice
    • SNMP alerts and SMTP notification
    • From planning to production to optimization—Big-Data-as-a-Service lifecycle
    • Create and secure environments
    • Monitor, manage and optimize
    • Optimize memory usage
  • HPE Ezmeral Container Platform Technical Overview
    • Control plane/management overview
    • Network architecture overview
    • Handling distributed stateful app (App Store and deployment)
    • Container application services
    • Storage architecture overview
    • Ephemeral and persistent disks
    • Application persistent storage
    • Rest API
  • HPE Ezmeral Container Platform Network
    • Overall network architecture
    • Linux virtual networking
    • Docker networking
    • HPE Ezmeral Container Platform gateway
    • Gateway Loadbalancer
    • Case study: HPE Ezmeral Container Platform gateway
    • Gateway configuration scenarios
    • Kubernetes core DNS
    • EPIC: DNS for containers
    • Container network
    • Kubernetes network
    • Virtualized networking
    • Networking in multi-tenant environment
  • Add-on and Picasso integration
    • Kubernetes Deployment and Add-ons
    • Picasso Cluster Deployment
Pobierz konspekt szkolenia w formacie PDF

Dodatkowe informacje

Wymagania wstępne
  • Unix/Linux user and administration experience
  • Hadoop/AI/big data application administration experience (Cloudera/Hortonworks, Jupyter Notebook, Tensorflow, etc.)
  • Experience in machine learning lifecycle (e.g. model training/development and model deployment)
  • bash/shell/python scripting
Poziom trudności
Czas trwania 3 dni
Certyfikat

The participants will obtain certificates signed by HPE (course completion).
Prowadzący

Authorized HPE Trainer

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