Novell ZENworks 11 Configuration Management Administration

The purpose of this course is to update the content of Course 3108 (Novell ZENworks 10.3 Configuration Management Administration) to match the Novell ZENworks 11 Configuration Management version of the product. It teaches students the concepts, processes, and architecture of Novell ZENworks 11 Configuration Management that is required core knowledge for anyone who plans to administer ZCM 11 or any integrated or related ZENworks products.

Training Level: 2 - Intermediate

Key Objectives

This course helps students become familiar with the purpose and components of Novell ZENworks 11 Configuration Management and enables them to perform advanced administrative tasks in a lab environment, or in a production environment under the direction of an experienced Novell ZENworks 11 Configuration Management network engineer. Students will also build their administrative knowledge by performing more involved administrative tasks for products that are integrated into ZCM 11.

Audience Summary

This course is ideal for those who have solid ZENworks experience and who want to learn about and implement the new features of ZENworks 11. The audience for this course includes a diverse group of professionals: ZENworks system administrators, integrators and engineers Networking consultants Reseller and partner technical-support staff.

Big Data on AWS

Big Data on AWS introduces you to cloud-based big data solutions and Amazon Elastic Map Reduce (EMR), the AWS big data platform. In this course, we show you how to use Amazon EMR to process data using the broad ecosystem of Hadoop tools like Pig and Hive. We also teach you how to create big data environments, work with Amazon DynamoDB, Amazon Redshift, and Amazon Kinesis, and leverage best practices to design big data environments for security and cost-effectiveness.

Course Objectives

This course is designed to teach you how to:

·         Understand Apache Hadoop in the context of Amazon EMR.

·         Understand the architecture of an Amazon EMR cluster.

·         Launch an Amazon EMR cluster using an appropriate Amazon Machine Image and Amazon EC2 instance types.

·         Choose appropriate AWS data storage options for use with Amazon EMR.

·         Know your options for ingesting, transferring, and compressing data for use with Amazon EMR.

·         Use common programming frameworks available for Amazon EMR including Hive, Pig, and Streaming.

·         Work with Amazon Redshift to implement a big data solution.

·         Leverage big data visualization software.

·         Choose appropriate security options for Amazon EMR and your data.

·         Perform in-memory data analysis with Spark and Shark on Amazon EMR.

·         Choose appropriate options to manage your Amazon EMR environment cost-effectively.

·         Understand the benefits of using Amazon Kinesis for big data.

Intended Audience This course is intended for:

·         Individuals responsible for designing and implementing big data solutions, namely Solutions Architects and SysOps Administrators.

·         Data Scientists and Data Analysts interested in learning about big data solutions on AWS.

Delivery Method

This course will be delivered through a mix of:

·         Instructor-Led Training (ILT).

·         Hands-on Labs.

Hands-On Activity

This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.

Big Data Technology Fundamentals

Big Data Technology Fundamentals provides baseline general knowledge of the technologies used in big data solutions. It covers the development of big data solutions using the Hadoop ecosystem, including Map Reduce, HDFS, and the Pig and Hive programming frameworks. This web-based course helps you build a foundation for working with AWS services for big data solutions. This course is offered at no charge, and can be used on its own or to help you prepare for the Big Data on AWS instructor-led course.

Course Objectives

This course is designed to teach you how to:

·         Identify common tools and technologies that can be used to create big data solutions.

·         Understand the Map Reduce programming framework, including the map, shuffle and sort, and reduce components.

·         Distinguish options available for creating a big data solution using the Hive programming framework.

Intended Audience

This course is intended for:

Individuals who are new to big data concepts, including Enterprise Solutions Architects, Big Data Solutions Architects, Data Scientists, and Data Analysts.

Delivery Method

This course will be delivered through:

·         Web-Based E-Learning.

DevOps Engineering on AWS

DevOps Engineering on AWS demonstrates how to use the most common DevOps patterns to develop, deploy and maintain applications on AWS. The course covers the core principles of the DevOps methodology and examines a number of use cases applicable to startup, small-medium business, and enterprise development scenarios.

Course Objectives

This course is designed to teach you how to:

·         Use the principal concepts and practices behind the DevOps methodology.

·         Design and implement an infrastructure on AWS that supports one or more DevOps development projects.

·         Use AWS Cloud Formation and AWS OpsWorks to deploy the infrastructure necessary to create development, test, and production environments for a software development project.

·         Set up Git on AWS and understand the array of options for enabling a Continuous Integration environment on AWS.

·         Use the core principles of Continuous Integration and Continuous Deployment.

·         Implement several common Continuous Deployment use cases using AWS technologies, including blue/green deployment and A/B testing.

·         Distinguish between the array of application deployment technologies available on AWS (including AWS CodeDeploy, AWS OpsWorks, AWS Elastic Beanstalk, and Amazon EC2 Container Service), and decide which technology best fits a given scenario.

·         Fine tune the applications you deliver on AWS for high performance and use AWS tools and technologies to monitor your application and environment for potential issues.

Intended Audience

This course is intended for:

·         "System Administrators.

·         Software Developers.

Systems Operations on AWS

System Operations on AWS is designed to teach those in a Systems Administrator or Developer Operations (DevOps) role how to create automatable and repeatable deployments of networks and systems on the AWS platform. The course covers the specific AWS features and tools related to configuration and deployment, as well as common techniques used throughout the industry for configuring and deploying systems.

Course Objectives this course is designed to teach you how to:

·         Use standard AWS infrastructure features such as Amazon Virtual Private Cloud (VPC), Amazon Elastic Compute Cloud (EC2), Elastic Load Balancing, and Auto Scaling from the command line.

·         Use AWS Cloud Formation and other automation technologies to produce stacks of AWS resources that can be deployed in an automated, repeatable fashion.

·         Build functioning virtual private networks with Amazon VPC from the ground up using the AWS Management Console.

·         Deploy Amazon EC2 instances using command line calls and troubleshoot the most common problems with instances.

·         Monitor the health of Amazon EC2 instances and other AWS services.

·         Manage user identity, AWS permissions, and security in the cloud.

·         Manage resource consumption in an AWS account using tools such as Amazon Cloud Watch, tagging, and Trusted Advisor.

·         Select and implement the best strategy for creating reusable Amazon EC2 instances.

·         Configure a set of Amazon EC2 instances that launch behind a load balancer, with the system scaling up and down in response to demand.

·         Edit and troubleshoot a basic AWS Cloud Formation stack definition.

Developing on AWS

The Developing on AWS course is designed to help individuals design and build secure, reliable and scalable AWS-based applications. In this course, we cover fundamental concepts and baseline programming for developing applications on AWS. We also show you how to work with AWS code libraries, SDKs, and IDE toolkits so that you can effectively develop and deploy code on the AWS platform.

Course Objectives

This course is designed to teach you how to:

·         Install and configure SDKs and IDE tool kits

·         Automate basic service operations using C# or Java

·         Use security models to manage access to AWS

·         Understand deployment models and usage with AWS

Intended Audience

This course is intended for: Developers

·         Delivery Method

This course will be delivered through a blend of:

·         Instructor-Led Training

·         Hands-on Labs

Advanced Operations on AWS

Deploy, monitor, measure, and scale your applications on Amazon Web Services.

In this course, you will learn how to deploy, operate, and scale your infrastructure by improving the performance, availability, and cost effectiveness of your applications on Amazon Web Services (AWS). You will learn about automating deployments, updating resources, and monitoring operational health of your workloads and applications. Hands-on labs will help you apply learning’s with actual applications and automated workloads.

What You’ll Learn

·         Create new Amazon Cloud Watch metrics and utilize them along with existing AWS service metrics

·         Conduct advanced automated bootstrapping of Amazon Elastic Compute Cloud (EC2) instances configured with Chef

·         Declare, deploy, and update your infrastructure as code with AWS Cloud Formation

·         Respond to operational needs by scaling with Auto Scaling

·         Fail away from an AWS Availability Zone

·         Automate tasks with Amazon Simple Workflow (SWF)

·         Use AWS Identity and Access Management (IAM) to delegate access to your teams and infrastructure components

Who Needs to Attend

·         Developers

·         System administrators

·         Others responsible for managing operations on the AWS platform