Planning Patch Management

Get to grips with patch management and how to plan and implement patches from deployment to retirement.

12 videos  //  77 minutes of training

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Course description

Your cloud solution will need to be patched. Learn about planning patches, the difference between manual and automated patches, workflows, types of updates, and automating workflows. You will also explore the various techniques and tasks required for automated maintenance. Finally, you’ll learn about monitoring, reporting and the application lifecycle.

Course syllabus

Planning Patch ManagementDuration: 6:36

Patch management should be planned properly and not simply performed. This episode introduces the considerations that must be made when planning for patch management.

Manual Patch ManagementDuration: 3:54

Manual patch management is achieved by using the internal operating system or application patch management features. It may be automated using scripting, but this episode focuses on the manual process.

Automated Patch Management LabDuration: 3:34

Automated patch management is a valuable part of cloud operations. This episode demonstrates automated Windows patches in cloud instances.

Update TypesDuration: 7:39

In this episode you will learn about the various update types that must be considered when implementing patch or update management. This information will help you to plan well for update processes.

Automated Workflows LabDuration: 7:13

Automated workflows allow you to automate many tasks that might otherwise consume significant time. This episode explains the types of tasks that might be automated

Backup Types LabDuration: 10:04

Learn about one of the most important regular maintenance tasks you'll need to perform: backups.

Backup Targets and OptionsDuration: 6:37

In this episode, you will learn about backup targets, schedules and other concepts. Selecting the best location to store backups is an important planning task and should be understood by all cloud professionals.

Maintenance Automation TechniquesDuration: 4:57

In this episode, you will explore common tasks that may be automated. While this episode does not address every possible task, it does address the most common tasks that are automated in cloud deployments.

Maintenance Automation TasksDuration: 6:45

The second part of this 2-part episode covers the participant and ownership structures, as well as the mapping function that maps them to different data and variables.

Provisioning and DeprovisioningDuration: 7:00

This episode teaches you about cloud provisioning and deprovisioning and it explains concepts like cloud bursting and cloud provider migrations.

Monitoring and ReportingDuration: 7:19

Monitoring and reporting is an important part of cloud operations. This episode provides an overview of the solutions in Azure as an example and also explains common reporting metrics.

Monitoring MetricsDuration: 5:46

In this final chapter episode, we review some common monitoring metrics used to monitor cloud solutions. This episode will provide a guide for the use of monitoring in your cloud implementations.

Meet the author

Tom Carpenter

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Tom Carpenter is a 25+ year veteran of the IT industry. He started in entry-level systems support and quickly moved into the role of a systems analyst and network engineer. He founded the technical content development and training company SysEdCo in 1997, which he continues to operate.

Having written more than 20 books for the IT industry, he brings a wealth of experience to any topic and holds many certifications from both vendors and vendor-neutral certification organizations. He is also the head of certification development for the CWNP program and heavily involved in objectives development and exam creation within the certification industry.

Tom uses AWS to run several business websites as well as test labs used for content creation and management. According to Tom, "AWS is everything I did in the 90s, and more, in the cloud!” Tom lives in Ohio with his lovely wife Julie and enjoys anything related to technology, learning and human potential. lth and status of a 60-node SIEM cluster designed to handle data from 60,000 data sources.

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