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VMware Site Recovery Manager: Install, Configure, Manage [V8.2]
| Summary: | Live Online (2 Days) English
(GMT-06:00) Central Standard Time (America/Chicago) VMware Learning This two-day, hands-on training course gives experienced VMware vSphere® administrators the knowledge to install, configure, and manage VMware Site Recovery Manager™ 8.2. This course also shows you how to write and test disaster recovery plans that use Site Recovery Manager. This course is also available in an On Demand format. For more information, select this link: VMware Site Recovery Manager: Install, Configure, Manage [V8.2] - On Demand. Product Alignment • VMware Site Recovery Manager [V8.2] | |||||||||||||||||||||||||||||||||||||||||||||||||
| Objectives: | By the end of the course, you should be able to meet the following objectives: • Summarize the components of Site Recovery Manager architecture • Deploy and configure the Site Recovery Manager appliance • Describe the principal disaster recovery topologies that are used with Site Recovery Manager • Configure inventory and resource mappings • Describe the storage replication options that are used with Site Recovery Manager • Configure Site Recovery Manager to leverage array-based replication • Describe VMware vSphere® Replication™ functionality • Describe the vSphere Replication architecture • Deploy and configure vSphere Replication for use with Site Recovery Manager • Build Site Recovery Manager protection groups based on vSphere Replication • Build, edit, execute, test, and remove a recovery plan • Perform a planned migration • Perform reprotect and failback using Site Recovery Manager and vSphere Replication | |||||||||||||||||||||||||||||||||||||||||||||||||
| Intended Audience: | vSphere administrators, architects, system engineers, and systems integrators who are responsible for the deployment or management of Site Recovery Manager | |||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites: | This class requires completion of one of the following courses: • VMware vSphere: Install, Configure, Manage [V6.x] • VMware vSphere: Fast Track [V6.x] • VMware vSphere: What’s New [V5.5 to V6.x] • VMware vSphere: Troubleshooting Workshop [V6.x] Or equivalent knowledge and administration experience with VMware ESXi™ and VMware vCenter Server™. | |||||||||||||||||||||||||||||||||||||||||||||||||
| Outline: | 1 Course Introduction • Outline the necessary information to effectively undertake this course • Identify resources for additional information 2 Overview and Architecture • Discuss Site Recovery Manager architecture • Examine disaster recovery options with Site Recovery Manager • Describe Site Recovery Manager integration with VMware vSphere® ClientTM • Discuss Site Recovery Manager features • Analyze Site Recovery Manager storage policies and integration options • Discuss how Site Recovery Manager supports several disaster recovery topologies • Identify use cases for Site Recovery Manager across various scenarios • Describe how VMware Site Recovery™ for VMware Cloud™ on AWS integrates with Site Recovery Manager. 3 Deploy & Configure Site Recovery Manager • Identify the requirements to deploy Site Recovery Manager • Discuss the benefits of the Site Recovery Manager appliance • Explore vSphere deployment models • Deploy the Site Recovery Manager appliance • Navigate the Site Recovery Manager configuration user interface • Describe the process to register Site Recovery Manager with VMware vCenter Server® • Configure site pairing • Identify how to perform updates to the Site Recovery Manager appliance 4 Configuring Inventory Mappings • Outline the importance of inventory mappings • Examine configuration options for inventory mappings • Outline the importance of placeholders 5 Using Array-based Replication • Describe array-based replication • Discuss the role of the Storage Replication Adapter (SRA) • Explore the relationship between devices, consistency groups and datastore groups • Configure array pairs 6 vSphere Replication • Explore vSphere Replication architecture • Examine vSphere Replication functionality • Formulate use cases for vSphere Replication • Deploy a vSphere Replication appliance • Configure vSphere Replication appliance settings • Configure a vSphere Replication appliance connection • Deploy a vSphere Replication server • Register a vSphere Replication server 7 Replicating Virtual Machines with vSphere Replication • Configure vSphere Replication for virtual machines • Explain the importance of datastore mappings • Describe vSphere Replication recovery point objective scheduling • Describe the vSphere Replication disk transfer protocol 8 Building Protection Groups • Define protection group functionality • Examine the differences between array-based protection groups, protection groups based on vSphere Replication, and storage profile protection groups • Create a protection group • Discuss protection group settings • Remove protection from a virtual machine • Create a storage profile protection group 9 Building Recovery Plans • Discuss recovery plan concepts • List recovery plan steps • Discuss network planning • Discuss customization options in recovery planning • Outline how to implement a recovery plan • Investigate recovery plan options 10 Testing and Running a Recovery Plan • Discuss use cases for Site Recovery Manager • Describe planned migration • Identify Site Recovery Manager workflows • Discuss the importance of VMware vSphere® VMFS resignaturing • Examine Site Recovery Manager integration with various vSphere technologies • Outline how to conduct a recovery plan test • Perform recovery plan test execution • Identify the effects on the storage layer during recovery steps • Explain a recovery plan execution in planned migration or disaster recovery mode • Understand storage layer changes for plan execution types • Identify the recovery steps for each execution type • Describe how to reprotect a data center • Examine failback steps 11 Monitoring and Troubleshooting • Discuss Site Recovery Manager alarms • Explore Site Recovery Manager history reports • Configuring advanced Site Recovery Manager settings • Describe how to modify logging levels • Explain how to collect log bundles • Identify key log locations | |||||||||||||||||||||||||||||||||||||||||||||||||
Displaying data: R code for Chapter 2 examples
Download the R code on this page as a single file here.
New methods on this page
Click on a function argument for a short description of its meaning. The variable names are plucked from the examples further below.
Read data from a comma-separated (.csv) file into a data frame. R will take columns having only numbers and make them numeric variables in the data frame. Columns having characters will be converted to variables, rather than to character variables. <- read.csv()
Inspect data in a data frame. The head function shows the first few lines of the data frame to confirm the data was read properly. The nrow function indicates the number of cases (rows) in the data frame.head()nrow()
Basic strip chart relating a numeric variable to a categorical variable:stripchart(, , ,
)
Frequency table or contingency table:table()
Bar graph for count data:barplot(, , )
Histogram for a numeric variable:hist(, )
Scatter plot showing association between two numeric variables:plot(, )
Other new methods:
Multiple-histogram plot.
Line plot.
Load an R package.
Set the desired ordering of categories of a factor variable in tables and graphs.
Figure 2.1-2. Locust serotonin
Strip chart of serotonin levels in the central nervous system of desert locusts that were experimentally crowded for 0 (the control group), 1, and 2 hours.
Read the data and store in data frame (here named locustData). The following command uses read.csv to grab the data from a file on the internet (on the current web site).
Show the first few lines of the data, to ensure it read correctly. Determine the number of cases in the data.
Draw a stripchart (the tilde '~' means that the first argument below is a formula, relating one variable to the other).
We show how to draw a fancier strip chart, closer to that shown in Figure 2.1-2, by including more options.
Figure 2.1-3. Education spending
A bar graph of education spending per student in different years in British Columbia.
Read the data into a data frame named educationSpending, and inspect.
Draw a bar graph. The names argument generates numbers between 1998 and 2004 in 1-year increments, to be used as labels along the horizontal axis.
A slightly fancier bar graph like that in Figure 2.1-3, which includes additional options, is shown .
Example 2.2A. Deaths from tigers
Frequency table and bar graph showing activities of 88 people at the time they were killed by tigers near Chitwan National Park, Nepal, from 1979 to 2006.
Read the data into data frame named tigerData
Generate a frequency table. The sort function is included to sort the categories by their frequencies.
You can arrange the frequency table vertically.
Use the addmargins command to include sums in your frequency table.
Draw a bar graph. The additional arguments cex.names = 0.5 shrinks the axis labels by 50%, and las = 2 flips the labels, so that they all fit in the window.
A slightly fancier bar graph of the data with more options, like that shown in Figure 2.2-1, is shown .
Example 2.2B. Desert bird abundance
Frequency table and histogram illustrating the frequency distribution of bird species abundance at Organ Pipe Cactus National Monument.
Read and inspect the data.
Generate a frequency table of the numeric bird abundance variable. The option right = FALSE ensures that abundance value 300 (for example) is counted in the 300-400 bin rather than in the 200-300 bin.
The same table oriented vertically and including the sum.
Draw a histogram of bird abundances.
Commands to draw a histogram with more options, such as Figure 2.2-3, are .
Figure 2.2-5. Salmon body size
Histograms of body mass of 228 female sockeye salmon sampled from Pick Creek in Alaska. The same data are plotted for three different interval widths: 0.1 kg, 0.3 kg, and 0.5 kg.
Read the data into data frame named salmonSizeData
Histograms with different bin widths (0.1, 0.3, and 0.5).
Example 2.3A. Bird malaria
Contingency table, grouped bar plot, and mosaic plot showing the association between egg removal treatment and incidence of malaria in female great tits.
Read the data from the data file and inspect.
Optional step: Set the desired order of treatment categories in tables and graphs. The factor command allows us to order the levels so that the category 'Egg removal' comes before 'Control' in tables and graphs (categories are otherwise ordered alphabetically).
Create a contingency table. Use table with the names of two categorical variables as arguments, beginning with the response variable.
Include row and column sums in the contingency table.
Draw a grouped bar graph using the contingency table.
Commands to produce a grouped bar graph with more options are shown .
Draw a mosaic plot. The 't' command flips (transposes) the table to ensure that the explanatory variable is along the horizontal axis.
Example 2.3B. Guppy father and son comparison
Scatter plot of the relationship between the ornamentation of male guppies and the average attractiveness of their sons.
Read the data from the file.
Draw a scatter plot using the formula approach (with the '~').
See for commands to draw a fancier scatter plot like that in Figure 2.3-3.
Example 2.3C. Human hemoglobin and elevation
Strip chart, box plot, and multiple histograms showing hemoglobin concentration in men living at high altitude in three different parts of the world and in a sea level population (USA).
Read the data.
Obtain the sample sizes in each of the four populations
Draw a strip chart of the hemoglobin data.
Commands for a fancier strip chart like that shown in Figure 2.3-4 are .
Draw a box plot, relating hemoglobin to population.
A box plot with more options, like that in Figure 2.3-4, is shown here.
Show the association between hemoglobin and population using the multiple histograms approach (Figure 2.3-5). The following commands use the lattice package, which must first be loaded.
we show commands to draw the multiple histograms in basic R, without using the lattice package. This approach is more tedious, but the resulting graphs are often easier to modify.
Example 2.4A. Measles outbreaks
Line graph showing confirmed cases of measles in England and Wales from 1995 to 2011. Annual counts are quarterly.
Read the data from file.
Drawing a line graph uses the same command as a scatter plot but adds the type = 'l' argument to draw a line graph instead.
Commands to draw a fancier line plot (like that in Figure 2.4-1) are shown .
file.choose() if instead you want a window to pop up that lets you select the file on your computer by point-and-click.serotoninLevel) on the y-axis to a categorical explanatory variable (treatmentTime) on the x-axis.