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@ -50,10 +50,9 @@ library(rattle) # Use weatherAUS as a "large" dataset.
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# name the resource group that we will create transiently for the
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# purposes of this script.
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# RG <- "my_dsvm_rg_sea" # Create if not already exist then kill.
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RG <- "dsvm"
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RG <- "my_dsvm_rg_sea" # Create if not already exist then kill.
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LOC <- "southeastasia" # Where the resource group (resources) will be hosted.
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VM <- "msvm001"
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VM <- "mydsvm001"
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VM_URL <- paste(VM, LOC, "cloudapp.azure.com", sep=".")
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```
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@ -0,0 +1,196 @@
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---
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title = "Using Azure Data Science Resources: Connect to Linux DSVM Quick Start"
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author= "Graham Williams"
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---
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# Use Case
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A Linux Data Science Virtual Machine (DSVM) is deployed, a remote
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command is executed to demonstrates it exists, and then the resource
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group is delete (unless the resource group pre-exists this script.
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This script is best run interactively to review its operation and to
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ensure that the interaction with Azure completes.
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# Preparation
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We assume the user already has an Azure subscription and we have
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obtained the credentials required. See
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[AzureSMR's Authentication Guide](https://github.com/Microsoft/AzureSMR/blob/master/vignettes/Authentication.Rmd)
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for details. We will then ensure a resource group exists and within
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that resource group create a Linux DSVM. A public ssh key is used to
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access the server in this script although a username and password is
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also an option. We create a Linux DSVM and a WindowsDSVM.
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# Setup
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To get started we need to load our Azure credentials as well as the
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user's ssh public key. Public keys on Linux are typically created on
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the users desktop/laptop machine and will be found within
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~/.ssh/id_rsa.pub. It will be convenient to create a credentials file
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to contain this information. The content's of the credentials file
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will be something like:
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```{r credentials, eval=FALSE}
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# Credentials come from app creation in Active Directory within Azure.
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TID <- "72f9....db47" # Tenant ID
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CID <- "9c52....074a" # Client ID
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KEY <- "9Efb....4nwV....ASa8=" # User key
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PUBKEY <- readLines("~/.ssh/id_rsa.pub") # For Linux DSVM
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PASSWORD <- "AmSj&%4aR3@kn" # For Windows DSVM
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```
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Save such information into a file with the name <USER>_credentials.R
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where <USER> is replaced with your username. Then we simply source
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that file in R.
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```{r setup}
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# Load the required subscription resources: TID, CID, and KEY.
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# Also includes the ssh PUBKEY for the user.
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USER <- Sys.getenv("USER")
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source(paste0(USER, "_credentials.R"))
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# Install the packages if required.
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## devtools::install_github("Microsoft/AzureSMR")
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## devtools::install_github("Azure/AzureDSR", auth_token=GIT_TOKEN)
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```
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```{r packages}
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# Load the required packages.
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library(AzureSMR) # Support for managing Azure resources.
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library(AzureDSR) # Further support for the Data Scientist.
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library(magrittr)
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library(dplyr)
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library(rattle) # Use weatherAUS as a "large" dataset.
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```
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```{r tuning}
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# Parameters for this script: the name for the new resource group and
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# its location across the Azure cloud. The resource name is used to
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# name the resource group that we will create transiently for the
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# purposes of this script.
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RG <- "my_dsvm_rg_sea" # Will be created if not already exist then kill.
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LOC <- "southeastasia" # Where the resource group (resources) will be hosted.
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LDSVM <- "mydsvm001"
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WDSVM <- "mydsvm002"
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```
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```{r connect}
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# Connect to the Azure subscription and use this as the context for
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# our activities.
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context <- createAzureContext(tenantID=TID, clientID=CID, authKey=KEY)
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# Check if the resource group already exists. Take note this script
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# will not remove the resource group if it pre-existed.
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context %>%
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azureListRG() %>%
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filter(name == RG) %>%
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select(name, location) %T>%
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print() %>%
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nrow() %>%
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equals(0) %>%
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not() %T>%
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print() ->
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rg_pre_exists
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```
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# Creation
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Create the resource group within which all resources we create will be
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grouped.
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```{r create resource group}
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if (! rg_pre_exists)
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{
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# Create a new resource group into which we create the VMs and
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# related resources. Resource group name is RG.
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# Note that to create a new resource group one needs to add access
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# control of Active Directory application at subscription level.
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azureCreateResourceGroup(context, RG, LOC)
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}
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```
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Create the actual Linux DSVM with public-key based authentication
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method. Name, username, and size can also be configured.
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```{r deploy}
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# Create the required Linux DSVM - generally 4 minutes.
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ldsvm <- deployDSVM(context,
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resource.group=RG,
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location=LOC,
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name=LDSVM,
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username=USER,
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size="Standard_DS1_v2",
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os="Linux",
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authen="Key",
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pubkey=PUBKEY)
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ldsvm
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```
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`deployDSVM` also supports deployment of Windows DSVM, which can be
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achieved by setting the argument of `os` to "Windows".
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```{r}
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wdsvm <- deployDSVM(context,
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resource.group=RG,
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location=LOC,
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name=WDSVM,
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username=USER,
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size="Standard_DS1_v2",
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os="Windows",
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password=PASSWORD)
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wdsvm
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```
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Prove that the server exists.
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```{r prove exists}
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# Send a simple system() command across to the new server to test its
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# existence. Expect a single line with an indication of how long the
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# server has been up and running.
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cmd <- paste("ssh -q",
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"-o StrictHostKeyChecking=no",
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"-o UserKnownHostsFile=/dev/null",
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ldsvm, "uptime")
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cmd
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system(cmd)
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```
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# Optional Stop
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We can stop the ...
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```{r}
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if (FALSE)
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operateDSVM(context, RG, LVM, operation="Stop")
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```
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# Optional Cleanup
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```{r optionally delete resource group}
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# Delete the resource group now that we have proved existence. There
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# is probably no need to wait. Only delete if it did not pre-exist
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# this script. Deletion seems to take 10 minutes or more.
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if (FALSE & ! rg_pre_exists)
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azureDeleteResourceGroup(context, RG)
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```
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Once deleted we are consuming no more.
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