Deploy Rancher on Azure for Kubernetes Management

Lately I have been hearing a lot about a solution named Rancher in the Kubernetes space. Rancher is an open source Kubernetes Multi-Cluster Operations and Workload Management solution. You can learn more about Rancher here: https://www.rancher.com.

In short you can use Rancher to deploy and manage Kubernetes clusters deployed to Azure, AWS, GCP their managed Kubernetes offerings like GCE, EKS, AKS or even if you rolled your own. Rancher also integrates with a bunch of 3rd party solutions for things like authentication such as Active Directory, Azure Active Directory, Github, and Ping and logging solutions such as Splunk, Elasticsearch, or a Syslog endpoint.

Recently training opened up for some Rancher/Kubernetes/Docker training so I decided to go. The primary focus was on Rancher while also covering some good info on Docker and Kubernetes. This was really good training with a lot of hands on time, however there was one problem with the labs. The labs had instructions and setup scripts ready to go to run Rancher local on your laptop or on AWS via Terraform. There was nothing for Azure.

I ended up getting my Rancher environment running on Azure but it would have been nice to have some scripts or templates ready to go to spin up Rancher on Azure. I did find some ARM templates to spin up Rancher but they deployed an old version and it was not clear in the templates on where they could be updated to deploy the new version of Rancher. I decided to spend some time building out a couple of ARM templates that can be used to quickly deploy Rancher on Azure and add a Kubernetes host to Rancher. In the ARM template I pulled together it pulls the Rancher container from Docker Hub so it will always deploy the latest version. In this blog post I will spell out the steps to get your Rancher up and running in under 15 minutes.

First off you can find the ARM Templates here on my Github here: https://github.com/Buchatech/DeployRanchertoAzure.

The repository consists of ARM templates for deploying Rancher and a host VM for Kubernetes. NOTE: These templates are intended for labs to learn Rancher. They are not intended for use in production.

In the repo ARM Template #1 named RancherNode.JSON will deploy an Ubuntu VM with Docker and the latest version of Rancher (https://hub.docker.com/r/rancher/rancher) from Docker Hub. ARM Template #2 named RancherHost.JSON will deploy an Ubuntu VM with Docker to be used as a Kubernetes host in Rancher.

Node Deployment

Deploy the RancherNode.JSON ARM template to your Azure subscription through “Template Deployment” or other deployment method. You will be prompted for the following info shown in the screenshot:

Host Deployment

Deploy the RancherHost.JSON ARM template to your Azure subscription through “Template Deployment” or other deployment method. Note that that should deploy this into the same Resource Group that you deployed the Rancher Node ARM template into. You will be prompted for the following info shown in the screenshot:

After the Rancher Node and Rancher Host ARM templates are deployed you should see the following resources in the new Resource Group:

NameType
RancherVNet Virtual network
RancherHost Virtual machine
RancherNode Virtual machine
RancherHostPublicIP Public IP address
RancherNodePublicIP Public IP address
RancherHostNic Network interface
RancherNodeNic Network interface
RancherHost_OSDisk Disk
RancherNode_OSDisk Disk

Next navigate the Rancher portal in the web browser. The URL is the DNS name of the Rancher Node VM. You can find the DNS name by clicking on the Rancher Node VM in the Azure portal on the overview page. Here is an example of the URL:

https://ranchernode.centralus.cloudapp.azure.com

The Rancher portal will prompt you to set a password. This is shown in the following screenshot.

After setting the password the Rancher portal will prompt you for the correct Rancher Server URL. This will automatically be the Rancher Node VM DNS name. Click Save URL.

You will then be logged into the Rancher portal. You will see the cluster page. From here you will want to add a cluster. Doing this is how you add a new Kubernetes cluster to Rancher. In this post I will show you how to add a cluster to the Rancher Host VM. When it’s all said and done Rancher will have successfully deployed Kubernetes to the Rancher Host VM. Note that you could add a managed Kubernetes such as AKS but we won’t do that in this blog. I will save that for a future blog post!

Click on Add Cluster

Under “From my own existing nodes” Click on custom, give the cluster a name and click Next.

Next check all the boxes for the Node Options since all the roles will be on a single Kubernetes cluster. Copy the code shown at the bottom of the page, click done and run the code on the Rancher Host.

In order to run the code on the Rancher Host you need to SSH in and run it from there. To do this follow these steps:

  1. In the Azure Portal, from within the resource group click on the Rancher Host VM.
  2. On the Overview page click on Connect.
  3. Copy “ssh ranchuser@rancherhost.centralus.cloudapp.azure.com” from the Connect to virtual machine pop up screen.
  4. Open a terminal in either Azure cloud shell or with something like a terminal via VS Code and past the “ssh ranchuser@rancherhost.centralus.cloudapp.azure.com” in.

Running the code will look like this:

When done you can run Docker PS to see that the Rancher agent containers are running.

In the Rancher portal under clusters you will see the Rancher host being provisioned

The status will change as Kubernetes is deployed.

Once it’s done provisioning you will see your Kubernetes cluster as Active.

From here you can see a bunch of info about your new Kubernetes cluster. Also notice that you could even launch Kubectl right from hereand start running commands! Take some time to click around to see all the familiar stuff you are used to working with in Kubernetes. This is pretty cool and simplifies the management experience for Kubernetes. 

If you want to add more nodes or need the configuration code again just click the ellipsis button and edit.

In Edit Cluster you can change the cluster name, get and change settings and copy the code to add more VMs to the cluster.

That’s the end of this post. Thanks for reading. Check back for more Azure, Kubernetes, and Rancher blog posts.

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Require Many Tags on Resource Groups via Azure Policy

Azure Policy can be used to enforce rules and effects on resources in your Azure subscriptions. It is a part of the Azure Governance and management toolbox native to Azure. I actually wrote a blog post all about Azure Policy here as a part of my native cloud management in azure blog series.

In this blog post I want to dig into Requiring Tags on Resource Groups via Azure Policy. There is a sample policy ARM Template to accomplish this here:

https://docs.microsoft.com/en-us/azure/governance/policy/samples/enforce-tag-on-resource-groups . What is not clear with the this policy template is how to add an enforce additional tags within the single ARM Template. This is important as you don’t want to have multiple templates to enforce multiple tags.

Well its actually pretty straight forward. You need to add the additional tags as Rules and Parameters. For example:

{
"not": {
"field": "[concat('tags[',parameters('Environment'), ']')]",
"exists": "true"
}
},

and

"Environment": {
"type": "String",
"metadata": {
"description": "Provides information on what the resource group is used for (useful for maintenance, policy enforcement, chargeback, etc.) Tag value: Dev, QA, Stage, Test, Prod. Example: Prod"
}
},

Be sure you add a parameter for every rule. Also in the example I gave I removed the “equals”: “[parameters(‘tagValue’)]” from the rules because I did not want to populate the tag value. I simply needed to require the tag and leave the value open for the person creating the resource to fill in. Here is the full example Policy ARM Template here:

{
  "mode": "all",
  "policyRule": {
    "if": {
      "allOf": [
        {
          "field": "type",
          "equals": "Microsoft.Resources/subscriptions/resourceGroups"
        },
        {
          "not": {
            "field": "[concat('tags[',parameters('BillTo'), ']')]",
            "exists": "true"
          }
        },
        {
            "not": {
              "field": "[concat('tags[',parameters('Functional Area'), ']')]",
              "exists": "true"
            }
          },
          {
            "not": {
              "field": "[concat('tags[',parameters('Environment'), ']')]",
              "exists": "true"
            }
          },
          {
            "not": {
              "field": "[concat('tags[',parameters('AppOwner'), ']')]",
              "exists": "true"
            }
          }
      ]
    },
    "then": {
      "effect": "deny"
    }
  },
  "parameters": {
    "BillTo": {
      "type": "String",
      "metadata": {
        "description": "Provides a charge code or cost center to attribute the bill for the resources too. Tag value: Cost Center. Example: team@domain.com"
      }
    },
    "Functional Area": {
        "type": "String",
        "metadata": {
          "description": "Provides information on department or team is responsible for administering/supporting the application. Tag value: Team name/email. Example: 1506548"
        }
      },
      "Environment": {
        "type": "String",
        "metadata": {
          "description": "Provides information on what the resource group is used for (useful for maintenance, policy enforcement, chargeback, etc.) Tag value: Dev, QA, Stage, Test, Prod. Example: Prod"
        }
      },
      "AppOwner": {
        "type": "String",
        "metadata": {
          "description": "The Business app owner to contact. Tag value: Business App owners’ email. Example: name@domain.com"
        }
      }
  }
}

After you create the Policy definition using the ARM template it will look like this:

When you assign the policy you will need to complete the parameters:

The next time someone deploys a resource group without the required tags in the subscription this policy is assigned to it will fail.

Thanks for reading!

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Where to host Docker Containers on Azure (AKS, ASE, or ASF)?

Azure Kubernetes Service (AKS) service Azure App Service Environment (ASE) Azure Service Fabric (ASF) Comparison

Scenario:

So, your team recently has been tasked with developing a new application and running it. The team made the decision to take a microservices based approach to the application. Your team also has decided to utilize Docker containers and Azure as a cloud platform. Great, now it’s time to move forward right? Not so fast. There is no question that Docker containers will be used, but what is in question is where you will run the containers. In Azure containers can run on Azure’s managed Kubernetes (AKS) service, an App Service Plan on Azure App Service Environment (ASE), or Azure Service Fabric (ASF). Let’s look at each one of these Azure services including an overview, pro’s, cons, and pricing.

This Azure Kubernetes Service (AKS) Pros and Cons chart is clickable.
This Azure App Service Environment (ASE) Pros and Cons chart is clickable.
This Azure Service Fabric (ASF) Pros and Cons chart is clickable.

Conclusion:

Choose Azure Kubernetes Service if you need more control, want to avoid vendor lock-in (can run on Azure, AWS, GCP, on-prem), need features of a full orchestration system, flexibility of auto scale configurations, need deeper monitoring, flexibility with networking, public IP’s, DNS, SSL, need a rich ecosystem of addons, will have many multi-container deployments, and plan to run a large number of containers. Also, this is a low cost.

Choose Azure App Service Environment if don’t need as much control, want a dedicated SLA, don’t need deep monitoring or control of the underlying server infrastructure, want to leverage features such as deployment slots, green/blue deployments, will have simple and a low number of multi-container deployments via Docker compose, and plan to run a smaller number of containers. Regarding cost, running a containerized application in an App Service Plan in ASE tends to be more expensive compared to running in AKS or Service Fabric. The higher cost of running containers on ASE is because with an App Service Plan on ASE, you are paying costs for a combination of resources and the managed service. With AKS and ASF you are only paying for the resources used.

Choose Service Fabric if you want a full micros services platform, need flexibility now or in the future to run in cloud and or on-premises, will run native code in addition to containers, want automatic load balancing, low cost.

A huge thanks to my colleague Sunny Singh (@sunnys101) for giving his input and reviewing this post. Thanks for reading and check back for more Azure and container contents soon.

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Monitoring Azure Kubernetes Service (AKS) with Azure Monitor & Log Analytics

Part of running Kubernetes is being able to monitoring the cluster, the nodes, and the workloads running in it. Running production workloads regardless of PaaS, VM’s, or containers requires a solid level of reliability. Azure Kubernetes Service comes with monitoring provided from Azure bundled with the semi-managed service. Kubernetes also has built in monitoring that can also be utilized.

It is important to note that AKS is a free service and Microsoft aims to achieve at least 99.5% availability for the Kubernetes API server on the master node side.

But due to AKS being a free service Microsoft does not carry an SLA on the Kubernetes cluster service itself. Microsoft does provide an SLA for the availability of the underlying nodes in the cluster via the Azure Virtual Machines SLA. Without an official SLA for the Kubernetes cluster service it becomes even more critical to understand your deployment and have the right monitoring tooling and plan in place so when an issue arises the DevOps or CloudOps team can address, investigate, and resolve any issues with the cluster.

The monitoring service included with AKS gives you monitoring from two perspectives including the first one being directly from an AKS cluster and the second one being all AKS clusters in a subscription. The monitoring looks at two key areas “Health status” and “Performance charts” and consists of:

Insights – Monitoring for the Kubernetes cluster and containers.

Metrics – Metric based cluster and pod charts.

Log Analytics – K8s and Container logs viewing and search.

Azure Monitor

Azure Monitor has a containers section. Here is where you will find a health summary across all clusters in a subscription including ACS. You also will see how many nodes and system/user pods a cluster has and if there are any health issues with the a node or pod. If you click on a cluster from here it will bring you to the Insights section on the AKS cluster itself.

If you click on an AKS cluster you will be brought to the Insights section of AKS monitoring on the actual AKS cluster. From here you can access the Metrics section and the Logs section as well as shown in the following screenshot.

Insights

Insights is where you will find the bulk of useful data when it comes to monitoring AKS. Within Insights you have these 4 areas Cluster, Nodes, Controllers, and Containers. Let’s take a deeper look into each of the 4 areas.

Cluster

The cluster page contains charts with key performance metrics for your AKS clusters health. It has performance charts for your node count with status, pod count with status, along with aggregated node memory and CPU utilization across the cluster. In here you can change the date range and add filters to scope down to specific information you want to see.

Nodes

After clicking on the nodes tab you will see the nodes running in your AKS cluster along with uptime, amount of pods on the node, CPU usage, memory working set, and memory RSS. You can click on the arrow next to a node to expand it displaying the pods that are running on it.

What you will notice is that when you click on a node, or pod a property pane will be shown on the right hand side with the properties of the selected object. An example of a node is shown in the following screenshot.

Controllers

Click on the Controllers tab to see the health of the clusters controllers. Again here you will see CPU usage, memory working set, and memory RSS of each controller and what is running a controller. As an example shown in the following screenshot you can see the kubernetes dashboard pod running on the kubernetes-dashboard controller.

The properties of the kubernetes dashboard pod as shown in the following screenshot gives you information like the pod name, pod status, Uid, label and more.

You can drill in to see the container the pod was deployed using.

Containers

On the Containers tab is where all the containers in the AKS cluster are displayed. An as with the other tabs you can see CPU usage, memory working set, and memory RSS. You also will see status, the pod it is part of, the node its running on, its uptime and if it has had any restarts. In the following screenshot the CPU usage metric filter is used and I am showing a containers that has restarted 71 times indicating an issue with that container.

 In the following screenshot the memory working set metric filter is shown.

You can also filter the containers that will be shown through using the searching by name filter.

You also can see a containers logs in the containers tab. To do this select a container to show its properties. Within the properties you can click on View container live logs (preview) as shown in the following screenshot or View container logs. Container log data is collected every three minutes. STDOUT and STDERR is the log output from each Docker container that is sent to Log Analytics.

Kube-system is not currently collected and sent to Log Analytics. If you are not familiar with Docker logs more information on STDOUT and STDERR can be found on this Docker logging article here:  https://docs.docker.com/config/containers/logging.

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Architect your Cloud with Azure Blueprints

Today as a part of the Azure Governance and management announcements at Microsoft Ignite 2018 Azure Blueprints Public Preview was announced. Azure Blueprints are a core part of the cloud governance and management story. They go hand and hand with Management Groups and will take the enterprise management story of Azure up a level. In this blog post I will take a deep dive into Azure Blueprints explaining what they are and give an example of how they can be used.

NOTE: This is a long blog post so I have also published this content as a whitepaper. The whitepaper PDF can be downloaded here.

BLUEPRINTS OVERVIEW

At a high-level Azure Blueprints help you meet organizational cloud standards, patterns, and requirements through governed subscriptions enabled and enforced by the grouping of artifacts like ARM templates, Azure policies, RBAC role assignments, and resource groups within a Blueprint.

Blueprints can be used to lay a cloud foundation, as cloud patterns, and group cloud governance frameworks. Blueprints are a one-click solution for deploying a cloud foundation, pattern, or governance framework to an Azure subscription. Think of an Azure Blueprint as re-usable design parameters for cloud that can be shared and used across an enterprise.

Azure architects typically map out and plan the many aspects of a cloud foundation for an organization such as access management, networking, storage, policy, security/compliance, naming conventions, tagging, monitoring, backup, locations, and more. Now Azure architects can step this designing a step further build these designs as Azure Blueprints and then apply them to subscriptions. The Blueprints give architects a way to orchestrate the deployment of grouped components to speed up the development and provisioning of new Azure environments ensuring they are meeting organizational compliance.

BLUEPRINTS ARE NOT AZURE POLICY

Azure policy is a service targeted to resource properties that exists or when being deployed with allow or explicit deny policies. It is used to ensure resources in an Azure subscription adhere to requirements and standards of an organization.

Azure policies can exist on their own or be a part of an Azure Blueprint. Blueprints do not replace Policy they are one of the Artifact types that make up a Blueprint.

THE MAKEUP OF A BLUEPRINT

Definition

A Blueprint consists of a Definition. The Definition is the design of what should be deployed it consists of the name of the Blueprint, the description and the Definition location. The Definition Location is the place in the Management Group hierarchy where this Blueprint Definition will be stored and determines the level assignment is allowed at. Currently you must have Contributor access to a Management Group to be able to save a Blueprint Definition to it. A Blueprint can be assigned at or below the Management Group it has set in its Definition Location. Here is a diagram to visualize Blueprint Assignment in relation to Management Group hierarchy:

Azure Blueprint Assignment

Artifacts

The Definition is where Blueprint Artifacts are added. As of right now the following is a list of the Artifact types:

  • Policy Assignments – Lets you add an Azure Policy. This can be a built-in or custom policy.
  • Role Assignments – Lets you add a user, app, or group and set the role. Only built-in roles are currently supported.
  • Azure Resource Manager templates – Lets you add an ARM Template. This does not let you import a parameters file. It does let you pre-set the parameters or set the parameters during assignment of the Blueprint.
  • Resource Groups – Lets you add a Resource Group to be created as a part of this Blueprint.

In my opinion the ARM Template artifact is the most impactful of the Blueprint artifact types because you can define such a variety of resources here. It opens the Blueprint to the power of ARM in general. Hopefully in the future we will see more scripting capability or the ability to load PowerShell scripts, runbooks, and or Functions.

There are two levels in the Artifacts. The first level is Subscription. The second level is Resource Group. Resource Group artifacts cannot be added to a Resource Group artifact. A Resource Group artifact can be created in a Subscription. An ARM Template artifact can only be created in a Resource Group artifact. A Policy Assignments or Role Assignments can be created at either the Subscription or Resource Group level.

Assignment

After a Blueprint has been built it needs to be applied. Applying a Blueprint is known as Blueprint assignment. The assignment is essentially the “what was deployed” for a Blueprint. This is how the artifacts are pushed out to Azure and used to track and audit deployments in Azure.

Sequencing

When the assignment of a Blueprint is processed the default order of resource creation is:

  • Role assignment artifacts at the Subscription level
  • Policy assignment artifacts at the Subscription level
  • Azure Resource Manager template artifacts at the Subscription level
  • Resource group artifacts and its child artifacts (role assignment, policy assignment, ARM Templates) at the Resource Group level

When a blueprint includes multiple Azure Resource Manager templates there may be a need to customize the sequencing order in which the Blueprint will deploy artifacts during assignment. You customize the artifact deployment sequence by deploying a Blueprint from an ARM Template declaring a dependency within it or declaring a dependency within an ARM Template artifact in the Blueprint. You declare a dependency using the dependsOn property in JSON. This essentially is a string array of artifact names.

Resource Locking

In cloud environments consistency is key. Naturally Azure Blueprints can also leverage resource locking in Azure. Blueprints have a Locking Mode. This Locking Mode can be applied to None or All Resources and is determined during the assignment of the Blueprint. The decision on cannot be changed later. If a locking state needs to be removed, then you must first remove the Blueprint assignment.

Some Blueprint artifacts create resources during assignment. These resources can have the following state:

  • Not Locked – Can be changed. Can be deleted.
  • Read Only – Can’t be changed and can’t be deleted.
  • Cannot Edit / Delete – Create, update, and delete within the resource group.

Artifacts that become Resource groups get the state of Cannot Edit / Delete automatically but you can create, update, and delete resources within them.

The high-level stages of an Azure Blueprint are Create it, assign it to a scope, and track it.

Anatomy of a Blueprint:

Azure Blueprint Anatomy

 

Blueprint does have a REST API. I am not covering the REST API in this blog post as I have not had the opportunity to spend much time working with it yet.

Now let’s look at building and assigning an Azure Blueprint.

BUILD A BLUEPRINT

Now I am going to give an example of building and using an Azure Blueprint in a cloud foundation mock scenario. In my mock scenario I have 3 Azure subscriptions. Each subscription should have a Core services Resource Group consisting of a core VNet with 3 subnets, an NSG for each subnet, and the web subnet should be ready for DMZ traffic. For the core VNet and any additional VNet added to the Core Services Resource Group I need network watcher deployed to it.

Each subscription also should have a core storage account and a blob storage that is ready for general storage needs. I want a tag applied to any Blueprint assignment labeling it with the assignment name, so it is easy to track. The last requirement I have is that I need the CloudOps team to automatically be owner of all core services resources. To accomplish all of this I created the following Blueprint:

Now let’s walk through the parts of creating and assigning the Blueprint. The first step is to create the Blueprint Definition.

In the basics step I give it a meaningful name and meaningful description. I set the Definition Location to the root of my Management groups. Doing this will allow me to assign this Blueprint to all 3 subscriptions in turn creating the core services RG in each subscription.

Next the Artifacts need to be added. Note that when adding an Artifact at the Subscription level you have these options as types:

The Resource Group Artifact type is only available at the subscription level and the ARM template Artifact type is only available at the Resource Group level. I added the Resource Group that the core networking and core storage will be deployed into.

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Cloud Security via Security Center

Another critical part of managing any cloud is security. In Azure Microsoft has a service called Security Center. I am going to cover Security Center at a high level here in this post as Security Center itself is a big topic and is frequently changing with new improvements. This provides continuous assessment of your clouds security posture. Security Center gives you a central place to monitor and manage your security. Security Center can even covers Hybrid Cloud with the ability to extend on-premises. With Security Center you can apply security policies to your cloud workloads and respond to attacks that occur.

Security Center has a “free” tier that can be used with any Azure subscription. In fact if you are running Azure you should at a minimum be utilizing the free tier of Security Center. The tiers are:

Not covered = not monitored by Security Center.

Basic Coverage = subscriptions under this “free” tier are under the limited, free level of Security Center.

Standard Coverage =  subscriptions under this “standard” tier have the maximum level coverage by Security Center.

Key features in Security Center are:

– Security policy, assessment, and recommendations / free / Security Center performs continuous assessment and recommendations based on security policies that are set. This is the core feature of Security Center.

– Event collection and search / standard / Security Center can store security events in a Log Analytics (LA) workspace. The events also are available in the LA workspace for searching.

– Threat Protection / standard / visibility into any detected security alerts and their severity level.

– Just in time VM access / standard / Just in time VM access locks down inbound traffic to IaaS VM’s. With this feature users are required to request access to the VM for a specified amount of time. A firewall rule is opened on an NSG allowing the access and then the ports are closed after the allotted window of access time. This can reduce the attack surface on VM’s.

NOTE: (Automate Just In Time VM Access Request With PowerShell – https://github.com/CharbelNemnom/Power-MVP-Elite/tree/master/Request%20JIT%20VM%20Access by Microsoft MVP Charbel Nemnom)

– Adaptive application controls / standard /  This feature allows you to choose what applications are allowed to run on your VMs. This feature uses machine learning to analyze the applications running in the VM and then you whitelist the ones you want to allow to run.

– Custom alerts / standard /  Security Center has a bunch of default alerts. Alerts fire when a threat, or suspicious activity occurs. You can find the list of the default alerts here: security alerts. Security Center also has custom alerts that you can setup. With these you define the conditions upon which an alert is fired.

– Threat intelligence  / standard /  this feature watches for known bad actors using threat intelligence data from Microsoft’s global products and services such as Azure, Office 365, Microsoft CRM online, Microsoft Dynamics AX, outlook.com, MSN.com, and Microsoft’s Digital Crimes Unit (DCU) and Microsoft Security Response Center (MSRC) .

It is important to note that Security Center leverages many other Azure services to power its services. Some of these other Azure services include:

  • Azure Policy
  • Log Analytics
  • Logic Apps
  • Machine Learning

Now that we looked at key features of Security Center let’s take a tour of Security Center. The best way to navigate Security Center is via the navigation on the left hand side and that is the way I will break it down. The menu sections are shown in the following table:

When you first click into Security Center you will see the Overview. Overview is also the first section under “General”. Here is a screenshot of the overview pain.

Essentially the overview pane gives you a summary of your security posture pulling in data from several sections in Security Center. Getting started is where you can launch a 60 day trial on the standard plan. Events brings you to a log analytics workspace dashboard to give you another display and search capabilities on your security data. Search will bring you directly to the log analytics search screen where you can search on your security data.

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Multiple Linux VM Deployment ARM Template

I looked for an existing ARM template that would create multiple Linux VM’s. I found only one that creates some in a scale set. The use case I was working with did not call for a scale set so I needed a different template.

I found a simple ARM template for creating multiple Windows VM’s on Azure here. It had exactly what I needed for my use case but did not cover Linux.

I modified the template and uploaded to Github in case this is helpful to anyone else. The repo has two templates. There is one for Ubuntu and one for SUSE. When you deploy the template it will need the following parameters:

The ARM template will create an availability set (AS) with N number of VM’s put in that AS, network interfaces, and public IP’s for each VM along with a VNet and Subnet as shown in the following screenshot:

Here is the link to download the ARM Template:

https://github.com/Buchatech/Multiple-Linux-VM-Deployment-ARM-Template

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Azure & Azure Stack Resource Group Cleanup Script

When building things in Azure & Azure Stack I tend to create a lot of temporary resources groups. I like to remove these when I am done. I have been using a PowerShell script for a while to help make this easier. I have decided to upload this script hoping others will find it useful as well. The script is named CleanupResourceGroups.ps1 and can be downloaded here:
https://gallery.technet.microsoft.com/Cleanup-Azure-Resource-d95fc34e

The script can be used two ways:

#1 the script can be run using -Like with an expression like where {$_.ResourceGroupName -like (‘*MySQL*’) in which the script would remove any resource group with MySQL in it. To use this option just un-comment the code in SECTION 1- Uses -Like, change MySQL to whatever you want, comment SECTION 2- Interactive RG selection code, and then run the script.

#2 the script can be run interactively allowing you to select multiple resource groups you want to remove. By default the SECTION 2- Interactive RG selection code is un-commented. If you run the script it will run interactively as shown in the following steps/screenshots.

After running the script it will prompt you to select an Azure subscription.

Next the script will give you a list of resource groups in the subscription you selected. Select the resource groups you want to remove and click Ok.

The script will loop through and remove the resource groups you selected. Note that script is using -Force so it will not prompt to ensure you intend to remove the resource groups. Make sure you want to remove the resource groups before running this script.

NOTE: When running this for Azure Stack ensure you are logged into the Azure Stack environment. For info on how to do this visit: https://bit.ly/2LkvddG

That is it. It is a simple script to make removing many resource groups easier. I hope you find this script useful as I have!

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The “argument is null or empty” error in Azure Automation Runbook

I was recently working on an Azure Automation runbook that provisions an empty resource group in Azure. I was running into an issue when the runbook ran that the variable being used with New-AzureRmRoleAssignment was null. The errors I was receiving are:

New-AzureRmRoleAssignment : Cannot validate argument on parameter ‘SignInName’. The argument is null or empty. Provide
an argument that is not null or empty, and then try the command again.
At line:96 char:39
+ New-AzureRmRoleAssignment -SignInName $RequesterSignIn -RoleDefinitio …
+ ~~~~~~~~~~~~~~~~
+ CategoryInfo : InvalidData: (:) [New-AzureRmRoleAssignment], ParameterBindingValidationException
+ FullyQualifiedErrorId :
ParameterArgumentValidationError,Microsoft.Azure.Commands.Resources.NewAzureRoleAssignmentCommand

and

New-AzureRmRoleAssignment : Cannot validate argument on parameter ‘ObjectId’. Specify a parameter of type ‘System.Guid’
and try again.
At line:97 char:37
+ New-AzureRmRoleAssignment -ObjectID $RequesterID -RoleDefinitionName  …
+                                     ~~~~~~~~~~~~
+ CategoryInfo          : InvalidData: (:) [New-AzureRmRoleAssignment], ParameterBindingValidationException
+ FullyQualifiedErrorId :
ParameterArgumentValidationError,Microsoft.Azure.Commands.Resources.NewAzureRoleAssignmentCommand

It turned out to be a permission issue with AzureRM.Resources CMDLETS not being able to talk to AAD specifically Get-AzureRmADUser that I was using for a variable.

To fix this I had to give the following permissions for the AAD directory to the AzureServicePrincipal Run As Account:

Windows Azure Active Directory (AAD)
Application Permissions

·       Read/Write directory data
·       Read directory data

Delegated Permissions
·       Read directory data
·       Read all users’ full profiles
·       Read all users’ basic profiles

Microsoft Graph
App Permissions
·       Read directory data

In your runbook code you will typically have

# Authenticate to Azure resources
$connectionName = “AzureRunAsConnection”

# Get the connection “AzureRunAsConnection “
$servicePrincipalConnection = Get-AutomationConnection -Name $connectionName
“Logging in to Azure…”
Login-AzureRmAccount `
-ServicePrincipal `
-TenantId $servicePrincipalConnection.TenantId `
-ApplicationId $servicePrincipalConnection.ApplicationId `
-CertificateThumbprint $servicePrincipalConnection.CertificateThumbprint

You may have a some differences like the connection variable and the name of the runasconnection. The point here is that the runas connection is what needs to have the proper permissions. You can find this account here to get the name and ApplicationID:

To give the permissions go to Azure Active Directory>the directory you are using in this automation>App registrations>and search based on the ApplicationID. Don’t forget to select All apps in the drop down.

Click on Add first and add the AAD and then Microsoft Graph permissions.

After you add the proper permissions make sure you click on Grant Permissions. The permissions are not actually applied until you do this. Once you click on Grant permissions you will see the prompt shown in the screenshot. Click Yes.

Verify the permissions have been added properly. In AAD go to All applications>select All applications. Find your service principle application.

Click on the service principle applications permissions.

Verify the AAD and graph permissions are listed. If the AAD and graph permissions are listed then the runbook should be good to go.

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Unlink yourself from unused AAD directories

Working in the world of consulting I am often added to other Azure Active Directories that are managed by someone else. After a while these can pile up like in the following screenshot.

I like to clean these up as the inviting organizations typically don’t remove you. Here is a quick way to do this. In a browser go to https://myapps.microsoft.com. It will look like this:

Click on your name and select the directory you want to remove. Click on your name again and click on the cog for the settings.

You should then see the option to “Leave the organization”. Click the link.

You will see the following pop-up. Click on Leave.

That’s it. You will no longer see the directory you just removed listed in the Azure portal under your directory list.

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