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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Deploy MySQL and WordPress on Azure Kubernetes Service (AKS)

In this blog post I am going to walk through the steps for deploying WordPress to Azure Kubernetes Service (AKS) using MySQL and WordPress Docker images. Note that using the way I will show you is one way. Another way to deploy WordPress to AKS would be using a Helm Chart. Here is a link to the WordPress Helm Chart by Bitnami https://bitnami.com/stack/wordpress/helm. Here are the images we will use in this blog post:
MySQL WordPress
apiVersion: v1
kind: Service
metadata:
name: wordpress-mysql
labels:
app: wordpress
spec:
ports:
– port: 3306
selector:
app: wordpress
tier: mysql
clusterIP: None

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: mysql-pv-claim
labels:
app: wordpress
spec:
accessModes:
– ReadWriteOnce
resources:
requests:
storage: 20Gi

apiVersion: apps/v1 # for versions before 1.9.0 use apps/v1beta2
kind: Deployment
metadata:
name: wordpress-mysql
labels:
app: wordpress
spec:
selector:
matchLabels:
app: wordpress
tier: mysql
strategy:
type: Recreate
template:
metadata:
labels:
app: wordpress
tier: mysql
spec:
containers:
– image: mysql:5.6
name: mysql
env:
– name: MYSQL_ROOT_PASSWORD
valueFrom:
secretKeyRef:
name: mysql-pass
key: password
ports:
– containerPort: 3306
name: mysql
volumeMounts:
– name: mysql-persistent-storage
mountPath: /var/lib/mysql
volumes:
– name: mysql-persistent-storage
persistentVolumeClaim:
claimName: mysql-pv-claim
apiVersion: v1
kind: Service
metadata:
name: wordpress
labels:
app: wordpress
spec:
ports:
– port: 80
selector:
app: wordpress
tier: frontend
type: LoadBalancer

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: wp-pv-claim
labels:
app: wordpress
spec:
accessModes:
– ReadWriteOnce
resources:
requests:
storage: 20Gi

apiVersion: apps/v1 # for versions before 1.9.0 use apps/v1beta2
kind: Deployment
metadata:
name: wordpress
labels:
app: wordpress
spec:
selector:
matchLabels:
app: wordpress
tier: frontend
strategy:
type: Recreate
template:
metadata:
labels:
app: wordpress
tier: frontend
spec:
containers:
– image: wordpress:4.8-apache
name: wordpress
env:
– name: WORDPRESS_DB_HOST
value: wordpress-mysql
– name: WORDPRESS_DB_PASSWORD
valueFrom:
secretKeyRef:
name: mysql-pass
key: password
ports:
– containerPort: 80
name: wordpress
volumeMounts:
– name: wordpress-persistent-storage
mountPath: /var/www/html
volumes:
– name: wordpress-persistent-storage
persistentVolumeClaim:
claimName: wp-pv-claim

The first thing we need to do is save these files as mysql-deployment.yaml and wordpress-deployment.yaml respectively.

Next, we need to setup a password for our MySQL DB. We will do this by creating a secret on our K8s cluster. To do this launch the bash or PowerShell in Azure cloud shell like in the following screenshot and run the following syntax:

kubectl create secret generic mysql-pass –from-literal=password=YOURPASSWORDHERE

Note: Replace “PASSWORDHERE” in the syntax with your own password.

The secret is now created. To ensure it was created you can run the following syntax to list the secrets:

kubectl get secrets

You also can see the secret in the Kubernetes dashboard as shown in the following screenshot.

Next the mysql-deployment.yaml and wordpress-deployment.yaml files from the beginning of this post need to be uploaded to Azure cloudrive storage.

You can also do this in the Cloudshell as shown in the following screenshot.

Run ls in the shell to make sure the files are on your clouddrive.

You will need your home drive. Mine was. /home/steve. To see this, click on Download. It will show you what yours is.

Next create the MySQL Pod and service by running the following syntax.

kubectl apply -f /home/steve/mysql-deployment.yaml

NOTE: You could use kubectl create /home/steve/mysql-deployment.yaml instead of apply to create the MySQL pod and service. I use apply because I typically use the declarative object configuration approach. kubectl apply essentially equals kubectl create + kubectl replace. In order to update an object after it has been created using kubectl create you would need to run kubectl replace.

There are pros and cons to using each and it is more of a preference for example when using the declarative approach there is no audit trail associated with changes. For more information on the multiple Kubernetes Object Management approaches go here: https://kubernetes.io/docs/concepts/overview/object-management-kubectl/overview.

Note that in the mysql yaml file it has syntax to create a persistent volume. This is needed so that the database stays in tact even if the pod fails, is moved etc. You can check to ensure the persistent volume was created by running the following syntax:

kubectl get pvc

Also, you can run the following syntax to verify the mysql pod is running:

kubectl get pods

Deploying the WordPress Pod and service is the same process. Use the following syntax to create the WordPress pod and service:

kubectl apply -f /home/steve/wordpress-deployment.yaml

Again, check to ensure the persistent volume was created. Use the following syntax:

kubectl get pvc

NOTE: When checking right after you created the persistent volume it may be in a pending status for a while like shown in the following screenshot:

You can also check the persistent volume using the K8s dashboard as shown in the following screenshot:

With the deployment of MySQL and WordPress we created 2 services. The MySQL service has a clusterip that can only be accessed internally. The WordPress service has an external IP that is also attached to an Azure Load Balancer for external access. I am not going to expand on what Kubernetes services are in this blog post but know that they are typically used as an abstracted layer in K8s used for access to Pods on the backend and follow the Pods regardless of the node they are running on. For more information about Kubernetes services visit this link: https://kubernetes.io/docs/concepts/services-networking/service.

In order to see that the services are running properly and find out the external IP you can run the following syntax:

kubectl get services (to see all services)

or

kubectl get services wordpress (to see just the WordPress service)

You also can view the services in the K8s dashboard as shown in the following screenshot:

Well now that we have verified the pods and the services are running let’s check out our new WordPress instance by going to the external IP in a web browser.

Thanks for checking out this blog post. I hope this was an easy to use guide to get WordPress up and running on your Azure Kubernetes Service cluster. Check back soon for more Azure and Kubernetes/Container content.

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Getting Started with Azure Kubernetes Service (AKS)

Azure Kubernetes Service (AKS) is a fully managed Kubernetes (K8s) offering from Microsoft on the Azure platform. AKS reduces the management overhead of running your own K8s instance while still being able to take full advantage of Container Orchestration. Microsoft takes care of the K8s health monitoring and maintenance. With AKS you only manage the agent nodes while Microsoft manages the master nodes. Also with AKS you get integration to many of the Azure services such as load balancers, RBAC, Azure storage etc.

In this blog post I am going to walk through the setup of an AKS cluster step by step. This is to serve as a intro to AKS to show how easy it is to get started with Kubernetes in Azure. In a follow up blog post I will dive into AKS more showing how to deploy an instance MySQL and WordPress containers on AKS. Before we get into the setup of AKS there are a few things to note:

  1. With the AKS managed service you only pay for the agent nodes within your AKS cluster. There is no cost for the master nodes and the managed service itself is free.
  2. At the time of this blog post AKS only supports Linux containers. There is a work around for this until Windows nodes and containers come to AKS.
  3. AKS is only available in the following Azure regions:
    -Australia East
    -Canada Central
    -Canada East
    -Central US
    -East US
    -East US2
    -Japan East
    -North Europe
    -Southeast Asia
    -UK South
    -West Europe
    -West US
    -West US 2
  4. The Kubernetes API server is exposed as a public fully qualified domain name (FQDN). Access should be restricted on this. It can be restricted using K8s RBAC and AAD.

Deploy AKS

Housekeeping is done, now let’s get into the deployment of AKS. The first thing you need to do within the Azure portal is go to Create a resource and search on Kubernetes. Select the Kubernetes Service.

Click on create.

You will now see the setup. The setup consists of the following sections shown in the following screenshot:

Let’s walk through each section.

Basics

Here you need to give your AKS instance a name, select the region, K8s version, DNS prefix, and number of nodes and count.

Authentication

Kubernetes has its own RBAC within its authentication and authorization system. Azure Active Directory (AAD) can be integrated with this for authentication. Once the AAD and K8s integration is setup AAD users can be used for Kubernetes role-based access control (RBAC) to cluster resources. Select yes to enable RBAC and integration with AAD.

It is recommended to setup your own service principle in AAD. For this blog post I let the deployment create one. The service principle is used by K8s for managing Azure cloud resources attached to the cluster. The service principle interacts with Azure APIs. For example when you setup a load balancer service in K8s AKS creates and Azure load balancer. The service principle is what is used for authentication to create the load balancer.

Networking

In this section you chose what you want for networking with AKS. If you select basic AKS will create all needed VNets, Subnets, NSG’s etc. AKS clusters cannot use the following ranges 169.254.0.0/16, 172.30.0.0/16, and 172.31.0.0/16. If you select advanced you can chose an existing VNet or create a new one specifying the subnet, IP range and DNS settings etc. You would select Advanced if you need more control over the virtual networking. 

HTTP application routing is used to make application endpoints publicly accessible in the AKS cluster. Enabling this essentially configures an Ingress controller in the AKS cluster. When getting started with AKS I recommend leaving this disabled and doing more research on K8s Ingress Controllers here https://kubernetes.io/docs/concepts/services-networking/ingress as there are other options making applications publicly accessible. In the meantime while getting started with AKS you can use the load balancer service type for external access to your applications running on AKS.

Monitoring

With AKS you have the option to utilize Container monitoring from Azure Monitor. This will give you performance and health monitoring. The monitoring data comes directly from an AKS cluster or from all the AKS clusters via Azure Monitor more specifically Log Analytics. In the future I plan to post a deeper blog about monitoring AKS.

If you chose to enable this you will need to setup a new  Log Analytics workspace or use an existing one.

Tags

You can set tags for the AKS cluster.

Create

After all the sections are completed the new AKS will need to validate. After it is validated click on Create.

Exploring AKS

After the AKS cluster is created you will see it in Azure under Kubernetes services.

Also you may notice two new resource groups in your Azure subscription. The first resource group will be the one you created during the AKS creation. This is the resource group that will contain the Azure K8s cluster service. If you selected an advanced network configuration during deployment to create a new VNet you will see that as well.

You will also see a second resource group with a name format similar to MC_ResourceGroupNAME_AKSClusterNAME_REGION. As shown in the following screenshot I have a resource group named MC_AKS12118RG_AKS12118_centralus. This resource group contains the individual AKS cluster resources such as the nodes.

This resource group also contains supporting Azure services like DNS, public IP’s, storage, load balancers, network security groups and more. Note do not make changes to the resources in this resource group directly. You should only make changes through the AKS service and K8s itself. For example when you deploy a new load balancer service in K8s the corresponding Azure load balancer will automatically be created.

Access Kubernetes Dashboard

Next you can access the K8s cluster via a shell or access the dashboard. Before you can access the dashboard the service principle account that was created during the AKS deployment will need a ClusterRoleBinding that assigns the K8s role dashboard-admin it. Run the following syntax from the Azure cloud shell to do this:

kubectl create clusterrolebinding kubernetes-dashboard -n kube-system --clusterrole=cluster-admin --serviceaccount=kube-system:kubernetes-dashboard

If the service principle account does not have the K8s dashboard-admin role you will see the following error when accessing the dashboard:

After the service principle account is all set go ahead and run the following syntax from Azure cloud shell.

az aks browse --resource-group CLUSTERRESOURCEGROUPNAME --name NAMEOFTHEAKSCLUSTER

Running that syntax will output a URL similar to the one shown in the following screenshot. Click on this and it will open the K8s dashboard in a new browser tab.

The following 3 screenshots show some of the K8s dashboard.

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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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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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Microsoft Professional Program for DevOps Finished!

I am a firm believer that no matter how old you are, how far along you are in your career, and regardless of the industry you are in it is important to continue educating yourself. This helps you expand your skillset, stay relevant, and sets you up for new opportunities as they come along. My field of information technology has been changing at a rapid pace and so for a while, I wanted a good way to ramp up on DevOps as a whole. A while back I found out that Microsoft added a new track to their Professional Program for DevOps. When I checked it out I found it to be very thorough and it was not just focused on Microsoft’s DevOps tooling but included non-Microsoft as well. I jumped in without hesitation and started learning.

I finally completed the program last week. Here is my certificate https://academy.microsoft.com/en-us/certificates/67284e84-8afe-4f13-b477-d7620949fb18. I am planning to dive into the program they have for cloud next. If you have not heard of Microsoft’s Professional Program DevOps before here more information about it:

“DevOps is the union of people, process, and products to enable continuous delivery of value to end users. This program helps the student learn about continuous integration and deployment, infrastructure as code, testing, databases, containers, and application monitoring: skills necessary for a DevOps culture in today’s workplace. This program focuses on Microsoft DevOps technologies as well as some OSS (Open Source Software) DevOps tools. Some of the Microsoft DevOps technologies covered in this course consist of Azure, Azure Resource Manager, IaaS, PaaS, IIS, Azure App Service, DevTest labs, Desired State Configuration (DSC), Azure Automation, OMS, Application Insights, SQL, Nuget, TFS, VSTS, and Visual Studio. Some of the OSS DevOps tools covered in this course consist of Jenkins, Git, Github, New Relic, Nagios, Chef, Docker, DC/OS, swarm, and Kubernetes.”

Here is a link to it:  https://academy.microsoft.com/en-us/tracks/devops

This program consists of 8 required courses. Each course runs for three months and starts at the beginning of a quarter. In the end, there is a capstone that has to be completed. This capstone course is the 8th one. You have four weeks to complete the capstone. The capstone is a bunch of hands-on stuff you have to do. Courses average 16-32 hours per course to complete and are taken via the edX.org platform https://www.edx.org/microsoft-professional-program-devops.

Here is a list of all of the DevOps program courses:

      • Introduction to Dev Ops Practices
      • Infrastructure as Code
      • Continuous Integration and Continuous Deployment
      • Configuration Management for Containerized Delivery
      • DevOps Testing
      • DevOps for Databases
      • Application Monitoring and Feedback Loops
      • Microsoft Professional DevOps Capstone Project
      • The DevOps Capstone Project contains:
        • Automation
          • Use ARM templates to deploy and configure Infrastructure in Azure
        • Continuous Integration
          • Implement Continuous Integration solution using Visual Studio Team services (VSTS)
        • Continuous deployment
          • Implement Continuous Deployment solution using Visual Studio Team Services (VSTS)
        • Testing
          • Implement Unit tests
          • Implement Testing in Production
        • Application Monitoring
          • Implement application monitoring solution using Application Insights

As you can see from that list this program is not just all about VSTS. There is a lot of Azure baked in as well as other non-Microsoft DevOps tooling. I highly recommend this course for anyone jumping into DevOps, or CloudOps and especially for folks with an IT pro background. If CloudOps is foreign to you here are a couple of blogs related to this topic: Sys Admin to Cloud Admin…ITSM to CloudOps…On-Prem to Azure Stack/Azure and Native Cloud Management in Azure.

My personal opinion is that Microsoft should move away from the certifications as they are and to this format. This format combines training and testing. When Microsoft first started the Professional Program for they only had a track for data scientists. They have added more and more tracks over time. Today there are tracks also for Big Data, Web Development, Software Development, AI, IT Support, and Cloud Administration.

Here is a link for all the tracks so you can check them out: https://academy.microsoft.com/en-us/professional-program/tracks. These programs are a great way to expand your learning. Check them out!

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