Automating the submission of WordPress Blog Posts to your Microsoft MVP Community Activities Profile using PowerShell

Introduction

In November last year (2017) I was honored to be awarded Microsoft MVP Status for Enterprise Mobility – Identity and Access. MVP Status is awarded based on community activities and even once you’ve attained MVP Status you need to keep your community activity contributions updated on your profile.

Up until recently this was done by accessing the portal and updating your profile, however mid last year a MVP PowerShell Module (big thanks to Francois-Xavier Cat and Emin Atac) was released that allows for some automation.

In this post I’ll detail using the MVP PowerShell Module to retrieve your latest WordPress Blog Post and submit it to your MVP Profile as a MVP Community Contribution.

Prerequisites

In order for this to work you will need;

  • to be a Microsoft MVP
  • Register at the MS MVP API Developer Portal using your MVP registered email/profile address
    • subscribe to the MVP Production Application
    • copy your API key (you’ll need this in the script below)

The Script

Update the script below for;

  • MVP API Key
    • Update Line 5 with your API key as detailed above
  • WordPress Blog URL (mine is blog.darrenjrobinson.com)
  • Your Award Category
    • Update Line 17 with your category $contributionTechnology = “Identity and Access”
    • type New-MVPContribution – ContributionTechnology and you’ll get a list of the MVP Award Categories

Award Categories.PNG

The Script

Here is the simple script. Run it after publishing a new entry you also want added to your Community Contributions Profile. No error handling, nothing complex, but you’re a MVP so you can plagiarise away for your submissions to make it do what suits your needs.

Summary

Hopefully that makes it simple to keep your MVP profile up to date. If you’re using a different Blogging platform I’m sure the basic process will work with a few tweaks after returning a query to get the content. Enjoy.

Automating the creation of Azure IoT Hubs and the registration of IoT Devices with PowerShell and VS Code

The creation of an Azure IoT Hub is quick and simple, either through the Azure Portal or using PowerShell. But what can get more time-consuming is the registration of IoT Devices with the IoT Hub and generation of SAS Tokens for them for authentication.

In my experiments with micro-controllers and their integration with Azure IoT Services I often find I keep having to manually do tasks that should have just been automated. So I did. In this post I’ll cover using PowerShell to;

  • create an Azure IoT Hub
  • register an Azure IoT Device
  • generate a SAS Token for the IoT Device to use for authentication to an Azure IoT Hub from a Mongoose OS enabled ESP8266 micro controller

IoT Integration

Prerequisites

In order to fully test this, ideally you will have a micro-controller. I’m using an ESP8266 based micro-controller like this one. If you want to test this out without physical hardware, you could generate your own DeviceID (any text string) and use the AzureIoT Library detailed further on to send MQTT messages.

You will also require an Azure Subscription. I detail using a Free Tier Azure IoT Hub which is limited to 8000 messages per day. And instead of using PowerShell/PowerShell ISE get/use Visual Studio Code.

Finally you will need the AzureRM and AzureIoT PowerShell modules. With WinRM 5.x you can get them from the PowerShell Gallery with;

install-module AzureRM
install-module AzureIoT

Create an Azure IoT Hub

The script below will create a Free Tier Azure IoT Hub. Change the location (line 15) for which Azure Region you will use (the commands on the lines above will list what regions are available), the Resource Group Name that will be created to hold it (line 18) and the name of the IoT Hub (line 23) and let it rip.

From your micro-controller we will need the DeviceID. I’m using the ID generated by the device which I obtained from the Device Configuration => Expert View of my Mongoose OS enabled ESP8266.

Device Config.PNG

Register the IoT Device with our Azure IoT Hub

Using the AzureIoT PowerShell module we can automate the creation/registration of the IoT Device. Update the script below for the name of your IoTHub and the Resource Group that contains it that you created earlier (lines 7 and 11). Update line 21 for the DeviceID or your new IoT Device. I’m using the AzureIoT module to do this. With WinRM 5.x you can install it quickly fromt the gallery with install-module AzureIoT

Looking at our IoTHub in the Azure Portal we can see the newly registered IoT Device.

DeviceCreated.png

Generate an IoT Device SAS Token

The final step is to create a SAS Token for our IoT Device to use to connect to the Azure IoTHub. Historically you would use the IoT Device Explorer to do that. Alternatively you can also use the code samples to implement the SAS Device Token generation via an Azure Function App. Examples exist for JavaScript and C#. However as of mid-January 2018 you can do it direct from VS Code or Azure Cloud Shell using the Azure CLI and the IOT Extension. I’m using this method here as it is the quickest and simplest method of generating the Device SAS Token.

The command to generate a token that would work for all Devices on an IoT Hub is

az iot hub generate-sas-token --hub-name

Here I show executing it via the Azure Cloud Shell after installing the IOT Extensions as detailed here. To open the Bash Cloud Shell select the >_ icon next to the notification bell in the right top menu list.

Generate IOT Device SAS Token.PNG

As we have done everything else via PowerShell and VS Code we can also do it easily from VS Code. Install the Azure CLI Tools (v0.4.0 or later in VS Code as detailed here. Then from within VS Code press Control + Shift + P to open the Command Palette and enter Azure: Sign In. Sign in to Azure. Then Control + Shift + P again and enter Azure: Open Bash in Cloud Shell to open a Bash Azure CLI Shell. You can check to see if you have the Azure CLI IOT Extension (if you’ve previously used the Azure CLI for IoT operations) by typing;

az extension show --name azure-cli-iot-ext

and install it if you don’t with;

az extension add --name azure-cli-iot-ext

Then run the same command from VS Code to generate the SAS Token

az iot hub generate-sas-token --hub-name

VSCode Generate SAS Token.PNG

NOTE: That token can then be used for any Device registered with that IOT Hub. Best practice is to have a token per device. To do that type

az iot hub generate-sas-token --hub-name  --device-id

Generate SAS Token VS Code Per Device.PNG

By default you will get a token valid for 1 hour. Use the –duration switch to specify the duration of the token you require for your environment.

We can now take the SAS Token and put it into our MQTT Config on our Mongoose OS IoT Device. Update the Device Configuration using Expert View and Save.

Mongoose SAS Config.PNG

We can then test our IoT Device sending updates to our Azure IoT Hub. Update Init.js using the telemetry sample code from Mongoose.

load('api_config.js');
 load('api_mqtt.js');
 load('api_sys.js');
 load('api_timer.js');

let topic = 'devices/' + Cfg.get('device.id') + '/messages/events/';

Timer.set(1000, true /* repeat */, function() {
 let msg = JSON.stringify({ ram: Sys.free_ram() });
 let ok = MQTT.pub(topic, msg, 1);
 print(ok, topic, '->', msg);
 }, null);

We can then see the telemetry being sent to our Azure IOT Hub using MQTT. In the Device Logs after the datestamp and before device/ if you see a 0 instead of 1 (as shown below) then your conenction information or SAS Token is not correct.

Mongoose IOT Events.png

On the Auzre IoT side we can then check the metrics and see the incoming telemetry using the counter Telemetry Metrics Sent as shown below.

Telemetry Metrics Sent.PNG

If you don’t have an IoT Device you can simulate one using PowerShell. The following example shows sending a message to our IoT Hub (using variables from previous scripts).

$deviceParams = @{
 iotConnString = $IoTConnectionString
 deviceId = $deviceID
}
$deviceKeys = Get-IoTDeviceKey @deviceParams 
# Get Device 
$device = Get-IoTDeviceClient -iotHubUri $IOTHubDeviceURI -deviceId $deviceID -deviceKey $deviceKeys.DevicePrimaryKey

# Send Message
$deviceMessageParams = @{
 deviceClient = $device
 messageString = "Azure IOT Hub"
}
Send-IoTDeviceMessage -deviceClient $deviceMessageParams

Summary

Using PowerShell we have quickly been able to;

  • Create an Azure IoT Hub
  • Register an IoT Device
  • Generate the SAS Token for the IoT Device to authenticate to our IoT Hub with
  • Configure our IoT Device to send telemetry to our Azure IoT Hub and verify integration/connectivity

We are now ready to implement logic onto our IoT Device for whatever it is you are looking to achieve.

 

Automating the generation of Microsoft Identity Manager Configuration Documentation

Introduction

Last year Microsoft released the Microsoft Identity Manager Configuration Documenter which is available here. It is a fantastic little tool from Microsoft that supersedes its predecessor from the Microsoft Identity Manager 2003 Resource Toolkit (which only documented the Sync Server Configuration).

Running the tool (a PowerShell Module) against a base out-of-the-box reference configuration for FIM/MIM Servers reconciled against an exported configuration from the MIM Sync and Service Servers from an implementation, generates an HTML Report document that details the existing configuration of the MIM Service and MIM Sync.

Overview

Last year I wrote this post based on an automated solution I implemented to perform nightly backups of a FIM/MIM environment during development.

This post details how I’ve automated another daily task for a large development environment where a number of changes are going on and I wanted to have documentation generated that detailed the configuration for each day. Partly to quickly be able to work out what has changed when needing to roll back/re-validate changes, and also to have the individual configs from each day so they could also be used if we need to rollback.

The process uses an Azure Function App that uses Remote PowerShell into MIM to;

  1. Leverage a modified (stream lined version) of my nightly backup Azure Function to generate the Schema.xml and Policy.xml MIM Service configuration files and the Lithnet MIIS Automation PowerShell Module installed on the MIM Sync Server to export of the MIM Sync Server Configuration
  2. Create a sub-directory for each day under the MIM Documenter Tool to hold the daily configs
  3. Execute the generation of the Report and have the Report copied to the daily config/documented solution

Obtaining and configuring the MIM Configuration Documenter

Download the MIM Configuration Documenter from here and extract it to somewhere like c:\FIMDoco on your FIM/MIM Sync Server. In this example in my Dev environment I have the MIM Sync and Service/Portal all on a single server.

Then update the Invoke-Documenter-Contoso.ps1 (or whatever you’ve renamed the script to) to make the following changes;

  • Update the following lines for your version and include the new variable $schedulePath and add it to the $pilotConfig variable. Create the C:\FIMDoco\Customer and C:\FIMDoco\Customer\Dev directories (replace Customer with something appropriate.
######## Edit as appropriate ####################################
$schedulePath = Get-Date -format dd-MM-yyyy
$pilotConfig = "Customer\Dev\$($schedulePath)" # the path of the Pilot / Target config export files relative to the MIM Configuration Documenter "Data" folder.
$productionConfig = "MIM-SP1-Base_4.4.1302.0" # the path of the Production / Baseline config export files relative to the MIM Configuration Documenter "Data" folder.
$reportType = "SyncAndService" # "SyncOnly" # "ServiceOnly"
#################################################################
  • Remark out the Host Settings as these won’t work via a WebJob/Azure Function
#$hostSettings = (Get-Host).PrivateData
#$hostSettings.WarningBackgroundColor = "red"
#$hostSettings.WarningForegroundColor = "white"
  • Remark out the last line as this will be executed as part of the automation and we want it to complete silently at the end.
# Read-Host "Press any key to exit"

It should then look something like this;

Azure Function to Automate execution of the Documenter

As per my nightly backup process;

  • I configured my MIM Sync Server to accept Remote PowerShell Sessions. That involved enabling WinRM, creating a certificate, creating the listener, opening the firewall port and enabling the incoming port on the NSG . You can easily do all that by following my instructions here. From the same post I setup up the encrypted password file and uploaded it to my Function App and set the Function App Application Settings for MIMSyncCredUser and MIMSyncCredPassword.
  • I created an Azure PowerShell Timer Function App. Pretty much the same as I show in this post, except choose Timer.
    • I configured my Schedule for 6am every morning using the following CRON configuration
0 0 6 * * *
  • I also needed to increase the timeout for the Azure Function as generation of the files to execute the report and the time to execute the report exceed the default timeout of 5 mins in my environment (19 Management Agents). I increased the timeout to the maximum of 10 mins as detailed here. Essentially added the following to the host.json file in the wwwroot directory of my Function App.
{
 "functionTimeout": "00:10:00"
}

Azure Function PowerShell Timer Script (Run.ps1)

This is the Function App PowerShell Script that uses Remote PowerShell into the MIM Sync/Service Server to export the configuration using the Lithnet MIIS Automation and Microsoft FIM Automation PowerShell modules.

Note: If your MIM Service is on a different host you will need to install the Microsoft FIM Automation PowerShell Module on your MIM Sync Server and update the script below to change references to http://localhost:5725 to whatever your MIM Service host is.

Testing the Function App

With everything configured, manually running the Function App and checking the output window if you’ve configured everything correct will show success in the Logs as shown below. In this environment with 19 Management Agents it takes 7 minutes to run.

Running the Azure Function.PNG

The Report

The outcome everyday just after 6am is I have (via automation);

  • an Export of the Policy and Schema Configuration from my MIM Service
  • an Export of the MIM Sync Server Configuration (the Metaverse and all Management Agents)
  • I have the MIM Configuration Documenter Report generated
  • If I need to rollback changes I have the ability to do that on a daily interval (either for a MIM Service change or an individual Management Agent change

Under the c:\FIMDoco\Data\Customer\Dev\Report directory is the HTML Configuration Report.

Report Output.PNG

Opening the report in a browser we have the configuration of the MIM Sync and MIM Service.

Report

 

Checking and patching your Microsoft Windows computer for Meltdown and Spectre

Overview

A Google team named Project Zero in mid 2017 identified vulnerabilities with many Intel, AMD and ARM CPU’s that allow speculative pre-processing of code to be abused. Speculative pre-processing aids performance which is why it exists. However when used maliciously it would allow an attacker to use JavaScript in a webpage to access memory that could contain information present in a users environment such as key strokes, passwords and personal sensitive information.

A very good overview on the how (and a little of the why) is summarised in a series of tweets by Graham Sutherland here.

Mitigation/Patching

In the January Security updates Microsoft have provided updates to protect its operating systems (Windows 7 SP1 and later). More on this below. They have also provided a PowerShell Module to inspect and report on the status of a Windows operating system.

What you are going to need to do is patch your Windows Operating System and update your computers firmware (BIOS).

Using an Administrative PowerShell session on a Windows workstation with Windows Management Framework 5.x installed the following three lines will download and install the PowerShell module, import it and execute it to report on the status.

Install-Module SpeculationControl
Import-Module SpeculationControl
Get-SpeculationControlSettings

The output below shows that the operating system does not contain the updates for the vulnerability.

PowerShell Check.PNG

Obtaining the Windows Security Updates

Microsoft included updates for its operating systems (Windows 7 SP1 and newer) on January 3 2018 in the January update as shown below.  They can be obtained from the Microsoft Security Portal here. Search for CVE-2017-5715 to get the details.

Patch1.PNG

Go to the Microsoft Update Catalog to obtain the update individually.

The quickest and easiest though is to press your Windows Key, select the Gear (settings) icon, Update & Security, Windows Update.

Update & Security.PNG

Check status, install the updates, and restart your Windows computer.

Windows Update.PNG

Speculation Control Status

After installing the updates and restarting the computer we can run the check again. It now shows we are partially protected. Protected for Meltdown but partially protected for Spectre. A BIOS update is required to complete the mitigation for Spectre.

Rerun Powershell Check.PNG

For me I obtained the latest BIOS for my laptop from the manufacturers support website. If you are also on a Lenovo Yoga 910 that is here. However for me the latest Lenovo firmware doesn’t include updates for this vulnerability. And my particular model of laptop isn’t listed as being affected. I’ll keep checking to see if that changes.

Summary

In Microsoft environments your patching strategy will get you most of the way with the Microsoft January Security updates. BIOS updates to your fleet will take additional planning and effort to complete.

 

Provisioning Hybrid Exchange/Exchange Online Mailboxes with Microsoft Identity Manager

Introduction

Working for Kloud all our projects involve Cloud services, and all our customers have varying and unique requirements. Recently one of our customers embarked on their migration from On-Premise Exchange to Exchange Online. Nothing really groundbreaking there though, however they had a number of unique requirements including management of Litigation Hold. And that needed to be integrated with their existing Microsoft Identity Manager implementation (that currently provisions new users to their Exchange 2013 environment). They also required that management of the Exchange environment still be possible via the Exchange Management Console against a local Exchange server. This post details how I integrated the environments using MIM.

Overview

In order to integrate the Provisioning and Lifecycle management of Exchange Online Mailboxes in a Hybrid Exchange with Microsoft Identity Manager I created a custom PowerShell Management Agent simply because it was going to provide the flexibility I needed.

Provisioning is based on the following process;

  1. MIM Creates new user in Active Directory (no changes to existing MIM provisioning process)
  2. Azure Active Directory Connect synchronises the user to Azure Active Directory
  3. The Exchange Online MIM Management Agent sees the corresponding AAD account for the new user
  4. MIM Declarative Rules trigger the creation of a new Remote Mailbox for the AD/AAD user against the local Exchange 2013 On Premise Server. This allows the EMC to be used to manage mailboxes On Premise even though the mailbox resides in Office365/Exchange Online
  5. AADC/Exchange synchronises the information as part of the Hybrid Exchange topology
  6. MIM sees the EXO Mailbox configuration for the new user and enables Litigation Hold against the EXO Mailbox (if required)

The following diagram graphically depicts this process.

EXO IDM Provisioning Solution.png

Exchange Online PowerShell MA

As always I’m using my favourite PowerShell Management Agent, the Grandfeldt PS MA now available on Github here.

Schema Script

The Schema script configures the schema required for current and future EXO management requirements. The Schema is based on a single Object Class “MailUser” but pulls the information from a combination of Azure AD User and Exchange Online Mailbox object classes for an associated account. Azure AD User objects are prefixed by ‘AAD’. Non AAD prefixed attributes are EXO Mailbox attributes.

Import Script

The Import script connects to both Azure AD and Exchange Online to retrieve Azure AD User accounts and if present the associated mailbox for a user.

It retrieves all Member AAD User Accounts and puts them into a Hash Table. Connectivity to AAD is via the AzureADPreview PowerShell module. It retrieves all Mailboxes and puts them into a Hash Table. It then processes all the mailboxes first including the associated AAD User account (utilising a join via userPrincipalName).

Following processing all mailboxes the remainder of the AAD Accounts (without mailboxes) are processed.

Export Script

The Export script performs the necessary integration against OnPremise Exchange Server 2013 for Provisioning and Exchange Online for the rest of management. Both utilise Remote Powershell. It also leverages the Lithnet MIIS Automation PowerShell Module to query the Metaverse to validate current object statuses.

Wiring it all up

The scripts above will allow you to integrate a FIM/MIM implementation with AAD/EXO for management of users EXO Mailboxes. You’ll need connectivity from the MIM Sync Server to AAD/O365 in order to manage them.  Everything else I wired up using a few Sets, Workflows, Sync Rules and MPR’s.

 

Geographically Visualizing your workforce using Microsoft Identity Manager, xMatters and Power BI

Introduction

In the last couple of weeks I’ve posted about visualizing relationships of data from Microsoft Identity Manager using Power BI. Earlier this week I posted about building a Management Agent for Microsoft Identity Manger to integrate with xMatters.

In this post I combine data from the last two in order to allow us to visualise the geographic office locations for an organisation and then summary data about it (how many employees are located there, and what departments).

Prerequisites

You’ll need an Azure AD and Office 365 subscription to allow you to create a Power BI Application. Too create a Power BI Application see Registering a Power BI Application in this post here.

You’ll also need the Power BI PowerShell Module. I’m using 2.0.0.9 available from the PowerShell Gallery here and of course the Lithnet MIIS PowerShell Module available from here.

Overview

Using our registered Power BI Application we’ll create a Dataset consisting of two tables. One for the xMatters Sites (that we also get the geographic co-ordinates of from the xMatters Management Agent), and the other with our xMatters Users that contains the officeLocation that maps to an xMatters Site.

I create a relationship between the two tables on xMattersSite displayName (which is the location name) and the xMattersUsers officeLocation. We can then create a nice visual using data from both tables.

Create the Dataset (two tables with relationship)

Initially I tried to create the dataset with a relationship as I’ve previously shown here. However that didn’t work. After some debugging I got the result I wanted after some trial and error using the Power BI API Explorer. So I’ll provide you with the raw JSON format for creating a New Dataset, Two Tables (xMattersSites and xMattersUsers) and a relationship between them (where xMattersSites\displayName joins with xMattersUsers\officeLocation) as per my xMatters Management Agent detailed here.

Start by authenticating to the Power BI API Explorer with an account in the environment where you created your Power BI Application and navigate to the Create Dataset section here.

Create Dataset

Update this JSON formatted object that details the Dataset, Tables and Relationships for your environment.

Paste your validated JSON object into the Body section of the API Explorer and select Call Resource.

Dataset Body

If your JSON object is formatted corrected you’ll get a 201 response and your DataSet and Tables with Relationship will be created.

Create Success

Switching over to Power BI you’ll see the xMatters Dataset in the bottom left, then the two tables in on the right hand side with their columns.

xMatters DataSet PBI.PNG

Load xMatters User Data into Power BI

Now that we have somewhere to put the data, lets populate the dataset. I’m using the Lithnet MIIS Automation PowerShell Module (detailed in the prerequsites to query the Metaverse and return all users. Then I refine the list down to those that are Active (based on my employeeActive Boolean attribute) then finally, only those users that are connected on the xMatters Management Agent (see lines 14 & 18).

The script will drop any existing values from the xMatters Users table then upload what we have retrieved from the Metaverse (and refined).

Upload Users.PNG

Load xMatters Site Data into Power BI

Again I’m also using the Lithnet MIIS Automation PowerShell Module to query the Metaverse and return all xMatters Sites.

The script will drop any existing values from the xMatters Sites table then upload what we have retrieved from the Metaverse.

Upload Sites.PNG

Creating the Power BI Visual

Now we have data we can build the visual. I’m using the ArcGIS Maps for Power BI visual which is available in the default set of visuals. Then by selecting displayName and geo the map will automagically show all xMatters Sites in their respective co-ordinates.

xMatters Sites to Map

We can then add a Card Visual and choose officeLocation and then configure the visual for Count of officeLocation and we’ll get a count of the employees at that location. As we can see below with the Sydney location selected from the map the card updates to tell me there are 665 Employees at that officeLocation.

Count of Employees at Selected Location

Pretty quickly we can also expand out other data points, like departments at a location, employees etc as shown below (I’ve obfuscated the departments and a number of the other office locations).

Summary.PNG

Conclusion

We haven’t generated any new data. We’ve taken information we already have in Microsoft Identity Manager from connected systems and quickly visualized it via Power BI. However providing this to the business and with the ability for consumers of the information to export it from the visual can be pretty powerful.

Building a FIM/MIM Management Agent for xMatters

Introduction

A couple of weeks ago one of my customers had a requirement to provision and manage identities into xMatters. The xMatters API Documentation looked straight-forward and I figured it would be pretty quick to knock up an PowerShell Management Agent.

The identification of users (People) in xMatters was indeed pretty quick. I was quickly able to enumerate all users (that had initially been seeded independent of FIM/MIM) and join them to corresponding users in the MetaVerse.

It was then as I started digging deeper that the relationship between Sites (Locations) and Email/Mobile (Devices) attributes became apparent. This post details how I approached it and a base xMatters MA that should get you started if you need to do something similar.

Overview

A key concept to keep in mind is that at the simplest level there are 3 key Object Types in xMatters;

  • People
    • User Objects along with basic naming attributes
  • Device
    • Each contact medium is a device. Email Address, Mobile Phone, Home Phone, Text Phone (SMS) etc.
  • Site
    • Location of the entity (person)

Associated with each is an id which can be either dynamically created on provisioning (by xMatters) or specified. For People there is also targetName which is the equivalent of UID/sAMAccountName. When using the API (for people) you can use either their ID or their targetName. For all other entities you need to use the ID.

For each entity as you’d expect there are different API URI’s. They are;

Finally to retrieve devices for a person use;

Other key points to consider that I uncovered are;

  • if you are updating a Device (e.g. someones Email Address or Phone Number) don’t specify the owner attribute (as you do when you create the Device). It considers that you are trying to change the owner and won’t allow it.
  • to update a Device you need to know the ID of the Device. I catered for this on my Import by bringing through People and Device ID’s.
  • When creating/updating a users location you need to specify the Site ID and Site Name. I brought these through as a separate ObjectClass into FIM/MIM and query the MV for them when Exporting
  • In my initial testing the API returned a number of different errors 400 (Bad Request), 409 Conflict (when trying to Add a Device that already exists), 404 (Not Found) along with API Timeouts. You need to account for these and perform processing appropriately
  • On success of Update, Create or Delete the API returns the full object that you performed the operation on. You need to capture this and let MIM know that on Success a full object being returned is Success and not an error
  •  xMatters expects phone numbers to be in E164 format (e.g +61 400 123 456). I catered for this on an import on another Management Agent
  • xMatters timezone is in the format of Country/Region. For Australia these are as follows. Correct, it doesn’t accept Australia/Canberra for ACT;
    • “NSW”  = “Australia/Sydney”
      “VIC”  = “Australia/Melbourne”
      “QLD”  = “Australia/Brisbane”
      “ACT”  = “Australia/Sydney”
      “WA”  = “Australia/Perth”
      “TAS”  = “Australia/Hobart”
      “NT”  = “Australia/Darwin”

xMatters PowerShell Management Agent

With all that introduction, here is a base xMatters PowerShell MA (implemented using the Granfeldt PowerShell MA) to get you started. You’ll need to tailor for your environment and trigger Provisioning, Deletes and Flow Rules for your environment and look to handle the xMatters API for your integration.

Schema Script

I’ve created two Object Classes. User and Site. User incorporates User Devices. Site is the locations (Sites) from xMatters.

Import Script

Credentials for the Import script to connect to xMatters are flowed in from the Management Agent Username and Password attributes. This isn’t using Paged Imports. If you have a large number of users you may want to consider that. After retrieving all of the People entities each is queried to obtain their Devices. I’m only bringing through SMS and Email Devices. You’ll need to modify for additional Devices.

Ensure that you flow into the MetaVerse (onto custom attributes) the IDs associated with your Devices (e.g MobileID and EmailID). That will allow you to use the ID when updating those attributes.

For Sites, I created a custom ObjectClass (Site) in the MV and used objectID of the SiteID and displayName for the Site Name (as shown below).

Attribute Flows.png

Export Script

This is where it gets a little more complicated. As PowerShell is not good at reporting webrequest responses we have to deal with the return from each API call and determine if we were successful or not. Then let FIM/MIM know so it can report that via the UI.

The Export script below deals with Adding, Deleting and Updating users. Update line 31 for your API URI for xMatters.

Summary

The detail above will get you started and give you a working Management Agent to import Users and Sites. You’ll need to do the usual steps (Set, Workflow, Sync Rule and MPR) to trigger Provisioning on the MA along with how you handle deletes.

 

Graphically Visualizing Identity Hierarchy and Relationships

Almost 15 years ago Microsoft released Microsoft Identity Integration Server (MIIS) 2003. Microsoft also released a couple of Resource Toolkits for MIIS to assist customers and IT Integrators’ implement the product as up to that time it’s predecessor (Microsoft Metadirectory Services) was only available as part of a Microsoft Consulting engagement.

At the same time Microsoft provided a Beta product – Microsoft PolyArchy Server. For someone who’s brain is wired in highly visually way, this was a wow moment. PolyArchy Server took a dataset from the Synchronisation Server and wrapped a small IIS website around it to expose intersecting relationships between data. When you selected a datapoint the visual would flip to the new context and display a list of entities associated with that relationship.

Microsoft proposed to deliver PolyArchy Server in calendar year 2006. However the product never made it to market. The concept of visualizing identity data was seeded in my brain and something I’ve always surfaced in one method or another as part of many Identity Management projects.

In this post I’ll detail how I’ve recently used Power BI to visualize relationship data from Microsoft Identity Manager.  The graphic below is an example (with node labels turned off) that represents Managers by Department by State.

Managers by Dept by State - Graphical.png

Using filters in the same report allows whoever is viewing the report to refine the visual based on State and Dept. By selecting a State from the map the visual will dynamically update to show that state only. Selecting a department only will show that department in each state.

Managers by Dept by State - Filtered.png

Hovering over the nodes will display the detail. I’ve turned off the node labels that show each nodes label to not expose the source of my dataset.

Managers by Dept by State - NSW Detail.png

Getting MIM MV User MetaData into Power BI

My recent post here details the necessary steps to get started publishing data directly in a Power BI Dataset using PowerShell. Follow the details listed there to register a Power BI Application.

Creating the DataSet

With that done the script below will create a DataSet in Power BI. My dataset is obviously specific to the environment I developed it in. You probably won’t have some of the attributes so you will need to update accordingly. The script is desinged to run on the MIM Sync Server. The MIM Sync Server will need to be able to connect to Azure and Power BI.

Publish data to the DataSet

Now that we have a Power BI DataSet (Table) we need to extract the data from the MIM MV and push it into the table. Using the Lithnet MIIS Automation PowerShell Module makes this extremely simple. Using the table schema created above I retrieve the values for each Active User, build a PowerShell Object and use the Power BI PowerShell Module to push the data to Power BI.

Creating the Power BI Visualization

The visualisation I’m using is the Journey Chart by MAQ Software which is available in the Power BI Store (free).

Journey Visual.PNG

With the Journey Visualization selected and dropped in we just have to select the attributes we want to visualize and the order of the relationships. The screenshot below shows the data sorted by State => managerName => accountName with Measure Data being accountName.

Visual Config.PNG

Conclusion

We never got PolyArchy Server from Microsoft, but we can quickly visualize basic relationship data from MIM with Power BI.

Automate the update of the data into Power BI, embed the Power BI Reports into your MIM Portal and provide access to the appropriate personnel.

 

A modern way to track FIM/MIM Attribute Value History utilizing Power BI

Introduction

Microsoft Identity Manager is fantastic for keeping data consistent between connected systems. Often however you want to know what a previous value of an attribute was. FIM/MIM however can only tell you the current value and the Management Agent it was received on and when.

In the past where I’ve had to provide a solution to either make sure an attribute has a unique value forever (e.g email address or loginID (don’t reuse email addresses or loginID)) or just attribute value history I’ve used two different approaches;

  • Store previous values in an SQL Table and have an SQL MA that flows out the values
  • Store historical values in a Multi-Valued attribute on the user object in the Metaverse

Both are valid approaches but often fall down when you want to quickly get a report on that metadata.

Recently we had a similar request to be able to know when Employees EndDates were updated in HR. Specifically useful for contractors who have their contracts extended. Instead of stuffing the info into a Multi-Valued attribute or an SQL DB this time I used Power BI. This provides the benefit of being able to quickly develop a graphical report and embed it in the FIM/MIM Portal.

Such a report looks like the screenshot below. Power BI Report

Using the filters on the right hand side of the report you can find a user (by EmployeeID or DisplayName), select them and see attribute value history details for that user in the main part of the report. As per the screenshot below Andrew’s EndDate was originally the 8th of December (as received on the 5th of November), but was changed to the 24th of November on the 13th of November.

End Date History

In this Post I describe how I quickly built the solution.

Overview

The process to do this involves;

  • creating a Power BI Application
  • creating a Power BI Dataset
  • creating a script to retrieve the data from the MV and inject it into the Power BI Dataset
  • creating a Power BI Report for the data
  • embedding the Report in the MIM Portal

Registering a Power BI Application

Head over to Power BI for Developers and Register an Application for Power BI. Login to Power BI with an account for the tenant you’ll be reporting data for. Give your Application a name and choose Native Application. Set the Redirect URL to https://localhost

CreatePBIApp

Choose the permissions for you Application. As we’ll be writing data into Power BI you’ll need a minimum of Read and Write all Datasets. Select Register App.

Create PBI App Permissions

Record your Client ID for your Application. We’ll need this to connect to Power BI.

Register the App

We need to authenticate to Power BI the first time using a UI to provide Authorization for our Application. In order to do that we need to add another Reply URL to our application. Head to the Apps Dev Portal, select your application and Edit the Application Manifest. Add an additional Reply URL for https://login.live.com/oauth20_desktop.srf as shown below.

Add Reply URL for AuthZ

The following PowerShell commands will then allow us to Authenticate utilizing the Power BI PowerShell module. If you don’t have the Power BI PowerShell Module installed un-comment Install-Module PowerBIPS -RequiredVersion 1.2.0.9 -Force  to install the PowerShell Power BI PowerShell Module.

Update for your Client ID for the App you registered in the previous steps.

# Install-Module PowerBIPS -RequiredVersion 1.2.0.9 -Force
Import-Module PowerBIPS -RequiredVersion 1.2.0.9

# PowerBI App
$clientID = "4036df76-4de6-43cb-afe6-1234567890"

$authtoken = Get-PBIAuthToken -ClientId $clientID

Sign in with an account for the Tenant where you created the Power BI App.

Interactive Login for Dataset Creation

Accept the permissions you chose when registering the Power BI App.

Authorize PowerBI App

Creating the Power BI Dataset

Now we will create the Power BI Table (Dataset) that we will use when we insert the records.

My table is named Employee and the DataSet EmployeeEndDateReport.  I’m keeping the table slim to enough info for our purpose. Date added to the dataset, employees Accountname, Displayname, Active state, EndDate and EndDateReceived. The following script will create the Dataset.

Populating the Dataset

With our table created, lets populate the table with employees that have an EndDate. As this is the first time we run it, we set a watermark date to add people from. I’ve gone with the previous year.  I then query the MV for Employees with an EndDate within the last 365 days, build a PowerShell Object with the columns from our table and insert them into Power BI. I also set a watermark of the last time we had an EndDate Received from the MA and output that to the watermark file. This is so next time we can quickly get only users that have an EndDate that was received since the last time we ran the process.

NOTE: for full automation you’ll need to change line 6 for your secure method of choice of providing credentials to scripts. 

Create a Power BI Report

Now in Power BI select your Data Set and design your report. Here is a sample one that I’ve put together. I simply selected the columns from the dataset and updated the look and feel. I then added in a column (individually for AccountName, DisplayName and Active) and chose it as Filter so that I have various ways of filtering whoever I’m looking for.

Power BI Report.png

Once you have run the process for a while and you have changed values for the attribute you are keeping history for, you will see when you select a user with changed values, you will see the history.

End Date History

Summary

To complete the solution you’ll want to automate the script that queries the MV for changes (probably after each run from the MA that provides the attribute you are recording history for), and you’ll want to embed the report in the MIM Portal. In this post here I detail how to do that step by step.

 

A quick start guide for Deploying and Configuring Node-RED as an Azure WebApp

Introduction

I’ve been experimenting and messing around with IoT devices for well over 10 years. Back then it wasn’t called IoT, and it was very much a build it and write it yourself approach.

Fast forward to 2017 and you can buy a microprocessor for a couple of dollars that includes WiFi. Environmental sensors are available for another couple of dollars and we can start to publish environmental telemetry without having to build circuitry and develop code. And rather than having to design and deploy a database to store the telemetry (as I was doing 10+ years ago) we can send it to SaaS/PaaS services and build dashboards very quickly.

This post provides a quick start guide to those last few points. Visualising data from IoT devices using Azure Platform-as-a-Service services. Here is a rudimentary environment dashboard I put together very quickly.

NodeRedDashboardUI.PNG

Overview

Having played with numerous services recently for my already API integrated IoT devices, I knew I wanted a solution to visualise the data, but I didn’t want to deploy dedicated infrastructure and I wanted to keep the number of moving parts to a minimum. I looked at getting my devices to publish their telemetry via MQTT which is  great solution (for scale or rapidly changing data), but when you are only dealing with a handful of sensors and data that isn’t highly dynamic it is over-kill. I wanted to simply poll the devices as required and obtain the current readings and visualise it. Think temperature, pressure, humidity.

Through my research I like the look of Node-RED for its quick and simplistic approach to obtaining data and manipulating it for presentation. Node-RED relies on NodeJS which I figured I could deploy as an Azure WebApp (similar to what I did here). Sure enough I could. However not long after I got it working I discovered this project. A Node-RED enabled NodeJS Web App you can deploy straight from Github. Awesome work Juan Manuel Servera.

Prerequisites

The quickest way to start then is to use Juan’s Azure WebApp wrapper for Node-RED. Follow his instructions to get that deployed to your Azure Subscription. Once deployed you can navigate to your Node-RED WebApp and you should see something similar to the image below.

DefaultNode-Red.PNG

The first thing you need to do is secure the app. From your WebApp Application Settings in the Azure Portal, use Kudu to navigate to the WebApp files. Under your wwwroot/WebApp directory you will find the settings.js file. Select the file and select the Edit (pencil) icon.

Node-Red-Settings

Comment in the adminAuth section around lines 93-100. To generate the encrypted password on a local install of NodeJS I ran the following command and copied the hash. Change ‘whatisagoodpassword’ for your desired password.

node -e "console.log(require('bcryptjs').hashSync(process.argv[1], 8));" whatisagoodpassword

Select Save, then Restart your application.

Node-Red-Password

On loading your WebApp again you will be prompted to login. Login and lets get started.

Login

Configuring Node-RED

Now it is time to pull in some data and visualise it. I’m not going to go into too much detail as what you want to do is probably quick different to me.

At its simplest though I want to trigger on a timer a call to my sensor API’s to return the values and display them as either text, a graph or a gauge. Below graphically shows he configuration for the dashboard shown above.

ConfigureNodeRED.PNG

For each entity on the dashboard there is and input. For me this is trigger every 15 minutes. That looks like this.

Get-15mins

Next is the API to get the data. The API I’m calling is an open GET with the API key in the URL so looks like this.

HTTPRequest

With the JSON response from the API I retrieve the temperature value and return it as msg for use in the UI.

Function

I then have the Gauge for Temperature. I’ve set the minimum and maximum values and gone with the defaults for the colours.

Guage

I’m also outputting debug info during setup for the raw response from the Function ….

DebugParsedOutput

….. and from the parsed function.

DebugHTTPRequest

These appear in the Debug pane on the right hand side.

DebugWindow

After each configuration change simply select Deploy and then switch over to your Node-RED WebApp. That will looks like your URI for your WebApp with UI on the end eg. http://.azurewebsites.net/ui

Conclusion

Thanks to Azure PaaS services and the ability to use a graphical IoT tool like Node-RED we can quickly deploy a solution to visualise IoT data without having to deploy any backend infrastructure. The only hardware is the IoT sensors, everything else is serverless.