Writing PowerShell Core AWS Lambda Functions ‚Äď Part IV


In this fourth blog, we’re going to write the PowerShell Lambda function. By the end of this blog, we’ll have tested our function, and be ready to package and upload it to AWS.

The Story So Far…

At this point, we have in place connectivity between our Facebook app and Lex and we’ve done a basic test to ensure that our commands are being parsed.

We’re ready to begin development of our PowerShell Lambda function! ūüôā

The Goal

When Lex receives data from Messenger that matches an Utterance pattern, it invokes a PowerShell Lambda function we will later write. When the script runs it obtains the value of the command slot, and then obtains a synopsis of what the cmdlet does. This information is returned back to Lex which in turn sends it back to Messenger for it to display.

Writing the Lambda Function

Let’s set about getting our PowerShell script in place.

Create the package

  • Launch PowerShell
  • Type New-AWSPowerShellLambda -Template Basic -ScriptName GetAWSPowerShellHelp
  • A directory will be created, GetAWSPowerShellHelp, containing two files, GetAWSPowerShellHelp.ps1 and readme.txt
  • Open GetAWSPowerShellHelp.ps1 in your editor of choice.
  • Copy the script below into the clipboard
  • Paste into your editor, removing any existing text
  • Save the file

Script Breakdown

Let’s take a look at the script in more detail:

Define Module Requirements

The Requires definition restricts the script from running unless AWSPowerShell.Netcore, version, is available.

Write the Event Data to Cloudwatch

The contents of the Lambda functions input data variable, $LamdaInput are converted from its object format to JSON, before being output. Use of Write-Host in a PowerShell Lambda function results in the data being written to Cloudwatch. This results in an entry in the log similar to below:

Set PowerShell Error Handling

The default value for the $ErrorActionPreference variable for PowerShell running in a Lambda function is Continue. Unfortunately, it appears within a Lambda function, if an error occurs during execution of a PowerShell script, this causes it to immediately exit and return an error to the caller. In our code there exists two possibilities for errors to be raised. To address this we set $ErrorActionPreference to Stop, and then use a Try..Catch block to handle errors and prevent exit. The specifics of our Try..Catch block are details next.

Process the Command Slot

As mentioned in an earlier blog in this series, input data is automatically read and cast into a PSobject called $LambdaInput. Using the sample JSON above as a guide, we can obtain the slot value for Command via $LambdaInput.currentIntent.slots.Command

An additional step we want to do is obtain the correct casing of the command. This is required because we will be querying a URL soon which will include the name of the command, and most web servers are case sensitive.

Obtain Online Help Information

A normal approach to getting help about a PowerShell command is via the Get-Help cmdlet. The AWSPowerShell.Netcore module implementation for PowerShell Lambda does not include help information. This is understandable, naturally, with Get-Help being an interactive command. So for us to obtain the synopsis information for a cmdlet we need to grab it from the online help.

Help is available from the AWS Tools for PowerShell Cmdlet Reference page for all cmdlets. For a specific one, this is available at:

https://docs.aws.amazon.com/powershell/latest/reference/items/cmdlet name.html

An example is below:

Knowing this, it is pretty straightforward to calculate the URL that we’ll be accessing:

For any given cmdlet’s page, we want to grab the Synopsis information. A look at the page source for the above one shows us this section:

We can use regex with a capture group to grab the text we need. I’ve opted to use the expression below after playing around a bit with the regex tester at Regex Storm. Note the use of a named capture group, synopsis, in our regex.

This is represented in PowerShell (with the addition of backticks to escape the double quotes) via:

Now we can proceed with scraping the synopsis information.

We get the content of the web page, then perform the regex match against it.

PowerShell uses a special variable, $matches, which is automatically populated if a successful match occurs. Because we used a named capture group in our expression, synopsis, a hashtable entry with this name is created.

This makes referencing the information simple.

We also want to ensure that if no match is found a message returned to indicate this.

The $description variable is set to the the value of the match. If this is null, however, it is updated to say that no help is available for the cmdlet.

Apply Catch Conditions

We need to apply the Catch conditions to react to errors that can occur within the Try block, since it could be that the :

  • cmdlet does not actually exist
  • cmdlet exists but there is no help webpage

These are handled by the first and second Catch statements respectively.

Create the Response

We then make use of a template JSON format, using the documentation here for information.

These settings indicates that the workflow should end and that the result be marked as successful. The $description variable in the here-string is automatically expanded by PowerShell to contain the value set in the previous steps.

Return the Response

Lastly, the $template string is returned from the PowerShell Lambda function. This will be received by Lex.


At this point, you can perform a test locally on your system just by making a couple of changes to your script.

  • Surround the lines from #Requires up to and including $commandparam = $LambdaInput.currentIntent.slots.Command in a remark block
  • Add your own definition after for $commandparam

Now you can run the script locally and receive console output.

Remember to undo those changes mentioned once you have completed testing the script.


At this point, we have written our PowerShell Lambda function and tested it locally. We’re nearly there!

In the next blog in the series, we’ll publish the function to Lambda, configure Lex to invoke it, and show it in operation from a couple of devices.

Thanks for reading! Feedback welcome!


Writing PowerShell Core AWS Lambda Functions ‚Äď Part III


In this third blog, we’ll be setting up the initial configuration of the Lex ‘bot that is going to be the intermediary between the Facebook page we setup earlier and our forthcoming PowerShell Lambda function. After a brief overview of what’s going to be needed, we’ll setup a Slot Type (with a bit of help from PowerShell), Slot, Intent, and Facebook Channel. With this done, we’ll do a basic test of the ‘bot which to give some insight into the event data format that our function will be receiving and processing.

The Story So Far…

At this point, we have a Facebook app and page setup, our development environment in place with all the prerequisites for writing & publishing PowerShell Lambda packages and taken a trip through the (currently) four cmdlets offered by the AWSLambdaPSCore module.

About Lex

Lex is an AWS service geared towards allowing the use of natural language, written or spoken, as a mechanism for driving other applications and services. It allows you to connect social media services like Facebook, a device such as an Alexa Dot, or your own application to Lex and process the input before providing a response back to the source.

Your Lex bot consists of one or more :

  • Intents – An objective, performed via a combination of the items below.
  • Utterances – Sequence of words which activate a specific Intent
  • Slots – Sets of values, akin to parameters, that are utilized in order for the objective to be achieved. The value of a slot can be filtered from an Utterance, or prompted for separately. Also akin to typical parameter behavior, the values provided to Slots can be restricted to a given format or list of values, using what are known as Slot types.
  • Prompts – Requests for additional information or confirmation of details already given.
  • Fulfilments – The steps that will be taken with all the previous provided that allows the Intent to be completed. In our case this will involve the invoking of a Lambda function and receipt of its output.
  • Channels – Communications services (currently Facebook, Kik, Slack, and Twilio SMS) that Lex can by interact with.

What’s Required

For our ‘bot, with the above in mind, we’re going to go for the following:

Intent Name GetPowerShellHelp
Utterances I want help with {command}

What does {command} do

I want help with an AWS cmdlet

Slot Type PSCommand (custom)
Slot Type Values Every command in the AWSLambdaPSCore module(!)
Slot Name command
Fulfillment Our Lambda function
Channel Facebook

Let’s set about getting these setup. ūüôā

Creating the ‘bot

    • Login to the AWS console
    • Click Services, Amazon Lex
  • With¬†Bot¬†selected on the left hand side, click Create

  • In the Create your bot window, click Custom bot
    • Bot name : MyPowerShellHelpBot
    • Language : Leave as default English (US)
    • Output voice: None. This is a text based application
    • Session timeout¬†: 1 min
    • IAM Role : This is created for you automatically
    • COPPA : No
  • Click Create

A few more seconds should see our bot created. Before we start creating the Intent though, we’re going to create a file that will be used by the Intent, the Slot type¬†PSCommand, mentioned above.

About Slot Types and Slots

Initially, Lex receives a set of words, the Utterance, which acts as a trigger to a specific Intent. In the simplest of Intents, no specifics are required other than the a fixed set of words.

e.g. “play a song for me”.

More often though, additional details will be required. After all, if we want to hear a song, sometimes you might want to hear music by a specific artist. However, creating an Utterance for every single artist would be an impossible task.

This is where Slots come into play. In the example above, the artist is your slot. Defining a Slot tells Lex that it needs specific information to process the request. Each Slot has an associated Slot type.

A Slot type really is just an enumeration that consist of a specific input value (or values), and the underlying value. A Slot type can have more than input value, known as a synonym.

e.g. In the Amazon.Number Slot type, an input value of “four” has an underlying value of 4.

Slot types help not only to translate input data into a more suitable format for processing, but also to restrict the input values that can be given. They can be used to prevent invalid data from being given BEFORE any processing is done. Whilst it also is possible to do pre-processing of input data, In our case, we don’t want our Lambda to run if it’s being provided with an invalid cmdlet name.

Creating the Slot Type File

We’re going to create a Slot type, called PScommand. This will consist of a list of commands from the current revision of the AWSPowerShell.NetCore module we have installed. Our Slot, command, is the parameter that we will be using within our PowerShell Lambda function.¬†Slot types can be imported as a zip compressed JSON file.

We’ll write a PowerShell script to make this JSON and zip file for us. Jump to your development environment of choice, paste the code below, and save it as a .ps1 file.

The here-string that you see is the core template format for slot type we’ll be using. The changes to be made here will involve filling the¬†enumerationValues array with a list of the¬†AWSPowerShell.NetCore modules cmdlets.

The script itself, after converting the JSON to a PSObject, enumerates through each command in the above module and appends an array consisting of a value element, set to the name of the command, and an empty array value for the synonyms attribute. Note that if we wanted to get really detailed, we could use the PowerShell aliases that exist for the commands in this module, placing them in the appropriate entries synonym value, but I’m going to keep it simple. Once this is complete, the PSObject is converted to a JSON file, before being zipped up.

Run the script to create both of these files.

Should you so want, you can take a look at psCommand.json.

Import the Slot Type File

Let’s import our new file:

    • Go back to the main Amazon Lex screen
    • Click Slot types
    • Click Actions, Import
    • On the Import slot type popup, click¬†Browse
    • Navigate to the directory containing your script and the¬†psCommand.zip, select the file and click Open
    • Click Import

Soon after, our Slot type, PScommand should be visible.

Create the Intent

Follow the steps below to create the intent. Similar to Slot types, it is possible to create a zipped JSON file with the Intent, but we’ll do this through the console for now to make it a bit clearer what is happening.

  • On the main Amazon Lex screen, click Bots
  • Click¬†MyPowerShellHelpBot
  • Click +Create Intent
  • In the Add intent window, click Create intent

  • In the Create intent window, call the type¬†getAWSPowerShellHelp¬†for the Intents name.
  • Click Add

Next, we configure the intent. Set to the following.

  • Sample utterances :
    • What does {command} do
    • I want help with {command}
    • I want help with an AWS cmdlet
  • Lambda initialization and validation
    • Do not set
  • Slots
    • Required : Checked
    • Name: command
    • Slot type:¬†PScommand
    • Prompt: What cmdlet?
    • Click the blue + button to add the slot
  • Confirmation prompt
    • Leave unchecked
  • Fullfillment
    • Return parameters to client

Now, scroll down to the bottom of the screen and click Save Intent

Build and Publish the ‘Bot
Before we begin configuration of the Channel, we need to build and publish the ‘bot.

Click Build and wait for the build to finish. On completion, you should find the Test bot window has expanded.

  • Click Publish
  • Next, we are prompted to create an alias by providing it with a name. An alias is simply a reference to a version of a build.
  • Enter Prod for the alias name
  • Click Publish

Once the bot is published, a confirmation screen will appear.

  • Click Close

Create the Facebook Channel

The next step involves us setting up a Channel, in our case for Facebook. Successful configuration of a Channel allows the creation of an endpoint through which Facebook will communicate with Lex.

At this point, grab the Page Access Token and App Secret Key you recorded in Part I of this series.

  • Click the¬†Channels¬†tab
  • Click Facebook¬†on the left hand side
  • Configure as follows:
    • Channel Name: MyFBChannel
    • Channel Description: AWS PowerShell Help Channel
    • KMS Key : Select aws/lex from the drop down list
    • Alias: Select Prod from the drop down list
    • Verify Token: MyVerifyToken
    • Page Access Token : Use the one you have from Part I
    • App Secret Key: Use the one you have from Part I
  • Click Activate

Activation results in a Callback URL, an endpoint that will be used by the Facebook app to communicate with Lex, being created.

Click Copy to copy into the clipboard.

Configure the Facebook Page and App

With the above configured in AWS, we now move on to configuring Facebook to use the Lex ‘bot.

Making the Application Live
In order to allow our application talk to Lex, the Facebook application (AWS PowerShell Help in my case) needs to go live. This requires, however, that the application is configured to provide a link to a privacy policy for users the app.

  • Click Settings, Basic.
  • Configure Privacy Policy URL with any valid web address. There does not need to be any policy a the address given.

    • At the top of the screen, click the slider to make the app live.
    • Set the category to Messaging
  • Click¬†Confirm when prompted if you wish to make the application public.

Shortly afterwards, the slider will go green and indicate ‘ON’

Configure a Webhook and Subscription
Now we’re going to setup the app to use the Callback URL from earlier.

  • Click Messenger on the left side of the screen
  • Click Settings directly below
  • Scroll down to Webhooks
  • Click Setup Webhooks
  • On the New Page Subscription window that opens, use the following settings:
    • Callback URL : Paste the text that was copied into your clipboard from the AWS console
    • Verify Token : MyVerifyToken
    • Subscription Fields: messages, messaging_postbacks, messaging_options
  • Click Verify and Save

Your subscription will be created.

  • Go to the App Review for Messenger section further down the screen
  • Click pages_messaging
  • Click¬†Add to Submission

  • Click the¬†Page Settings¬†hyperlink in the text Looking for pages_messaging_subscripts? It’s moved to Page Settings.
  • This will take you to the Messenger Platform Settings

Because we are using Messenger as our communication method with our Lex ‘bot, some additional configuration needs to be carried out.

We don’t want the app to require manual intervention, so we need to tell Facebook this.

  • Go to the General Settings section
  • Set Response Method to¬†Responses are all automated

Additionally, we want our app to be the one first notified if a message is received by our Facebook page.

  • Go to the Subscribed Apps section
  • Set Primary Receiver¬†to¬†AWS PowerShell Help¬†
  • Ensure Secondary Receiver is now set to¬†Page Inbox

Testing Interaction With Lex ‘bot

Now let’s perform some basic checks of our apps interoperability with Lex.

  • Scroll to the Your Messenger Link section
  • Click Copy link to place the address in your clipboard

  • Paste the URL into the address bar of a new tab in your browser
  • Enter the following text into the message bar:
    • What does Get-EC2Host do?
    • Press return
    • I want help with Get-EC2Host
    • Press return

For each of the text entries above, you should receive a message back.

Remember that at this point we have set Fulfillment to Return parameters to client¬†in the bot’s Intent configuration. This is why you should be seeing the name of¬†Intent being invoked and the Slot provided. Our Lambda still needs to be created.

We’ve verified connectivity between Facebook and Lex, that the messages we have sent are triggering the right Intent and the parameter (slot) is properly parsed.

Let’s jump back to Lex so we can take a look at how this information is natively output.

Viewing the JSON Output

Note that the response that you saw in the Messenger window was a modified version of the actual event data that is raised. This was handled by the Channel.

Let’s take a look at the pre-formatted data.

  • Go back to the Amazon Lex screen
  • Click Bots
  • Click MyPowerShellHelpBot
  • Expand the Test bot window on the right hand side of the screen
  • In Chat with your bot…¬†type I want help with Get-EC2Host
  • In the¬†Indirect response section below, click Detail

You Test bot window should resemble the below:

The text in the Indirect response window is the exact JSON data that our Lambda will receive once it’s up and running.


In this slightly longer than usual blog, we’ve covered the basics of a Lex ‘bot and components that are used with it, created a Slot type consisting of the AWS PowerShell commands, configured an Intent and Channel and setup interoperability between Lex (via the Channel) to the Facebook app. We then performed testing both from Facebook Messenger and also using the Test ‘bot in the AWS console. Lastly, we’ve had an introduction to the format of the¬†event data that is going to be passed to our forthcoming PowerShell Lambda function.

This leads us nicely up to the next blog, in which we’ll create our PowerShell Lambda function, upload it to AWS, and configure it to be activated by our Lex ‘bot.

Thanks for reading! Feedback welcome!


Recommended Further Reading

Create and Edit Custom Slot Types –¬†https://developer.amazon.com/docs/custom-skills/create-and-edit-custom-slot-types.html



Writing PowerShell Core AWS Lambda Functions ‚Äď Part II


In this second blog, we’ll be setting up our development environment to allow us to create and publish Lambda compatible PowerShell packages. This will involve installing the .NET Core SDK, PowerShell Core and two AWS specific PowerShell modules, namely AWSPowerShell.NetCore and¬†AWSLambdaPSCore. We’ll also spend a bit of time looking at the cmdlets provided with the latter module.

The Story So Far

In the previous blog, we provided a brief overview on the use of PowerShell Lambda functions and how they process incoming and outgoing data. Then, we set about getting the Facebook app and page setup that is going to be used by our PowerShell driven ‘bot.

Now, let’s carry out the installation of the following

      • PowerShell Core 6.0
      • .Net Core 2.1 SDK
      • AWSPowerShell.NetCore Module
      • AWSLambdaPSCore Module

PowerShell Core 6.0

Various installations of PowerShell Core exist, dependent on your distribution platform. A link to installation instructions for each of these is listed below. Note that as part of the installation process, other prerequisites are installed, such as .Net Core.

Installing PowerShell Core on Windows
Installing PowerShell Core on Linux
Installing PowerShell Core on macOS
Installing PowerShell Core on ARM

.Net Core 2.1 SDK

PowerShell Core is built on top of .NET Core. As such, the Lambda support for PowerShell uses the same .NET Core 2.1 Lambda runtime for both .NET Core and PowerShell based Lambda functions. From a functionality point of view, the cmdlets in the AWSLambdaPSCore module ALSO need the .NET Core 2.1 SDK for packaging your functions for Lambda.

You can find the 2.1 SDK and installation instructions for your distribution here:

AWS Modules

We can now install our two AWS modules, AWSPowerShell.Netcore and AWSLambdaPSCore.

A couple of things worthwhile pointing out regards the installation of these modules:

  1. By default the PSGallery is not a trusted source for installing modules. If you have not configured this to be so, you will be prompted to confirm if you trust this source for the installation of a module.
  2. In the Scope parameter for the installation of the modules, I’ve set the value to CurrentUser. You can also set this to Global, but bear in mind if you choose this other option some platforms might require your PowerShell session to be running in an elevated context.

AWSPowerShell.Netcore Module

This module houses, as of version,¬† 4488 cmdlets, split across 125 different AWS services. These are the cmdlets that our solution will offer interactive help on. Suffice to say, I’ll skip giving an overview on the main ones in these!

Launch PowerShell Core from a terminal session via:

Next, to install the module, we use the command below.

AWSLambdaPSCore Module

Lastly, we can install the AWS Lambda PowerShell Core module. These cmdlets in this module provide options for reporting available template information, creating your PowerShell script, creating an entire deployment package and the creation of the Lambda function itself.

Use the following command for installation:

Once complete, we can see the current list of commands available in the module via Get-Command.

NB. If you wish to see more extensive information about the cmdlets in the module, such as Scriptblock and ParameterSets, you can use the following to return all properties:


Let’s take a look at these commands in a bit more detail:


It’s important to be aware that the source of the input event data dictates its format and properties.

Whilst on a technical level PowerShell does not need to know the schema of JSON data being received before being able to cast it to a PSObject, it is still the case that in order to make effective use of the data therein, you will need to have an idea of how it is organized. Given the growing number of services whose events can be processed by Lambda, this can involve quite a bit of work.

Fortunately, AWS make things a bit simpler for starting out with a PowerShell Lambda function by providing a group of starter templates both offline (as part of the default install of the module) and online that cover some of the event sources/destinations formats that the Lambda function may need to use.

Should you so wish to, you can view them on your browser directly via either of the two URLs below:

As of the date of this blog, these comprise a set of blueprints for the CloudFormation, Code Commit, Amazon Rekognition, Kinesis, S3, SNS, and SQS services. There is additionally a generic template provided, Basic, which ultimately just contains details of the predefined variables for the Lambda context and event source data and details of logging to CloudWatch. You can see the Basic templates content in the HelloWorld example for one of the cmdlets below.

The list of blueprints is actively updated, which is where Get-AWSPowerShellLambdaTemplate assists. It provides a quick point of reference for the templates that are currently available for you to use when creating your solution.

When you execute this cmdlet without any parameters, it queries by default the URLs listed above and then casts the JSON data to a PSObject. If content is not available in either of these two locations, then the locally installed blueprints are returned.

There is also a parameter documented in the help for this cmdlet, InstalledOnly, which is intended to only parse locally installed templates and skip an online check. However, as far as I can see at the moment, this switch is not processed at all.


The New-AWSPowerShellLambda cmdlet is capable of either creating a basic, new Lambda function in a single PowerShell script file, or alternatively an entire project, consisting additionally of project, bootstrap, and parameter default files. The latter option is typically only used for advanced cases where additional manual intervention (e.g. adding additional files, or setting default values for parameters in your function) is required before creating the deployment package and needs to be invoked with the WithProject switch parameter. We’ll being doing all our work in a simple PowerShell script, so for the purposes of this blog will not explore this switch further.

An example of the use of the command and what it does is below:

Creating a ‘HelloWorld’ Lambda based on the Basic template

The ‘HelloWorld’ folder and file structure

‘HelloWorld.ps1’ contents

Subsequent to your work being complete, the script or project can be either directly turned into a Lambda function (using Publish-AWSPowerShellLambda), or put into a state which allows its later deployment via a deployment service, such as Cloudformation, using NewAWSPowerShellLambdaPackage. Details of both are below.


This penultimate cmdlet handles the heavy lifting of taking your script/project, putting it into a state suitable for deployment, and then creating the function itself with the appropriate parameters and with the package uploaded. This step extensively uses the .NET Core SDK, and behind the scenes installs the .NET Amazon.Lambda.Tools package. Once this step is complete, your Lambda function should be accessible to be used as an event handler for another service (Lex in our case).


This cmdlet is used to bundle up a script/project into a package and subsequent zip file that is available for use at a later date by another service or even in a separately defined Lambda project which you configure manually. We’ll not be using this cmdlet during this series of blogs.


At this point, we’ve put in place all the prerequisites for starting scripting of our Lambda function and learnt a bit about the cmdlets provided in the AWSLambdaPSCore module.

In the next blog, we’re going to start on the first stage of our Lex work. It’ll involve setting up a Slot, Intent, and a Channel which will link the ‘bot to the Facebook page created in the first blog. We’ll also cover the event data format, which will link us nicely into the third blog, which involves writing the Lambda function itself.

Thanks for reading! Feedback welcome!