Tag Archives: Amazon Alexa

Understanding the Different Ways to Invoke Lambda Functions

Post Syndicated from George Mao original https://aws.amazon.com/blogs/architecture/understanding-the-different-ways-to-invoke-lambda-functions/

In our first post, we talked about general design patterns to enable massive scale with serverless applications. In this post, we’ll review the different ways you can invoke Lambda functions and what you should be aware of with each invocation model.

Synchronous Invokes

Synchronous invocations are the most straight forward way to invoke your Lambda functions. In this model, your functions execute immediately when you perform the Lambda Invoke API call. This can be accomplished through a variety of options, including using the CLI or any of the supported SDKs.

Here is an example of a synchronous invoke using the CLI:

aws lambda invoke —function-name MyLambdaFunction —invocation-type RequestResponse —payload  “[JSON string here]”

The Invocation-type flag specifies a value of “RequestResponse”. This instructs AWS to execute your Lambda function and wait for the function to complete. When you perform a synchronous invoke, you are responsible for checking the response and determining if there was an error and if you should retry the invoke.

Many AWS services can emit events that trigger Lambda functions. Here is a list of services that invoke Lambda functions synchronously:

Asynchronous Invokes

Here is an example of an asynchronous invoke using the CLI:

aws lambda invoke —function-name MyLambdaFunction —invocation-type Event —payload  “[JSON string here]”

Notice, the Invocation-type flag specifies “Event.” If your function returns an error, AWS will automatically retry the invoke twice, for a total of three invocations.

Here is a list of services that invoke Lambda functions asynchronously:

Asynchronous invokes place your invoke request in Lambda service queue and we process the requests as they arrive. You should use AWS X-Ray to review how long your request spent in the service queue by checking the “dwell time” segment.

Poll based Invokes

This invocation model is designed to allow you to integrate with AWS Stream and Queue based services with no code or server management. Lambda will poll the following services on your behalf, retrieve records, and invoke your functions. The following are supported services:

AWS will manage the poller on your behalf and perform Synchronous invokes of your function with this type of integration. The retry behavior for this model is based on data expiration in the data source. For example, Kinesis Data streams store records for 24 hours by default (up to 168 hours). The specific details of each integration are linked above.

Conclusion

In our next post, we’ll provide some tips and best practices for developing Lambda functions. Happy coding!

 

About the Author

George MaoGeorge Mao is a Specialist Solutions Architect at Amazon Web Services, focused on the Serverless platform. George is responsible for helping customers design and operate Serverless applications using services like Lambda, API Gateway, Cognito, and DynamoDB. He is a regular speaker at AWS Summits, re:Invent, and various tech events. George is a software engineer and enjoys contributing to open source projects, delivering technical presentations at technology events, and working with customers to design their applications in the Cloud. George holds a Bachelor of Computer Science and Masters of IT from Virginia Tech.

Build your own Solo: A Star Wars Story L3-37 droid

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/build-star-wars-l3-37-droid/

It is a truth universally acknowledged…that everyone wants their own Star Wars droid. If you’re now thinking “No, not me!”, then you obviously haven’t met the right droid yet. But Patrick ‘PatchBOTS‘ Stefanski has, and that droid is L3-37 from the newly released Solo: A Star Wars Story.

Release the droids

Visit your local maker event, such as Maker Faire, and you’re sure to meet at least one droid builder. Building a Star Wars droid is pretty much every maker’s dream, and YouTube droid-building sensation Patrick Stefanski is living that dream. On his Youtube channel PatchBOTS, Patrick is showcasing his maker chops with truly impressive recreations of characters such as BB-8 and our personal favourite, Chopper from Star Wars Rebels.

L3-37

Patrick’s new L3-37 build uses the free Alexa Voice Service and a Raspberry Pi 3 to augment a 3D-printed base model with robotics and AI.

Solo Star Wars Story L3-37 droid PatchBOTs

He designed L3-37’s head based on press images and trailers, and then adjusted some of the visual aesthetic after watching the movie. When he realised that the Amazon Echo Dot he’d started the build with wouldn’t allow him to implement some of the features he had planned, including a unique wake word, Patrick decided to use a Raspberry Pi instead.

Solo Star Wars Story L3-37 droid PatchBOTs

A wake word is the word a home assistant uses to recognise that you’re addressing it. For Amazon Alexa, the standard wake words are ‘Alexa’, ‘Echo’, ‘Amazon’, and ‘computer’. While these are fine for standard daily use, Patrick wanted his droid to acknowledge its own name, L3-37. He also wanted to make L3-37 react with a voice response and movement whenever it heard its name. Using the Raspberry Pi enabled him to edit the home assistant code to include these functionalities, and in this way he made L3-37 truly come to life.

Build your own L3-37 home assistant

If you’d like to build your own L3-37 (and why wouldn’t you), Patrick is in the process of adding the complete set of instructions and code to his Github account. The 3D printer files are available now to get you started, along with the list of ingredients for the build, including servos, NeoPixels, and every propmaker’s staple: Rub n Buff.

If you want buy the parts for this project, why not use the affiliate links Patrick provides in the L3-37 video description to help him fund future projects? And while you’re there, leave a comment to show him some love for this incredible droid build, and also subscribe to his channel to see what he comes up with next.

Solo Star Wars Story L3-37 droid

We’re definitely going to be taking some of the lessons learned in this project to work on our own builds, and we hope you’ll do the same and share your work with us via social media.

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Serverless Architectures with AWS Lambda: Overview and Best Practices

Post Syndicated from Andrew Baird original https://aws.amazon.com/blogs/architecture/serverless-architectures-with-aws-lambda-overview-and-best-practices/

For some organizations, the idea of “going serverless” can be daunting. But with an understanding of best practices – and the right tools — many serverless applications can be fully functional with only a few lines of code and little else.

Examples of fully-serverless-application use cases include:

  • Web or mobile backends – Create fully-serverless, mobile applications or websites by creating user-facing content in a native mobile application or static web content in an S3 bucket. Then have your front-end content integrate with Amazon API Gateway as a backend service API. Lambda functions will then execute the business logic you’ve written for each of the API Gateway methods in your backend API.
  • Chatbots and virtual assistants – Build new serverless ways to interact with your customers, like customer support assistants and bots ready to engage customers on your company-run social media pages. The Amazon Alexa Skills Kit (ASK) and Amazon Lex have the ability to apply natural-language understanding to user-voice and freeform-text input so that a Lambda function you write can intelligently respond and engage with them.
  • Internet of Things (IoT) backends – AWS IoT has direct-integration for device messages to be routed to and processed by Lambda functions. That means you can implement serverless backends for highly secure, scalable IoT applications for uses like connected consumer appliances and intelligent manufacturing facilities.

Using AWS Lambda as the logic layer of a serverless application can enable faster development speed and greater experimentation – and innovation — than in a traditional, server-based environment.

We recently published the “Serverless Architectures with AWS Lambda: Overview and Best Practices” whitepaper to provide the guidance and best practices you need to write better Lambda functions and build better serverless architectures.

Once you’ve finished reading the whitepaper, below are a couple additional resources I recommend as your next step:

  1. If you would like to better understand some of the architecture pattern possibilities for serverless applications: Thirty Serverless Architectures in 30 Minutes (re:Invent 2017 video)
  2. If you’re ready to get hands-on and build a sample serverless application: AWS Serverless Workshops (GitHub Repository)
  3. If you’ve already built a serverless application and you’d like to ensure your application has been Well Architected: The Serverless Application Lens: AWS Well Architected Framework (Whitepaper)

About the Author

 

Andrew Baird is a Sr. Solutions Architect for AWS. Prior to becoming a Solutions Architect, Andrew was a developer, including time as an SDE with Amazon.com. He has worked on large-scale distributed systems, public-facing APIs, and operations automation.

AIY Projects 2: Google’s AIY Projects Kits get an upgrade

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/google-aiy-projects-2/

After the outstanding success of their AIY Projects Voice and Vision Kits, Google has announced the release of upgraded kits, complete with Raspberry Pi Zero WH, Camera Module, and preloaded SD card.

Google AIY Projects Vision Kit 2 Raspberry Pi

Google’s AIY Projects Kits

Google launched the AIY Projects Voice Kit last year, first as a cover gift with The MagPi magazine and later as a standalone product.

Makers needed to provide their own Raspberry Pi for the original kit. The new kits include everything you need, from Pi to SD card.

Within a DIY cardboard box, makers were able to assemble their own voice-activated AI assistant akin to the Amazon Alexa, Apple’s Siri, and Google’s own Google Home Assistant. The Voice Kit was an instant hit that spurred no end of maker videos and tutorials, including our own free tutorial for controlling a robot using voice commands.

Later in the year, the team followed up the success of the Voice Kit with the AIY Projects Vision Kit — the same cardboard box hosting a camera perfect for some pretty nifty image recognition projects.

For more on the AIY Voice Kit, here’s our release video hosted by the rather delightful Rob Zwetsloot.

AIY Projects adds natural human interaction to your Raspberry Pi

Check out the exclusive Google AIY Projects Kit that comes free with The MagPi 57! Grab yourself a copy in stores or online now: http://magpi.cc/2pI6IiQ This first AIY Projects kit taps into the Google Assistant SDK and Cloud Speech API using the AIY Projects Voice HAT (Hardware Accessory on Top) board, stereo microphone, and speaker (included free with the magazine).

AIY Projects 2

So what’s new with version 2 of the AIY Projects Voice Kit? The kit now includes the recently released Raspberry Pi Zero WH, our Zero W with added pre-soldered header pins for instant digital making accessibility. Purchasers of the kits will also get a micro SD card with preloaded OS to help them get started without having to set the card up themselves.

Google AIY Projects Vision Kit 2 Raspberry Pi

Everything you need to build your own Raspberry Pi-powered Google voice assistant

In the newly upgraded AIY Projects Vision Kit v1.2, makers are also treated to an official Raspberry Pi Camera Module v2, the latest model of our add-on camera.

Google AIY Projects Vision Kit 2 Raspberry Pi

“Everything you need to get started is right there in the box,” explains Billy Rutledge, Google’s Director of AIY Projects. “We knew from our research that even though makers are interested in AI, many felt that adding it to their projects was too difficult or required expensive hardware.”

Google AIY Projects Vision Kit 2 Raspberry Pi
Google AIY Projects Vision Kit 2 Raspberry Pi
Google AIY Projects Vision Kit 2 Raspberry Pi

Google is also hard at work producing AIY Projects companion apps for Android, iOS, and Chrome. The Android app is available now to coincide with the launch of the upgraded kits, with the other two due for release soon. The app supports wireless setup of the AIY Kit, though avid coders will still be able to hack theirs to better suit their projects.

Google has also updated the AIY Projects website with an AIY Models section highlighting a range of neural network projects for the kits.

Get your kit

The updated Voice and Vision Kits were announced last night, and in the US they are available now from Target. UK-based makers should be able to get their hands on them this summer — keep an eye on our social channels for updates and links.

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Raspberry Pi Spy’s Alexa Skill

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/pi-spy-alexa-skill/

With Raspberry Pi projects using home assistant services such as Amazon Alexa and Google Home becoming more and more popular, we invited Raspberry Pi maker Matt ‘Raspberry Pi Spy‘ Hawkins to write a guest post about his latest project, the Pi Spy Alexa Skill.

Pi Spy Alexa Skill Raspberry Pi

Pi Spy Skill

The Alexa system uses Skills to provide voice-activated functionality, and it allows you to create new Skills to add extra features. With the Pi Spy Skill, you can ask Alexa what function each pin on the Raspberry Pi’s GPIO header provides, for example by using the phrase “Alexa, ask Pi Spy what is Pin 2.” In response to a phrase such as “Alexa, ask Pi Spy where is GPIO 8”, Alexa can now also tell you on which pin you can find a specific GPIO reference number.

This information is already available in various forms, but I thought it would be useful to retrieve it when I was busy soldering or building circuits and had no hands free.

Creating an Alexa Skill

There is a learning curve to creating a new Skill, and in some regards it was similar to mobile app development.

A Skill consists of two parts: the first is created within the Amazon Developer Console and defines the structure of the voice commands Alexa should recognise. The second part is a webservice that can receive data extracted from the voice commands and provide a response back to the device. You can create the webservice on a webserver, internet-connected device, or cloud service.

I decided to use Amazon’s AWS Lambda service. Once set up, this allows you to write code without having to worry about the server it is running on. It also supports Python, so it fit in nicely with most of my other projects.

To get started, I logged into the Amazon Developer Console with my personal Amazon account and navigated to the Alexa section. I created a new Skill named Pi Spy. Within a Skill, you define an Intent Schema and some Sample Utterances. The schema defines individual intents, and the utterances define how these are invoked by the user.

Here is how my ExaminePin intent is defined in the schema:

Pi Spy Alexa Skill Raspberry Pi

Example utterances then attempt to capture the different phrases the user might speak to their device.

Pi Spy Alexa Skill Raspberry Pi

Whenever Alexa matches a spoken phrase to an utterance, it passes the name of the intent and the variable PinID to the webservice.

In the test section, you can check what JSON data will be generated and passed to your webservice in response to specific phrases. This allows you to verify that the webservices’ responses are correct.

Pi Spy Alexa Skill Raspberry Pi

Over on the AWS Services site, I created a Lambda function based on one of the provided examples to receive the incoming requests. Here is the section of that code which deals with the ExaminePin intent:

Pi Spy Alexa Skill Raspberry Pi

For this intent, I used a Python dictionary to match the incoming pin number to its description. Another Python function deals with the GPIO queries. A URL to this Lambda function was added to the Skill as its ‘endpoint’.

As with the Skill, the Python code can be tested to iron out any syntax errors or logic problems.

With suitable configuration, it would be possible to create the webservice on a Pi, and that is something I’m currently working on. This approach is particularly interesting, as the Pi can then be used to control local hardware devices such as cameras, lights, or pet feeders.

Note

My Alexa Skill is currently only available to UK users. I’m hoping Amazon will choose to copy it to the US service, but I think that is down to its perceived popularity, or it may be done in bulk based on release date. In the next update, I’ll be adding an American English version to help speed up this process.

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