By the time you’re finished, you should be able to repurpose the bot to respond with more useful information than this tutorial. There’s no state to maintain, no storage, no databases. All it will do is respond to a single command. In the first tutorial, we’ll explore how to set up a bot in AWS Lambda, linking in AWS API Gateways, and then attaching it to Slack. The code I’ll show you will be written in Python, but it’s all simple enough that you could translate it into Node, Java, Go, or whatever language your environment provides. But the concepts are easily transferred to Microsoft Azure, Google Compute or any other serverless environment you choose.
These two tutorials will use Amazon’s AWS resources. You’ll be able to run your bot full time, in the cloud, without needing to run a server or provision any compute resources in your cloud environment. We’re going to work together to create a modern bot that you can interact with via Slack - the ubiquitous chat service of the modern technology company.īut we’re going to mix in some magic I would have loved twenty years ago. In two tutorials, I’m going to bring you into my world. I ran the bot on leased servers - expensive and overpowered for the simple nature of a bot. For many years my language of choice was Perl. For some reason, writing bots for chat programs has become somewhat of a hobby. It was written in AppleScript and required that I kept my Macintosh Quadra running 24/7, hoping the dial-up internet never flaked out. It asked a question, assessed answers and kept scores. It hosted a trivia channel on IRC - the massive public chat network popular through the 90s and early 2000s. Twenty years ago, I wrote my first automated chatbot. This week we have a guest post from Rick Measham, as Software Development Manager and Technology Team Leader at MessageMedia.
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