In my recent post I explained how I enable SSL for Cloud Foundry apps on IBM Cloud with my own custom domain. Today, I focus on securing apps running in Docker containers in the Kubernetes service on IBM Cloud.The good news is that I only had to follow what is written in the documentation and in my previous blog post. Here are the details.
Henrik's thoughts on life in IT, data and information management, cloud computing, cognitive computing, covering IBM Db2, IBM Cloud, Watson, Amazon Web Services, Microsoft Azure and more.
Monday, July 23, 2018
Wednesday, July 18, 2018
Now on GitHub: Understand and build chatbots the easy way
Recently, I posted about a then upcoming Meetup and my talk about chatbots. Here is a quick follow-up. To compile stuff for that presentation and some other upcoming talks, I created a GitHub repository "chatbot-talk2018". I has lots of links to get started and to deepen understanding around chatbot technology. Moreover, it contains a presentation in Markdown for GitPitch for you to use and extend. And finally, I wrote this brief introduction to some chatbot terms or concepts:
- Intents are what the user aims for, the desired action or result of the interaction. An intent can be to retrieve a weather report.
- Entities are (real or virtual) subjects or objects. For the example of the weather report, entities can be the city or country, e.g., Friedrichshafen in Germany, or date and time information such as "today afternoon".
- A dialog, dialog flow or dialog tree
is used to structure the interaction. Typically, an interaction lasts
longer than the user providing input and the chatbot returning a single
answer. A dialog can be highly complex with several levels, subbranches,
(directed) links between dialog nodes and more.
For a weather chatbot, a dialog could be constructed that, after a greeting, asks the user about the location and time for a weather report, then asks if additional information, such as a weather outlook for the next few days, is needed. - Slots are supported by several chatbot systems. Slots are used to specify the data items that need to be specified in order to produce the result of an intent. To return a weather report, e.g., at least the location and maybe the date or time is needed.
- Context is state information that is carried from step to step for a specific user interaction. The context typically stores the information that is already gathered as input (see "slot"), result-related data or metadata, or general chat information, e.g., the user name.
Monday, July 16, 2018
Extended: Manage and interact with Watson Assistant from the command line
Remember my blog posts about how to manage Watson Assistant from the command line and how to test context for a conversation? Well, that tool did not work well for server actions which I used in this tutorial on building database-driven Slackbot. The good news is that I found time to extend my command line Watson Conversation Tool to support credentials for IBM Cloud Functions.
With the recent update to the tool there are two new features:
With the recent update to the tool there are two new features:
- Use the option "-outputonly" with the "-dialog" option to only print the output text, not the entire JSON response object. I introduced it to be able to demo dialog flows from the command line. Not everybody needs all the metadata for every dialog turn. Here is how it looks like when in action:
- In order to test dialog server actions, I need to provide the credentials for IBM Cloud Functions (ICF) in a private context variable. I recently blogged about how to enable the Watson botkit middleware for those server actions. For my tool, just provide the ICF key token as part of the configuration file. A sample is part of the GitHub repository.
Chatbot dialog on the command line |
Friday, July 13, 2018
How to: Enable Let's Encrypt SSL wildcard certificates for your IBM Cloud apps
Private data - secured |
Tuesday, July 3, 2018
Learn about chatbots at upcoming IBM Cloud Meetup
Learn how to chat at the Meetup |
If you followed my blog and the chatbot-related posts, you probably already know what to expect. First, I am going to introduce you to chat / conversation services and the standard terms. Then, we jointly will take a look at the IBM Cloud solution tutorials and the chatbot-related resources. I plan to finish with a demo showing how to build a chatbot from scratch in few minutes and to integrate it into Slack. If you are close to Stuttgart, join me on July 17th for the chatbot session.
If you have feedback, suggestions, or questions about this post, please reach out to me on Twitter (@data_henrik) or LinkedIn.
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