I want to share my experience in the cloud, AI, and agents development areas.
The post outlines using the Evaluation Framework in watsonx Orchestrate ADK to verify AI Agent behavior through a practical example: Galaxium Travels, a fictional booking system. It details setting up the environment, defining user Stories, generating synthetic Test Cases, and running evaluations, crucial for ensuring AI reliability and transparency.
This blog post explores managing local filesystem access with Podman Desktop on macOS. It discusses two options: mapping an existing local folder as a volume to the container, and creating a local Podman volume and accessing data inside the container. Detailed steps for both approaches are provided, addressing potential access rights issues.
The blog post details an example implementation of a connection server using Shelly 3EM, IBM Cloud Cloudant, and Grafana. It aims to store historical data for visualizing electricity consumption. The project involves detailed architecture, environment setup, Python, FastAPI, Podman, and more usage. The setup covers Raspberry Pi, Podman Compose, and IBM Cloud Code Engine environments, with prerequisites and detailed configurations. The approach allows users to monitor and visualize power consumption efficiently and cost-effectively using Grafana.
This extract is from a bash automation script in the question-answering GitHub project. The bash script automates the deployment to IBM Cloud Code Engine. The extraction is about the building and pushing a container to the IBM Cloud Container Registry.
This blog post is about using the domain mapping functionality in IBM Cloud Code Engine to use custom domains and TLS certificates for your applications. The source code related to an example setup is in the GitHub project example WebApp build on Vue.js. But now we are going to use a wild card certificate for our domain *.example.com. With a TLS certificate for that domain.
This blog post is about using the IBM Watson Natural Language Processing Library for Embed on IBM Cloud Code Engine and is related to my blog post Run Watson NLP for Embed on your local computer with Docker. IBM Cloud Code Engine is a fully managed, serverless platform where you can run container images or batch jobs.
IBM Watson Assistant is a SaaS offering from IBM to build conversational assistants. IBM Watson Assistant is using artificial intelligence which helps to understand users in context, to provide them easy and fast, consistent, and accurate answers across various applications, devices, or channels. IBM Watson Assistant is built on natural language understanding (NLU), natural language processing (NLP) and machine learning (ML). The first version was already very good, and IBM clients and partners were starting to take these advantages; for example Watson Assistant was used at the International Space Station. Here you can find some more details: CIMON brings AI to the International Space Station. Based on the feedback from clients, the IBM development and design team has created a brand new experience and added new functionalities to the service for example they expanded the integration possibilities with extensions. In this blog post I focus especially on custom extensions development and setup.
This "blog post"/"cheat sheet" is about "Open the door for root users in OpenShift (example StatefulSet)". The topic is in context of two blog posts I wrote called Run a PostgreSQL container as a non-root user in OpenShift and Open the door for root users in Red Hat OpenShift¶.
This "blog post"/"cheat sheet" is about "Open the door for root users in OpenShift". The topic is in context of an older blog post I wrote called Run a PostgreSQL container as a non-root user in OpenShift. Let's look for the opposite perspective this blog post.
This cheat sheet is an extension to a blog post I made which is called: Configure a project in an IBM Cloud Red Hat OpenShift cluster to access the IBM Cloud Container Registry . In that related blog post we used the IBM Cloud Container registry to get the container images to run our example application. Now in this cheat sheet we will use the Red Hat OpenShift internal container registry and the Docker build strategy to deploy the same example application to OpenShift.
Thomas Suedbroecker's Blog 