Daniel Hinojosa

GRAAL The Magnificent!

9:00 AM MDT

Graal is a VM and an awesome VM at that. Able to run a variety of languages and fast. The execution times can be impressive too. This VM can run anything, JavaScript, Python 3, Ruby, R, JVM-based languages like Java, Scala, Kotlin, and LLVM-based languages such as C and C++.

We are living in truly exciting times. So much interesting technology including the VM space. Graal is a virtual machine and shared memory system for multiple languages. GraalVM can either run standalone or embedded in OpenJDK or node.js. Graal can even embed inside databases such as MySQL or Oracle. In the presentation, we look at this exciting VM, how to start it, how to run polyglot applications, and how to integrate all within the same VM.

Quarkus

11:00 AM MDT

Graal has already proved to be an important advancement in Java. One such feature is AOT, Ahead of Time Compiling which takes JVM byte code and converts it as a native application as if it was written in C. This means a great deal for those who need to develop fast microservices with natively compiled speed.

This presentation will start with a quick introduction to Graal VM. Then jump into how to bootstrap and get started with Quarkus micro service. From there will discuss the standard set APIs, convert your application into a native image, and then containerize it for deployment.

Kafka Connect: Harnessing Data Stores

1:00 PM MDT

In this presentation, we will discuss Kafka Connect. Kafka Connect is an opensource project from Confluent. Kafka Connect provides us a way to move data from a data store as a source and stream or batch that information into Kafka. Kafka Connect also gives us a way to take information from Kafka and send that to another data store, a Sink. Every source and sink can be connected to and from various databases and message queues.

What this presentation will entail:

• A brief overview and review of Kafka
• The Architecture of Kafka Connect
• Where to find connectors
• Standalone vs Distributed
• Connecting a Source
• Creating Single Message Transforms
• Connecting a Sink

At the end of this presentation, we will have a live demonstration of watching a data pipeline using data stores.

Machine Learning Data Pipelines

3:00 PM MDT

This workshop builds an entire event driven data pipeline with Machine Learning and Kafka. From Kafka where we use producers or Kafka Connect to generate information, we then will Kafka Streams to apply a machine learning model to make business decisions.

This intensive lab will start by integrating sources into our backplane, then train our models, and operationalize our model using Kafka Streams. We will then create result topics when we can read in as a report and display visualizations of our data. The result will also be scalable and fault tolerant.

Machine Learning Data Pipelines

5:00 PM MDT

This workshop builds an entire event driven data pipeline with Machine Learning and Kafka. From Kafka where we use producers or Kafka Connect to generate information, we then will Kafka Streams to apply a machine learning model to make business decisions.

This intensive lab will start by integrating sources into our backplane, then train our models, and operationalize our model using Kafka Streams. We will then create result topics when we can read in as a report and display visualizations of our data. The result will also be scalable and fault tolerant.