Senior Principal Technical Marketing Manager
Daniel Oh
Daniel Oh works for Red Hat as Senior Principal Developer Advocate and is also in charge of the CNCF ambassador to encourage developers' participation in cloud-native app development at scale and speed. He's obviously specialized in cloud-native microservices and serverless development, Quarkus, DevOps & Agile practices, Microprofile, Open Hybrid Cloud, and Kubernetes across regions. He's been delivering technical seminars and workshops to elaborate on emerging technologies for developers & IT ops teams, and keep influencing them to enable this paradigm and technologies. He's been talking about rapidly changing emerging technologies at international conferences.
Daniel Oh's contributions
Article
Simplify Java persistence using Quarkus and Hibernate Reactive
Turn to Quarkus when you're using JPA to manage persistent objects in applications. The Hibernate ORM extension simplifies the persistent layer implementation.
Article
Visualize your Apache Kafka Streams using the Quarkus Dev UI
Learn how to use the Dev UI in Quarkus to visualize Apache Kafka Streams. Quarkus hooks into Kafka's API and lets you implement stream processing applications.
Article
Boost throughput with RESTEasy Reactive in Quarkus 2.2
Learn how to improve performance when developing reactive Java applications using the Red Hat build of Quarkus 2.2 and RESTEasy Reactive features.
Article
Deploy a Java application using Helm, Part 2
Get a step-by-step guide to using Helm charts for Red Hat JBoss Enterprise Application Platform to build a bootable JAR with enterprise capabilities.
Article
Deploy a Java application using Helm, Part 1
Learn a simpler way to deploy a Java application to Red Hat OpenShift using Helm charts, then connect the application to a PostgreSQL database.
Article
Learn Quarkus faster in the Developer Sandbox for Red Hat OpenShift
Accelerate your Quarkus skills with quick starts in the Developer Sandbox for Red Hat OpenShift. You'll spend less time configuring and more time building, testing, and deploying.
Article
Build even faster Quarkus applications with fast-jar
Try this quick exercise to see why applications packaged with fast-jar support faster startup times than those packaged with the legacy Quarkus JAR format.
Article
Enhancing the development loop with Quarkus remote development
Set up a new Quarkus project, then configure it for live coding on a remote Red Hat OpenShift cluster, just like you would in your local environment.
Simplify Java persistence using Quarkus and Hibernate Reactive
Turn to Quarkus when you're using JPA to manage persistent objects in applications. The Hibernate ORM extension simplifies the persistent layer implementation.
Visualize your Apache Kafka Streams using the Quarkus Dev UI
Learn how to use the Dev UI in Quarkus to visualize Apache Kafka Streams. Quarkus hooks into Kafka's API and lets you implement stream processing applications.
Boost throughput with RESTEasy Reactive in Quarkus 2.2
Learn how to improve performance when developing reactive Java applications using the Red Hat build of Quarkus 2.2 and RESTEasy Reactive features.
Deploy a Java application using Helm, Part 2
Get a step-by-step guide to using Helm charts for Red Hat JBoss Enterprise Application Platform to build a bootable JAR with enterprise capabilities.
Deploy a Java application using Helm, Part 1
Learn a simpler way to deploy a Java application to Red Hat OpenShift using Helm charts, then connect the application to a PostgreSQL database.
Learn Quarkus faster in the Developer Sandbox for Red Hat OpenShift
Accelerate your Quarkus skills with quick starts in the Developer Sandbox for Red Hat OpenShift. You'll spend less time configuring and more time building, testing, and deploying.
Build even faster Quarkus applications with fast-jar
Try this quick exercise to see why applications packaged with fast-jar support faster startup times than those packaged with the legacy Quarkus JAR format.
Enhancing the development loop with Quarkus remote development
Set up a new Quarkus project, then configure it for live coding on a remote Red Hat OpenShift cluster, just like you would in your local environment.
