Wei Hu
Kubernetes and Microservices with Multi-Model Databases
#1about 3 minutes
Understanding multi-model vs specialized database architectures
A converged database simplifies development by supporting multiple data types like JSON and graph within a single engine, avoiding the complexity of managing many specialized databases.
#2about 3 minutes
Oracle's approach to supporting Kubernetes deployments
Oracle provides container images and build tools for custom deployments and certifies its database on popular Kubernetes distributions like Red Hat OpenShift.
#3about 3 minutes
Achieving native database observability in Kubernetes
Database metrics and logs are made visible within Kubernetes by exporting them to open-source tools like Prometheus, Loki, and Grafana for unified monitoring.
#4about 5 minutes
Managing any Oracle database with a Kubernetes operator
The Oracle Kubernetes operator allows you to manage the lifecycle of databases using kubectl, whether they are running inside the cluster, on-premises, or in the cloud.
#5about 3 minutes
Enabling mission-critical transactions in Kubernetes
Oracle extends Kubernetes with native transaction management, supporting both strongly consistent (XA) and eventually consistent (Saga) patterns for reliable microservices.
#6about 5 minutes
Using a converged database for microservice architectures
Simplify microservice data management by using pluggable databases within a single converged instance, which provides isolation without the operational overhead of multiple database types.
#7about 5 minutes
Building reliable event-driven microservices with TEQ
Oracle's Transactional Event Queues (TEQ) provide a built-in, Kafka-like messaging system that guarantees transactional consistency between data changes and event publishing.
#8about 2 minutes
Getting started with hands-on Oracle cloud labs
Explore these concepts further by using free, hands-on workshops and labs available on the Oracle Cloud to see real code examples and implementations.
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