Oracle Backend for Microservices and AI
Oracle Backend for Microservices and AI allows developers to build microservices in Helidon and/or Spring Boot and provisions a “backend as a service” with Oracle Database and other infrastructure components that operate on multiple clouds. Oracle Backend for Microservices and AI vastly simplifies the task of building, testing, and operating microservices platforms for reliable, secure, and scalable enterprise applications.
Version 1.3.1 (production) released October, 2024Oracle Backend for Microservices and AI Version 1.3.0 is now generally available and suitable for production use. This version supports and recommends Helidon 4.1.1, Spring Boot 3.3.x, 3.2.x, Spring 6.1 and Spring Cloud 2023.0.x, with limited backwards compatibility for Spring Boot 2.7.x.
If you are building Spring Boot applications with Oracle Database, you should also check out Spring Cloud Oracle which is the home of a number of the components used in Oracle Backend for Microservices and AI, and which you can also use in your own applications!
Oracle Backend for Microservices and AI Version 1.3.1 introduces Oracle AI Microservices Sandbox as a Developer Preview feature.
The Oracle AI Microservices Sandbox provides a streamlined environment where developers and data scientists can explore the potential of Generative Artificial Intelligence (GenAI) combined with Retrieval-Augmented Generation (RAG) capabilities. By integrating Oracle Database 23ai AI Vector Search, the Sandbox enables users to enhance existing Large Language Models (LLMs) through RAG.
It provides a “sandbox” for experimentation and iteration, allowing you to easily optimize a chatbot/RAG use case by exploring different models, chunking strategies, vector similarity algorithms, prompts, model parameters, memory, re-ranking, and evaluation.
This feature is provided as a “developer preview” meaning it is provided for developers to experiment with, without any formal support, but with the expectation that it may become a formal feature in a future release. You may open issues in GitHub and best-effort assistance will be provided. Please be aware that this feature is under development, and not yet considered stable. Functionality, interfaces, etc., may change in non-backwards compatible ways.
For more information about this developer preview feature, please visit:
- the GitHub repo
- the documentation
- this OCI Cloud Coaching session titled Building a real chatbot with Oracle Database 23ai, (video) which includes discussion of the background concepts and a demonstration of this feature
To learn more about deploying and using Oracle Backend for Microservices and AI, we recommend our CloudBank AI self-paced, on-demand hands-on lab.
In the CloudBank AI hands-on lab, you can learn how to:
- Install Oracle Backend for Microservices and AI.
- Set up a development environment for Helidon and/or Spring Boot.
- Build Spring Boot microservices from scratch using Spring Web to create Representational State Transfer (REST) services.
- Use service discovery and client-side load balancing.
- Use Spring Actuator to allow monitoring of services.
- Create services that use asynchronous messaging with Java Message Service (JMS) instead of REST.
- Implement the Saga pattern to manage data consistency across microservices.
- Use the APISIX API Gateway to expose services to clients.
- Build a conversational chatbot using Spring AI and self-host LLMs with Ollama.
To learn more, watch this short introductory video:
In addition to an Oracle Autonomous Database Serverless instance, the following software components are deployed in an Oracle Cloud Infrastructure (OCI) Container Engine for Kubernetes cluster (OKE cluster):
- Apache APISIX API Gateway and Dashboard
- Apache Kafka
- Grafana
- HashiCorp Vault
- Jaeger
- Apache Kafka
- Loki
- Netflix Conductor
- OpenTelemetry Collector
- Oracle Autonomous Database Serverless
- Oracle Backend for Microservices and AI Command Line Interface (CLI)
- Oracle Backend for Microservices and AI Visual Studio Code Plugin
- Oracle Coherence
- Oracle Database Operator for Kubernetes (OraOperator or the operator)
- Oracle Database Observability Exporter
- Oracle Transaction Manager for Microservices (MicroTx)
- Prometheus
- Promtail
- Spring Boot Admin dashboard
- Spring Cloud Config server
- Spring Cloud Eureka service registry
- ServiceOps Center
- Strimzi Kafka Operator
Developers also have access to development or build time services and libraries including:
- A command-line interface (CLI) to manage service deployment and configuration, including database schema management.
- Visual Studio Code (VS Code) plugin to manage service deployment and configuration.
- IntelliJ plugin to manage service deployment and configuration.
- Spring CLI support for project creation.
- Spring Data (Java Persistence API (JPA) and Oracle JDBC) to access Oracle Database.
- Oracle Java Database Connectivity (Oracle JDBC) drivers.
- Spring Cloud Config client.
- Spring Eureka service discovery client.
- Spring Cloud OpenFeign.
- OpenTelemetry Collector (including automatic instrumentation).
- Spring Starters for Oracle Universal Connection Pool (UCP), Oracle Wallet, Oracle Advanced Queuing (AQ), and Transactional Event Queues (TxEventQ).
We’d love to hear from you! You can contact us in the #oracle-db-microservices channel in the Oracle Developers slack workspace, or open an issue in GitHub.