Author: Paul Parkinson

As AI services and the data they consume and create become more important and prevalent in various applications and processes, so do the platforms and architectures they are built upon. As usual, there is no “one size fits all.” However, what is briefly presented here is an optimized approach to such data-driven AI application architectures. All of the source code mentioned and more can be found here and a free “Develop with Oracle AI and Database Services: Gen, Vision, Speech, Language, and OML” workshop (where all of the use cases are based on the U.N.’s 17 Sustainable Development Goals) giving many more examples can be found here.

Often multiple network calls must be made in a given AI app, entailing calls to the AI services as well as calls to retrieve and persist the content (whether it be text, audio, images, video, etc.) that is the input or output. The persistent information is then often processed and analyzed further, and additional calls, AI or otherwise, are made in reaction.

In this sixth article of the series, we describe and provide the full source for a mixed reality app that takes any visual and audio input from a user's surroundings, processes it with various AI, and returns output of summaries, results of generative AI, etc.

This is the sixth piece in a series on developing XR applications and experiences using Oracle and focuses on visual and audio input from a user's surroundings, processing it with various AI, and returning output of summaries, results of generative AI, etc. Find the links to the first five articles below: 

In this article, I will show you how to quickly create an entirely free app using a JavaScript program that runs within the free Oracle database and calls Hugging Face AI, the results of which are stored in the database and can then be accessed using SQL, JSON, REST, or any other language. All of the source code is available here.

A common flow of applications in general and AI applications specifically involves an app calling an AI service and then storing the information in the database where it may be retrieved and processed (e.g., using OML) further and/or analyzed and queried later.

Here, in just a few simple steps, we'll develop a mobile multiplayer game using Unity and Oracle's Backend for Parse.

A Brief Introduction of Unity and Parse Platform

Unity is a cross-platform game engine developed by Unity Technologies, first announced and released in June 2005 at Apple Worldwide Developers Conference as a Mac OS X game engine. The engine has since been gradually extended to support a variety of desktop, mobile, console, and virtual reality platforms. The Parse Platform is a back-end for mobile developers, open-sourced by Facebook/Meta in 2016, that helps to store data in the cloud, manage identity log-ins, handle push notifications, and run custom code in the cloud. Oracle has created an adapter to take advantage of all the features of the Oracle converged database while using Parse APIs.

The saga pattern is used to provide data integrity between multiple services and to do so for potentially long-running transactions. There are many, cursory as they tend to be, blogs written on sagas and long-running transactions. In this piece, I will not go into detail comparing the advantages and disadvantages of sagas with XA two-phase commit (2PC), distributed locking, etc., and will simply state that XA and 2PC require distributed locks (con) which manage ACID properties such that the user can simply execute rollback or commit (pro) whereas sagas use local transactions only and so do not require distributed locks (pro) but require the user to implement compensation, etc. logic (con). As Teddy Roosevelt said, “Nothing worth having comes easy.”

What I will do is show a full code example of a microservices application involving a saga, including participant compensation logic, which can be found at this repo.   

This is the fifth piece in a series on developing XR applications and experiences using Oracle and focuses on XR applications of healthcare, vision AI, training and collaboration, and messaging, including other topics such as multi-platform development, etc. Find the links to the first four articles below: 

Develop XR With Oracle, Ep 1: Spatial, AI/ML, Kubernetes, and OpenTelemetry
Develop XR With Oracle, Ep 2: Property Graphs and Data Visualization
Develop XR With Oracle, Ep 3: Computer Vision AI, and ML
Develop XR With Oracle, Ep 4: Digital Twins and Observability

This blog is written to give a succinct description and example of a modern full stack microservice app including a React front-end service that conducts GraphQL queries against a Spring Boot Data JPA back-end service that in turn maps to an Oracle database.

As such, I'll start right off with a link to the app source.

This is the fourth piece in a series on developing XR applications and experiences using Oracle and focuses on XR applications of computer vision AI and ML and its related use in the metaverse.  Find the links to the first three articles below: 

• Develop XR With Oracle, Ep 1: Spatial, AI/ML, Kubernetes, and OpenTelemetry
• Develop XR With Oracle, Ep 2: Property Graphs, Data Visualization, and Metaverse
• Develop XR With Oracle, Ep 3: Computer Vision AI, ML, and Metaverse

As with the previous posts, here I will again specifically show applications developed with Oracle database and cloud technologies, HoloLens 2, Mixed Reality Toolkit, and Unity platform.

This is the second in a series of blogs discussing unified observability with microservices and the Oracle database. The first piece went into the fundamentals and basic use cases. This second blog will take a deeper dive into the Metrics, Logs, and Tracing exporters (which can be found at https://github.com/oracle/oracle-db-appdev-monitoring), describing them and showing how to configure them, Grafana, alerts, etc.  I will also refer the reader to the latest version of the Unified Observability in Grafana Workshop that has just been published which demonstrates the principles, provides code and configuration examples, etc.  All of the code for the workshop can also be found at the https://github.com/oracle/microservices-datadriven repos (specifically in the observability directory). 

Particularly with the dawn of microservices, robust observability is an absolute requirement, and the better the tools and techniques used in the space, the more effective and enjoyable observability is for the (DevOps) user and thus the focus on this key area.

This article provides a quick tour of Oracle's Transactional Event Queues (TEQ) and so attempts to cover as much as possible at a high-level while giving quick, low-level, and code examples at the same time. There is quite a bit of material, and there are multiple workshops related to TEQ and its use in modern application development and microservices that can be found at the end of this piece.

This article corresponds to a 12-minute video that can be found here...

Oracle Transactional Event Queues (previously known as Advanced Queueing) has been around and widely used for decades (long before Kafka) and is well-harden technology. Here is a timeline to give an idea.