Unleashing the Power of Oracle Enterprise Manager Cloud Control for Oracle Exadata Cloud

Introduction: Understanding Oracle Enterprise Manager Cloud Control

Oracle Enterprise Manager Cloud Control is a comprehensive management solution that offers a unified and centralized approach to managing Oracle environments. Specifically designed for Oracle Exadata Cloud, this powerful tool empowers organizations to streamline operations, enhance performance, and optimize resources effectively.

Streamlined Management with Oracle Enterprise Manager Cloud Control

Centralized Monitoring and Administration

Oracle Enterprise Manager Cloud Control provides a centralized platform for monitoring and administering Oracle Exadata Cloud environments. With real-time insights into system performance, resource utilization, and application health, administrators gain full visibility and control over their infrastructure.

Proactive Performance Management

By leveraging advanced monitoring capabilities, Oracle Enterprise Manager Cloud Control enables proactive performance management. Administrators can identify potential issues, analyze trends, and take preemptive actions to ensure optimal performance and prevent downtime.

Automated Provisioning and Scaling

One of the key benefits of Oracle Enterprise Manager Cloud Control is its ability to automate provisioning and scaling tasks. With predefined templates and policies, administrators can effortlessly deploy new resources, scale capacity up or down as needed, and optimize resource utilization based on workload demands.

Enhanced Security and Compliance

Comprehensive Security Controls

Oracle Enterprise Manager Cloud Control offers a wide range of security controls to safeguard Oracle Exadata Cloud environments. From user authentication and access control to encryption and audit logging, administrators can enforce stringent security measures to protect sensitive data and ensure compliance with regulatory requirements.

Continuous Compliance Monitoring

With built-in compliance management features, Oracle Enterprise Manager Cloud Control enables continuous monitoring of regulatory compliance. Administrators can define and enforce compliance policies, conduct regular audits, and generate compliance reports to demonstrate adherence to industry standards and regulations.

Optimized Resource Management

Efficient Resource Allocation

Oracle Enterprise Manager Cloud Control optimizes resource management by providing tools for efficient allocation and utilization of resources. By analyzing workload patterns and performance metrics, administrators can allocate resources dynamically, optimize resource utilization, and eliminate resource bottlenecks.

Cost Optimization

By optimizing resource usage and improving operational efficiency, Oracle Enterprise Manager Cloud Control helps organizations minimize costs associated with Oracle Exadata Cloud deployment. Administrators can identify opportunities for cost savings, optimize licensing agreements, and streamline resource provisioning to achieve maximum ROI.

Conclusion: Empowering Organizations with Oracle Enterprise Manager Cloud Control

Oracle Enterprise Manager Cloud Control is a game-changing solution for organizations leveraging Oracle Exadata Cloud. From streamlined management and enhanced security to optimized resource utilization and cost savings, this powerful tool offers a comprehensive suite of features to empower organizations and drive business success.

Continue reading

Audit Active Data Guard with Data Safe in Oracle Cloud

We’re excited to announce that Oracle Data Safe can now monitor the database activity of Active Data Guard configurations for Oracle Database on Oracle Exadata Database Service on Dedicated Infrastructure (formerly known as Exadata Cloud Service) and Oracle Base Database Service (formerly known as Oracle Database Cloud Service).

Active Data Guard (ADG) is an evolution of Oracle Data Guard technology that incorporates significant innovation designed for a specific purpose - to offload work from the production database, freeing up resources for critical transactions. ADG enables read-only access to a physical standby database while redo application is active. Workloads such as reporting, analytics, backups, queries, and even occasional writes (a new ADG feature as of Oracle Database 19c) can be offloaded from the production system to a synchronized physical standby database. These workloads would otherwise consume valuable resources on the primary production site; therefore, ADG saves valuable CPU and I/O cycles and promotes efficient use of system resources in the configuration. Since ADG opens up standby databases for read/write workloads, most regulatory and compliance requirements emphasize the need to monitor the database activity on standby databases, though less rigorously compared to the primary production database.

Data Safe now provides a single pane of glass monitoring database activity for all the database peers in an ADG configuration (including the primary database and all the associated standby databases) without worrying about redundant audit record collection. A brief insight into the mechanism within Oracle Database auditing that enables the feature in Data Safe explains why this is important.

Unified audit records within the Oracle Database are written to a table in the AUDSYS schema called AUD$UNIFIED. When the database is not writable (typically occurs when the database is closed or is read-only as in ADG), the Oracle Database writes audit records to external operating system spillover .BIN files. The audit data of the spillover files is presented in the view GV$UNIFIED_AUDIT_TRAIL.

The view UNIFIED_AUDIT_TRAIL is a UNION ALL of the table AUDSYS.AUD$UNIFIED and the view GV$UNIFIED_AUDIT_TRAIL.

The capability to monitor audit records from standby databases is built into the UNIFIED_AUDIT_TRAIL since unified audit was introduced in Oracle Database 12c. However, because audit records from the primary database (written to the database table AUD$UNIFIED) are captured in redo and replicated to the standby, it was challenging to separate activity on the standby from activity on the primary. Oracle Database 19c Release Update 21 (19.21) introduced a new column, SOURCE, in UNIFIED_AUDIT_TRAIL, making it easy to differentiate the origin of audit records. That new column helps avoid redundant audit record collection from ADG.

Figure1: Unified audit trail with SOURCE column to differentiate the origin of audit records

Leveraging the SOURCE column value in the UNIFIED_AUDIT_TRAIL view enables Data Safe to monitor the entire ADG configuration with a single primary database and multiple standby databases as a single target with multiple unified audit trails. The primary database in the ADG (as identified by the system-generated failover connection string with role-based database service) has an audit trail to collect from the database table AUDSYS.AUD$UNIFIED by querying the  UNIFIED_AUDIT_TRAIL view with SOURCE set to DATABASE. Each database in the ADG will have an audit trail to collect from that database’s corresponding spillover files by querying the UNIFIED_AUDIT_TRAIL view with SOURCE set to FILE.

A sample monitoring configuration for an ADG with one primary and two standby databases is represented here.

Figure2: Database activity monitoring of ADG as a single target with multiple unified audit trails

Once you register the primary, along with any ADG peers, in Data Safe as a database target, the associated audit profile contains the details of the multiple audit trails discovered automatically from the metadata. The audit trails will have an indicator (FILE or TABLE) to identify the SOURCE of audit records, as shown here.

Figure3: Audit profile of the single ADG target with multiple unified audit trails in Data Safe

Collecting unified audit records in Data Safe commences once you start the corresponding audit trails, and audit reports show the ADG target's audit events from the primary and standby databases.

Sample login activity report of the ADG target is shown here with audit events from both primary and standby databases. The column database unique name lets you correlate activity to the specific database in the ADG target where the audit event was triggered.

Figure4: Audit report in Data Safe of the ADG target showing audit events from all the databases

In a nutshell, Data Safe provides a single pane of glass monitoring database activity for all the Oracle databases in ADG configuration as a single target with multiple unified audit trails.

Source: oracle.com

Continue reading

Oracle Analytics Cloud : Set up and configure Oracle Analytics Cloud environments using Terraform

Oracle Analytics Cloud (OAC) is a single and complete platform that empowers your entire organization to ask any question of any data, across any environment, on any device. It fits into your ecosystem, enabling analysis in the cloud while also providing easy access to any data source. The result? The best use of all your data, no matter where it is.  Oracle Analytics Cloud provides a variety of options for intelligent analysis without being overwhelming to deploy and manage, making it an effective way to engage more people in analysis and extend your organization’s expertise.

When you first deploy OAC, you have a choice: either you can provision and configure your OAC environment manually, or you can use Terraform to create and maintain your OAC environment. Terraform is an infrastructure-as-code tool that allows you to build, change, and version your infrastructure using code techniques. It will enable you to set up configuration files to define your applications or infrastructure and store your infrastructure's state to modify or update. You can use Terraform to create and maintain multiple OAC environments. Not only will it automate the manual steps of deployment, but it will also allow the consistent rollout of additional OAC instances as needed.

This blog uses OAC with a private end point as a sample architecture to describe how to create and setup these resources with Terraform. Based on your requirements, you can update the Terraform script to add or update network resources such as VCNs, subnets, routing tables, security lists, etc.

For the above architecture, you will perform the following tasks with Terraform:

• Setup OCI network resources for the OAC private endpoint (PE) environment.
• Create a VCN, a public subnet for the Bastion Host, and two separate private subnets for the database and OAC.
• Oracle Autonomous Database (ADB) will be provisioned with the given configuration.
• An OAC instance with a private access channel (PAC) will be provisioned with the provided configuration.
• PAC egress IPs will be configured in the security list of the database private subnet (to establish connectivity between OAC and ADB).
• A Bastion host will be setup to access private subnet resources, e.g., ADB and OAC, for maintenance purposes.( Bastion Host is a compute instance to access private network resources from an external network such as the Internet).
• The required routing and security rules will be configured so that the environment is ready to use.

Terraform Artifacts

These are the Terraform scripts that are provided in the "Deployment Scripts" section.

• Variable.tf — Terraform variable file which contains all variable definitions.
• Config.tf—Terraform Config file which contains all variable values. Variables are grouped into different categories, e.g., VCN, Subnet, ADB etc., and are self-explanatory. The sample values provided in the attached file are just an example.
• Deployment.tf — Terraform resource file for the OCI environment, which will set up all network resources (including VCN and subnets) and provision all PaaS components such as the Autonomous database, OAC, private access channel, and Bastion host. (For your reference, a Terraform resource for Oracle Database VM has also been provided as commented section in Deployment.tf).

How to Use these Terraform artifact

Prerequisites: Terraform should be installed on the machine where you are planning to execute these scripts.

• Make a directory on your machine where Terraform is installed.
• Copy Variable.tf, Config.tf, and Deployment.tf files into the directory.
• Provide all the values required in Config.tf for provider, VCN, subnets, and PaaS resources.
• Set resource_suffix_dev as “Dev” or “Test," as this will be used in all resource names, e.g., Dev_Public_Subnet. You can change it based on your naming specifications.
• Execute " terraform plan -var-file=config.tfvars"
• Execute " terraform apply -var-file=config.tfvars "

Execution of Terraform Script

Output: all network resources (VCN, Internet GW, Service GW, Nat GW, Subnets, Route Tables, Security Lists) and all PaaS components (OAC, PAC, ADB, and Bastion host) will be deployed for the OAC environment.

Test OAC Connectivity with Oracle Autonomous Database

Once the Terraform deployment completes, you can test the connectivity of OAC with your ADB instance. Please follow these steps to make OAC connection with ADB. 

◉ Log in to your OAC Instance.

◉ In the upper right corner, click the “Create” button and select Oracle Autonomous Data Warehouse Cloud.

◉ Enter the details as shown in the example by filling in the connection name, your username and password, and by uploading the ADB Wallet.zip file.

◉ Click Save.

◉ ( To download ADB wallet - 1. Navigate to Oracle Autonomous Database instance 2. click Database connection, 3. Under wallet type, make sure Instance Wallet is selected and then click Download wallet 4. Enter a wallet Password and click Download)

Download Terraform artifacts from Github

You can download Terraform Artifacts from this GitHub Repository.

OAC Terraform Artifacts

Source: oracle.com

Continue reading

Oracle Cloud Guard and Hybrid Tablespace Encryption

“There are two types of encryption: one that will prevent your sister from reading your diary and one that will prevent your government” – Bruce Schneier

What is Hybrid Tablespace Encryption? With the latest release updates of Oracle 19c (19.16 and above as 19.18 is the latest as of February 2023), it is now possible to decrypt redo operations in a hybrid cloud DR configurations where the cloud database is encrypted with TDE (Transparent Data Encryption) and the on-prem database is not.

We start seeing more often Oracle on-prem databases using Data Guard with the standby database being in the cloud, mostly in OCI. When the on-prem database is not using TDE and the cloud one is, it is important to ensure that redo data is encrypted during the transportation process. The Advanced Security Option places a key role here as this new feature is controlled via the (dynamic) TABLESPACE_ENCRYPTION initialization parameter.

V$PARAMETER_VALID_VALUES shows the accepted values of all database init.ora parameters, here is what we have for tablespace encryption (viewable even in ADB):

In a multitenant environment, remember that you need to change the value of TABLESPACE_ENCRYPTION in the root container. You cannot set TABLESPACE_ENCRYPTION in a PDB.

Here is how to set-up the encryption depending on (1) have/not have the Advanced Security Option and (2) how you would like to encrypt:

• AUTO_ENABLE is the default for cloud databases. It encrypts all new tablespaces if you have the Oracle Advanced Security license.
• If an existing tablespace is not encrypted, then the database writes a warning to the alert log.
• Encrypted tablespaces cannot be converted to unencrypted tablespaces.
• Because all tablespaces must be encrypted in OCI, setting TABLESPACE_ENCRYPTION to DECRYPT_ONLY or MANUAL_ENABLE will be ignored in the cloud and the database will behave as if the setting is AUTO_ENABLE.
• In the primary database, this setting encrypts the new tablespace with an encryption key.
• In a standby database, this setting adds a key to the new tablespace and encrypts all blocks.
• DECRYPT_ONLY prevents new tablespaces from being encrypted. Use it in your on-prem database in case you do not have the Advanced Security Option.
• If an existing tablespace is encrypted, then the database writes a warning to the alert log.
• Unencrypted tablespaces cannot be changed to encrypted tablespaces!
• MANUAL_ENABLE enables you to selectively encrypt tablespaces if the database is licensed for Oracle Advanced Security. This is the default for both on-prem primary and standby databases.

Note that (1) for RAC, set TABLESPACE_ENCRYPTION to the same value for all instances of the primary database, and for all instances of the standby database and (2) modifying TABLESPACE_ENCRYPTION does not affect the master key rotation operations.

On the second topic, Oracle Cloud Guard is useful when wanting to maintain good security posture by detecting weak security configurations and activities that can indicate cloud security risks. Cloud Guard detects security problems within a customer tenancy by ingesting audit and configuration data about resources in each region, processing it based on detector rules, and correlating the problems at the reporting region. Identified problems will be used to produce dashboards and metrics and may also trigger one or more provided responders to help resolve the problem.

Here are the key features of Oracle Cloud Guard:

• Detects misconfigured resources and identifies risky activities.
• Delivers out-of-the-box recipes that apply security best practices with a few clicks.
• Provides automated responders to trigger corrective actions.
• Gives a global view of customer’s overall security posture of their OCI tenancy, including security and risk scores and activity maps.

Enabling Cloud Guard is simple. The first step us to select/define the policies and then select some basis information:

And just click the “Enable” button.

Source: juliandontcheff.wordpress.com

Continue reading

Oracle Spatial Studio 22.1 now on Oracle Cloud Marketplace

Oracle Spatial Studio is a no-code web tool for accessing the spatial features of Oracle Database. The release of Oracle Spatial Studio 22.1 introduces a variety of valuable new capabilities as summarized here. The Oracle Cloud Marketplace has now been updated with this latest version for new deployments. Please find the listing here. The following walks you through the Marketplace deployment.

Before you begin

Review the prerequisites listed under Usage Instructions, namely 1) if your OCI user is not in the OCI Administrators group, then assign required policies and 2) create Secret(s) in OCI Vault to store passwords.

Once prerequsitises are complete you may Launch Stack to begin the stack wizard.

Enter Stack Information

You may leave defaults, or edit the stack name and description.

Click Next to continue.

Configure Variables

Compute Instance

Leave the default resource name prefix, or edit if desired. Select an Availability Domain and then Server Instance (Compute) Shape.

Note: You now have the option to deploy Spatial Studio to flexible shapes (”Flex shapes”) with the ability to customize the number of OCPUs and the amount of memory for your instance. You now also have the option to deploy to Arm-based compute, which has seen growing popularity for Cloud deployments. The minimun recommended Flex memory for Spatial Studio is 4GB.

Scroll down to continue.

Advanced Configuration

You may leave the default HTTPS port and Spatial Studio admin user name or edit if desired. As described in the prerequisites, you must select a Secret to use for the admin password.

Scroll down to continue.

Configure Networking

You may leave defaults for network configuration which creates new virtual network for the deployment. You may also select an existing virtual network.

Scroll down to continue.

Add SSH keys

Browse and select (or copy/paste) your SSH public key.

Scroll down to continue.

Configure Autonomous Database

On first startup, Oracle Spatial Studio requires connection to an Oracle Database for its metadata repository. The Oracle Spatial Studio deployment process on the Cloud Marketplace now provides the following options for metadata repository configuration:

1. Automatically create a new Oracle Autonomous Data Warehouse and configure Spatial Studio’s metadata repository. When deployment is complete you may log in to Spatial Studio and begin working immediately.

2. Automatically use an existing database and configure Spatial Studio’s metadata repository. When deployment is complete you may log in to Spatial Studio and begin working immediately.

3. Defer metadata repository until first login. When deployment is complete you will log in to Spatial Studio and be prompted to supply database connection info to generate Spatial Studio’s metadata repository.

Select your preferred strategy for Spatial Studio's metadata reopository connection. If creating a new Autonomous Data Warehouse or using an existing Autonomous Data Warehouse, you will need to select a Secret for the database user's password.

Click Next to continue.

Review

Review the summary of your stack configuration.

Scroll to the bottom and check Run Apply in order to automatically run the stack (i.e., perform the deployment) after you click Create..

Click Create to create and apply the stack.

Monitor progress

You will be navigated to the Job Details page for your stack Apply job. Log content will begin to appear after roughly 1 minute, and deployment will complete in roughly 5 minutes. When State shows Succeeded your job is done. If State shows Failed then the log will contain the cause, such as lack of resource quota in your account.

Scroll down to the bottom of the log for important details:

◉ URL to access your Spatial Studio instance (labelled instance_https_url)

◉ Links for those interested in configuring a HTTPS certificate and configuring Oracle IDCS as SSO provider

You may also click on the Application Information tab which provides a button to open your Spatial Studio instance aliong with other deployment info. As noted in Comments, wait 2-3 minutes after Apply job completion to access your Spatial Studio instance.

Access your Spatial Studio instance

After waiting 2-3 minutes following stack Apply job completion, click the button to Open Spatal Studio or navigate to the instance URL shown in the log. The deployment is pre-configured with a self-signed HTTPS certificate, so you will see a browser security warning. Accept and proceed to the site.

Log in using the Spatial Studio administrator user name (default is admin unless changed in the stack wizard) and password (password associated with the Secret used in the stack wizard).

Source: oracle.com

Continue reading

Develop XR With Oracle Ep 3: Computer Vision AI, ML, and Metaverse

This is the third 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.

The first piece can be found here and the second piece can be found here.

Again, I will specifically show applications developed with Oracle database and cloud technologies, HoloLens 2, Mixed Reality Toolkit, and Unity platform.

Throughout the blog, I will reference this corresponding demo video.

Extended Reality (XR), Metaverse, and HoloLens

I will refer the reader to the first piece in the series for an overview of XR and Hololens.

The first blog in this series was based on a data-driven microservices workshop and demonstrated a number of aspects that will be present in the metaverse, such as online shopping, by interacting with 3d models of food/products, 3d/spatial real-world maps, etc. as well as backend DevOps (Kubernetes and OpenTelemetry tracing), etc. 

The second blog was based on a number of graph workshops and demonstrated visualization, creation, and manipulation of models, notebooks, layouts, and highlights for property graph analysis used in social graphs, neural networks, and the financial sector (eg, money laundering detection).

In both of these blogs and in this third blog as well, the subject matter can be shared and actively collaborated up, even in real-time, remotely.  These types of abilities are key to the metaverse concept and will be expanded upon and extended to concepts such as digital doubles in these future pieces. 

This blog will not go into computer vision AI in-depth and will instead focus on the XR-enablement of it and Oracle database and cloud.

Capabilities and Possibilities of Computer Vision with XR

Computer vision AI provides a number of capabilities including image classification, object detection, text detection, and document AI.  

I predominantly use the Hololens to demonstrate concepts in this series as it is the technology closest to what will be the most common and everyday usage of XR in the future, however, the concepts I show in these blogs can be applied to one extent or another in different flavors of XR and devices (and indeed I will be giving examples of such in future blogs).

One thing that most, if not all, of these devices, have in common is a visual interface (ie computer and camera) between the user and the real world. Inherently this has the capability of capturing and processing the visual stimuli surrounding the user and so the link between it and Computer Vision AI is a logical and synergistic one.

This is also true of AI audio and speech which I will also be demonstrating in a future piece.

Image classification and object detection

Imagine the potential to help those with vision impairment, Alzheimer’s, ... by having the XR device give contextual audio and visual feedback about one's surroundings.

 

The first part of the video shows object detection applied to XR. These are the steps involved...

1. A picture of the user's current view is taken by the Hololens (I use an explicit button for this but of course, it could be done automatically, periodically, in reaction to voice command, etc.).

2. This image is automatically uploaded to Oracle object store and database for further analysis. This in and of itself is a handy feature for storing data retrieved from the users' surroundings without the user needing to explicitly instruct it to or even be aware of the various contextual, etc. information being gathered.  

3. The image is then processed by the Vision AI service and a JSON response containing the name, confidence, bondingPolygon normalizedVertices, categorization, etc. is returned to the Hololens.  This is what the image processing and JSON response sent to the Hololens look like in the Oracle cloud console...

4. The Hololens app then processes this JSON, using the vertices/coordinates to recreate the polygons/rectangles and labels. 

5. The location of the user (ie the Hololens headset camera) was saved when the initial picture was taken and a raycast is made from that point, through the coordinates of the 2d rectangles, and onto the  3d spatial surface mesh of the room. (Note the 2d representation is only shown in the demonstration to illustrate the routine described and likely in an actual app, only the end result of the spatially mapped cubes would exist.)

6. 3d cubes are then created at the intersection points of these raycasts on the surface mesh.

7. In addition, once created, the labels are fed to a speech-to-text program that speaks the object's name.  This audio is also 3d spatially mapped.  

8. This provides an extremely efficient and fast technique as a single 2d image is used to map the enter view visually and audibly in 3d and this mapping persists in the exact same locations beyond restarts of the Hololens/app.  (The accuracy and so forth could of course be enhanced further with multiple takes/pics, and captured automatically without the user needing to push a button, etc.)

Imagine the potential to assist with vision impairment, Alzheimer’s, identification of unknown and difficult to isolate items, analysis of threats, interests, etc. by having the XR device give contextual audio and visual feedback about one's surroundings!

This information/representation can in turn be shared in the metaverse across any number of different XR devices (that includes basic phones and simple computer monitors) to facilitate digital doubles, collaboration, etc. in a very efficient and lightweight manner that simultaneously takes advantage of the powerful capabilities of the Oracle database and/in cloud.

Document AI

Imagine using XR and AI to enhance social interactions and engage in more meaningful conversations IN REAL LIFE.

The second part of the video shows the use of the document AI service, again with the Hololens camera capture technique used in the first part of the video, except this time text from the picture (with varying orientation, distance, etc.) is identified. Again this can be used for helping the user read, etc. as in the object detection example, and can also be fed into the Oracle database's powerful ML capabilities to run processing against any number of models, notebooks, etc. In this case, I scan books. This is a shot of that picture with the text processed, in the OCI console.

We could, as I did in the first blog, use this to make suggestions as far as other books that are related or, as I did in the second blog, do some graph analysis to find correlations and commonalities.  In this particular example, however, I have fed the text to a number of  GPT-3 conversation models which then feedback a conversational response. This response, or again any information from various models, can be given to the user to, eg, strike up a conversation with the owner of the books.

This of course is not limited to books or conversations.  The possibilities really are endless as far as the use of this combination of XR and providing the user with information and analysis about the environment they are in (something Oracle tech enables perfectly). 

I can also imagine the user advertising or "wearing" information about themselves the same way they wear clothes, etc. but in a potentially more complex, conveying fashion (meaning "fashion" in both senses of the word and meaning "senses" in both definitions of that word).  The metaverse is full of talk of companies finding new ways to advertise and interactions in a virtual world.  Users should be at least as empowered to express themselves and to do so in the real world.

Source: oracle.com

Continue reading

Develop XR with Oracle Cloud, Database on HoloLens, Ep 2: Property Graphs, Data Visualization, and Metaverse

This is the second piece in a series on developing XR applications and experiences using Oracle.

The first piece can be found here

Again I will specifically show applications developed with Oracle database and cloud technologies, Hololens 2 (Microsoft Mixed Reality Headset), MRTK (Mixed Reality Toolkit) APIs (v2.7.2), and Unity (v2021.1.20f) platform.

Read More: Develop XR with Oracle Cloud, Database on HoloLens, Ep 1: Spatial, AI/ML, Kubernetes, and OpenTelemetry

Throughout the blog, I will reference a corresponding demo video found here 

Extended Reality (XR), Metaverse, and HoloLens

I will refer the reader to the first piece in the series for an overview of XR and Hololens.

The first blog in this series was based on a data-driven microservices workshop and described a number of aspects that will be present in the metaverse such as online shopping, DevOps, etc. and I will continue to delve into these areas in this series. One area in particular that I will focus more and more on is collaboration. The graphs in this workshop including models, notebooks, etc. can all be shared and actively collaborated up, even in real-time, remotely. These types of abilities will be expanded upon and extended to concepts such as digital doubles, etc. in these future pieces. 

This blog will not go into property graph concepts deeply and will instead focus on the XR-enablement of them using examples in existing graph workshops.

Basics of creating property graphs

There are essentially four parts or stages to (visual) graph analysis... the actual data, the relationships and graph modeling of that data, notebooks written (in PGQL, eg) for analysis, and visualization of the notebook output in various layouts and highlights. 

The creation of a property graph model from existing tables looks like this...

Forced graph layout and community detection

The following force graph layout shows community detection (specifically strongly connected components and the Kosaraj algorithm for community detection in the case)... 

The following is an XR Hololens representation of the same where vertex and edge labels are shown as well as the directional relationship of those edges and objects all of which can be manipulated via GGV (gaze, gesture, and voice).

Concentric graph layout with rotation and movement

There are numerous types of layouts, each with its own customization settings, tailored for viewing different aspects from different vantage points. Here we see a Concentric layout.

The following is an XR Hololens representation of the same. As with all of the XR representations discussed, it is possible to manipulate and analyze the graph visualizations through GGV, however, in this case, I have also added rotation and movement to the final visual representation in order to provide multiple angles and position the graph in a way as best suited to analysis as possible. I've also added spatial audio in this case just for fun though I will be exploring it as an additional tool for analysis and detection as well

Visual Data and Graph Modeling

Finally, the video shows a concept for visual data and graph modeling where data sources (in this case basic tables but not limited to such) are represented as objects (cubes) that can be dropped on a common platform/dock. This action results in processing on the Oracle database side to create a graph model, correlations, commonalities, etc., and produce as output other objects that can, in turn, be studied and used in further combinations and analysis.

Additional Thoughts

The use cases for properties graphs are literally endless and I have only scratched the service of how they can be visualized in XR. I look forward to putting out more blogs on this topic and other areas of XR with Oracle Cloud, Database soon.

Source: oracle.com

Continue reading

Develop XR with Oracle Cloud, Database on HoloLens, Ep 1: Spatial, AI/ML, Kubernetes, and OpenTelemetry

This is the first piece in a series on developing XR applications and experiences using Oracle. Specifically, I will show applications running with the following:

◉ Oracle database and cloud technologies

◉ Hololens 2 (Microsoft Mixed Reality Headset)

◉ MRTK (Mixed Reality Toolkit) APIs (v2.7.2)

◉ Unity (v2021.1.20f) platform (leading software for creating and operating interactive, real-time 3D content)

Throughout the blog, I will reference a corresponding video found at https://youtu.be/MBaQ8ohI80E.

Extended Reality (XR) and HoloLens

XR (extended reality) is the umbrella term for VR, AR, and MR. The fourth evolution, metaverse (omniverse, etc.), or mesh, essentially refers to one extent or another and the inevitable integration of XR into the everyday, analogous to how smartphones are today.

While the concepts shown can be applied to one extent or another in different flavors of XR and devices, the focus is on what will be the most common and everyday usage of XR in the future: the eventual existence of XR glasses. This being the case, the HoloLens is used for developing and demonstrating, as it is the most advanced technology that exists currently to that end. The HoloLens presents holograms and sounds spatially to the wearer/user who can interact with them via hands, speech, and eye gaze. There is much more to the HoloLens than this basic definition, of course, and much more ahead in this space in general.

The XR Hololens application(s) is developed using the MRTK, which provides an extensive array of APIs that are portable across devices. This is of course to a varying degree depending on the nature and capability of the device but, is in line with Apple ARKit, Google ARCore, etc. It is also forward-looking such that it will be applicable to future devices (glasses, etc.) from other vendors such as Apple and others.

Demonstrations

I will start the series by demonstrating an XR version of a popular Oracle LiveLabs workshop “Simplify Microservices with converged Oracle Database." It demonstrates a number of different areas of modern app dev, as well as DevSecOps, including Kubernetes, microservices and related data patterns, Spatial, Maps, AI/ML/OML, Observability (in particular tracing), basic Graph, etc.

Future installments of this series will continue to give examples and explain XR-enablement of Oracle Database functionality such as Graph, IoT, Event Mesh, Sagas, ML, Unified Observability, Chaos testing, and more. Additionally, future installments will address industry use cases as well as Oracle AI cloud offerings such as computer vision, speech recognition, and text semantics that work in tandem with the database. At the same time, I will show more aspects and use cases of XR/MR with these services.

Video 1: “GrabDish” (Online Store/Food Delivery) Frontend

The microservices workshop and the XR version of it use a “GrabDish” food delivery service application to show the concepts mentioned. 

The video and this blog are broken into two demos: I will list the Oracle technologies used, followed by the MRTK/Hololens that use them. Unity is the development tool that brings these two together (Unreal Engine is an alternative).

◉ Food options (sushi, burger, pizza) are shown as 3d images. These images are loaded from the cloud object store via the Oracle database that fronts them.

◉ Users can select all objects with either hand, voice/speech, or eye-gaze (simply by staring at it).

◉ Users can then bring the object closer to them by making a hand gesture or saying "come to me" and once the image is close can rotate it by simply staring at one side or another, or can grab it and move it in this way.

◉ Once the food is selected, a suggestive sale for a drink is generated via AI/ML/OML (in the original workshop this is a food and wine pairing and in the XR version this is a tea pairing for the sushi selected).

◉ "Dwell" refers to a prolonged eye-gaze at a particular location. This is demonstrated when the user dwells their eye-gaze on a tea, and as a result, hears the name of the tea spoken. This audio is also retrieved via the database.

◉ The items selected for the order are placed on a new MRTK resource called a dock. This is a very useful construct (serving a container and categorization mechanism) that allows a number of items to be placed on it and resized such that all fit. 

◉ A dwell button with volumetric UI is then selected to place the order. The order is inserted into the Oracle database in JSON format and the appropriate inventory is reduced using relational SQL. This demonstrates two of the many data types supported by the Oracle converged database.

◉ Another data model supported in the database is spatial. This is demonstrated when the "Deliver Order" button is selected. The restaurant and delivery addresses (in this case, Rittenhouse Square in Philadelphia) are sent to the Oracle spatial cloud service backed by the Oracle database where a routing API is used to GeoCode the driving path between the two addresses and return the result as GeoJSON. This is then fed to the Map API (Google, BingMaps, Mapbox, etc.), where it is plotted on a 3D map. A car follows this ray trace between points in the 3D map in the HoloLens. Again, this map can be manipulated via hand, speech, and eye-gaze.

◉ These data types can be accessed in the Oracle database via any number of languages and also via REST endpoints.

Video 2: "GrabDish" DevOps (Kubernetes, Health Probes, Tracing/OpenTelemetry, etc.)

◉ A 3D visual representation of a live Kubernetes cluster and its related resources including namespaces, deployments, pods (fronted/dispatch to by services), etc. is shown in the same hierarchical relationship as the in Kubernetes, and resources/objects can be grabbed, rotated, moved, and scaled, etc. in a relational and proportionate manner. 

◉ The tags for these resources re-orient themselves so that they are always facing the user. Because the HoloLens is constantly spatially mapping the mesh of the environment, the placement of the objects remains consistent even across restarts. This can, of course, be extended to incorporate remote and GPS aspects and the mesh can be shared for digital double, remote placement (eg advanced remote assist, etc.) use cases.

◉ Each pod has a menu with various options/actions, including the ability to select and view that pod’s logs. The logs can be read either by scrolling with the hand or by simply reading them as eye-tracking is used to scroll and advance the page.

◉ The original workshop is opened in a browser in order to set the health advertised by the Order service to "down". This is done to trigger the Kubernetes health probes to restart the service. This is reflected in the XR application by the pod turning red in color and an audible alert about the health status. The sound is also spatially mapped. The source is the pod object so that if the pod is across the room, the sound comes from across the room.

◉ Visual tracing is then demonstrated by placing an order. OpenTracing/OpenTelemetry is used to trace the flow of information through this system. This is translated and mapped to the visual representation of the Kubernetes objects and database involved. Specific order and saga tags are selected in order to identify and particular trace and these labels can be visually observed flowing through the graph of nodes. This of course has greater potential in graph analytics.

Source: oracle.com

Continue reading