--- title: RheoData Blog (6) description: RheoData Blog Posts (6) --- [![RheoData - Logo - transparent-1](https://rheodata.com/hs-fs/hubfs/RheoData%20-%20Logo%20-%20transparent-1.png?width=250&height=50&name=RheoData%20-%20Logo%20-%20transparent-1.png "RheoData - Logo - transparent-1")](https://rheodata.com/) - Who We Are - [About Us](https://rheodata.com/who-we-are) - Services - Consulting - [The Studio](https://rheodata.com/the-studio) - Accelerators - [FrostCore](https://rheodata.com/frostcore) - [FrostAI](https://rheodata.com/frostai) - [RedCore](https://rheodata.com/redcore) - [RedAI](https://rheodata.com/redai) - [RedGuard](https://rheodata.com/redguard) - [BlueCore](https://rheodata.com/bluecore) - [Calypso](https://rheodata.com/calypso) - Services - [Data Integration](https://rheodata.com/data-integration) - [Analytics](https://rheodata.com/data-analytics) - [Multi-Cloud](https://rheodata.com/multi-cloud) - [Oracle@Google Cloud](https://rheodata.com/oracle-google-cloud) - [Exadata & Oracle Database](https://rheodata.com/exadata-and-oracle-database-26ai) - Verticals - [Manufacturing](https://rheodata.com/manufacturing) - [Retail](https://rheodata.com/retail) - [State & Local](https://rheodata.com/sled) - [Customer Stories](https://rheodata.com/customer-stories) - [Altec](https://rheodata.com/customer-stories/altec-oci-goldengate-data-migration) - [Shoe Carnival](https://rheodata.com/customer-stories/shoe-carnival-goldengate-microservices-migration) - [Icon](https://rheodata.com/customer-stories/icon-transatlantic-replication) - [Inovalon](https://rheodata.com/customer-stories/inovalon-data-pipeline-automation) - Resources - [Blog](https://rheodata.com/en-us/blog) - Books - [Pro Oracle GoldenGate 23ai](https://rheodata.com/pro-oracle-goldengate-23ai-for-the-dba-pdf-landing-page) - [Contact](https://rheodata.com/contact) 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[Analytics](https://rheodata.com/data-analytics) - [Multi-Cloud](https://rheodata.com/multi-cloud) - [Oracle@Google Cloud](https://rheodata.com/oracle-google-cloud) - [Exadata & Oracle Database](https://rheodata.com/exadata-and-oracle-database-26ai) - Verticals - [Manufacturing](https://rheodata.com/manufacturing) - [Retail](https://rheodata.com/retail) - [State & Local](https://rheodata.com/sled) - [Customer Stories](https://rheodata.com/customer-stories) - [Altec](https://rheodata.com/customer-stories/altec-oci-goldengate-data-migration) - [Shoe Carnival](https://rheodata.com/customer-stories/shoe-carnival-goldengate-microservices-migration) - [Icon](https://rheodata.com/customer-stories/icon-transatlantic-replication) - [Inovalon](https://rheodata.com/customer-stories/inovalon-data-pipeline-automation) - Resources - [Blog](https://rheodata.com/en-us/blog) - Books - [Pro Oracle GoldenGate 23ai](https://rheodata.com/pro-oracle-goldengate-23ai-for-the-dba-pdf-landing-page) - [Contact](https://rheodata.com/contact) [![](https://rheodata.com/hs-fs/hubfs/Imported_Blog_Media/blog-feature-Logo-Nov-26-2025-07-14-39-7226-PM.png?width=100&height=100&name=blog-feature-Logo-Nov-26-2025-07-14-39-7226-PM.png)](https://rheodata.com/) - Who We Are - [About Us](https://rheodata.com/who-we-are) - Services - Consulting - [The Studio](https://rheodata.com/the-studio) - Accelerators - [FrostCore](https://rheodata.com/frostcore) - [FrostAI](https://rheodata.com/frostai) - [RedCore](https://rheodata.com/redcore) - [RedAI](https://rheodata.com/redai) - [RedGuard](https://rheodata.com/redguard) - [BlueCore](https://rheodata.com/bluecore) - [Calypso](https://rheodata.com/calypso) - Services - [Data Integration](https://rheodata.com/data-integration) - [Analytics](https://rheodata.com/data-analytics) - [Multi-Cloud](https://rheodata.com/multi-cloud) - [Oracle@Google Cloud](https://rheodata.com/oracle-google-cloud) - [Exadata & Oracle Database](https://rheodata.com/exadata-and-oracle-database-26ai) - Verticals - [Manufacturing](https://rheodata.com/manufacturing) - [Retail](https://rheodata.com/retail) - [State & Local](https://rheodata.com/sled) - [Customer Stories](https://rheodata.com/customer-stories) - [Altec](https://rheodata.com/customer-stories/altec-oci-goldengate-data-migration) - [Shoe Carnival](https://rheodata.com/customer-stories/shoe-carnival-goldengate-microservices-migration) - [Icon](https://rheodata.com/customer-stories/icon-transatlantic-replication) - [Inovalon](https://rheodata.com/customer-stories/inovalon-data-pipeline-automation) - Resources - [Blog](https://rheodata.com/en-us/blog) - Books - [Pro Oracle GoldenGate 23ai](https://rheodata.com/pro-oracle-goldengate-23ai-for-the-dba-pdf-landing-page) - [Contact](https://rheodata.com/contact) # RheoData Blog ### Browse By: Everything Cloud GoldenGate Business Insights AI 19c ai pipelines 18c 21c 12c machine learning 23ai database goldengate 21c 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replication lag detection GoldenGate response file GoldenGate trail file management GoldenGate troubleshooting solutions GoldenGate unified console GoldenGateMCP Google Cloud Platform Google Cloud Storage Google-AlloyDB HashiCorp Hybrid queries Oracle IT cost optimization IT infrastructure simplification IT leadership mental health Initial Load Inventory management data lag LLM inference optimization Large language model performance MCP Server for Oracle MCP Server, Mental Health Awareness Month tech industry Migration readiness Model Context Protocol Model inference costs OMA assessment ONNX embedding model Oracle Operating Model Oracle 23ai features Oracle 26ai features Oracle AI Data Platform Oracle AI Solutions Oracle Autonomous Database migration Oracle CPAT vs OMA comparison Oracle Database 23ai vectors Oracle Database 26ai vectors Oracle EBS migration Oracle Exadata on Google Cloud This is a search field with an auto-suggest feature attached. - There are no suggestions because the search field is empty. ## [Identifying Predefined Administrative Accounts in Autonomous Database or any other Oracle database](https://rheodata.com/en-us/blog/identifying-predefined-administrative-accounts-in-autonomous-database-or-any-other-oracle-database) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:08 PM A quick post as a reminder for myself some time down the road. After all, we all need reminders... [CONTINUE READING](https://rheodata.com/en-us/blog/identifying-predefined-administrative-accounts-in-autonomous-database-or-any-other-oracle-database) ## [Installing Oracle GoldenGate Monitor Agent 12.2.1.2 – Silent](https://rheodata.com/en-us/blog/installing-oracle-goldengate-monitor-agent-12-2-1-2-silent) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:07 PM This post is mostly for anyone at RheoData to use get a sense of how the Oracle GoldenGate Monitor... [CONTINUE READING](https://rheodata.com/en-us/blog/installing-oracle-goldengate-monitor-agent-12-2-1-2-silent) ## [Configure Oracle GoldenGate’s ServiceManager as a Linux Service](https://rheodata.com/en-us/blog/configure-oracle-goldengates-servicemanager-as-a-linux-service) Posted by [rheostage5132](https://rheodata.com/en-us/blog/author/rheostage5132) | Nov 10, 2025 9:30:06 PM After installing Oracle GoldenGate with a manual ServiceManager, you realize that the... [CONTINUE READING](https://rheodata.com/en-us/blog/configure-oracle-goldengates-servicemanager-as-a-linux-service) ## [Building a Data Governance Framework](https://rheodata.com/en-us/blog/build-data-governance-framework) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:06 PM # Building a Data Governance Framework Data governance is crucial for any organization looking to... [CONTINUE READING](https://rheodata.com/en-us/blog/build-data-governance-framework) ## [Installing Nginx on AWS EC2 instance](https://rheodata.com/en-us/blog/installing-nginx-on-aws-ec2-instance) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:05 PM I’ve been helping clients with Oracle GoldenGate (Microservices) implementation – one thing that... [CONTINUE READING](https://rheodata.com/en-us/blog/installing-nginx-on-aws-ec2-instance) ## [Transforming Oracle GoldenGate Operations with AI: Building MCP Servers for Real-World Impact](https://rheodata.com/en-us/blog/transforming-oracle-goldengate-operations-with-ai-mcp-servers) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:04 PM Remember when everyone said the cloud was just a fad? We’re hearing similar skepticism about AI in... [CONTINUE READING](https://rheodata.com/en-us/blog/transforming-oracle-goldengate-operations-with-ai-mcp-servers) ## [Add a deployment to Oracle GoldenGate 19c Microservices](https://rheodata.com/en-us/blog/add-a-deployment-to-oracle-goldengate-19c-microservices) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:03 PM Once you have an up and running Oracle GoldenGate Microservices environment, there may come a time... [CONTINUE READING](https://rheodata.com/en-us/blog/add-a-deployment-to-oracle-goldengate-19c-microservices) ## [Oracle’s Vector Datatype](https://rheodata.com/en-us/blog/vector-datatype) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:03 PM At Oracle Cloud World 2023, Oracle announced they were moving toward enabling Artificial... [CONTINUE READING](https://rheodata.com/en-us/blog/vector-datatype) ## [GoldenGate Parameter Files – Format and Logic](https://rheodata.com/en-us/blog/goldengate-parameter-files-format-and-logic) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:02 PM As we have done multiple engagements with Oracle GoldenGate and helped clients get the most out of... [CONTINUE READING](https://rheodata.com/en-us/blog/goldengate-parameter-files-format-and-logic) ## [Configuring Nginx on AWS EC2 for Oracle GoldenGate 21c](https://rheodata.com/en-us/blog/configuring-nginx-on-aws-ec2-for-oracle-goldengate-21c) Posted by [Bobby Curtis](https://rheodata.com/en-us/blog/author/bobby-curtis) | Nov 10, 2025 9:30:01 PM When installed, Oracle GoldenGat (Microservices) will set up “services” that require a port number... [CONTINUE READING](https://rheodata.com/en-us/blog/configuring-nginx-on-aws-ec2-for-oracle-goldengate-21c) ### Recent Posts #### [Coordinated Replicats: Faster, Lower-Risk GoldenGate Loads](https://rheodata.com/en-us/blog/coordinated-replicats-initial-load) Posted at Jun 26, 2026 11:08:13 AM ![Post Featured Image](https://rheodata.com/hubfs/Gemini_Generated_Image_509fjc509fjc509f.png) #### [Forward Deployed Engineering: The Operating Model the Agentic Era Demands](https://rheodata.com/en-us/blog/forward-deployed-engineering-agentic-era) Posted at May 30, 2026 11:46:34 AM ![Post Featured Image](https://rheodata.com/hubfs/Gemini_Generated_Image_r8vpntr8vpntr8vp.png) #### [The Bowl Is Broken: A CEO's Note on Mental Health Month and Tech Team Burnout](https://rheodata.com/en-us/blog/tech-team-burnout-mental-health-month-2026) Posted at May 12, 2026 7:23:33 AM ![Post Featured Image](https://rheodata.com/hubfs/IMG_2142.jpg) ### Posts by Tag - [Cloud (88)](https://rheodata.com/en-us/blog/tag/cloud) - 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[vector database consolidation (1)](https://rheodata.com/en-us/blog/tag/vector-database-consolidation) See all - - [4](https://rheodata.com/en-us/blog/page/4) - [5](https://rheodata.com/en-us/blog/page/5) - [6](https://rheodata.com/en-us/blog/page/6) - [7](https://rheodata.com/en-us/blog/page/7) - [8](https://rheodata.com/en-us/blog/page/8) - ##### About RheoData RheoData is based out of Metro Atlanta, GA and provide expert Oracle, Microsoft, Google, and Snowflake services.  Let us  know how we can help! ##### Links - [About Us](https://rheodata.com/who-we-are) - [FrostCore](https://rheodata.com/frostcore) - [RedCore](https://rheodata.com/redcore) - [BlueCore](https://rheodata.com/bluecore) ##### Contact us [hello@rheodata.com](mailto:hello@rheodata.com) ©RheoData2026. All Rights Reserved. ```json { "@context" : "https://schema.org", "@type" : "Organization", "address" : { "@type" : "PostalAddress", "addressCountry" : "US", "addressRegion" : "GA" }, "description" : "Elite specialist partner for Oracle, Snowflake, BigQuery, and AI-ready data platforms.", "email" : "hello@rheodata.com", "foundingDate" : "2020", "logo" : "https://rheodata.com/hubfs/RheoData%20-%20Logo%20-%20transparent-1.png", "name" : "RheoData", "sameAs" : [ "https://www.linkedin.com/company/rheodata" ], "url" : "https://rheodata.com" } ``` ```json { "@context" : "https://schema.org", "@type" : "WebSite", "name" : "RheoData", "potentialAction" : { "@type" : "SearchAction", "query-input" : "required name=search_term_string", "target" : "https://rheodata.com/search?q={search_term_string}" }, "url" : "https://rheodata.com" } ``` ```json { "@context" : "https://schema.org", "@type" : "BlogPosting", "author" : { "@type" : "Person", "name" : "", "url" : "" }, "dateModified" : "2026-04-17T17:31:04+0000", "datePublished" : "2025-10-30T17:41:53+0000", "description" : "RheoData Blog Posts (6)", "headline" : "<span id="hs_cos_wrapper_name" class="hs_cos_wrapper hs_cos_wrapper_meta_field hs_cos_wrapper_type_text" style="" data-hs-cos-general-type="meta_field" data-hs-cos-type="text" >rheodata_blog listing page</span>", "image" : "", "mainEntityOfPage" : { "@id" : "https://rheodata.com/en-us/blog/page/6", "@type" : "WebPage" }, "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://rheodata.com/hubfs/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "A quick post as a reminder for myself some time down the road. After all, we all need reminders every once in a while! Prior to Oracle Database 12c finding a list of default users within the database was always a pain. In Oracle Database 12c or later, this has become much simpler. Oracle introduced a column on the *_users views that allows the end users to identify what users are maintained by Oracle. This column name is ORACLE_MAINTAINED. The value of the column is either “N” or “Y”. If it is “Y”, then user account is maintained by Oracle. A simple query of the ALL_USERS view will return about 57 different accounts that are maintained by Oracle in Oracle Database 19c (Autonomous Data Warehouse). select * from all_users where oracle_maintained = 'Y' order by username; For more information, the Oracle Database 19c docs can be referenced here.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Identifying Predefined Administrative Accounts in Autonomous Database or any other Oracle database", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/identify_predefined_accounts-1024x638-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/identifying-predefined-administrative-accounts-in-autonomous-database-or-any-other-oracle-database", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "This post is mostly for anyone at RheoData to use get a sense of how the Oracle GoldenGate Monitor Agent needs to be installed. The approach taken is to ensure that it is installed via the -silent process making it easier to install when looking at CI/CD processes and needing to get the agent installed quickly. This post is also intended to be high-level notes for myself for me to look at later if needed. The steps to get Oracle GoldenGate Monitor Agent installed are as follows: 1. Download the Oracle GoldenGate Monitor Agent from OTN (here) 2. Unzip the downloaded zip file in a directory that is easily accessed. $ cd /tmp $ unzip fmw_12.2.1.2.0_ogg_Disk1_1of1.zip -d ./gg_mon 3. Create a response file and add needed information $ cd /tmp/gg_mon $ touch gg_mon.rsp [oracle@rtlvedgo04 gg_agent]$ cat gg_mon.rsp #DO NOT CHANGE THIS. Response File Version=1.0.0.0.0 [GENERIC] #The oracle home location. This can be an existing Oracle Home or a new Oracle Home ORACLE_HOME=/u01/app/oracle/oem_agent/134000/agent_13.4.0.0.0 INSTALL_TYPE=GoldenGate Monitor Agent Installation You have new mail in /var/spool/mail/oracle 4. Confirm Java 8 is available $ which java $ java -version /u01/app/java/jdk1.8.0_202/bin/java 5. Install the Oracle GoldenGate JAgent /u01/app/java/jdk1.8.0_202/bin/java -jar ./fmw_12.2.1.2.0_ogg.jar -silent ./gg_mon.rsp 6. Monitor the installation of Oracle GoldenGate JAgent Launcher log file is /tmp/OraInstall2021-12-06_04-17-03PM/launcher2021-12-06_04-17-03PM.log. Extracting the installer . . . . Done Checking if CPU speed is above 300 MHz. Actual 2100.000 MHz Passed Checking swap space: must be greater than 512 MB. Actual 32767 MB Passed Checking if this platform requires a 64-bit JVM. Actual 64 Passed (64-bit not required) Checking temp space: must be greater than 300 MB. Actual 1038 MB Passed Preparing to launch the Oracle Universal Installer from /tmp/OraInstall2021-12-06_04-17-03PM Log: /tmp/OraInstall2021-12-06_04-17-03PM/install2021-12-06_04-17-03PM.log Copyright (c) 2016, Oracle and/or its affiliates. All rights reserved. Reading response file.. Skipping Software Updates Validations are enabled for this session. Verifying data Copying Files Percent Complete : 10 Percent Complete : 20 Percent Complete : 30 Percent Complete : 40 Percent Complete : 50 Percent Complete : 60 Percent Complete : 70 Percent Complete : 80 Percent Complete : 90 Percent Complete : 100 The installation of Oracle Fusion Middleware 12c GoldenGate Monitor & Veridata 12.2.1.2.0 completed successfully. Logs successfully copied to /u01/app/oraInventory/logs. 7. Create the Agent instance $ ./createMonitorAgentInstance.sh Please enter absolute path of Oracle GoldenGate home directory : /u01/app/ogg/oracle19c/19100/core Please enter absolute path of OGG Agent instance : /u01/app/ogg/oracle19c/19100/core/oggmon_agent/12.2.1.2/agent_inst Please enter unique name to replace timestamp in startMonitorAgent script (startMonitorAgentInstance_20211206163005.sh) : Successfully created OGG Agent instance. 8. Create the wallet for the Agent $ cd /u01/app/ogg/oracle19c/19100/core/oggmon_agent/12.2.1.2/agent_inst $ cd bin $ export JAVA_HOME=/u01/app/java/jdk1.8.0_202 $ ./pw_agent_util.sh -jagentonly Please create a password for Java Agent: Please confirm password for Java Agent: Dec 06, 2021 4:33:10 PM oracle.security.jps.JpsStartup start INFO: Jps initializing. Dec 06, 2021 4:33:10 PM oracle.security.jps.JpsStartup start INFO: Jps started. Wallet is created successfully. 9. Adjust the Agent to the environment where you are running it $ cat ./Config.properties | egrep -v ^#|^$ jagent.host=localhost jagent.jmx.port=5555 interval.regular=60 interval.quick=30 monitor.host=localhost monitor.jmx.port=5502 monitor.jmx.username=oggmsjmxusr jagent.username=oggmajmxusr reg.retry.interval=10 instance.query.initial.interval=5 incremental.registration.quiet.interval=5 maximum.message.retrieval=500 jagent.rmi.port=5559 agent.type.enabled=OEM status.polling.interval=5 message.polling.interval=5 reg.retry.times=-1 jagent.backward.compatibility=false jagent.ssl=false jagent.keystore.file=jagentKeyStore jagent.truststore.file=jagentKeyStore jagent.restful.ws.timeout=15000 jagent.ggsci.timeout=30 10. Enable monitoring in the GLOBALS file $ cd $OGG_HOME $ vi GLOBALS Add the parameter ENABLEMONITORING to the GLOBALS file. 11. Access GGSCI and verify that the JAGENT is available and start it if needed. $ ./ggsci Oracle GoldenGate Command Interpreter for Oracle Version 19.1.0.0.4 OGGCORE_19.1.0.0.0_PLATFORMS_191017.1054_FBO Linux, x64, 64bit (optimized), Oracle 19c on Oct 17 2019 21:16:29 Operating system character set identified as UTF-8. Copyright (C) 1995, 2019, Oracle and/or its affiliates. All rights reserved. GGSCI (rtlvedgo04.labcorp.com) 1> info jagent JAgent is running. GGSCI (rtlvedgo04.labcorp.com) 2> info all Program Status Group Lag at Chkpt Time Since Chkpt MANAGER RUNNING JAGENT RUNNING PMSRVR STOPPED Note: in the above example, when using Oracle GoldenGate 12.3 or later the ENABLEMONITORING parameter will also enable Performance Metric Service. After confirming that the JAgent has been started, you are done. Hope this helps! Enjoy!!", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Installing Oracle GoldenGate Monitor Agent 12.2.1.2 – Silent", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/blog-feature-Logo-Oct-31-2025-04-57-26-6962-PM.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/installing-oracle-goldengate-monitor-agent-12-2-1-2-silent", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "After installing Oracle GoldenGate with a manual ServiceManager, you realize that the ServiceManager will not come back up on a reboot. Although this can be annoying, Oracle GoldenGate is doing what it was asked to. Additionally, after the ServiceManager has been configured, there is no way to convert the ServiceManager to daemon process, unless they whole deployment is rebuilt. I came up with a way to start Oracle GoldenGate’s ServiceManager through using the Linux SystemCTL process. By using systemctl, a manual ServiceManager can be turned into a rebootable service. Let’s look at how this is done. Shell Script The first thing that needs to be done is to produce a shell script that will call the startSM.sh script. The startSM.sh script is provide by Oracle to start the ServiceManager, but there are a few environment variables that must be set before it can be ran. By writing a wrapper script to call the startSM.sh script, all that can be done in a single pass. The contents of the script is as follows: File 1: startServiceManager.sh #!/bin/bash # Copyright (c) 2020 RheoData, LLC and/or its affiliates. All rights reserved. # # Since: March 2019 # Author: bobby@rheodata.com # Description: Start ServiceManager # # DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS HEADER. # export OGG_HOME=/opt/app/oracle/product/21.3.0/oggcore_21c export DEPLOYMENT_HOME=/opt/app/oracle/gg_deployments/ServiceManager export OGG_ETC_HOME=/opt/app/oracle/gg_deployments/ServiceManager/etc export OGG_VAR_HOME=/opt/app/oracle/gg_deployments/ServiceManager/var echo Starting ServiceManager $DEPLOYMENT_HOME/bin/startSM.sh echo Done By looking at the startServiceManager.sh script, it clearly pointed out that the $OGG_HOME, $DEPLOYMENT_HOME, $OGG_ETC_HOME, and $OGG_VAR_HOME are defined. These are the environment variables that are needed to bring up the ServiceManager. Service File The next thing that needs to be configured is the service file. This file is used by systemd process to interact with the service. This file is broken down into three parts – Unit, Service, Install. The Unit section holds the description and other items that describe the service. The Service section is where we define the type, user, group and the shell script that will be executed. In this case, we are calling startServiceManage.sh. File 2: ServiceManager.service [Unit] Description=Oracle GoldenGate 21c ServiceManager Control [Service] Type=forking User=oracle Group=oinstall ExecStart=/bin/bash /home/oracle/scripts/startServiceManager.sh [Install] WantedBy=multi-user.target Once this file is create, it needs to be save to /etc/systemd/system directory. This is the default location for all the services that are running on RHEL/OEL. Create the Service With the shell script and services file create, now is the time to create the service itself. This process is straight forward. $sudo su – $systemctl daemon-reload $systemctl enable ServiceManager.service Since this is a new service that is being created, the daemons must be reloaded. This pulls in the ServiceManager.service file to the systemd process. Then the enable call will create a symbolic link between the ServiceManager.service file in /etc/systemd/system/multi-user.target.wants and the same file in /etc/system/system. After the service is enabled, we can force the ServiceManager down by simply killing the process. Don’t worry any associated deployments services and extract/replicat process will stay running. With the ServiceManager down, start it back up with the new services; with: $sudo su – $systemctl start ServiceManager Check the Service If everything is working, the ServiceManager will be brought up and accessible. The status of the ServiceManager can then be checked using the status option of systemctl. $sudo su – $systemctl status ServiceManager $ systemctl status ServiceManager ● ServiceManager.service - Oracle GoldenGate 21c ServiceManager Control Loaded: loaded (/etc/systemd/system/ServiceManager.service; enabled; vendor preset: disabled) Active: active (running) since Tue 2023-01-31 17:21:34 GMT; 3h 15min ago Main PID: 22414 (ServiceManager) CGroup: /system.slice/ServiceManager.service └─22414 /opt/app/oracle/product/21.3.0/oggcore_21c/bin/ServiceManager –quiet This is how you convert a manual start ServiceManager into a ServiceManager that will be started on reboot.", "author" : { "@type" : "Person", "name" : "rheostage5132", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/rheostage5132" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Configure Oracle GoldenGate’s ServiceManager as a Linux Service", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/rd_configure_sm_service-1024x553-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/configure-oracle-goldengates-servicemanager-as-a-linux-service", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "Building a Data Governance Framework Data governance is crucial for any organization looking to leverage its data effectively. It provides a structured approach to managing, using, and protecting data assets. Let’s break down how to build a data governance framework in a simple and understandable way. What is Data Governance? Data governance is the overall management of the availability, usability, integrity, and security of data in an enterprise. It involves establishing policies, procedures, and standards to ensure data is consistent, reliable, and trustworthy. Key Components of a Data Governance Framework Here are the essential components you need to focus on when building your framework: 1. Define Goals and Objectives First, determine what you want to achieve with data governance. What are the business drivers? Common goals include: Improving data quality Ensuring regulatory compliance Enhancing decision-making Increasing data security 2. Identify Roles and Responsibilities Clearly define roles and responsibilities for data governance. Key roles include: Data Owner: Responsible for data definition, quality, and usage. Data Steward: Implements data policies and procedures. Data Custodian: Manages the technical aspects of data storage and access. Data Governance Council: Oversees the data governance program. 3. Establish Data Policies and Standards Create policies and standards that govern how data is managed and used. These should cover: Data quality rules Data security and privacy Data access and usage Data retention and disposal 4. Implement Data Quality Management Data quality is essential. Implement processes to: Identify and correct data errors Monitor data quality metrics Establish data validation rules 5. Develop a Data Dictionary and Metadata Management Create a data dictionary to document data elements, definitions, and relationships. This helps ensure everyone is on the same page. 6. Establish Communication and Training Ensure everyone in the organization understands the data governance framework. Provide training and regular communication to promote awareness and adherence. 7. Monitor and Measure Success Continuously monitor the effectiveness of your data governance framework. Track key metrics and make adjustments as needed. Steps to Implement Your Framework Here’s a simple step-by-step approach: Assessment: Evaluate your current data management practices. Planning: Define goals, roles, policies, and standards. Implementation: Roll out the framework and provide training. Monitoring: Track metrics and make improvements. Continuous Improvement: Regularly review and update the framework. Why Data Governance Matters Effective data governance leads to better decision-making, improved data quality, and reduced risk. It empowers organizations to use data as a strategic asset. By following these steps, you can build a robust and effective data governance framework that supports your organization’s goals.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Building a Data Governance Framework", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/AdobeStock_1040748327-1.jpg", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/build-data-governance-framework", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "I’ve been helping clients with Oracle GoldenGate (Microservices) implementation – one thing that keeps coming up is how Nginx is installed. Each environment has different approaches. I wrote how to install this on Oracle Enterprise Linux in an earlier approach. Now, I have to provide a way to install Nginx on the AWS EC2 instance to support Oracle GoldenGate (Microservices). Before installing NGINX, ensure that you have an active EC2 compute node on AWS. In my case, I’m using an EC2 instance on the AWS Free Tier. Now that I have an EC2 compute node, the first thing to do is SSH into it. $ ssh -I ~/.ssh/rd-usf-tst.pem ec2-user@ Note: The pem file permissions should be 400 (chmod 400). Then ssh’ing into the EC2 node will go straight through. With being logged into the ECS instance, you’ll need to su over to the root user. $ sudo su -  After logging in as the root user, you’ll need to run “amazon-linux-extras” to get nginx installed. $ amazon-linux-extras install nginx1.12 What is interesting after confirming installation, the AWS output says that the “extra” items has reached the end of support. From what I can tell this really doesn’t mean anything other than AWS needs to update it soon. Just be aware. To confirm that NGINX has been installed, use the “list” sub-command for “yum”. $ yum list install nginx Now with NGINX installed, you can configure Oracle GoldenGate (Microservices) to use it. Enjoy!!", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Installing Nginx on AWS EC2 instance", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/aws-extras-1-3.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/installing-nginx-on-aws-ec2-instance", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "Remember when everyone said the cloud was just a fad? We’re hearing similar skepticism about AI in enterprise data management today. But here’s what I’ve learned after thirty years in technology leadership: the organizations that dismiss transformative technologies early often spend the most catching up later. The difference this time? AI isn’t just changing how we work with data—it’s fundamentally reshaping what’s possible when humans and systems collaborate intelligently. I’ve watched teams struggle with Oracle GoldenGate troubleshooting for hours, digging through logs and configuration files, when the right AI integration could surface those insights in minutes. That breakthrough moment came when we discovered Anthropic’s Model Context Protocol. Suddenly, we weren’t just talking about AI as some distant future capability—we had a practical, secure way to connect AI directly to the enterprise systems our teams use every day. The Challenge: When AI Meets Enterprise Reality Walk into any enterprise data center, and you’ll find the same frustrating disconnect. Marketing teams are buzzing about AI transformation while database administrators are still manually checking replication lag at 2 AM. The promise is compelling, but the execution? That’s where most organizations stumble. I’ve seen too many AI projects that look impressive in demos but crumble under real-world operational pressure. Teams invest months building fragile custom integrations that break every time Oracle releases an update. Meanwhile, the DBAs who could benefit most from AI assistance continue working with the same tools they’ve used for years, waiting for someone to bridge that gap between possibility and practicality. Oracle’s microservices framework already gives us solid programmatic access through REST APIs. We can automate deployments and monitor replication status dynamically. But imagine if your database administrators could simply ask, “Which extracts are running slowly today?” and get immediate, accurate answers from live system data. The Model Context Protocol: Finally, a Standard That Makes Sense At Google NEXT this year, when Anthropic announced the Model Context Protocol, I knew we’d found something different. This wasn’t another flashy AI demo—it was a practical solution to the standardization problem that’s been holding back enterprise AI adoption. Think of MCP as creating a universal connection standard between AI and your existing infrastructure—like how USB-C eliminated the chaos of proprietary cables. One standardized interface that works across different AI platforms and evolves with your systems. But here’s what makes MCP genuinely powerful for enterprise environments: it respects your security boundaries. Instead of training AI models on sensitive data, MCP lets AI access live information through controlled, secure interfaces. Your critical data stays exactly where it belongs while AI gains the context it needs to provide meaningful assistance. Building MCP Servers That Actually Work in Production Let me show you how we approach MCP development for Oracle GoldenGate, using principles that work for any enterprise system integration. The architecture starts simple but reflects years of hard-won lessons about enterprise integrations: # server.py - Your integration foundation import sys from mcp.server.fastmcp import FastMCP mcp = FastMCP(GoldenGateMCP) # main.py - Your execution entry point from server import mcp if __name__ == __main__: mcp.run(transport='stdio') This foundation looks straightforward, but what’s happening underneath reflects everything we’ve learned about building systems that teams can depend on. Clean separation between configuration and execution makes managing different environments infinitely easier. Tools That Solve Real Problems The real work happens when you build tools around business operations, not just technical functions. Here’s how we structure our Oracle GoldenGate integration: class GoldenGateOperations: def __init__(self, config: dict = None): if config is None: from config_loader import load_config config = load_config() # Secure configuration management gg_config = config[golden_gate] self.host = gg_config[host] self.username = gg_config[username] self.process_configs = gg_config[processes] async def get_process_status(self, process_type: str): Retrieve real-time status for GoldenGate processes if process_type not in self.process_configs: available_types = list(self.process_configs.keys()) raise ValueError(fProcess type '{process_type}' not configured. Available: {available_types}) # Secure API interaction with proper authentication config = self.process_configs[process_type] url = fhttp://{self.host}:{config['port']}/services/v2/{config['endpoint']} # Enterprise security practices auth_credentials = f{self.username}:{config['password']} encoded_auth = base64.b64encode(auth_credentials.encode()).decode() headers = {Authorization: fBasic {encoded_auth}} response = requests.get(url, headers=headers, verify=False) return json.dumps(response.json(), indent=2) See what we’re doing here? Configuration stays external, authentication follows security best practices, and error handling gives clear feedback. These aren’t just coding preferences—they’re operational necessities when building systems that teams will stake their reputation on. Natural Language for Operations Teams The transformation happens when you expose these capabilities through conversational interfaces: @mcp.tool() async def get_extract_status(): Check the current status of all extraction processes return await gg_operations.get_process_status(extracts) @mcp.tool() async def get_replicat_status(): Monitor replication process health and performance return await gg_operations.get_process_status(replicats) Suddenly, your operations team can ask “Are all our extracts running normally?” and get immediate answers based on live system data. That’s when AI stops feeling like a science project and starts delivering real value. Strategy Beyond the Code Building the MCP server is the foundation, but successful implementation requires thinking strategically about how teams actually work. Enhancing Existing Workflows The most successful AI implementations enhance established processes rather than disrupting them. Your database administrators already have proven workflows for monitoring GoldenGate environments. Smart MCP servers accelerate these processes without forcing teams to abandon what’s already working. Starting with monitoring and status checking creates immediate value while building confidence. Teams can verify AI responses against familiar tools, gradually building trust in the system. Security That Actually Works Enterprise AI demands enterprise-grade security from day one: Credential Management: Enterprise-grade secrets management, never hardcoded passwords Network Security: Proper network segmentation and access controls Audit Logging: Complete tracking of all AI interactions with enterprise systems Data Governance: AI interactions that comply with organizational data policies Getting Teams on Board Technical implementation is often the straightforward part. Real success requires thoughtful change management: Start with Power Users: Find team members comfortable with new technology who can become advocates Demonstrate Clear Value: Show concrete time savings and improved accuracy, not just impressive technology Provide Fallback Options: Teams need confidence they can perform critical tasks even if AI systems are unavailable Iterate Based on Feedback: The best implementations evolve based on real user experiences Connecting to Production Systems Once your MCP server is tested and ready, connecting it to platforms like Claude Desktop requires attention to operational details. Configuration management becomes critical here. Your claude_desktop_config.json should reflect organizational deployment standards: { mcpServers: { GoldenGateOperations: { command: /opt/python/bin/uv, args: [ --directory, /opt/mcp/goldengate-server, run, main.py ] } } } Use absolute paths, establish consistent deployment locations, and ensure your configuration integrates with existing DevOps processes. These operational details determine whether your solution scales across the enterprise or remains a clever proof of concept. What Success Looks Like in the Real World When MCP servers work effectively, they transform how teams interact with complex enterprise systems. Here’s what we’ve observed: Faster Problem Resolution: Database administrators diagnose replication issues in minutes instead of hours, using natural language queries to quickly identify bottlenecks and configuration problems. Better Team Collaboration: Operations teams share system status and troubleshooting insights more effectively when AI provides context-rich explanations of system behavior. Smarter Decision Making: Managers get real-time operational insights without needing deep Oracle GoldenGate expertise. Reduced Learning Curves: New team members become productive faster when they can ask systems questions in plain English. The Bigger Picture MCP servers represent more than just another integration approach. They signal a fundamental shift toward more accessible, context-aware enterprise operations. Organizations wrestling with complex data architectures and the demand for real-time operational intelligence will find standardized protocols like MCP becoming essential infrastructure. Teams that embrace these approaches early gain significant competitive advantages in operational efficiency and system reliability. The key? Approach these implementations with the same discipline and strategic thinking you’d apply to any critical enterprise system. This isn’t about experimenting with AI—it’s about building production-ready solutions that genuinely enhance your team’s capabilities and improve business outcomes. Summary Building MCP servers for Oracle GoldenGate operations demonstrates a practical approach to enterprise AI integration—one that delivers immediate value while establishing the foundation for broader transformation initiatives. The technical implementation is straightforward when you apply proper architectural thinking and enterprise-grade practices. The real value emerges when operations teams can interact with complex systems using natural language while maintaining security, reliability, and compliance. Success requires balancing technical capabilities with thoughtful change management, ensuring AI enhancements integrate seamlessly with existing workflows and team practices. Organizations taking this measured, strategic approach build AI capabilities that scale across their enterprise architecture while delivering measurable operational improvements. The question isn’t whether AI will transform enterprise data operations—it’s whether your organization will lead that transformation or spend years catching up. MCP servers provide a clear, practical path forward for teams ready to bridge the gap between AI potential and enterprise reality. What’s our objective here? Clear communication, team success, and technology that serves the mission. That’s strategic AI integration in practice. Ready to Transform Your Enterprise Operations? At RheoData, we’ve built MCP servers and AI integrations for some of the most demanding enterprise environments. We understand the difference between impressive demos and production-ready solutions that your teams can depend on. Whether you’re looking to enhance Oracle GoldenGate operations, integrate AI with other enterprise systems, or develop a comprehensive AI strategy that aligns with your business objectives, our team brings the architectural expertise and operational experience to make it happen. Let’s coordinate on your next AI integration project. Contact us to discuss how MCP servers can transform your enterprise operations while maintaining the security, reliability, and performance your business demands. Ready to get started? Reach out to cloud@rheodata.com or visit rheodata.com to learn more about our enterprise AI integration services. Your success is our success. Let’s build something remarkable together.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Transforming Oracle GoldenGate Operations with AI: Building MCP Servers for Real-World Impact", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/AdobeStock_589427987-1.jpg", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/transforming-oracle-goldengate-operations-with-ai-mcp-servers", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "Once you have an up and running Oracle GoldenGate Microservices environment, there may come a time when you need to add another deployment to the enviornment. Adding deployments is easily done using Oracle GoldenGate Configuration Assistant (OGGCA). In the below video, I show you how to add a deployment to an existing ServiceManager. Additionally, I discuss each of the screens in the OGGCA process to hopefully provide a better understanding of the process of setting up deployments. Enjoy!! twitter: @dbasolved", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Add a deployment to Oracle GoldenGate 19c Microservices", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/blog-feature-Logo-Oct-31-2025-04-57-26-6962-PM.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/add-a-deployment-to-oracle-goldengate-19c-microservices", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "At Oracle Cloud World 2023, Oracle announced they were moving toward enabling Artificial Intelligence (AI) within many of their products. Oracle is making huge steps forward for many people to use AI daily. As 2023 ended, many other industry leaders announced they would do the same. Regarding databases, Oracle is the only industry leader that leverages its core product for many different things. For at least a decade, Oracle has turned the Oracle Database into a Swiss army knife by enabling it to support different modern data types, analytics, and development paradigms, all in one product. It is only natural that with the AI revolution starting, Oracle would build a data type that enables organizations to use Retrieval-Augmented Generation (RAG) within the databases. By adding a “vector” datatype, Oracle simplifies data architectures and the building of RAG or Private-LLM configurations for organizations. Where is the Vector datatype? If you use an Oracle Database today, you will not immediately have access to the Vector datatype. Even if you use the latest version, 23.3.x.x, on Oracle Cloud Infrastructure (OCI), you cannot access this datatype (Believe me, I tried). You have to be part of the beta program for the next release of Oracle Database, which will provide you details on the Vector datatype before the initial release in 23.4. In short, and for the moment, if you are not part of the beta program, this datatype will be available soon! What is the Vector datatype? The Vector datatype is a modern datatype designed to efficiently store, manage, and index massive amounts of high-dimensional data. This data type is growing in interest and is used to create additional value for generative AI use cases and applications. Vector Settings? The vector datatype is used within standard Oracle tables. This enables database schemas to use the data in real-time. The following command shows a simple example: sql> CREATE TABLE rd_vectors (id NUMBER, embed VECTOR); This simple example shows that the vector datatype can be set as a column within a table. Enabling it this way allows you to specify vectors of different dimensions with different formats. Think of this as a catch-all setting for vector data. It is great to have a catch-all; however, you can limit the type of vectors created by imposing constraints on the stored data. In this example, you can only store up to 1024 dimensions, and they must be formatted as INT8 (8-bit integers): sql> CREATE TABLE rd_vectors_int8 (id NUMBER, embed VECTOR(1024, INT8); With this complex example, you must have 1024 dimensions, each of which must be 8-bit integers (INT8). The number of dimensions should be greater than 0 with no limit. The dimensions formats are INT8, FLOAT32, and FLOAT64. FLOAT32 and FLOAT64 are the IEEE standards, and the Oracle Databases will automatically cast the values as needed. Examples of setting additional dimension formats are: sql> CREATE TABLE rd_vectors_int8 (id NUMBER, embed VECTOR(1024, FLOAT32); sql> CREATE TABLE rd_vectors_int8 (id NUMBER, embed VECTOR(1024, FLOAT64); Vector Forms? With the understanding of Vector settings, there are a few forms that a vector can take. Understanding these forms will help in defining the proper vector for your requirements: Important Note: A vector can be NULL, but the dimensions cannot be NULL. (example: You cannot have [(1.1, NULL, 2.3)] Examples of Vectors: Now that you understand the Vector datatype, how does the Oracle Database see the datatype? The following SQL example shows that the table rd_vector is created with only vector datatypes using different variations. sql> CREATE TABLE vector.rd_vector ( v1 VECTOR, v2 VECTOR(3, FLOAT32), v3 VECTOR(2, FLOAT64), v4 VECTOR(1, INT8), v5 VECTOR(1, *), v6 VECTOR(*, FLOAT32), v7 VECTOR(*, *) ); sql> desc vector.rd_vector; Name                                         Null?   Type ----------------------------------------- -------- —————————————— V1                                                         VECTOR(*, *)  V2                                                         VECTOR(3, FLOAT32) V3                                                         VECTOR(2, FLOAT64) V4                                                         VECTOR(1, INT8) V5                                                         VECTOR(1, *) V6                                                         VECTOR(*, FLOAT32) V7                                                         VECTOR(*, *) Hopefully, Oracle will release Oracle Database 23.4 soon! There will be many opportunities to use vector data types as organizations expand their usage of Generative AI. Enjoy!", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Oracle’s Vector Datatype", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/oracle-vector-datatype-1-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/vector-datatype", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "As we have done multiple engagements with Oracle GoldenGate and helped clients get the most out of their investment; we have realized that 90% of the parameter files we deal will are not structured in a way that makes sense. Traditionally, Oracle GoldenGate parameter files are text files that are read and loaded into memory for execution. The order in which these files are read have an impact on how Oracle GoldenGate will operate. In this post, we will highlight the basics of how a parameter file should be structured for readability as well as operational practicality. With newer versions of Oracle GoldenGate, there are two architectures – Classic and Microservices. Depending on the architecture you are using will determine the number of parameter files you have to review. For the purpose of this post, we will look at parameter files that are associated with the Microservices architecture; meaning only looking at the extract and replicat parameter files. Parameter File Formats Every parameter file starts off with the basic first line of either Extract or Replicat followed by the name of the process. After that many clients randomly throw parameters throughout the file, leading to either missing data or unexpected errors. As basic format of the parameter file, a skeleton key is below as an example. After reviewing this structure, we’ll show you some examples of do’s and don’ts. [EXTRACT || REPLICAT] [MACRO SETTINGS] [LOGIN SETTINGS] [MEMORY MANAGEMENT] [ENVIRONMENT SETTINGS] [REPORTING] [DDL] [DATABASE OPTIONS] [TRANSACTION LOG OPTIONS] [MISC.] [TABLE || MAP] The above skeleton key is designed to provide a guidance as to how the parameter file should be laid out. Not all categories will be used in all parameter file; please use it as a guide to write better parameter files. Capture Process With in Oracle GoldenGate the capture process is also know as the Extract. The extract comes in two vesions – Non-Integrated and Integrated. In both cases, a single parameter file is used. At the same time, many clients get the formatting of a parameter file crossed up. In this example, everything is set at random in the file. There is no logic or reason for where items are placed. The end goal is to have a working extract. At the same time, if you take the stand point of the parameter file is read from top-down, then items are being set before they need to be. Although this parameter file works, it is messy and difficult to follow what is going on. Note: Values of the parameter file has been modified to protect the client Extract Bad Format: EXTRACT DBOPTIONS ALLOWUNUSEDCOLUMN DBOPTIONS LOBBUFSIZE 2097152 USERID ggate@, PASSWORD SETENV (ORACLE_HOME=“$ORACLE_HOME) SETENV (ORACLE_SID=“$ORACLE_SID) LOGALLSUPCOLS UPDATERECORDFORMAT COMPACT TRANLOGOPTIONS MININGUSER ggate@, MININGPASSWORD TRANLOGOPTIONS INTEGRATEDPARAMS (max_sga_size 2048,parallelism 4, downstream_real_time_mine Y) TRANLOGOPTIONS BUFSIZE 4096000 TRANLOGOPTIONS EXCLUDEUSERID 9 CACHEMGR CACHESIZE 16GB, CACHEDIRECTORY /gg/dirtmp 300GB RMTHOST , MGRPORT 7809 WARNLONGTRANS 2h, CHECKINTERVAL 10m TABLEEXCLUDE MIP.TPC_EN* TABLEEXCLUDE MIP.SIB* TABLE MIP.*; When we run this through the skeleton key format that is provided above it becomes a lot easier to read and work with. Extract Skeleton Format: EXTRACT USERID ggate@, PASSWORD --CACHEMGR CACHESIZE 16GB, CACHEDIRECTORY /gg/dirtmp 300GB SETENV (ORACLE_HOME=“$ORACLE_HOME) SETENV (ORACLE_SID=“$ORACLE_SID) WARNLONGTRANS 2h, CHECKINTERVAL 10m DBOPTIONS ALLOWUNUSEDCOLUMN DBOPTIONS LOBBUFSIZE 2097152 TRANLOGOPTIONS MININGUSER ggate@, MININGPASSWORD TRANLOGOPTIONS INTEGRATEDPARAMS (max_sga_size 2048,parallelism 4, downstream_real_time_mine Y) TRANLOGOPTIONS BUFSIZE 4096000 TRANLOGOPTIONS EXCLUDEUSERID 9 LOGALLSUPCOLS UPDATERECORDFORMAT COMPACT TABLEEXCLUDE MIP.TPC_EN* TABLEEXCLUDE MIP.SIB* TABLE MIP.*; After rewriting the extract parameter file, you can quickly see items that should be removed or adjusted. Example of this is the setting for CACHEMGR. Although this parameter is correct from a syntax point-of-view, this setting is turned on by default with newer versions of Oracle GoldenGate. In the skeleton format above, notice that it is proceeded with a double dash. This means that the parameter has been commented out of parameter file and will not be ran upon starting up. After that you can quickly scan other parameters as needed to define what is going to happen. This same formatting can be used in other parameters files as well, especially the Apply process (i.e. Replicat). By using this organized flow to a parameter file, the Oracle GoldenGate Administrator or the DBA can quickly identify what is happening in the file or if anything has changed. The added bonus of this format is it can be used in all versions of Oracle GoldenGate – on-premises and cloud. If you need help with your Oracle GoldenGate implementation, feel free to drop us a line at hello@rheodata.com", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "GoldenGate Parameter Files – Format and Logic", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/blog-feature-Logo-Oct-31-2025-04-57-26-6962-PM.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/goldengate-parameter-files-format-and-logic", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ``` ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "articleBody" : "When installed, Oracle GoldenGat (Microservices) will set up “services” that require a port number for access. For the first run of the Oracle GoldenGate Configuration Assistant (OGGCA), the assistant will create the ServiceManager (1 port) and the first deployment (5 ports). That means six ports would need to be opened on a firewall to run a single Oracle GoldenGate (Microservices) deployment. This only increases by five ports for each deployment built under a single ServiceManager. To address this, an open-source solution called NGINX allows all the ports within the deployment to be consolidated to a single port. The single port that can be used with NGINX is either 80 (HTTP) or 443 (HTTPS); which will enable Oracle GoldenGate (Microservices) to be used over a standard firewall port Downloading Binaries The NGINX binaries need to be downloaded regardless of where you install Oracle GoldenGate (Microservices). For Oracle Enterprise Linux, I documented the process here. When you start to expand the installation base for Microservices, the installation of NGINX becomes similar yet different. To install NGINX on an Amazon Web Services (AWS) EC2 instance, the following steps should be followed. For more details, you can also reference this blog post on installing Nginx -> here or here. 1. SSH into the AWS EC2 instance $ ssh -I ~/.ssh/rd-usf-tst.pem ec2-user@ 2. Sudo to Root $ sudo su – 3. Use Amazon Extras to install NGINX $ amazon-linux-extras install nginx1.12 4. Confirm installation $ yum list install nginx After installing the NGINX on the AWS EC2 instance, the next thing that must be done is to configure it against the Oracle GoldenGate (Microservices) environment. Configure NGINX Oracle has made it easy for Oracle GoldenGate administrators to configure the NGINX interface after the installation. They provided a script called “ReverseProxySettings” in the $OGG_HOME/lib/utl directory. This script is used to build the Nginx configuration file based on the deployments running on the AWS EC2 node. The steps to configure the reverse proxy are as follows: 1. Change to the Reverse Proxy directory under $OGG_HOME $ cd $OGG_HOME/lib/utl/reverseproxy 2. Run ReverseProxySettings with options (unsecure access) $ ./ReverseProxySettings -u oggadmin -P -o ogg.conf http://localhost: 3. Copy the config file to the NGINX directory $ sudo cp ogg.conf /etc/nginx/conf.d/nginx.conf 4. Create a dummy cert $ sudo sh /etc/ssl/certs/make-dummy-cert /etc/nginx/ogg.pem 5. Start NGINX $ sudo nginx & 6. Test/validate NGINX config $ sudo nginx -t 7. Reload NGINX $ sudo nginx -s reload 8. Access the ServiceManager and other services without port numbers Note: The ogg.pem must be downloaded and uploaded to your local cert wallet to access via a web browser. End Result Once everything with the NGINX is configured, Oracle GoldenGate (Microservices) can be accessed by URL using the standard port of 80 (HTTP) or 443 (HTTPS). This enables Oracle GoldenGate (Microservices) environments to be accessed over standard firewall rules.", "author" : { "@type" : "Person", "name" : "Bobby Curtis", "sameAs" : "", "url" : "https://rheodata.com/en-us/blog/author/bobby-curtis" }, "dateModified" : "10/11/2025", "datePublished" : "10/11/2025", "headline" : "Configuring Nginx on AWS EC2 for Oracle GoldenGate 21c", "image" : { "@type" : "ImageObject", "height" : 400, "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/Imported_Blog_Media/nginx-url-noport-1-1.png", "width" : 750 }, "mainEntityOfPage" : "https://rheodata.com/en-us/blog/configuring-nginx-on-aws-ec2-for-oracle-goldengate-21c", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "url" : "https://50642793.fs1.hubspotusercontent-na1.net/hubfs/50642793/RheoData%20-%20Logo%20-%20transparent-1.png" }, "name" : "RheoData", "url" : "rheodata.com" } } ```