Webcasts
Abstract
In this session, we will demonstrate how to quickly deploy a containerized IBM Sterling Order Management System (OMS) and Order Service containers using Minikube. This setup allows you to spin up instances rapidly, making it ideal for proof of concept (POC) deployments or exploring the product’s capabilities. We will also deploy supporting dependencies like Elasticsearch and Cassandra using Kubernetes operators, all on a desktop-sized machine. Whether you are getting hands-on experience, or just curious to learn how the system works in a contained environment, this session will provide the practical insights you need without requiring large-scale infrastructure.
Content
Webinar Session Details:
Title: Quick POC Setup and Exploration: IBM Sterling Order Management System and Order Service via Minikube
Presenter:
Chiranjeevi Dasegowda - Senior Support Engineer, IBM Sterling OMS.
Sameer Saeed - Support Engineer, IBM Sterling OMS
Session Material:
Chiranjeevi Dasegowda - Senior Support Engineer, IBM Sterling OMS.
Sameer Saeed - Support Engineer, IBM Sterling OMS
Session Material:
Presentation deck - https://ibm.biz/BdnVnS
Session recording - https://ibm.biz/BdnVnE
Question and Answer:
Question 1 - How should we size our infrastructure for the Order Service, considering storage and server requirements?
Answer -
Sizing your infrastructure depends heavily on your specific business use case, including data volume, query complexity, and expected load. While we recommend conducting your own benchmarking in a staging or pre-production environment, we are happy to share some internal reference points to help guide your planning.
Answer -
Sizing your infrastructure depends heavily on your specific business use case, including data volume, query complexity, and expected load. While we recommend conducting your own benchmarking in a staging or pre-production environment, we are happy to share some internal reference points to help guide your planning.
Storage Needs:
- Based on internal observations, storage requirements are approximately:
1.5 GB per 1 Million Order Lines (MOL)
For example, if your system stores 1 million order lines per year, you can expect to need 7.5 GB of storage after 5 years.
Server Requirements:
A typical setup we have tested includes:
6 nodes total:
- 3 nodes for Order Search
- 3 nodes for Order Archive
- Based on internal observations, storage requirements are approximately:
1.5 GB per 1 Million Order Lines (MOL)
For example, if your system stores 1 million order lines per year, you can expect to need 7.5 GB of storage after 5 years.
Server Requirements:
A typical setup we have tested includes:
6 nodes total:
- 3 nodes for Order Search
- 3 nodes for Order Archive
Each node configured with:
- 8 CPU cores
- 32 GB RAM
- 8 CPU cores
- 32 GB RAM
Note: These figures are based on internal testing and should not be considered definitive. Actual requirements may vary depending on your workload. Performance and resource usage scale linearly with data volume in our tests, but we strongly recommend validating this in your own environment.
Best Practices:
- Review your projected data growth, query patterns, and performance expectations.
- Before finalizing your infrastructure, benchmark your configuration under realistic conditions. This will help ensure your deployment is optimized for your specific workload and growth trajectory.
- Refer to official tuning and sizing guides:
Elasticsearch Heap Sizing & Performance Guide: Elastic Guide
Cassandra Data Modeling & Partition Sizing: Cassandra Guide
- Review your projected data growth, query patterns, and performance expectations.
- Before finalizing your infrastructure, benchmark your configuration under realistic conditions. This will help ensure your deployment is optimized for your specific workload and growth trajectory.
- Refer to official tuning and sizing guides:
Elasticsearch Heap Sizing & Performance Guide: Elastic Guide
Cassandra Data Modeling & Partition Sizing: Cassandra Guide
Question 2: Can Order Service be used to aggregate orders from multiple systems, not just from OMS?
Answer:
Yes, Order Service can be used to aggregate orders from multiple systems, not just the Order Management System (OMS). In version 10, Order Service supports independent deployment using Kubernetes Operators, which allows it to function as a standalone service. This flexibility enables integration with a variety of order sources beyond OMS.
While OMS offers out-of-the-box (OOB) integration with Order Service, you can also send orders from other non-OMS systems. To do this, you would need to implement your own mechanism to transfer data from those systems into Order Service. Order Service provides a set of APIs that allow external systems to create and query order data, making it possible to build custom integrations based on your specific needs.
Additionally, order archival is supported as long as the orders are present in Order Service and are indexed with the appropriate Elasticsearch index key.
Presentation
Multimedia
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Document Information
Modified date:
05 June 2025
UID
ibm17233374