Use cases

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Generic use cases

IBM Fusion Data Foundation addresses critical use cases when it establishes a storage infrastructure, and it adds persistence to application workloads.

  • Administer consumption of storage hardware
    • Deploy storage services with maximum flexibility and mobility and decoupled from the physical hardware.
    • Expand storage as needed (for example, add capacity).
    • Provide ready to use dashboards in the Red Hat OpenShift Administrator Console to indicate storage health and status.
    • Alert users when there is a storage issue.
    • Self-healing and recovery of issues that are related to storage infrastructure.
    • Run an internal image registry on IBM Fusion Data Foundation storage.
    • Add storage for Red Hat OpenShift Logging.
    • Add storage for Red Hat OpenShift Monitoring.
  • Develop containerized applications, which consume persistent storage
    • Implement simple and consistent data access whether on premises or in the cloud.
    • Use well-known standard Kubernetes APIs, Operators, and use of persistent volume claims and persistent volumes.
    • Develop, test, and deploy end-to-end with one consistent platform.
    • Take advantage of common types of storage classes:
      • Block storage is suitable for databases and systems of record.
      • File storage is suitable for messaging, data aggregation, workloads machine learning, and deep learning.
      • Object storage is suitable for images, non-binary files, documents, snapshots, or backups. Object Storage is especially relevant for AI workloads. S3 APIs are the de facto standard for object storage.

Specific use cases

This reference architecture is valuable for cross-industry enterprises that want to deploy a private cloud solution with programmable Infrastructure as a Service (IaaS), Containers as a Service (CaaS), and Platform as a Service (PaaS) capabilities. Specific target use cases, where IBM Fusion Data Foundation can be applied, aim at:

  • Data gravity
    • A key use case in which RHOCP can take advantage of the IBM Z platform is the colocation of containerized applications with traditional workloads. For example, data lakes, databases, transactional systems, or other traditional workloads running in Linux on IBM Z or z/OS. In such a scenario the applications can be located close to the data to optimize latency, response time, deployment, security, service, and cost. For example, in combination with Oracle databases, the resulting synergy can dramatically improve the Total Cost of Ownership (TCO).
  • Consolidation and TCO Reduction
    • When consolidating an RHOCP environment from x86 platforms to IBM Z, customers can achieve economic and operational advantages.
    • Most of the 3-dimensional scalability (vertical, horizontal, and combined) results in high flexibility without the need for a new hardware footprint. This is a key advantage for dynamic workloads and unpredictable growth.

  • Business continuity

    • For business continuity, consider these two aspects:
      • For high availability (HA), IBM Z provides an internal network with significantly more reliability based on a higher degree of redundancy in the hardware. Because virtualization happens within a single hardware environment, the networking traffic is more predictable with less latency compared to x86 environments.
      • Building a disaster recovery (DR) setup with IBM Z is much simpler in such an environment because you must deal with fewer hardware units.

Target industries

IBM Fusion Data Foundation is intended for generic orchestration and lifecycle management of containerized workloads. While it is used widely among industries, the most relevant background of IBM Fusion Data Foundation for IBM Z customers is in industries such as:

  • Banking and insurance with a strong focus on high availability, transactions, and security.
  • Government with a strong focus on high availability and security.
  • Retail with a strong focus on scalability and coping with peak loads.
  • Cloud and computing services with a strong focus on high availability, variable load, and scalability.

Additional industries, which can benefit include:

  • Media
  • Telecommunications
  • Education
  • Transportation
  • Pharmaceutical and medical products, healthcare
  • Hospitality and travel
  • Manufacturing
  • Utilities and energy
  • Electronics
  • Chemicals
  • Consumer products
  • Metals and natural resources
  • Construction and engineering
  • Food and beverage processing