HA - High Availability

Enhanced Definition

High Availability (HA) refers to the capability of an IT system or component to remain operational and accessible for a high percentage of the time, minimizing downtime and ensuring continuous service delivery. In the mainframe and z/OS context, HA is paramount for critical enterprise applications, focusing on robust architectures that prevent single points of failure and enable rapid recovery from outages.

Key Characteristics

- Redundancy: Implementation of duplicate hardware components (e.g., CPUs, I/O paths, power supplies, network adapters) and software instances to provide backup in case of failure.
- Fault Tolerance: The system's ability to continue operating without interruption despite the failure of one or more components, often achieved through automatic failover mechanisms.
- Rapid Recovery and Failover: Mechanisms for quickly detecting failures and automatically or semi-automatically switching workloads and resources to an alternate, healthy component or system.
- Data Integrity and Consistency: Ensuring that data remains consistent and uncorrupted across redundant systems during normal operations and especially during failover events.
- Scalability: Often integrated with horizontal scaling capabilities (e.g., z/OS Parallel Sysplex) to distribute workloads and enhance resilience against individual system failures.
- Proactive Monitoring and Automation: Continuous monitoring of system health and performance, coupled with automation tools (e.g., SA z/OS) to detect issues and initiate recovery actions.

Use Cases

- Online Transaction Processing (OLTP): Ensuring continuous availability of critical applications like CICS and IMS for banking, airline reservations, and retail point-of-sale systems.
- Database Systems: Providing uninterrupted access to DB2 and IMS databases through data sharing groups and replication technologies, crucial for real-time data access.
- Core z/OS Services: Maintaining the availability of essential system components such as JES, VTAM, and vital system utilities to support all running applications.
- Enterprise Resource Planning (ERP): Supporting large-scale ERP systems running on z/OS, where any downtime can significantly impact business operations.
- Batch Processing: While less critical for immediate availability, HA ensures that critical batch jobs can be restarted or continued on another system in case of an outage.

Related Concepts

HA on z/OS is fundamentally built upon the z/OS Parallel Sysplex architecture, which allows multiple z/OS systems to share resources and workloads. The Coupling Facility (CF) is a cornerstone of Sysplex, providing high-speed shared memory and locking services essential for data sharing and inter-system communication. Workload Manager (WLM) plays a crucial role in maintaining service levels and distributing workloads across available systems, especially during partial failures. For disaster recovery, GDPS (Geographically Dispersed Parallel Sysplex) extends HA capabilities across geographical distances, providing continuous availability and rapid recovery from site-wide disasters.

Best Practices:

Implement a Parallel Sysplex: Design and configure a robust Parallel Sysplex environment as the foundation for z/OS HA, leveraging its shared data and workload balancing capabilities.
Utilize Redundant Hardware and Paths: Ensure all critical hardware components, including power, network, and storage paths, are fully redundant to eliminate single points of failure.
Automate Operations with SA z/OS: Employ IBM System Automation for z/OS (SA z/OS) to automate monitoring, problem detection, and recovery actions, reducing manual intervention and recovery times.
Regularly Test Failover Procedures: Conduct periodic, planned failover tests for applications and systems to validate recovery processes and ensure staff proficiency.
Implement Data Sharing and Replication: Use technologies like DB2 Data Sharing, IMS Data Sharing, and storage replication (e.g., PPRC - Peer-to-Peer Remote Copy) to ensure data consistency and availability across systems.
Perform Capacity Planning for Failover: Ensure that each individual system or a subset of systems within an HA configuration has sufficient capacity to handle the full workload in the event of a component or system failure.