Effective practices are enablers, which can improve performance, data availability, environment stability, resource consumption, and data accuracy.
Use of an Enterprise Scheduler
The scheduling service in InfoSphere Information Server (IIS) leverages the operating system (OS) scheduler, the common enterprise scheduler can provide these capabilities beyond those of a common OS scheduler:
- Centralized control, monitoring, and maintenance of job stream processes
- Improved insight into and control of cycle processes
- Improved intervention capabilities, including alerts, job stream suspension, auto-restarts, and upstream/downstream dependency monitoring
- Reduced time-to-recovery and increased flexibility in recovery options
- Improved ability to monitor and alert for a mission-critical process that may be delayed or failing
- Improved ability to automate disparate process requirements within and across systems
- Improved load balancing to optimize the use of resources or to compensate for the loss of a given resource
- Improved scalability and adaptability to infrastructure or application environment changes
Use of data Source Timestamps
When they exist or can be added to data, ‘created’ and ‘last updated’ timestamps can greatly reduce the impact of Change Data Capture (CDC) operations. Especially, if the data warehouse, data model and load process store that last successful run time of CDC jobs. This reduces the number of rows required to be processed and reduces the load on the RDBMS and/or ETL application server. Leveraging ‘created’ and ‘last updated’ can, also, greatly reduce the processing time required to perform the same CDC processes.
Event-based scheduling, when coupled with an Enterprise scheduler, can increase data availability, distribute work opportunistically. Event-based scheduling can allow all or part of a process stream to begin as soon as predecessor data sources have completed the requisite processes. This can allow processes to begin as soon as possible, which can reduce resource bottlenecks and contention. This, potentially, allows data to be made available earlier than a static time-based schedule. Event-based scheduling can also delay processing, should the source system requisite processing completion be delayed; thereby, improving data accuracy in the receiving system.
Integrated RDBMS Maintenance
Integrating RDBMS Maintenance into the process job stream can perform on-demand optimization as the processes move through their flow, improving performance. Items such as indexing, distribution, and grooming, maintenance at key points ensure that the data structures are optimized for follow on processes to consume.
Application Server and Storage Space Monitoring and Maintenance
Monitoring and actively clearing disk space can not only improve overall performance, and reduce costs, but it also improves application stability.
Data Retention Strategies
Data Retention strategies, an often overlooked form of data maintenance, which deals with establishing policies ensure only truly necessary data is kept and that information by essential category, which is no longer necessary is purged to limit legal liability, limit data growth, storage costs, and improve RDBMS performance.
Use Standard Practices
Use of standard practices both, application and industry, allows experienced resources to more readily understand the major application activities, their relationships, dependency, design, and code. This facilitates resourcing and support over the life cycle of the application.