Summary

Openlink Commodities* is a powerful energy trading and risk management (ETRM) platform, widely adopted across commodity and financial services sectors. However, achieving optimal performance presents several challenges. Chief among them is the platform’s complexity and dependence on highly customized data models and workflows. 

As organizations scale and adapt it to support a broader array of trading instruments and risk analytics, the system often becomes weighed down by custom scripts, extensive deal rules, and inefficient reporting. While business-critical, these layers of customization frequently lead to performance bottlenecks, particularly during batch processing, simulation runs, and settlements, where large data volumes and complex calculations converge.

Infrastructure and system integration pose additional hurdles. Openlink relies on backend databases (such as Oracle or SQL Server), with performance closely tied to database design, hardware configuration, and network architecture. Poorly tuned queries, limited memory, and disk I/O constraints can significantly slow operations. Moreover, inadequate integration with external systems, like market data feeds, accounting tools, or risk engines, can introduce avoidable latency.

Sustaining peak performance requires close coordination between business analysts, developers, and IT operations. Continuous monitoring, profiling, and tuning are key to keeping the platform responsive to evolving business needs. The following sections outline specific focus areas that can help maintain long-term system health and performance.

IT Environment

A skilled IT team is essential to properly install and maintain Openlink, ensuring it runs smoothly and efficiently. Given the platform’s complexity, success depends on the right combination of tools, infrastructure, and proactive maintenance. Consider the following factors:

Citrix vs Remote Desktop (RDP)

Many organizations opt to host Openlink within their internal cloud environments instead of deploying it locally. Choosing the right virtualization tool is critical for a positive user experience. While RDP may seem attractive due to its lower cost, Citrix generally outperforms it in scalability, performance, and ease of management.

Proper Hardware

Having the right hardware is vital for any software implementation, especially so for ETRM systems like Openlink. It’s not just about quantity (memory, CPUs, number of machines), but also about data transfer rates. Openlink transfers substantial amounts of data between client machines and the database servers. Network bandwidth, storage capacity, and throughput are just as important as memory and CPU allocation.

• OS/DB Patches – Keeping operating systems and databases updated with the latest patches is essential. Though downtime for updates can be inconvenient, the long-term performance gains are worth it.
• Monitoring – It’s crucial to monitor both the network and the database system. Are some servers under- or over-utilized? Is the database overloaded during peak times? Continuous monitoring can prevent major issues.

Application Maintenance

The Openlink application requires just as much, if not more attention than the hardware. Without routine maintenance, performance will deteriorate over time. Addressing the following areas early can prevent future issues.

Purging/Archiving

Though it may make people uneasy, purging outdated or unused data is critical. Openlink generates a significant amount of temporary data, which can quickly inflate the database. Regularly purge logs, query result tables, and other transient data to prevent system bloat.

Maturing Deals

Maturing deals is crucial for maintaining system health. Maturing a deal doesn’t delete it; it simply marks the close event and sets the status to “matured.” Failing to do this causes simulation results and queries to grow unnecessarily. Unlike older versions, newer versions allow the user to unmature a deal.

Statistics

Regularly updating database statistics ensures optimal performance. Some organizations choose to “lock” statistics once they reach a favourable state, but ongoing updates generally yield better results.

Cleaning up system logs

System logs can accumulate large amounts of data, especially when debug levels are elevated. As log files grow, read/write operations slow down. Deleting these files regularly preserves space and helps sustain performance.

Configuration Clean Up

Over time, unused configurations, such as unused portfolios, desktop layouts, or curves for unimplemented products, can accumulate. Even user accounts for former employees can linger. Cleaning up these configurations improves system efficiency and reduces clutter.

Server reboots

Memory leaks, bugs, and other issues can slow servers over time. Regular reboots, especially for grid or script engines, can help maintain performance.

Resource Allocation

Effective resource allocation is essential, and there’s no universal solution. Thoughtful planning, continuous monitoring, and some trial and error are necessary.

• Script/Grid Engines – The right number of engines improves performance. Too few leads to user wait times; too many waste resources.
• Allocation relative to Services – Ensure each Service has enough engines. Overloading a cluster with too many Services can create bottlenecks. Long-running jobs can block queues if enough engines aren’t available. A busy dispatcher cannot assign new jobs.
• Local vs Remote Execution – Deciding whether to execute tasks locally or remotely affects user experience. Waiting on a remote, blocked service can be frustrating.

Custom Code

Openlink’s extensibility via OpenJVS and OpenComponents offers immense flexibility but can also severely impact performance. A deeper dive into code optimization is planned for a separate post. Here are the fundamentals:

Be nice to the database

The database is the core of Openlink operations. To keep plugins running efficiently:

• Simplify queries – Avoid large or complex queries. Minimize type conversions, unions, case statements, and outer joins. Let the client handle computation when possible.
• Use plugin-specific query tables – Reduce strain on the query_result table by using plugin-specific alternatives (e.g., query_result_plugin). Always clean up queries after use with methods like Query.clear().
• Avoid DB calls in loops – Structure your code to make a single, efficient database call rather than repeated ones in a loop.

The File System is not your friend

File system access is inherently slower, especially on network drives. Keep these in mind:

• Limit large file operations – Minimize reading/writing large files.
• Manage logging efficiently – Avoid logging unnecessary information during processing. Buffer logs in memory and write them after the process concludes.

Memory Management

While OpenJVS and OpenComponents offer more advanced capabilities than AVS, they still interact with the Openlink core and require careful memory handling:

• Manual cleanup – Dispose of large objects (e.g., Simulation Results) when done. Garbage collectors don’t recognize object size, so cleanup may be delayed.
• Avoid fragmentation – Repeated allocation and disposal in loops leads to memory fragmentation and performance loss.

Caching Cache

Take advantage of internal and user-defined caches:

• Use built-in methods to access cached data, like Ref.getValue() and Ref.getShortName() to convert between names and unique IDs. 
• For other frequently used data that isn’t cached (e.g., gas/power locations, info fields), implement user-defined caches via the User_Cache_Loader.java plugin.

‘Bulk’ API

Favor bulk operations over iterative ones. Common bulk-friendly classes/methods include:

• Deals – Use Reval to load many transactions quickly. Use TranProcessing to book multiple transactions in one operation.
• Bulk methods – Look for methods like ByQid, ByQuery, or Bulk. For instance, prefer Nomination.retrieveByQid() over looping Nomination.retrieve(). Use Transaction.eventBulkUpdate() and Transaction.tranInfoBulkInsert() for efficiency.

Reduce the number of plugins

Executing plugins adds overhead. Reduce performance impacts by:

• Combining Plugins – Avoid having multiple Trading Pre-Process plugins for similar tasks. Consolidate logic when feasible.
• Using core features – Openlink’s Operations Services allows users to build expressions for simple tasks without needing plugins. It uses a familiar interface like Report Builder and saves development time.

How capSpire can help

The teams at capSpire have deep expertise with Openlink. We can support your organization with day-to-day operations, system health checks, application configuration, and performance tuning.

Let’s talk.

All CTRM/ ETRM platforms referenced on this site are the trade names and trademarks of their respective owners, including ION Group and its subsidiaries.

capSpire, LLC and the ION Group are unaffiliated entities.

*Openlink Commodities is also referred to as Openlink or Endur.