New EU vehicle emission regulations have created an onerous workload for car manufacturers.
When prospective car-buyers access an online Peugeot Citroen’s (Groupe PSA) site, they need to know if the vehicle configuration they select meets the new WLTP (world harmonised light-duty vehicles test procedure) standard. To deliver the expected user experience, meaning having a snappy web site, the WLTP calculations should be completed in less than 100ms. Also the calculations need to be accurate and reliable enough to avoid fines that could reach up to €100 million annually.
Peugeot Citroen’s mainframe system does not have the power to meet the demand for checking WLTP compliance in real-time.
If the WLTP software layer is executed entirely on the mainframe, it is limited to 200 requests/sec. But the Peugeot Citroen requirement is to support 3000 requests/sec.
Rather than update the mainframe, which would be expensive, Groupe PSA decided to offload the WLTP processing to a networked 3-server X86 cluster It used an in-memory, real-time analytics SW product called InsightEdge from GigaSpaces, implemented through CAP Gemini. The difficulty of computing WLTP compliance at individual car configuration level is indicated by CAP Gemini deciding in-memory software was needed.
A trio of X86 servers running InsightEdge in-memory software to work out vehicle emissions delivers 15 times more requests per second than the mainframe can do alone.
A caching alternative was rejected because it meant accessing the mainframe to execute complex queries and analytics, which slowed things down.
The caching alternative would not support added intelligence for processing and simplifying the requests on the fly, with aggregation and masking. InsightEdge co-locates data and business logic in the same memory space to lighten storage IO and context switch needs and speed request processing.
Groupe PSA’s deployed WLTP software has an adapter layer on the mainframe, which connects via an orchestration layer to InsightEdge. That SW is deployed on a cluster of three HPE ProLiant DL380-G9 servers running in full high-availability mode, and with 16 partitions.
This InsightEdge system delivers a 15-19ms query and analytics response time, and handles up to 95.2 per cent of calculation requests without accessing the mainframe. So the mainframe is not entirely off-loaded.