RMF Distributed Data Server
E752532
RMF Distributed Data Server is a z/OS component that collects, consolidates, and serves performance and resource usage data from multiple systems for monitoring and analysis.
All labels observed (1)
| Label | Occurrences |
|---|---|
| RMF Distributed Data Server canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8706829 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RMF Distributed Data Server Context triple: [RMF, component, RMF Distributed Data Server]
-
A.
TimesTen
TimesTen is an in-memory relational database from Oracle designed for extremely low-latency, high-throughput data management and real-time analytics.
-
B.
RethinkDB
RethinkDB is an open-source, distributed NoSQL database designed for real-time applications by pushing live updates to clients as data changes.
-
C.
Caché
Caché is a tributary stream that feeds into the Bléone River in southeastern France.
-
D.
Jepsen
Jepsen is a surname most notably associated with individuals such as display technology innovator Mary Lou Jepsen.
-
E.
Ray Serve
Ray Serve is a scalable model serving library built on the Ray framework that enables deploying and managing machine learning models in production.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RMF Distributed Data Server Target entity description: RMF Distributed Data Server is a z/OS component that collects, consolidates, and serves performance and resource usage data from multiple systems for monitoring and analysis.
-
A.
TimesTen
TimesTen is an in-memory relational database from Oracle designed for extremely low-latency, high-throughput data management and real-time analytics.
-
B.
RethinkDB
RethinkDB is an open-source, distributed NoSQL database designed for real-time applications by pushing live updates to clients as data changes.
-
C.
Caché
Caché is a tributary stream that feeds into the Bléone River in southeastern France.
-
D.
Jepsen
Jepsen is a surname most notably associated with individuals such as display technology innovator Mary Lou Jepsen.
-
E.
Ray Serve
Ray Serve is a scalable model serving library built on the Ray framework that enables deploying and managing machine learning models in production.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
performance monitoring server
ⓘ
z/OS component ⓘ |
| abbreviation | RMF DDS NERFINISHED ⓘ |
| accesses |
RMF Monitor III data
ⓘ
RMF Postprocessor data ⓘ |
| collects |
performance data
ⓘ
resource usage data ⓘ |
| collectsFrom | multiple z/OS systems ⓘ |
| configurationScope |
sysplex-wide
ⓘ
system-wide ⓘ |
| consolidates | performance data from multiple systems ⓘ |
| designedFor | z/OS sysplex environments ⓘ |
| developedBy | IBM NERFINISHED ⓘ |
| documentedIn |
IBM RMF User’s Guide
NERFINISHED
ⓘ
IBM z/OS MVS System Management Facilities documentation NERFINISHED ⓘ |
| enables |
cross-system performance views
ⓘ
near real-time performance monitoring ⓘ |
| exposes | RMF performance metrics ⓘ |
| integratesWith |
RMF Monitor I
NERFINISHED
ⓘ
RMF Monitor II NERFINISHED ⓘ RMF Monitor III NERFINISHED ⓘ |
| monitorsResource |
CPU utilization
ⓘ
I/O activity ⓘ storage usage ⓘ workload manager (WLM) performance ⓘ |
| partOf | Resource Measurement Facility NERFINISHED ⓘ |
| provides |
centralized performance data access
ⓘ
machine-readable performance data ⓘ standardized performance data interface ⓘ |
| requires | RMF to be active on z/OS ⓘ |
| runsOn | IBM z/OS NERFINISHED ⓘ |
| serves | performance data to monitoring tools ⓘ |
| supports |
Sysplex-wide data aggregation
ⓘ
capacity planning ⓘ historical performance analysis ⓘ performance analysis ⓘ trend analysis ⓘ workload monitoring ⓘ |
| supportsClient |
RMF PM (Performance Monitoring) clients
ⓘ
web-based monitoring applications ⓘ |
| supportsSecurity |
RACF-based access control
ⓘ
z/OS security mechanisms ⓘ |
| usedFor |
automation of performance reporting
ⓘ
integration with external monitoring frameworks ⓘ |
| usesProtocol |
HTTP
ⓘ
REST-like interfaces ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: RMF Distributed Data Server Description of subject: RMF Distributed Data Server is a z/OS component that collects, consolidates, and serves performance and resource usage data from multiple systems for monitoring and analysis.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.