To both assess the efficacy of the SRDP capabilities, the usage patterns, and drive decision making based on informed data we will rely on metrics throughout the project.


Note: Unless otherwise noted collected metrics should be available on weekly, monthly, semester and cumulative timescales.

Status Progression

DISCUSS Ongoing discussion

PROPOSED Ready to become a requirement, approvals pending

RQT: WAVE 1 Now an official requirement

COMPLETE Implemented and in use

Archive Content Metrics

DescriptionPurposeTraceabilityStatus
Report the number and volume of calibration results ingested to the archiveTrack usage of space and coverage of SRDP product in the archive.TUC02.5.1

RQT: WAVE 1

Report the number and volume of Execution Blocks ingested in the archive (differentiate those from PI projects from system)Overall Archive utilization

PROPOSED

Report the number and volume of image products ingested to the archive (differentiate by telescope and collection)Track usage of space and coverage of SRDP product in the archive.

PROPOSED

Report the number and volume of data products reingested into the archive as a result of QA processes on data products already delivered (QA3) or reprocessing with better pipelines.

Track usage of space in the archive.

Determine whether data replacement method should involve removal of old products, or their retention as deprecated items.

New

PROPOSED

Archive Usage Metrics

Unless otherwise noted all requirements should be  reported both as the number of primary products and the total data volume.

DescriptionPurposeTraceabilityStatus
Number of registered users that download each type of product.This metric as different from the total download volume allows us to determine how widespread the SRDP user community is.TUC12.5.1

RQT: WAVE 1

Total number of product downloads of each type (including anonymous users). This should be both a total number and a number per collection.Total volume of data and products going out is one of the key performance indicators for the project.TUC12.5.1

RQT: WAVE 1

Number of products downloaded by a member of the observing team, both during and after the product proprietary period

Understand data reuse and other usage patterns.TUC12.5.1

RQT: WAVE 1

Method of Data DeliveryUnderstand how users prefer to access data, deprecate unused methods.TUC12.5.1

RQT: WAVE 1

Number of products downloaded by users not on original observing teams from particular projects. (JT)Understand impact, legacy value, and community interest in data from particular projects, thinking more about large projects.

Capability Usage Metrics

DescriptionPurposeTraceabilityStatus
Report the number of times the standard calibration pipeline was triggered.

Determine overall usage of the pipeline.

Normalize error reporting and other pipeline related reports.

TUC02.5.1

RQT: WAVE 1

Number and type of customization choices made by the user as part of the download from the archive.

Understand usage patterns, gauge interest for various options

Understand resource implications of capabilities

TUC12.5.1

RQT: WAVE 1

Number of times (by telescope) each capability is triggered and the options set

Guide development of new capabilities, ensure delivered capabilities are useful



PROPOSED

Physical location of pipeline runsCV, NM, XSEDE, AWS, PartnerX etcNew

PROPOSED

Workflow Metrics

DescriptionPurposeTraceabilityStatus
Report the number of times (and reason) that the standard products required intervention before passing QA.

Gauge efficienciency and maturity of pipeline.

Estimate effort required for QA in future performance periods.

TUC02.5.1

RQT: WAVE 1

The number of times that a pipeline failed to produce a valid product and needed to switched to manual.Understand the success rate of the pipeline to mediate between additional modes and increased robustness.New

PROPOSED

Duration of each pipeline run (wall clock)Monitoring of computing resource usageNew

PROPOSED

Number of cores for each pipeline runMonitoring of computing resource usageNew

PROPOSED

Memory allocation for each pipeline runMonitoring of computing resource usageNew

PROPOSED

Time needed to flag data for calibration (if any)Monitoring of human and computing resource usageNew

PROPOSED

Time taken for weblog review of each pipeline runMonitoring of human resource usageNew

PROPOSED

Data volume of products from each pipeline runMonitoring of computing/archive resource usageNew

PROPOSED

Time spent on queue before executionResource Estimation and Management

PROPOSED

Total Elapsed time between submission and deliveryUser Experience Monitoring

PROPOSED

Product Quality Metrics

DescriptionPurposeTraceabilityStatus
Report the number of times that calibrations are reported by the PI as deficient.

Gauge efficiency and maturity of pipeline.

Estimate effort required for QA in future performance periods.

Monitor the rate of bad data released by the SRDP project.

TUC02.5.1

RQT: WAVE 1

Report the number of times that image products are reported by the PI as deficient and the final disposition (not sufficient for science, bad pipeline, PI Education)

Gauge efficiency and maturity of pipeline.

Estimate effort required for QA in future performance periods.

Monitor the rate of bad data released by the SRDP project.

New

PROPOSED

Report the number of times that pipeline runs are rerun as a result of an error being discovered in the pipeline or observational data/metadata by NRAO staff (after delivery to the PI).

Monitor the rate of bad data released by the SRDP project.

Help estimate resource requirements for reprocessing of large volumes of data.

New

PROPOSED

Report number of pipeline runs needed on a dataset before delivery to the PI (for flagging, or tweaking of pipeline parameters to produce a satisfactory result)

Gauge efficiency and maturity of pipeline.

Monitoring of human and computing resource usage

New

PROPOSED





Deployment Metrics

DescriptionPurposeTraceabilityStatus
Average and peak number of simultaneous users (Archive and Workflow frontends)Resource estimation, load balancingNew

PROPOSED

MTBF, MTTRService uptime reporting, reliability.New

PROPOSED

Average and peak number of each capability execution.Resource estimation, load balancing (might be redundant, but can be quite resource intensive depending on dataset)New

PROPOSED





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2 Comments

  1. We probably also need one to describe the sizes of the queues for processing at each site (I guess that would be a deployment metric).

  2. As Claire pointed out in the Ops review (SRDP-320) publication metrics would also be very interesting. The NRAO library usually is responsible for these, but noting them here for completeness.