feat(server): add SSR React rendering summary metric #991
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https://github.com/americanexpress/one-app/actions/runs/4919317274/jobs/8786780018?pr=991 appears to be unrelated to the changes made? |
| const ssrNamespace = createMetricNamespace('ssr'); | ||
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| createSummary({ | ||
| name: ssrNamespace('react_rendering', 'seconds'), |
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are we tracking this in seconds or miliseconds?
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seconds is the base unit of time for metrics:
https://prometheus.io/docs/practices/naming/#base-units
from what I can tell they attempt to follow SI https://en.wikipedia.org/wiki/International_System_of_Units
side note: Grafana is used by a lot of different teams, at least one rocket company uses it for their launches (Astra, IIRC)
Yeah: #994 |
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| function createSummary(opts) { | ||
| const { name } = opts; | ||
| if (summaries[name]) { |
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this is great for safety but it's hidden, we should instead throw an error as in startSummaryTimer
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🤔 mirrors counters.js & gauges.js, maybe a subsequent PR?
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ok not a big deal but would be cleaner
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| const ssrNamespace = createMetricNamespace('ssr'); | ||
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| createSummary({ |
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shouldn't the user call this function?
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user?
FWIW following the existing pattern, i.e. src/server/metrics/holocron.js and src/server/utils/pollModuleMap.js
there might be a better way of managing the metrics, but IMO would be best to do that refactor in a different PR rather than block this metric?
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by user i mean the entity consuming it (in this case, the dev). If we are following a pattern then ok we could improve the code later
Description
Add a
oneapp_ssr_react_rendering_secondssummary metric split byrenderMethodNamelabel.Motivation and Context
Server-Side Rendering (SSR) can be resource intensive. It is useful to operators to know a bit more about the time taken to render the HTML via React.
How Has This Been Tested?
Run locally, comparing manual timers (
process.hrtime.bigint) to the values visible inhttp://localhost:3005/metrics.Types of Changes
Checklist:
What is the Impact to Developers Using One App?
DevOps has more telemetry to track server utilization to aid SSR efficiency in modules and possible server scaling.