Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Updated translations - (machine translation) #19827

Merged
merged 2 commits into from
Jan 31, 2025
Merged

Updated translations - (machine translation) #19827

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
141223a
chore: add translations
svc-docs-eng-opensource-bot Jan 29, 2025
8f63fc0
fix: verify-mdx fix
gmanandhar-nr Jan 30, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
60 changes: 33 additions & 27 deletions ...m-integrations/gcp-integrations-list/google-vertexai-monitoring-integration.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -686,17 +686,19 @@ This integration collects GCP data for VertexAI.

<table>
<thead>
<th>
Metric
</th>
<tr>
<th>
Metric
</th>

<th>
Unit
</th>
<th>
Unit
</th>

<th>
Description
</th>
<th>
Description
</th>
</tr>
</thead>

<tbody>
Expand Down Expand Up @@ -790,17 +792,19 @@ This integration collects GCP data for VertexAI.

<table>
<thead>
<th>
Metric
</th>
<tr>
<th>
Metric
</th>

<th>
Unit
</th>
<th>
Unit
</th>

<th>
Description
</th>
<th>
Description
</th>
</tr>
</thead>

<tbody>
Expand Down Expand Up @@ -852,17 +856,19 @@ This integration collects GCP data for VertexAI.

<table>
<thead>
<th>
Metric
</th>
<tr>
<th>
Metric
</th>

<th>
Unit
</th>
<th>
Unit
</th>

<th>
Description
</th>
<th>
Description
</th>
</tr>
</thead>

<tbody>
Expand Down
6 changes: 3 additions & 3 deletions src/i18n/content/es/docs/apis/rest-api-v2/migrate-to-nrql.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -60,21 +60,21 @@ FROM Metric
WHERE appId = $APP_ID AND metricTimesliceName = 'HttpDispatcher'
```

| Valor (RPM) | Función NRQL | | -------------------------- | ------------------------------------------------------------------------------------------------- | | `average_response_time` | `average(newrelic.timeslice.value) * 1000` | | `calls_per_minute` | `rate(count(newrelic.timeslice.value), 1 minute)` | | `call_count` | `count(newrelic.timeslice.value)` | | `min_response_time` | `min(newrelic.timeslice.value) * 1000` | | `max_response_time` | `max(newrelic.timeslice.value) * 1000` | | `average_exclusive_time` | `average(newrelic.timeslice.value['totalExclusive'] / newrelic.timeslice.value['count']) * 1000` | | `average_value` | `average(newrelic.timeslice.value)` | | `total_call_time_per_minute` | `rate(sum(newrelic.timeslice.value), 1 minute)` | | `requests_per_minute` | `rate(count(newrelic.timeslice.value), 1 minute)` | | `standard_deviation` | `stddev(newrelic.timeslice.value) * 1000` | | `average_time` | `average(newrelic.timeslice.value) * 1000` | | `count` | `count(newrelic.timeslice.value)` | | `used_bytes_by_host` | `average(newrelic.timeslice.value) * 1024 * 1024` | | `used_mb_by_host` | `average(newrelic.timeslice.value)` | | `total_used_mb` | `sum(newrelic.timeslice.value)` | | `average_call_time` | `average(newrelic.timeslice.value) * 1000` | | `total_value` | `sum(newrelic.timeslice.value)` | | `min_value` | `min(newrelic.timeslice.value)` | | `max_value` | `max(newrelic.timeslice.value)` | | `rate` | `rate(sum(newrelic.timeslice.value), 1 second)` | | `throughput` | `rate(count(newrelic.timeslice.value), 1 second)` | | `as_percentage` | `average(newrelic.timeslice.value) * 100` | | `errors_per_minute` | `rate(count(newrelic.timeslice.value), 1 minute)` | | `error_count` | `count(newrelic.timeslice.value)` | | `total_time` | `sum(newrelic.timeslice.value) * 1000` | | `sessions_active` | `average(newrelic.timeslice.value)` | | `total_visits` | `sum(newrelic.timeslice.value)` | | `percent` | `average(newrelic.timeslice.value) * 100` | | `percent(CPU/User Time)` | `100 * sum(newrelic.timeslice.value) / $TIME_WINDOW_IN_SECONDS` | | `time_percentage` | `100 * sum(newrelic.timeslice.value) / $TIME_WINDOW_IN_SECONDS` | | `utilization` | `100 * sum(newrelic.timeslice.value) / $TIME_WINDOW_IN_SECONDS` | | `visits_percentage` | `100 * sum(newrelic.timeslice.value) / $TIME_WINDOW_IN_SECONDS` |
\| Valor (RPM) | Función NRQL | | -------------------------- | ------------------------------------------------------------------------------------------------- | | `average_response_time` | `average(newrelic.timeslice.value) * 1000` | | `calls_per_minute` | `rate(count(newrelic.timeslice.value), 1 minute)` | | `call_count` | `count(newrelic.timeslice.value)` | | `min_response_time` | `min(newrelic.timeslice.value) * 1000` | | `max_response_time` | `max(newrelic.timeslice.value) * 1000` | | `average_exclusive_time` | `average(newrelic.timeslice.value['totalExclusive'] / newrelic.timeslice.value['count']) * 1000` | | `average_value` | `average(newrelic.timeslice.value)` | | `total_call_time_per_minute` | `rate(sum(newrelic.timeslice.value), 1 minute)` | | `requests_per_minute` | `rate(count(newrelic.timeslice.value), 1 minute)` | | `standard_deviation` | `stddev(newrelic.timeslice.value) * 1000` | | `average_time` | `average(newrelic.timeslice.value) * 1000` | | `count` | `count(newrelic.timeslice.value)` | | `used_bytes_by_host` | `average(newrelic.timeslice.value) * 1024 * 1024` | | `used_mb_by_host` | `average(newrelic.timeslice.value)` | | `total_used_mb` | `sum(newrelic.timeslice.value)` | | `average_call_time` | `average(newrelic.timeslice.value) * 1000` | | `total_value` | `sum(newrelic.timeslice.value)` | | `min_value` | `min(newrelic.timeslice.value)` | | `max_value` | `max(newrelic.timeslice.value)` | | `rate` | `rate(sum(newrelic.timeslice.value), 1 second)` | | `throughput` | `rate(count(newrelic.timeslice.value), 1 second)` | | `as_percentage` | `average(newrelic.timeslice.value) * 100` | | `errors_per_minute` | `rate(count(newrelic.timeslice.value), 1 minute)` | | `error_count` | `count(newrelic.timeslice.value)` | | `total_time` | `sum(newrelic.timeslice.value) * 1000` | | `sessions_active` | `average(newrelic.timeslice.value)` | | `total_visits` | `sum(newrelic.timeslice.value)` | | `percent` | `average(newrelic.timeslice.value) * 100` | | `percent(CPU/User Time)` | `100 * sum(newrelic.timeslice.value) / $TIME_WINDOW_IN_SECONDS` | | `time_percentage` | `100 * sum(newrelic.timeslice.value) / $TIME_WINDOW_IN_SECONDS` | | `utilization` | `100 * sum(newrelic.timeslice.value) / $TIME_WINDOW_IN_SECONDS` | | `visits_percentage` | `100 * sum(newrelic.timeslice.value) / $TIME_WINDOW_IN_SECONDS` |

Si la función incluye `$TIME_WINDOW_IN_SECONDS`, significa que debes reemplazarla con la ventana de tiempo que deseas consultar.

Por ejemplo, si consulta un intervalo de tiempo de 30 minutos, reemplazará `$TIME_WINDOW_IN_SECONDS` por `1800`.

### Apdex métricas

| Valor (RPM) | Función NRQL | | ------------- | ---------------------------------------------------------------------------------- | | `score` | `apdex(newrelic.timeslice.value)` | | `s` | `apdex(newrelic.timeslice.value)` o `count(newrelic.timeslice.value)` | | `t` | `apdex(newrelic.timeslice.value)` o `sum(newrelic.timeslice.value)` | | `f` | `apdex(newrelic.timeslice.value)` o `sum(newrelic.timeslice.value['totalExclusive'])`| | `count` | `apdex(newrelic.timeslice.value)` | | `value` | `apdex(newrelic.timeslice.value)` | | `threshold` | `max(newrelic.timeslice.value)` | | `threshold_min` | `min(newrelic.timeslice.value)` |
\| Valor (RPM) | Función NRQL | | ------------- | ---------------------------------------------------------------------------------- | | `score` | `apdex(newrelic.timeslice.value)` | | `s` | `apdex(newrelic.timeslice.value)` o `count(newrelic.timeslice.value)` | | `t` | `apdex(newrelic.timeslice.value)` o `sum(newrelic.timeslice.value)` | | `f` | `apdex(newrelic.timeslice.value)` o `sum(newrelic.timeslice.value['totalExclusive'])`| | `count` | `apdex(newrelic.timeslice.value)` | | `value` | `apdex(newrelic.timeslice.value)` | | `threshold` | `max(newrelic.timeslice.value)` | | `threshold_min` | `min(newrelic.timeslice.value)` |

### Métricas para EndUser &amp; Mobile

Estas métricas devolverán el mismo resultado que obtendría de la REST API v2, pero algunos resultados pueden diferir de lo que ve en la New Relic UI. Esto se debe a que la UI emplea evento en lugar de datos de intervalo de tiempo. Si desea obtener los mismos resultados que la UI, debe consultar el evento directamente.

| Valor (RPM) | Función NRQL | | ----------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | `average_response_time` | `sum(newrelic.timeslice.value) / count(newrelic.timeslice.value) * 1000 `| | `error_percentage` | `(filter(count(newrelic.timeslice.value), WHERE metricTimesliceName = 'EndUser/errors') / filter(count(newrelic.timeslice.value), WHERE metricTimesliceName = 'Browser'))`| | `average_fe_response_time` | `sum(newrelic.timeslice.value['totalExclusive']) / count(newrelic.timeslice.value) * 1000` | | `average_be_response_time` | `1000 * (sum(newrelic.timeslice.value) - sum(newrelic.timeslice.value['totalExclusive'])) / count(newrelic.timeslice.value)` | | `average_network_time` | `(sum(newrelic.timeslice.value) - sum(newrelic.timeslice.value['totalExclusive']) - sum(newrelic.timeslice.value['sumOfSquares'])) / count(newrelic.timeslice.value)` | | `total_network_time` | `(sum(newrelic.timeslice.value) - sum(newrelic.timeslice.value['totalExclusive']) - sum(newrelic.timeslice.value['sumOfSquares']))` | | `network_time_percentage` | `(sum(newrelic.timeslice.value) - sum(newrelic.timeslice.value['totalExclusive']) - sum(newrelic.timeslice.value['sumOfSquares'])) / $TIME_WINDOW_IN_SECONDS` | | `total_fe_time` | `sum(newrelic.timeslice.value['totalExclusive'])` | | `fe_time_percentage` | `100 * sum(newrelic.timeslice.value['totalExclusive']) / $TIME_WINDOW_IN_SECONDS` | | `average_dom_content_load_time` | `average(newrelic.timeslice.value) * 1000` | | `average_queue_time` | `average(newrelic.timeslice.value['totalExclusive']) * 1000` | | `total_queue_time` | `sum(newrelic.timeslice.value['totalExclusive']) * 1000` | | `total_dom_content_time` | `sum(newrelic.timeslice.value) * 1000` | | `total_app_time` | `sum(newrelic.timeslice.value['sumOfSquares'])` | | `average_app_time` | `sum(newrelic.timeslice.value['sumOfSquares']) / count(newrelic.timeslice.value)` | | `average_sent_bytes` | `sum(newrelic.timeslice.value['totalExclusive']) * 1000` | | `average_received_bytes` | `1000 * sum(newrelic.timeslice.value) / count(newrelic.timeslice.value)` | | `launch_count` | `count(newrelic.timeslice.value)` |
\| Valor (RPM) | Función NRQL | | ----------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | `average_response_time` | `sum(newrelic.timeslice.value) / count(newrelic.timeslice.value) * 1000 `| | `error_percentage` | `(filter(count(newrelic.timeslice.value), WHERE metricTimesliceName = 'EndUser/errors') / filter(count(newrelic.timeslice.value), WHERE metricTimesliceName = 'Browser'))`| | `average_fe_response_time` | `sum(newrelic.timeslice.value['totalExclusive']) / count(newrelic.timeslice.value) * 1000` | | `average_be_response_time` | `1000 * (sum(newrelic.timeslice.value) - sum(newrelic.timeslice.value['totalExclusive'])) / count(newrelic.timeslice.value)` | | `average_network_time` | `(sum(newrelic.timeslice.value) - sum(newrelic.timeslice.value['totalExclusive']) - sum(newrelic.timeslice.value['sumOfSquares'])) / count(newrelic.timeslice.value)` | | `total_network_time` | `(sum(newrelic.timeslice.value) - sum(newrelic.timeslice.value['totalExclusive']) - sum(newrelic.timeslice.value['sumOfSquares']))` | | `network_time_percentage` | `(sum(newrelic.timeslice.value) - sum(newrelic.timeslice.value['totalExclusive']) - sum(newrelic.timeslice.value['sumOfSquares'])) / $TIME_WINDOW_IN_SECONDS` | | `total_fe_time` | `sum(newrelic.timeslice.value['totalExclusive'])` | | `fe_time_percentage` | `100 * sum(newrelic.timeslice.value['totalExclusive']) / $TIME_WINDOW_IN_SECONDS` | | `average_dom_content_load_time` | `average(newrelic.timeslice.value) * 1000` | | `average_queue_time` | `average(newrelic.timeslice.value['totalExclusive']) * 1000` | | `total_queue_time` | `sum(newrelic.timeslice.value['totalExclusive']) * 1000` | | `total_dom_content_time` | `sum(newrelic.timeslice.value) * 1000` | | `total_app_time` | `sum(newrelic.timeslice.value['sumOfSquares'])` | | `average_app_time` | `sum(newrelic.timeslice.value['sumOfSquares']) / count(newrelic.timeslice.value)` | | `average_sent_bytes` | `sum(newrelic.timeslice.value['totalExclusive']) * 1000` | | `average_received_bytes` | `1000 * sum(newrelic.timeslice.value) / count(newrelic.timeslice.value)` | | `launch_count` | `count(newrelic.timeslice.value)` |

### Seriales temporales y resúmenes

Expand Down
Loading
Loading