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Add content/es/docs/debug-application-cluster/resource-metrics-pipeline.md #13648

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87 changes: 87 additions & 0 deletions content/es/docs/tasks/_index.md
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---
title: Tasks
main_menu: true
weight: 50
content_template: templates/concept
---

{{< toc >}}

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This section of the Kubernetes documentation contains pages that
show how to do individual tasks. A task page shows how to do a
single thing, typically by giving a short sequence of steps.

{{% /capture %}}

{{% capture body %}}

## Web UI (Dashboard)

Deploy and access the Dashboard web user interface to help you manage and monitor containerized applications in a Kubernetes cluster.

## Using the kubectl Command-line

Install and setup the `kubectl` command-line tool used to directly manage Kubernetes clusters.

## Configuring Pods and Containers

Perform common configuration tasks for Pods and Containers.

## Running Applications

Perform common application management tasks, such as rolling updates, injecting information into pods, and horizontal Pod autoscaling.

## Running Jobs

Run Jobs using parallel processing.

## Accessing Applications in a Cluster

Configure load balancing, port forwarding, or setup firewall or DNS configurations to access applications in a cluster.

## Monitoring, Logging, and Debugging

Setup monitoring and logging to troubleshoot a cluster or debug a containerized application.

## Accessing the Kubernetes API

Learn various methods to directly access the Kubernetes API.

## Using TLS

Configure your application to trust and use the cluster root Certificate Authority (CA).

## Administering a Cluster

Learn common tasks for administering a cluster.

## Administering Federation

Configure components in a cluster federation.

## Managing Stateful Applications

Perform common tasks for managing Stateful applications, including scaling, deleting, and debugging StatefulSets.

## Cluster Daemons

Perform common tasks for managing a DaemonSet, such as performing a rolling update.

## Managing GPUs

Configure and schedule NVIDIA GPUs for use as a resource by nodes in a cluster.

## Managing HugePages

Configure and schedule huge pages as a schedulable resource in a cluster.

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If you would like to write a task page, see
[Creating a Documentation Pull Request](/docs/home/contribute/create-pull-request/).

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5 changes: 5 additions & 0 deletions content/es/docs/tasks/debug-application-cluster/_index.md
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title: "Monitoring, Logging, and Debugging"
weight: 80
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reviewers:
- raelga
title: Pipeline de métricas de recursos
content_template: templates/concept
---

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Desde Kubernetes 1.8, las métricas de uso de recursos, tales como el uso de CPU y memoria del contenedor,
están disponibles en Kubernetes a través de la API de métricas. Estas métricas son accedidas directamente
por el usuario, por ejemplo usando el comando `kubectl top`, o usadas por un controlador en el cluster,
por ejemplo el Horizontal Pod Autoscaler, para la toma de decisiones.

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## La API de Métricas

A través de la API de métricas, Metrics API en inglés, puedes obtener la cantidad de recursos usados
actualmente por cada nodo o pod. Esta API no almacena los valores de las métricas,
así que no es posible, por ejemplo, obtener la cantidad de recursos que fueron usados por
un nodo hace 10 minutos.

La API de métricas está completamente integrada en la API de Kubernetes:

- se expone a través del mismo endpoint que las otras APIs de Kubernetes bajo el path `/apis/metrics.k8s.io/`
- ofrece las mismas garantías de seguridad, escalabilidad y confiabilidad

La API está definida en el repositorio [k8s.io/metrics](https://github.com/kubernetes/metrics/blob/master/pkg/apis/metrics/v1beta1/types.go). Puedes encontrar
más información sobre la API ahí.

{{< note >}}
La API requiere que el servidor de métricas esté desplegado en el clúster. En otro caso no estará
disponible.
{{< /note >}}

## Servidor de Métricas

El [Servidor de Métricas](https://github.com/kubernetes-incubator/metrics-server) es un agregador
de datos de uso de recursos de todo el clúster.
A partir de Kubernetes 1.8, el servidor de métricas se despliega por defecto como un objeto de
tipo [Deployment](https://github.com/docs/concepts/workloads/controllers/deployment/) en clústeres
creados con el script `kube-up.sh`. Si usas otro mecanismo de configuración de Kubernetes, puedes desplegarlo
usando los [yamls de despliegue](https://github.com/kubernetes-incubator/metrics-server/tree/master/deploy)
proporcionados. Está soportado a partir de Kubernetes 1.7 (más detalles al final).

El servidor reune métricas de la Summary API, que es expuesta por el [Kubelet](/docs/admin/kubelet/) en cada nodo.

El servidor de métricas se añadió a la API de Kubernetes utilizando el
[Kubernetes aggregator](/docs/concepts/api-extension/apiserver-aggregation/) introducido en Kubernetes 1.7.

Puedes aprender más acerca del servidor de métricas en el [documento de diseño](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/metrics-server.md).

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