More small modifications to docs

For large catalogs, this can result in THREDDS pods taking an hour or more to start. This is not

merely an inconvenience - in order to benefit from advanced features in Kubernetes such as

recovery from failure and demand-based auto-scaling, pods must start quickly in order to begin

recovery from failure and demand-based autoscaling, pods must start quickly in order to begin

taking load as soon as possible. There are two things that can be done to address this problem:

  * Keep a copy of the catalogs on the local disk of each node that may have THREDDS pods scheduled

it is possible to integrate other metrics gathering systems, such as [Prometheus](https://prometheus.io/),

to allow scaling based on any of the collected metrics (e.g. network I/O, requests per second).

The ESGF Helm chart allows `HorizontalPodAutoscaler` resources to be defined for the THREDDS and Nginx file

server components using the `data.{thredds,fileServer}.hpa` variables. These variables define the `spec`

section of the HPA, except for the `scaleTargetRef` section which is automatically populated with the correct

reference. For more information about HPA configuration, see the

By default, autoscaling is disabled in the ESGF Helm chart. To enable autoscaling for the THREDDS and

Nginx file server components, the chart allows `HorizontalPodAutoscaler` resources to be defined using

the `data.{thredds,fileServer}.hpa` variables. These variables define the `spec` section of the HPA, except

for the `scaleTargetRef` section which is automatically populated with the correct reference.

For more information about HPA configuration, see the

[Kubernetes HPA Walkthrough](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/).

> **WARNING**

              type: Utilization

              averageUtilization: 80

```

By default, autoscaling is not enabled.