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fix a few things in the readme #2025

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Aug 21, 2018
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fix a few things in the readme #2025

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543ff4e
fix a few things in the readme
bpownow Aug 20, 2018
7dde536
customize --> kustomize again
bpownow Aug 21, 2018
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8 changes: 4 additions & 4 deletions README.md
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Expand Up @@ -25,11 +25,11 @@ sudo docker run \

cAdvisor is now running (in the background) on `http://localhost:8080`. The setup includes directories with Docker state cAdvisor needs to observe.

**Note**: If you're running on CentOS, Fedora, RHEL, or are using LXC take a look at our [running instructions](docs/running.md).
**Note**: If you're running on CentOS, Fedora, or RHEL (or are using LXC), take a look at our [running instructions](docs/running.md).

We have detailed [instructions](docs/running.md#standalone) on running cAdvisor standalone outside of Docker. cAdvisor [running options](docs/runtime_options.md) may also be interesting for advanced usecases. If you want to build your own cAdvisor Docker image see our [deployment](docs/deploy.md) page.
We have detailed [instructions](docs/running.md#standalone) on running cAdvisor standalone outside of Docker. cAdvisor [running options](docs/runtime_options.md) may also be interesting for advanced usecases. If you want to build your own cAdvisor Docker image, see our [deployment](docs/deploy.md) page.

For [Kubernetes](https://github.com/kubernetes/kubernetes) users, cAdvisor can be run as a daemonset. See the [instructions](deploy/kubernetes) for how to get started, and for how to kustomize it to fit your needs.
For [Kubernetes](https://github.com/kubernetes/kubernetes) users, cAdvisor can be run as a daemonset. See the [instructions](deploy/kubernetes) for how to get started, and for how to [kustomize](https://github.com/kubernetes-sigs/kustomize#kustomize) it to fit your needs.

## Building and Testing

Expand All @@ -56,7 +56,7 @@ There is also an official Go client implementation in the [client](client/) dire
## Roadmap

cAdvisor aims to improve the resource usage and performance characteristics of running containers. Today, we gather and expose this information to users. In our roadmap:
- Advise on the performance of a container (e.g.: when it is being negatively affected by another, when it is not receiving the resources it requires, etc)
- Advise on the performance of a container (e.g.: when it is being negatively affected by another, when it is not receiving the resources it requires, etc).
- Auto-tune the performance of the container based on previous advise.
- Provide usage prediction to cluster schedulers and orchestration layers.

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