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Fix few typos in readme

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Simon Podlipsky
2021-06-04 10:31:52 +02:00
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README.md
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@ -24,7 +24,7 @@ This work is a fork of a previous [open-source GoFlow code](https://github.com/c
It lives in its own GitHub organization to be maintained more easily.
Among the differences with the original code:
The serializer and transport options have been revamped to make this program more user friendly.
The serializer and transport options have been revamped to make this program more user-friendly
and target new use-cases like logging providers.
Minimal changes in the decoding libraries.
@ -46,17 +46,17 @@ send it to a file (or stdout).
GoFlow2 is a wrapper of all the functions and chains thems.
You can build your own collector using this base and replace parts:
* Use different transport (eg: RabbitMQ instead of Kafka)
* Convert to another format (eg: Cap'n Proto, Avro, instead of protobuf)
* Decode different samples (eg: not only IP networks, add MPLS)
* Different metrics system (eg: [OpenTelemetry](https://opentelemetry.io/))
* Use different transport (e.g: RabbitMQ instead of Kafka)
* Convert to another format (e.g: Cap'n Proto, Avro, instead of protobuf)
* Decode different samples (e.g: not only IP networks, add MPLS)
* Different metrics system (e.g: [OpenTelemetry](https://opentelemetry.io/))
### Protocol difference
The sampling protocols have distinct features:
**sFlow** is a stateless protocol which sends the full header of a packet with router information
(interfaces, destination AS) while **NetFlow/IPFIX** rely on templates that contain fields (eg: source IPv6).
(interfaces, destination AS) while **NetFlow/IPFIX** rely on templates that contain fields (e.g: source IPv6).
The sampling rate in NetFlow/IPFIX is provided by **Option Data Sets**. This is why it can take a few minutes
for the packets to be decoded until all the templates are received (**Option Template** and **Data Template**).
@ -65,7 +65,7 @@ Both of these protocols bundle multiple samples (**Data Set** in NetFlow/IPFIX a
in one packet.
The advantages of using an abstract network flow format, such as protobuf, is it enables summing over the
protocols (eg: per ASN or per port, rather than per (ASN, router) and (port, router)).
protocols (e.g: per ASN or per port, rather than per (ASN, router) and (port, router)).
To read more about the protocols and how they are mapped inside, check out [page](/docs/protocols.md)
@ -89,7 +89,7 @@ Monitoring via Prometheus metrics
To read about agents that samples network traffic, check this [page](/docs/agents.md).
To setup the collector, download the latest release corresponding to your OS
To set up the collector, download the latest release corresponding to your OS
and run the following command (the binaries have a suffix with the version):
```bash
@ -132,7 +132,7 @@ By default, the samples received will be printed in JSON format on the stdout.
}
```
If you are using a log integration (eg: Loki with Promtail, Splunk, Fluentd, Google Cloud Logs, etc.),
If you are using a log integration (e.g: Loki with Promtail, Splunk, Fluentd, Google Cloud Logs, etc.),
just send the output into a file.
```bash
$ ./goflow2 -transport.file /var/logs/goflow2.log
@ -162,7 +162,7 @@ $ sudo docker run -p 6343:6343/udp -p 2055:2055/udp -ti netsampler/goflow2:lates
The JSON format is advised only when consuming a small amount of data directly.
For bigger workloads, the protobuf output format provides a binary representation
and is preferred.
It can also be extended wtih enrichment as long as the user keep the same IDs.
It can also be extended with enrichment as long as the user keep the same IDs.
If you want to develop applications, build `pb/flow.proto` into the language you want:
When adding custom fields, picking a field ID ≥ 1000 is suggested.
@ -208,8 +208,8 @@ Are you using GoFlow2 in production at scale? Add yourself here!
### Contributions
This project welcomes pull-requests, wether it's documentation,
instrumentation (eg: docker-compose, metrics), internals (protocol libraries),
This project welcomes pull-requests, whether it's documentation,
instrumentation (e.g: docker-compose, metrics), internals (protocol libraries),
integration (new CLI feature) or else!
Just make sure to check for the use-cases via an issue.