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Custom

In this guide, we'll learn how to send your custom logs to Dassana. Currently, Dassana can ingest the following log formats: nd-json, json object, and csv. We've also included instructions for configuring log aggregators such as Fluentd and Vector to stream your logs to Dassana.

Log Types

nd-json

curl https://ingestion.dassana.cloud/logs \
-X POST \
-H 'Content-type: application/x-ndjson' \
-H 'x-dassana-app-id: YOUR_APP_ID' \
-H 'x-dassana-token: YOUR_DASSANA_TOKEN' \
--data-binary '{"foo": "bar"}
{"bar": "baz"}
{"baz": "qux"}'

More info on the nd-json format can be found here.

Additional Headers

To send gzipped data, add the following headers:

Content-Encoding: gzip
Accept-Encoding: gzip

{
"Records": [...]
}

If your events are encapsulated in an object (as seen above), add a x-dassana-data-key: Records header so that the array of events can be processed accordingly.

csv

There are two CSV data types we support: data with headers and without. For example:

time,duration,SrcDevice,DstDevice,Protocol,SrcPort,DstPort,SrcPackets,DstPackets,SrcBytes,SrcBytes
761,4434,Comp132598,Comp817788,6,Port12597,22,89159,85257,15495068,69768940
764,13161,Comp178973,Comp164069,17,137,137,325,0,30462,0
765,14369,Comp492856,Mail,6,Port30344,443,227,214,32300,9844
765,14431,Comp782574,Mail,6,Port28068,443,1637,3313,75302,1220077

The above data contains headers on the first line. If your CSV data is of this type, ingest the data as follows:

curl https://ingestion.dassana.cloud/logs?withHeader=true \
-X POST \
-H 'Content-type: text/csv' \
-H 'x-dassana-app-id: YOUR_APP_ID' \
-H 'x-dassana-token: YOUR_DASSANA_TOKEN' \
--data-binary @foo.csv

If your data does not contain headers, for example:

761,4434,Comp132598,Comp817788,6,Port12597,22,89159,85257,15495068,69768940
764,13161,Comp178973,Comp164069,17,137,137,325,0,30462,0
765,14369,Comp492856,Mail,6,Port30344,443,227,214,32300,9844
765,14431,Comp782574,Mail,6,Port28068,443,1637,3313,75302,1220077

Explicity include the headers in the csvHeader parameter to ingest as follows:

curl https://ingestion.dassana.cloud/logs?withHeader=false&csvHeader=time,duration,SrcDevice,DstDevice,Protocol,SrcPort,DstPort,SrcPackets,DstPackets,SrcBytes,SrcBytes \
-X POST \
-H 'Content-type: text/csv' \
-H 'x-dassana-app-id: YOUR_APP_ID' \
-H 'x-dassana-token: YOUR_DASSANA_TOKEN' \
--data-binary @foo.csv
gzip

To send gzipped data, add the following headers:

Content-Encoding: gzip
Accept-Encoding: gzip

json object

curl https://ingestion.dassana.cloud/logs \
-X POST \
-H 'Content-type: application/json' \
-H 'x-dassana-app-id: YOUR_APP_ID' \
-H 'x-dassana-token: YOUR_DASSANA_TOKEN' \
--data-binary '{ "foo": "bar" }'
Gotchas

JSON arrays and gzip encoding are not supported for Content-type: application/json. If you want to send json arrays then use the nd-json header.

Aggregators

Fluentd

In this section, we'll configure Fluentd to stream logs to Dassana.

  1. Locate your configuration file:
  • The default (td-agent) config file path is /etc/td-agent/td-agent.conf
  • For calyptia-fluentd the default config file path is /etc/calyptia-fluentd/calyptia-fluentd.conf
  • If you installed via Ruby Gem, create the configuration file as follows
    sudo fluentd --setup /etc/fluent
    sudo vi /etc/fluent/fluent.conf
  • For a docker container the default config file path is /fluentd/etc/fluent.conf
  1. Edit your source in the configuration file as follows.

Add the following keys to your source

<source>
...
time_key time # This must match the name of the time key extracted in Dassana's app setup
time_format %Y-%m-%dT%H:%M:%S # This must match the time format selected in Dassana's app setup
...
</source>
  1. Add the following output with your Dassana token and App Id to your configuration file. Ensure the match pattern equals the tag you set in the source.
<match your_input>
@type http endpoint https://ingestion.dassana.cloud/logs headers
{"x-dassana-app-id":"YOUR_APP_ID", "x-dassana-token":"YOUR_TOKEN",
"Content-type":"application/x-ndjson"} bulk_request true
<buffer>
@type memory chunk_limit_size 5MB flush_interval 1s retry_max_times 5
retry_type periodic retry_wait 2
</buffer>
</match>

Alternatively, if you are ingesting csv logs, include the following output. If your data does not include headers, set the withHeader parameter in the endpoint to be false, and add a csvHeader parameter to equal your headers as comma-seperated values. You can find an example of this in the CSV ingestion section above.

<match your_input>
@type http endpoint https://ingestion.dassana.cloud/logs?withHeader=true
headers {"x-dassana-app-id":"YOUR_APP_ID", "x-dassana-token":"YOUR_TOKEN",
"Content-type":"text/csv"}
<buffer>
@type memory chunk_limit_size 5MB flush_interval 1s retry_max_times 5
retry_type periodic retry_wait 2
</buffer>
</match>
  1. Restart or start Fluentd after editing the configuration file. Ex:
sudo systemctl restart td-agent

Vector

In this section, we'll configure Vector to stream logs to Dassana.

  1. Edit your vector.toml config file to include the following sink if you are ingesting json logs
#####             #####
## Your source here ##
##### #####

[sinks.dassana]
type = "http"
inputs = [ "YOUR_SOURCE_NAME" ]
uri = "https://ingestion.dassana.cloud/logs"
compression = "gzip"
encoding.codec = "ndjson"
batch.max_bytes = 100000
[sinks.dassana.request.headers]
Content-type = "application/x-ndjson"
Content-Encoding = "gzip"
x-dassana-app-id = "YOUR_APP_ID"
x-dassana-token = "YOUR_DASSANA_TOKEN"

Alternatively, if you are ingesting csv logs, include the following sink. If your data does not include headers, set the withHeader parameter in the endpoint to be false, and add a csvHeader parameter to equal your headers as comma-seperated values. You can find an example of this in the CSV ingestion section above.

#####             #####
## Your source here ##
##### #####

[sinks.dassana]
type = "http"
inputs = [ "YOUR_SOURCE_NAME" ]
uri = "https://ingestion.dassana.cloud/logs?withHeader=true"
compression = "gzip"
encoding.codec = "text"
batch.max_bytes = 100000
[sinks.dassana.request.headers]
Content-type = "text/csv"
Content-Encoding = "gzip"
x-dassana-app-id = "YOUR_APP_ID"
x-dassana-token = "YOUR_DASSANA_TOKEN"
  1. Restart Vector after editing the configuration file. Ex:
sudo systemctl start vector