The aci-streamer use the Cisco ACI API subscription to provide streaming on events on a ACI classes.
According to the Cisco documentation
subscription works for:
"The REST API supports the subscription to one or more MOs during your active API session.
When any MO is created, changed, or deleted because of a user- or system-initiated action, an event is
generated. If the event changes the data on any of the active subscribed queries,
the APIC will send out a notification to the API client that created the subscription."
The most basic example is subscribing to events on the ACI class faultInst
to get continues stream of fault events.
The streamed events are by default written to stdout and the format is json, so it's easy to consume by any
systems like Loki and Elastic.
In the above screenshot we have combined Prometheus and Loki data sources in the same dashboard.
In the middle row we have the Loki logs based on a “stream” from the aci-streamer called faults.
In the left graph we have the log panel for Loki logs. The query is based on the upper left Grafana variable
filters that are applied for the whole dashboard.
{fabric=~"$Aci",stream="faults",podid=~"$Podid",nodeid=~"$Nodeid",severity=~"$Severity"}
On the right graph we create a simple fault rate metric based on the log data.
sum by (nodeid,severity) (rate({stream="faults",fabric=~"$Aci",podid=~"$Podid",nodeid=~"$Nodeid",severity=~"$Severity"}[5m]))
The rest of the graphs are based on the aci-exporter
Prometheus data using the same label filters, so we can drill down both on pod, node and severity.
The events streams are configured by a definition of streams
. The below example create a stream of ACI created sessions.
streams: sessions: # The ACI class to subscribe to class_name: aaaActiveUserSession # The query parameters to use for the subscription query_parameter: "?query-target=self&query-target-filter=and(wcard(aaaActiveUserSession.status,\"created\"))" # The json root of where data is collected root: imdata.0.aaaActiveUserSession.attributes # A json key called mesg that has a format, Go fmt.Sprintf, where source property names is inserted # This is typical a field that do not exist in the original json message: name: mesg format: "%s - %s" property_names: - name - ipAddress
Original message from ACI looks like:
{ "subscriptionId": ["72066106679951361"], "imdata": [{ "aaaActiveUserSession": { "attributes": { "annotation": "", "childAction": "", "descr": "", "dn": "uni/usersessext/actsession-CwqMYooyRDKiftKyopDgGw==", "expiryTime": "2020-08-04T14:14:09.692+00:00", "extMngdBy": "", "hashToken": "CwqMYooyRDKiftKyopDgGw==", "ipAddress": "10.10.20.141", "lcOwn": "local", "loginTime": "2020-08-04T14:04:09.692+00:00", "modTs": "2020-08-04T14:04:09.691+00:00", "name": "admin", "nameAlias": "", "ownerKey": "", "ownerTag": "", "rn": "", "status": "created", "uType": "local", "uid": "0" } } }] }
After processed by the above streams configuration:
{ "annotation": "", "childAction": "", "descr": "", "dn": "uni/usersessext/actsession-CwqMYooyRDKiftKyopDgGw==", "expiryTime": "2020-08-04T14:14:09.692+00:00", "extMngdBy": "", "hashToken": "CwqMYooyRDKiftKyopDgGw==", "ipAddress": "10.10.20.141", "lcOwn": "local", "loginTime": "2020-08-04T14:04:09.692+00:00", "modTs": "2020-08-04T14:04:09.691+00:00", "name": "admin", "nameAlias": "", "ownerKey": "", "ownerTag": "", "rn": "", "status": "created", "uType": "local", "uid": "0", "mesg": "admin - 10.10.20.141", "fabric": "ACI Fabric1", "stream": "sessions" }
The structure has been flattened from the root
definition. Three additional keys has been added:
fabric
the name of the ACI fabricstream
then name of the stream configurationmesg
the created new fieldThe main reason for the use of the
mesg
definition is to create a combined log key to use when saved to the log
system.
A typical Loki configuration for the above example would be:
pipeline_stages: - json: expressions: # Get the stream name stream: stream - labels: stream: - match: # Use selector for each stream selector: '{stream="sessions"}' stages: - json: # Define the json keys to use expressions: message: mesg status: status fabric: fabric - labels: # Define which keys to be used as labels status: fabric: - output: # The key to use to write as Loki data source: message
With the Loki selector
different stream's that are logged to the same file descriptor that the
aci-streamer writes to can be handled in unique ways.
With aci-streamer we can for a stream also use a configuration directive called labels
. We use the example to stream
ACI faults.
streams: faults: class_name: faultInst root: imdata.0.faultInst.attributes query_parameter: "" labels: - property_name: dn regex: "^topology/pod-(?P<podid>[1-9][0-9]*)/node-(?P<nodeid>[1-9][0-9]*)/sys/.*" message: name: message format: "%s - %s [dn: %s]" # Names are add to the format in the order they are written property_names: - descr - dn
In the above example we define that the property key dn
should be parsed with a regular named expression. The above
will result in two, if matched, new keys called podid
and nodeid
with value.
This will result in the following stream data:
{ "ack": "no", "cause": "threshold-crossed", "changeSet": "crcLast:4", "childAction": "", "code": "F381328", "created": "2020-08-03T23:09:28.395+00:00", "delegated": "no", "descr": "TCA: CRC Align Errors current value(eqptIngrErrPkts5min:crcLast) value 4% raised above threshold 1%", "dn": "topology/pod-1/node-102/sys/phys-[eth1/3]/fault-F381328", "domain": "infra", "highestSeverity": "warning", "lastTransition": "2020-08-04T16:14:27.106+00:00", "lc": "raised", "occur": "951", "origSeverity": "warning", "prevSeverity": "cleared", "rn": "", "rule": "tca-eqpt-ingr-err-pkts5min-crc-last", "severity": "warning", "status": "modified", "subject": "counter", "type": "operational", "podid": "1", "nodeid": "102", "message": "2020-08-04T16:14:27.106+00:00 - TCA: CRC Align Errors current value(eqptIngrErrPkts5min:crcLast) value 4% raised above threshold 1% [dn: topology/pod-1/node-102/sys/phys-[eth1/3]/fault-F381328]", "fabric": "ACI Fabric1", "timestamp": "2020-08-04T16:14:27.106000000Z", "stream": "faults" }
Even if podid
or nodeid
was not part of the original event, except part of the dn
key, they are now separate keys.
For more information about configuration please see the example-config.yaml
For configuration options please see the
example-config.yml
file.
All attributes in the configuration has default values, except for the fabric and the different streams sections.
A fabric profile include the information specific to an ACI fabrics, like authentication and apic(s) url.
If there is multiple apic urls configured the aci-streamer will use the first apic it can log in to starting with the first
in the list.
All configuration properties can be set by using environment variables. The prefix is ACI_STREAMER_
and property
must be in uppercase. So to set the property port
with an environment variable ACI_STREAMER_PORT=7121
.
go build -o build/aci-streamer *.go
By default, the aci-streamer will look for a configuration file called config.yaml
. The directory search paths are:
./build/aci-streamer -fabric XYZ
Where XYZ is a named entry in the fabrics section of the configuration file.
To run against the Cisco ACI sandbox:
./build/aci-streamer -config example-config.yaml -fabric cisco_sandbox
Make sure that the sandbox url and authentication is correct. Check out Cisco sandboxes on
https://devnetsandbox.cisco.com/RM/Topology - "ACI Simulator AlwaysOn"
By default, the output is sent to standard out. The output kan also be directed to a file using the
-output
flag. When written to a file aci-streamer use the log4go package to write the output.
The main reason for this to get file rotation on the output, which is good if aci-streamer is deployed
with a sidecar in kubernetes, like promtail.
Internal metrics are exposed in Prometheus exposition format on the endpoint /metrics
.
To get the metrics in openmetrics format use header Accept: application/openmetrics-text
Please see the example file loggers/promtail.yaml.
Please see the example file loggers/filebeat.yaml.
This work is licensed under the GNU GENERAL PUBLIC LICENSE Version 3.
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