1. git clone https://github.com/opendistro-for-elasticsearch/opendistro-build
2. cd opendistro-build/helm/opendistro-es/
3. helm package .
4. helm install opendistro-es --set elasticsearch.data.persistence.size="100Gi",elasticsearch.client.replicas=3,elasticsearch.data.replicas=3 opendistro-es-1.13.1.tgz
port forward kibana to localhost:
kubectl port-forward svc/opendistro-es-kibana-svc 5601:443
then pls visit -> localhost:5601
with username: admin
and pwd: admin
Import the Opni dashboard by following steps:
- click
Stack Management -> Saved Objects -> Import
- hit
Import
underSelect a file to import
, selectopni-dashboard.ndjson
from this directory. - Click the blue button
Import
at the bottom, and then clickDone
. Now you can navigate toKibana -> Dashboard
to try out the Opni Logs Dashboard.
-
from your browser, browse to: https://companyname.slack.com/apps
-
Click the
Get Essential Apps
button -
Search for and select
Incoming WebHooks
-
Click
Add to Slack
-
Select the channel to post alerts to
-
Hit
Add incoming Webhooks integration
-
Copy the
Webhook URL
-
browse to kibana at
localhost:5601
-
Click the menu button on the left of
Home
at top left -
Select
Alerting
and then clickDestinations
-
Hit
Add destination
, put a name for the destination, and paste the Webhook URL from step 7 to the boxWebhook URL
, then ClickCreate
- Click
Alerting
and then selectMonitors
- put a name for
Monitor name
- in
Define the monitor
section, selectlogs
for index andtime
for time field - For the query that pops up from step 3, select
For the last 1 minute(s)
andWHERE anomaly_level is Anomaly
, clickCreate
- put a trigger name in the
Trigger name
box, for Trigger condition, selectIS ABOVE 10
- scroll down to the
Configure actions
section - put
slack notification
as Action name, select the configured Slack Destination as Destination. - Put the message you want in
Message Subject
and ClickCreate
You are ready to go!
Navigate to Menu
-> Dev Tools
and paste the following codes in the left side console:
POST training_signal/_doc/
{
"@timestamp": "2021-01-01T00:00:00",
"training_method" : "nulog",
"status" : "submitted"
}
then click ▻
to send request to launch nulog training!
the output on the right side should be like this:
{
"_index" : "training_signal",
"_type" : "_doc",
"_id" : "puhts3gB0Gdvef1IavPR",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 27,
"_primary_term" : 2
}
remember to copy the _id
so you can track the status of the job simply by:
GET training_signal/_doc/puhts3gB0Gdvef1IavPR