Using Grafana 7.2 and Elasticsearch 7.5.1.
Everyting is up and running in Openshift. Elasticsearch datasource is correctly configured and a very simple Dashboard created.
From a Springboot service also running in Openshift I am sending logs to Elasticsearch using Fluentd.
The documents stored in Elasticsearch are like this (taken from Grafana "Logs" result panel):
Edited: following @karan shah suggestion, I add the original log that I am sending to Elastichsearch through Fluentd:
{
"onpay":{
"traceId":"9999",
"inout":"OUT",
"startTime":"2020-10-01T10:13:43.806+0200",
"finishTime":"2020-10-01T10:13:43.827+0200",
"executionTime":21.0,
"entrySize":124.0,
"exitSize":124.0,
"differenceSize":0.0,
"user":"pgallello",
"methodPath":"http://localhost:8083/api/serviceEntryPoint",
"errorMessage":null,
"className":"com.myorganization.mypackage.MyController",
"methodName":"serviceTemplateEntryPoint"
}
}
It is a Elasticsearch document with a field "message", which is the one I want to base my dashboard in. Note two things at this point:
Problem 1:
What I need to do (and I am not getting) is the tricky part: I need to get an histogram showing the average of the value of executionTime field per interval.
Following official documentation, particularly this official video from Grafana, I should be able to change de Group By field to Average and to select @value from the field selector. Unfortunately, that @value value does not appear there (May the _source = [object Object]
field have something to do?)
Problem 2:
The other doubt is whether the Query field is valid in that format or what is the way to access to the executionTime field, which is inside the message field inside the Elasticsearch document. In a sort of hierarchy message -> onpay -> executionTime
.
Fluentd config file:
<source>
@type forward
port 24224
bind "0.0.0.0"
</source>
<filter onpayapp.**>
@type parser
key_name "onpayapp"
reserve_data true
<parse>
@type "json"
</parse>
</filter>
<match onpay.**>
@type copy
<store>
@type "elasticsearch"
host "elasticdb"
port 9200
logstash_format true
logstash_prefix "applogs"
logstash_dateformat "%Y%m%d"
include_tag_key true
type_name "app_log"
tag_key "@log_name"
flush_interval 1s
<parse>
@type json
</parse>
<buffer>
flush_interval 1s
</buffer>
</store>
<store>
@type "stdout"
</store>
</match>
Currently what you have there is the entire json as a string in the message field. So Elastic would not be able to apply any mathematical operations on that. What you need to do is using fluentd parse the log line as json so in the Elastic document every field (like logger and level) within that json is part of the elastic document. Once you have that Elastic mostly automatically interpret that executionTime is number and make it available for aggregations. After that you will see that field in your Grafana dropdown.
Here you can understand more on _source field.
Add your original log line as well to the question, I think it might help understand what you want to ingest so a suggestion can be made on the possible fluentd configuration.
Updated Answer based on additional information provided
For simplicity I used docker setup to run and parse the log pattern provided in the question.
Fluentd Configuration
I have used HTTP input so it allows me to curl but you can switch back to forwarder. I have removed filter as I am assuming your source is already JSON so you do not need to parse it as JSON. You can add the matching pattern back if you have multiple types of data processed through the pipeline.
<source>
@type http
port 9880
bind 0.0.0.0
</source>
<match *>
@type copy
<store>
@type "elasticsearch"
host "es01"
port 9200
logstash_format true
logstash_prefix "applogs"
logstash_dateformat "%Y%m%d"
include_tag_key true
type_name "app_log"
tag_key "@log_name"
flush_interval 1s
<parse>
@type json
</parse>
<buffer>
flush_interval 1s
</buffer>
</store>
<store>
@type "stdout"
</store>
</match>
Fluent Docker Image
# fluentd/Dockerfile
FROM fluent/fluentd:v1.11-debian-1
USER root
RUN touch ~/.gemrc
RUN echo ':ssl_verify_mode: 0' >> ~/.gemrc
RUN buildDeps="sudo make gcc g++ libc-dev" \
&& apt-get update \
&& apt-get install -y --no-install-recommends $buildDeps \
&& sudo gem install fluent-plugin-elasticsearch \
&& sudo gem sources --clear-all \
&& SUDO_FORCE_REMOVE=yes \
apt-get purge -y --auto-remove \
-o APT::AutoRemove::RecommendsImportant=false \
$buildDeps \
&& rm -rf /var/lib/apt/lists/* \
&& rm -rf /tmp/* /var/tmp/* /usr/lib/ruby/gems/*/cache/*.gem
USER fluent
Docker Compose You can choose to run just one node of elasticsearch. I already had this setup running.
services:
es01:
image: docker.elastic.co/elasticsearch/elasticsearch:7.8.0
container_name: es01
environment:
- node.name=es01
- cluster.name=es-docker-cluster
- discovery.seed_hosts=es02,es03
- cluster.initial_master_nodes=es01,es02,es03
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
ulimits:
memlock:
soft: -1
hard: -1
volumes:
- data01:/usr/share/elasticsearch/data
ports:
- 9200:9200
networks:
- elastic
healthcheck:
interval: 20s
retries: 10
test: curl -s http://localhost:9200/_cluster/health | grep -vq '"status":"red"'
es02:
image: docker.elastic.co/elasticsearch/elasticsearch:7.8.0
container_name: es02
environment:
- node.name=es02
- cluster.name=es-docker-cluster
- discovery.seed_hosts=es01,es03
- cluster.initial_master_nodes=es01,es02,es03
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
ulimits:
memlock:
soft: -1
hard: -1
volumes:
- data02:/usr/share/elasticsearch/data
ports:
- 9201:9200
networks:
- elastic
healthcheck:
interval: 20s
retries: 10
test: curl -s http://localhost:9201/_cluster/health | grep -vq '"status":"red"'
es03:
image: docker.elastic.co/elasticsearch/elasticsearch:7.8.0
container_name: es03
environment:
- node.name=es03
- cluster.name=es-docker-cluster
- discovery.seed_hosts=es01,es02
- cluster.initial_master_nodes=es01,es02,es03
- bootstrap.memory_lock=true
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
ulimits:
memlock:
soft: -1
hard: -1
volumes:
- data03:/usr/share/elasticsearch/data
ports:
- 9202:9200
networks:
- elastic
healthcheck:
interval: 20s
retries: 10
test: curl -s http://localhost:9202/_cluster/health | grep -vq '"status":"red"'
kib01:
image: docker.elastic.co/kibana/kibana:7.8.0
container_name: kib01
ports:
- 5601:5601
environment:
ELASTICSEARCH_URL: http://es01:9200
ELASTICSEARCH_HOSTS: http://es01:9200
networks:
- elastic
healthcheck:
interval: 10s
retries: 20
test: curl --write-out 'HTTP %{http_code}' --fail --silent --output /dev/null http://localhost:5601/api/status
fluentd:
build: ./fluentd
volumes:
- "./fluentd/conf/:/fluentd/etc/:ro"
networks:
- elastic
ports:
- "9880:9880"
volumes:
data01:
driver: local
data02:
driver: local
data03:
driver: local
networks:
elastic:
driver: bridge
Curl for Test
curl -X POST -d 'json={ "onpay": { "traceId": "9999", "inout": "OUT", "startTime": "2020-10-01T10:13:43.806+0200", "finishTime": "2020-10-01T10:13:43.827+0200", "executionTime": 21.0, "entrySize": 124.0, "exitSize": 124.0, "differenceSize": 0.0, "user": "pgallello", "methodPath": "http://localhost:8083/api/serviceEntryPoint", "errorMessage": null, "className": "com.myorganization.mypackage.MyController", "methodName": "serviceTemplateEntryPoint" }}' http://localhost:9880/
Once you get all your json keys ingested like this, Elastic will auto-map most fields and allow search, aggregation etc based on the field type. You can change the field type & formatting from kibana index management if you want.