I would like to know what is the best setup to have an elasticsearch data node and kibana server on separate machines. I have setup multiple elasticsearch data nodes and would like to show all dashboards on one server but not sure how to do that. I do not want to have different urls to view different dashboards. I set up the data nodes with logstash shipper on each machine so all I need now is to have kibana get data from each different data node. Is that possible?
I edited the config file for kibana as follows:
elasticsearch: "http://"192.168.xx.xxx":9200"
So far Kibana 3 do not support what you need. You can refer to this.
As the webpage say, maybe you want to set an proxy or a redirect page.
Related
I have elastic search cluster.
Currently designing a python service for client for read and write query to my elastic search. The python service will not be maintained by me. Only internally python service will call our elastic search for fetching and writing
Is there any way to configure the elastic search so that we get to know that the requests are coming from python service, Or any way we can pass some extra fields while querying based on that fields we will get the logs
There is no online feature in elasticsearch to resolve your request. (you want to check the source and add fields to query).
but there is a solution for audit logs.
https://www.elastic.co/guide/en/elasticsearch/reference/current/enable-audit-logging.html
What you can do is placing a proxy in front of it and do the logging there, we have an Apache in front of our Elastic clusters to enable SSL-offloading there and add logging and ACL possibilities.
I've installed filebeat in a server, collecting all the logs from all the containers i have. With filebeat i indicate to which elasticsearch and kibana hosts he must send them (both, elasticsearch and kibana are running as a service in another server). So now all the logs appear in kibana. My question is, all those logs that appear there, are stored somewhere? In elasticsearch or in kibana?
Thank you in advance
All the data is stored inside Elasticsearch.
Kibana is a visualization engine on top of Elasticsearch. Kibana itself also stores its configuration data inside an internal Elasticsearch index called .kibana.
Whatever you can see from Kibana always comes from Elasticsearch.
You can learn more about Elasticsearch here and Kibana here.
I have a ton of services: Node(s), MySQL(s), Redis(s), Elastic(s)...
I want to monitor how they connect to each other: Connection rate, Number alive connection... (Node1 create 30 connection to Node2/MySQL/Redis per second...) like Haproxy stat image attached below.
Currently i have two options:
Haproxy (proxy): I want to use single service Haproxy to archive this but it's seem very hard to use ALC detect what connection need forward to what service.
ELK (log center): I need to create log files on each service (Node, MySQL, Redis...) and then show them on the log center. I see that a ton of works to do that without built-in feature like Haproxy stat page.
How to do this? Is log center good in this case?
The problem
I think your problem is not collecting and pipelining the statistics to Elasticsearch, but instead the ton of work extracting metrics from your services because most of them do not have metric files/logs.
You'd then need to export them with some custom script, log them and capture it with filebeat, stream to a logstash for text processing and metric extraction so they are indexed in a way you can do some sort of analytics, and then send it to elasticsearch.
My take on the answer
At least for the 3 services you've referenced, there are Prometheus exporters readily available and you can find them here. The exporters are simple processes that will query your services native statistics APIs and expose a prometheus metric API for Prometheus to Scrape (poll).
After you have Prometheus scraping the metrics, you can display them in dashboards via Grafana (which is the de facto visualization layer for Prometheus) or bulk export your metrics to wherever you want (Elasticsearch, etc..) for visualization and exploration.
Conclusion
The benefits of this approach:
Prometheus can auto-discover new nodes you add to your networks
Readily available exporters from haproxy, redis and mysql for
Prometheus
No code needed, each exporter requires minimal
configuration specific to each monitored technology, it can easily
be containerized and deployed if your environment is container
oriented, otherwise you just need to run each exporter in the
correct machines
Prometheus is very, very easy to deploy
Use ELK - elasticsearch logstash and kibana stack with filebeat. Filebeat -will share the log file content with logstash
Logstash-will scan, filter and share the needed content to elastic search
Elasticsearch- will work as a db, store the content from logstash in json format as documents.
Kibana- with kibana you can search the required info. Also you can plot graphs and other visuals with the relevant data.
I want to setup sort of aggregation for multiple Elasticsearch clusters based on Cross Cluster Search feature.
I have the following layout:
As seed for Cross Cluster Search I am using the only available via network cluster address.
After querying I am getting error:
[elasticsearch][172.16.10.100:9300] connect_timeout[30s]
I can't change publish_host for nodes, because that address used inside the cluster for node communication.
Is there any option to force Cross Cluster Search to use only provided address?
Or any other way to setup kinda proxy for user to be able to search/visualize in kibana data from multiple isolated elasticsearch clusters?
I believe that the only solution is to upgrade to Elasticsearch 7, which provides the cluster.remote.${cluster_alias}.proxy option where you can specify the incoming IP address for the cross cluster search.
I have started working on ELK recently and have a doubt regarding handling of multiple types of logs.
I have two sets of logs on my server that I want to analyse, one from my android application and the other from my website. I have successfully transferred logs from this server via filebeat to the ELK server.
I have created two filters for either types of logs and have successfully imported these logs into logstash and then Kibana.
This link helped do the above stuff.
https://www.digitalocean.com/community/tutorials/how-to-install-elasticsearch-logstash-and-kibana-elk-stack-on-centos-7
The above link directs to use the logs in the filebeat index in Kibana and start analysing(I successfully did for one type of logs). But the problem that I am facing is that since both these logs are very different, they need to be analysed differently. How do I do this in Kibana. Should I create multiple filebeat indexes there and import them, or should it be just one single index, or some other way. I am not very clear on this(could not find much documentation), hence would request to please help and guide me here.
Elasticsearch organizes by index and type. Elastic used to compare these to SQL concepts, but now offers a new explanation.
Since you say that the logs are very different, Elastic is saying that you should use different indexes.
In Kibana, the visualization is tied to an index. If you had one panel from each index, you can show them both on the same dashboard.