Kibana using lots memory

Is Digital Oceans 1-click-deploy ELK stack poorly configured on purpose?

Kibana is using too much memory

I wanted to see what juicy stats and info I could get out of the logs some of my servers were creating. Eventually I ran into the kibana using lots memory error. But I went through the Install ELK on ubuntu 14.04 tutorial and all was well but the certificate  creation didn’t go too well so when filebeat and topbeat was installed on the client they would not restart and give an error:

ERR SSL client failed to connect with: dial tcp i/o timeout

So it turned out to be a mission so I resorted to using the One click install image tutorial and it worked like a charm.

I started with a 1Gb droplet and that gave issues like logstash just stopping, elasticsearch just stopping and kibana just stopping. So you had to restart and then after a while it still wouldn’t work.

Kibana node memory keeps increasing

So I moved to the 2Gb droplet and added it to newrelic so I could see what was ccasuing these problems. And I think I have found the culprit:


As you can see node just starts going out of hand from the start until it runs out of memory.

So is Digital ocean deliberately leaving this issue / not configuring this issue so that you go for a more powerful droplet. They are in the business of making you use more VPS’s.

But I digress…

Node is the kibana part of the ELK stack and this issue has been highlighted without a clear answer (like always) on Github and another one

But suggestions are saying add this to bin/kibana at the top:


On the one click install that is located at:


and it should look like:

exec "${NODE}" $NODE_OPTIONS "${DIR}/src/cli" ${@}

I will implement this and let you know the results

Update (The following day)


So I set the limit to 500 and duely it restarted at 440 mb used, according to this graphic:


So summing up it may be possible to run this on a 1Gb RAM droplet.

The java instance for logstash runs at about 250mb max memory usage. Java for elasticsearch seems to max at 600 mb but maybe that is just because of the amount of data it has to search through / keep in memory. I’m also not sure if you can limit this amount. Filebeat uses about 15mb max. Rsyslog uses about 10mb.

So can you run the ELK stack on a 1Gb droplet?

Processes and Memory being used on the ELK stack

User Process Count CPU Memory
elasticsearch java 1 8.5% 564 MB
kibana node 1 0.4% 325 MB
logstash java 1 3.8% 239 MB
root java 1 81.1% 154 MB
root apt-get 1 7.5% 42.6 MB
root filebeat 1 0.0% 12.6 MB
root fail2ban-server 1 0.0% 9.37 MB
syslog rsyslogd 1 0.0% 7.96 MB
www-data nginx 4 0.0% 6.16 MB
newrelic nrsysmond 2 0.1% 5.43 MB
root vim 1 0.0% 5.21 MB
root bash 1 0.0% 3.72 MB
root sudo 1 0.0% 2.03 MB
root init 1 0.0% 1.71 MB
root sshd 1 0.0% 1.62 MB
sshd sshd 1 0.0% 1.4 MB
root nginx 1 0.0% 1.09 MB
root getty 6 0.0% 944 KB
messagebus dbus-daemon 1 0.0% 820 KB
root systemd-udevd 1 0.0% 739 KB

So the total excluding kibana is: 1059.75 mb

Well it looks like we are over budget as it stands. I will keep monitoring.

Making the ELK Stack run on a 1Gb Droplet (Update)

Well we can see that we can stop Kibana going out of control on the memory side. Now that try save some money by limiting it so it only needs a 2Gb droplet.

We are going to limit Kibana to 250Mb and Elasticsearch to 500Mb and hopefully everything goes smoothly. To change the limit on elasticsearch memory change: /etc/default/elasticsearch

Add the following:


That is what I had the best success with. Although there are additional steps outlined on stackoverflow.

So we will implement the above and wait until it safely runs under 1Gb memory, otherwise we are  going to flip the switch and just downgrade to 1Gb and reboot.


We are still seeing the jaggered edges created by the periodic increase and dropping of kibana memory usage.


And this is pushing over out 1Gb max. Also elasticsearch is using 650 mb of memory or there abouts when we have told it to use 512 max. Maybe it realises there is spare memory so I will be downgrading it now to a 1Gb droplet.

So far so good…the retrieval or records and visualisation generation in kibana is less speedy but I can deal with it. Here is the current memory situation:

kibana-on-1-gb-droplet screen-shot-2016-09-17-at-12-10-04-pm

Well that didn’t work…

Elasticsearch is still using > 512mb memory and logstash stops as soon as it starts. So if I set the heap size in sudo vim /etc/init.d/elasticsearch:



the elasticsearch service does not start…

Ah you need to also edit sudo vim /etc/elasticsearch/elasticsearch.yml

and add the following:

bootstrap.memory_lock: true

I will continue monitoring stability


 Oh no looks like Kibana has died. The stability of the system is coming into question now.


Hmm it seems there is a one must die situation, as logstash also just dies after a while…

Somehow the server has dow, couldn’t ssh and newrelic not showing the server but on DO it still said it was up. After turning off and on from DO console I am now getting this error and it is the last straw.


Tis’ a shame but it is not in the price range at this stage. Will stop the server.