So let's go back to our configuration file, and here we are going to define where all our logs that
are processed up until here are going to land.
And this is the plugin that I showed you in the fluency part, which is called elastic search.
So this will connect fluently to ElasticSearch in order to send the data there.
And we're going to add some configuration here.
So obviously, we want to know where the host address is.
So this is the ElasticSearch host in our application,
ElasticSearch Master.
That is a service name of ElasticSearch.
This is the namespace and this is basically the whole name of service inelastic.
So that is going to be the host.
Then we have the port where ElasticSearch is running at
and we have the index name and we can give it any name we want.
I'm going to call that epilogues.
If you have multiple micro services, you can also create index per micro service or you can group a
couple of micro services in one index.
So basically the index allows you to group log entries from services applications in a way that is logical
for you and some other configuration here, like include TICKIE.
This is the tag name that I mentioned.
And we also have some buffer configuration.
So obviously we don't want to write every single entry line by line as it's processed by fluid.
So we buffer them and then we send that to ElasticSearch.
So this is the configuration for that and this will be enough to send our logs to ElasticSearch.
So I'm going to save that.
We see the updates and again, I'm going to restart.
Demon set, so the pots have restarted and now let's go to our cabana here, you basically see list
of different applications.
For now, we just need keyboarder.
And here in the management section, in instict management, you can actually manage both ElasticSearch
indices and Kibwana indices.
So in the data section, in index management, we can actually see and manage ElasticSearch indices.
And this is the index that we define in our configuration.
This is The Epilogues.
So our index was successfully created.
A good thing with ElasticSearch indices is that you don't have to create them before they get dynamically
created if it doesn't exist.
And here we also see how many entries this index has, which is 21.
This is a number of logs in our application.
So if we click here, we just see some metadata.
We can see the log entries in order to do that or in order to see those log entries and Cubano, we
need to go to index patterns in the Cubano section and create what's called banner index.
So based on the ELASTICSEARCH index that we created, we're going to create here a key banner index.
So here we're just going to say the name, this is actually the name Petten, so you can match multiple
indices or we can also write the name direct because we just have one and create index pattern.
So now we can see the logs.
So let's go back to Keyboarder Discover.
And this is our index, and here you see logs from Java EP, we have the log tag here and the whole
logline is a value.
And after Java, if we also have the logs from the node.
Jessep So if I spend one of those, I have a structured view of all the techs.
And these are the ones actually that got added by this company is metadata.
So these are enriched with some capabilities, additional data.
You have a container named the host port name, ID namespace, et cetera.
So you can actually filter and search based on those values.