I want to parse my logs with grok pattern.
This is my sample log file, which has 7 |*| characters in every log.
2022-12-15 01:11:22|*|639a7439798a26.27827512|*|5369168485-532|*|3622857|*|app.DEBUG|*|Checking the step |*|{"current_process":"PROVIDE PROBLEM INFORMATION","current_step":"SUBMIT_MEMO","queue_steps":}|*|{"_environment":"test","_application":"TEST"}
I am creating fields with grok pattern, but at the end I am trying to pick only last JSON part after 7th |*|{"\_environment":"test","\_application":"TEST"} in every log and parse it with JSON filter in Logstash.
How can I get only JSON object after 7th |*| object in every log?
Try this:
grok {
match => [ "message", "(?<notRequiredField>(?:.*?(\*)+){6}.*?((\*)+))\|%{GREEDYDATA:requiredField}" ]
}
mutate {
remove_field => [ "notRequiredField" ]
}
Related
I will try to explain what I want to achieve. I have grok pattern to match simple log line. There is response message json body in the log line and I am able to parse it with custom regex pattern and I see it in kibana dashboard as expected. The thing is I would like to extract some data from the body itself.
Here is the working grok pattern:
{TIMESTAMP_ISO8601:timestamp}%{SPACE}*%{LOGLEVEL:level}:%{SPACE}*%{DATA}%{BODY:body}
Custom pattern for BODY:
BODY (Body:.* \{.*})
And I see it parsed using grok debugger:
{
"timestamp": "2022-11-04 17:09:28.052",
"level": "INFO",
"body": {\"status\":200,\"page\":1, \"fieldToBeParsed\":12 .....//more json conten}
}
Is there any way to parse some of the content of the body together with the whole body.
So I can get result similar to:
{
"timestamp": "2022-11-04 17:09:28.052",
"level": "INFO",
"body": {\"status\":200,\"page\":1, \"fieldToBeParsed\":12 .....//more json conten},
"parsedFromBody: 12
}
Example:
{TIMESTAMP_ISO8601:timestamp}%{SPACE}*%{LOGLEVEL:level}:%{SPACE}*%{DATA}%{BODY:body}%
{FROMBODY:frombody}%
Thank you!
Once you have used grok to parse a field, you can use a second grok filter to parse fields created by the first grok. Do not try to do both in one grok, it may or may not work. The matches are a hash, and Java hashes are not ordered.
grok { match => { "body" => "fieldToBeParsed\":%{NUMBER:someField:int}" } }
I'm trying to use grok and logstash to index some numeric datas. Datas structure is something like:
[integer,integer,integer,...,integer]
I created a index pattern in logstash, and using grok i write this filter:
grok {
match => { "message" => "\[%{NUMBER:opcode:int},%{NUMBER:sender:int},%{NUMBER:alertbitmap:int},%{NUMBER:bat:int},%{NUMBER:ant:int},%{NUMBER:resbat:int},%{NUMBER:temp:int},%{NUMBER:presatm:int},%{NUMBER:umid:int},%{NUMBER:vertical:int},%{NUMBER:analog1:int},%{NUMBER:analog2:int},%{NUMBER:analog3:int},%{NUMBER:analog4:int},%{NUMBER:spostam:int},%{NUMBER:contporta1:int},%{NUMBER:contporta2:int},%{NUMBER:digital1:int},%{NUMBER:digital2:int},%{NUMBER:digital3:int},%{NUMBER:digital4:int},%{NUMBER:time:int}\]" }
}
but when I explore index pattern in logstash the type is still string. How can i resolve this problem? Thanks in advance
I have a pattern of logs that contain performance&statistical data. I have configured LogStash to dissect this data as csv format in order to save the values to ES.
<1>,www1,3,BISTATS,SCAN,330,712.6,2035,17.3,221.4,656.3
I am using the following LogSTash filter and getting the desired results..
grok {
match => { "Message" => "\A<%{POSINT:priority}>,%{DATA:pan_host},%{DATA:pan_serial_number},%{DATA:pan_type},%{GREEDYDATA:message}\z" }
overwrite => [ "Message" ]
}
csv {
separator => ","
columns => ["pan_scan","pf01","pf02","pf03","kk04","uy05","xd06"]
}
This is currently working well for me as long as the order of the columns doesn't get messed up.
However I want to make this logfile more meaningful and have each column-name in the original log. example-- <1>,www1,30000,BISTATS,SCAN,pf01=330,pf02=712.6,pf03=2035,kk04=17.3,uy05=221.4,xd06=656.3
This way I can keep inserting or appending key/values in the middle of the process without corrupting the data. (Using LogStash5.3)
By using #baudsp recommendations, I was able to formulate the following. I deleted the csv{} block completely and replace it with the kv{} block. The kv{} automatically created all the key values leaving me to only mutate{} the fields into floats and integers.
json {
source => "message"
remove_field => [ "message", "headers" ]
}
date {
match => [ "timestamp", "YYYY-MM-dd'T'HH:mm:ss.SSS'Z'" ]
target => "timestamp"
}
grok {
match => { "Message" => "\A<%{POSINT:priority}>,%{DATA:pan_host},%{DATA:pan_serial_number},%{DATA:pan_type},%{GREEDYDATA:message}\z" }
overwrite => [ "Message" ]
}
kv {
allow_duplicate_values => false
field_split_pattern => ","
}
Using the above block, I was able to insert the K=V, pairs anywhere in the message. Thanks again for all the help. I have added a sample code block for anyone trying to accomplish this task.
Note: I am using NLog for logging, which produces JSON outputs. From the C# code, the format looks like this.
var logger = NLog.LogManager.GetCurrentClassLogger();
logger.ExtendedInfo("<1>,www1,30000,BISTATS,SCAN,pf01=330,pf02=712.6,pf03=2035,kk04=17.3,uy05=221.4,xd06=656.3");
I'm trying to parse some epoch timestamps to be something more readable.
I looked around for how to parse them into a normal time, and from what I understand all I should have to do is something like this:
mutate
{
remove_field => [ "..."]
}
grok
{
match => { 'message' => '%{NUMBER:time}%{SPACE}%{NUMBER:time2}...' }
}
date
{
match => [ "time","UNIX" ]
}
An example of a message is: 1410811884.84 1406931111.00 ....
The first two values should be UNIX time values.
My grok works, because all of the fields show in Kibana with the expected values, and all the values fields I've removed aren't there so the mutate works too. The date section seems to do nothing.
From what I understand the match => [ "time","UNIX" ] should do what I want (Change the value of time to be a proper date format, and have it show on kibana as a field.) . So apparently I'm not understanding it.
The date{} filter replaces the value of #timestamp with the data provided, so you should see #timestamp with the same value as the [time] field. This is typically useful since there's some delay in the propagation, processing, and storing of the logs, so using the event's own time is preferred.
Since you have more than one date field, you'll want to use the 'target' parameter of the date filter to specify the destination of the parsed date, e.g.:
date {
match => [ "time","UNIX" ]
target => "myTime"
}
This would convert the string field named [time] into a date field named [myTime]. Kibana knows how to display date fields, and you can customize that in the kibana settings.
Since you probably don't need both a string a date version of the same data, you can remove the string version as part of the conversion:
date {
match => [ "time","UNIX" ]
target => "myTime"
remove_field => [ "time" ]
}
Consider also trying with UNIX_MS for milliseconds.
date {
timezone => "UTC"
match => ["timestamp", "UNIX_MS"]
target => "#timestamp"
}
My input has timestamp in the format of Apr20 14:59:41248 Dataxyz.
Now in my output i need the timestamp in the below format:
**Day Month Monthday Hour:Minute:Second Year DataXYZ **. I was able to remove the timestamp from the input. But I am not quite sure how to add the new timestamp.
I matched the message using grok while receiving the input:
match => ["message","%{WORD:word} %{TIME:time} %{GREEDYDATA:content}"]
I tried using mutate add_field.but was not successful in adding the value of the DAY. add_field => [ "timestamp","%{DAY}"].I got the output as the word ´DAY´ and not the value of DAY. Can someone please throw some light on what is being missed.
You need to grok it out into the individual named fields, and then you can reference those fields in add_field.
So your grok would start like this:
%{MONTH:month}%{MONTHDAY:mday}
And then you can put them back together like this:
mutate {
add_field => {
"newField" => "%{mday} %{month}"
}
}
You can check with my answer, I think this very helpful to you.
grok {
match => { "message" => "%{TIMESTAMP_ISO8601:time} \[%{NUMBER:thread}\] %{LOGLEVEL:loglevel} %{JAVACLASS:class} - %{GREEDYDATA:msg}" }
}
if "Exception" in [msg] {
mutate {
add_field => { "msg_error" => "%{msg}" }
}
}
You can use custom grok patterns to extract/rename fields.
You can extract other fields similarly and rearrange/play arounnd with them in mutate filter. Refer to Custom Patterns for more information.