I ma new to Grok and logstash.
2016/02/18 - 03:52:08|service|Info|some message in different format
2016/02/18 - 03:52:08|service|Info|Time to process "tweet_name" is 40.1081357 second(s)
I will have messages like above format. What I want is, I want to extract the following things,
datetime
service
loglevel
message
tweetname
timetoprocess
Item 5 and 6 will be available only if the message starts with Time to process
I have written a grok but i am not sure how to extract item 5 and 6. Because #5 and #6 will be available only in certain line of log message.
filter {grok { match => { "message" => "(?<datetime>(([0-9]+)\/*)+ - ([0-9]+:*)+)\|%{WORD:service}\|%{WORD:loglevel}\|%{GREEDYDATA:message}" }}}
how can I get item #5 and #6 and apply the grok?
I would suggest using two grok stanzas. First, pull off the common stuff (your #1-#3). Put the remaining stuff back into [message] using the 'overwrite' parameter to grok{}. That's pretty much what you have in the grok you provided, but it'll be more clear if you use built-in patterns like %{YEAR}
Then, use a second grok stanza with match patterns to handle the other types of values left over. Something like this:
grok {
match => { "message" => "Time to process \"%{DATA:tweet_name}\" is %{NUMBER:tweet_sec} second\(s\)" }
}
If you have other messages for which you'd like to make fields, add more patterns to the grok stanza. It will process them in order until it finds a match and then exit out.
You have to add new grok for different message.
It will process them sequentially,after matching correct pattern it exit out.
Related
This is the input I am using for logstash.
ItemId,AssetId,ItemName,Comment
11111,07,ABCDa,XYZa
11112,07,ABCDb,XYZb
11113,07,ABCDc,XYZc
11114,07,ABCDd,XYZd
11115,07,ABCDe,XYZe
11116,07,ABCDf,XYZf
11117,07,ABCDg,XYZg
Date,Time,Mill Sec,rows,columns
19-05-2020,13:03:46,534,2,2
19-05-2020,13:03:46,539,2,2
19-05-2020,13:03:46,544,2,2
19-05-2020,13:03:46,549,2,2
19-05-2020,13:03:46,554,2,2
I need to remove first 8 lines from the csv and make the next line as column header and parse rest of lines as usual. Is there a way to do that in logstash?
You could do this using the file input and then read it line by line using grok to make sure it has the right amount of fields comma separated and ignore the header one
Your input will look like this:
input {
file {
path => "/path/to/my.csv"
start_position => beginning
}
}
This will read each line into an event with the data in the field named message and then send it to your filters.
In your filter you'll use grok with a pattern like this:
filter {
grok {
match => { "message" => [
"^%{DATE:Date},%{TIME:Time},%{NUMBER:Mill_Sec},%{NUMBER:rows},%{NUMBER:colums}$"
]
}
}
}
This will present each line as an event looking like this:
{
"colums": "2",
"Time": "13:03:46",
"Mill_Sec": "554",
"rows": "2",
"Date": "19-05-2020"
}
You can use mutate to remove unwanted fields (like message) prior to going to your output part. If there is no match with the pattern defined you'll get a tag with the value _grokparsefailure in your tags, you can use that to decide to send it to your output or not. As you defined that it has to be numbers, it will also fail on the header one and thus leave you with only 'real' events.
This can be done by having your output defined like this:
output {
if "_grokparsefailure" not in [tags] {
elasticsearch {
...
}
}
}
You should do this before the file gets to Logstash. There are ways to do it within Logstash, for example by using a mutliline code then doing exotic grok matches to remove the first N lines (or removing lines until a particular regex), then doing a split followed by a plain ol' csv filter. You need to be even more careful than usual with header rows. It's a big mess.
Much better to put something in front of Logstash to handle this issue.
If the files are local to your logstash instance, you could use the Exec input plugin to deal with the irregularities.
input {
exec {
command => "/path/to/command_or_script" # sh or py or js etc
interval => 60
}
}
On Linux, this command will print a file from the 8th line on...
command => "tail +8 /path/to/file"
This one (again for Linux) will drop everything until a line that starts with date, and print everything after that
command => "sed -n -e '/^date/,$p' /path/to/file"
You can avoid read the same file over and over again by deleting or archiving it in a script (rather than a one-liner as used in these examples)
After trimming the unwanted leading lines, you should be able to use the csv filter in a normal way.
Note that if you want to autodetect_column_names that pipeline workers must be set to 1.
Your content is not CSV format. Your task is convert it to true CSV format.
Below is the log which is being generated from spring application and trying to create custom grok filters
{"#timestamp":"2021-02-19T10:27:42.275+00:00","severity":"INFO","service":"capp","pid":"19592","thread":"SmsListenerContainer-9","class":"c.o.c.backend.impl.SmsBackendServiceImpl","rest":"[SmsListener] [sendSMS] [63289e8d-13c9-4622-b1a1-548346dd9427] [synemail] [ABSENT] [synfi] [0:0:0:0:0:0:0:1] [N/A] [N/A] [End Method]"}
Output expecting after applying the filters is
id => "63289e8d-13c9-4622-b1a1-548346dd9427"
token1 => "synemail"
First, I'd recommend parsing the text as a json to extract the "rest" value into a field. Then, assuming that the "rest" value has always the same structure, and in particular that the id is always within the third [] block and the token always within the fourth [], this grok rule should work for you
\[%{DATA}\] \[%{DATA}\] \[%{DATA:id}\] \[%{DATA:token1}\]
Note that you can always test your grok rules in Kibana, using the Grok debugger: https://www.elastic.co/guide/en/kibana/7.11/xpack-grokdebugger.html
And if you don't want to apply grok to the json directly without preprocessing it, this is the rule:
"rest":"\[%{DATA}\] \[%{DATA}\] \[%{DATA:id}\] \[%{DATA:token1}\]
Update based on the OP comments:
Assuming that the field you're parsing is "message" and that its value is a json as a text with escaped quotes, the full configuration of the Logstash grok filter something like:
grok {
match => { "message" => '\"rest\":\"\[%{DATA}\] \[%{DATA}\] \[%{DATA:id}\] \[%{DATA:token1}\]' }
}
I am trying to filter my logs matching few patterns I have. e.g:
E/vincinity/dholland_view_sql_global/IN/Cluster_Node/SSL-CACHE/Dsal1
F/vincinity/dholland_view_sql_local/IN/Cluster_Node3/SSL-CACHE/Dsal4
R/vincinity/dholland_view_sql_bran/IN/Cluster_Node/Sample/vr1.log
Now I want to grep these 3 paths from a bunch of logs: basically the pattern that I want to extract is logs containing "vincinity" "sql" and "IN" so with regex it would be simply *vincinity*sql*IN*
I tried this grok filter:
grok {
match => { "Vinc" => "%{URIPATHPARAM:*vincinity*sql*IN*}" }
}
Then I get _grokparsefailure in kibana - I'm brand new to grok, so perhaps I'm not approaching this correctly.
From the grok filter documentation
The syntax for a grok pattern is %{SYNTAX:SEMANTIC}
The way the grok filter should work is
grok {
match => {
"message" => "%{PATTERN:named_capture}"
}
}
Where message is the field that you want to parse, this is the default field that most inputs place your unparsed loglines in.
The URIPATHPARAM pattern is one predefined in logstash through a regex language called Onigurama. It may match your whole log message, but it will not capture certain chunks of it for you.
For help constructing a grok pattern, check out the docs, they link to a couple useful pattern construction tools.
The correct format for using a custom pattern in your grok block is:
(?<field_name>the pattern here)
or you can define your own custom pattern (using regular expression) in seperate file (my-pattern.txt) like this :
MYPATH_MUST_BE_UPPERCASE Regex_Pattern
save it in ./patterns directory and then use it this way:
grok {
patterns_dir => "./patterns"
match => ["message" , "%{MYPATH_MUST_BE_UPPERCAS:path}"]
}
in your case :
(?<vincinity>(?>/\s*.*?vincinity.*?\s*)+)
(?<sql>(?>/\s*.*?sql.*?/\s*)+)
(?<in>(?>\s*.*?(IN).*?\s*)+)
I am trying to extract the CPU usage and timestamp from the message:
2015-04-27T11:54:45.036Z| vmx| HIST ide1 IRQ 4414 42902 [ 250 - 375 ) count: 2 (0.00%) min/avg/max: 250/278.50/307
I am using logstash and here is my logstash.config file:
input {
file {
path => "/home/xyz/Downloads/vmware.log"
start_position => beginning
}
}
filter {
grok{
match => ["message", "%{#timestamp}"]
}
}
output{
stdout {
codec => rubydebug
}
}
But its giving me grok parse error, Any help would really be appreciated. Thanks.
As per the message from Magnus, you're using the grok match function incorrectly, #timestamp is the name of a system field that logstash uses as the timestamp the message was recieved at, not the name of a grok pattern.
First I recommend you have a look at some of the default grok patterns you can use which can be found here, then I also recommend you use the grok debugger finally, if all else fails, get yourself in the #logstash irc channel (on freenode), we're pretty active in there, so I'm sure someone will help you out.
Just to help you out a bit further, this is a quick grok pattern I have created which should match your example (I only used the grok debugger to test this, so results in production might not be perfect - so test it!)
filter {
grok {
match => [ "message", "%{TIMESTAMP_ISO8601}\|\ %{WORD}\|\ %{GREEDYDATA}\ min/avg/max:\ %{NUMBER:minimum}/%{NUMBER:average}/%{NUMBER:maximum}" ]
}
}
To explain slightly, %{TIMESTAMP_ISO8601} is a default grok pattern which matches the timestamp in your example.
You will notice the use of \ quite a lot, as the characters following this need to be escaped (because we're using a regex engine and spaces, pipes etc have a meaning, by escaping them we disable that meaning and use them literally).
I have used the %{GREEDYDATA} pattern as this will capture anything, this can be useful when you just want to capture the rest of the message, if you put it at the end of the grok pattern it will capture all remaining text.
I have then taken a bit from your example (min/avg/max) to stop the GREEDYDATA from capturing the rest of the message, as we want the data after that.
%{NUMBER} will capture numbers, obviously, but the bit after the : inside the curly braces defines the name that field will be given by logstash and subsequently saved in elasticsearch.
I hope that helps!
I'm trying to parse through a grok filter some very various exception, so I wrote a grok filter, with the help of rubular.com, to parse every single type of exception. The filter is:
grok {
match => { message => "^(?<year>\d{4})-(?<month>\d{1,2})-(?<day>\d{1,2})\W(?<hours>\d{2}):(?<minutes>\d{2}):(?<seconds>\d{2})(,)[0-9]*(.*)(?<log_level>(ERROR|INFO)) (?<exception>(.*\n^Axis.*\n.*\n.*\n.*\n.*\n.*\n.*\n.*)|(com.*trying.*\ncom.*is:.*\n.*java.*)|(com.*\n^org.*\n###.*non valido\n\n.*^###.*\n^###.*\n^###.*)|(.*trying.*\n^com.*ServiceException.*\n### Error querying.*\n\n.*\n^###.*\n.*)|(.*trying.*\n^com.*ServiceException.*\n^###.*\n^###.*)|(.*trying.*\n^com.*)|(.*\n^org.*\n###.*Exception.*\n### Cause:.*)|(com.*\n^org.*\n###.*)|(.*\n^java.*CORBA.*\n.*)|(.*\n^java*.*)|(com.*\n^com.*)|(.*null\n^Axis.*\n.*\n.*\n.*\n.*\n.*\n.*\n.*\n.*\n.*\n.*)|(.*\n))"}
}
which as you can see as a lot of OR conditions in the exception field and a lot of \n to take the carriage returns. The problem is that, from what I understood, Logstash can read only one line at a time and can't match multiple lines (so, even if on rubular this pattern was working perfectly, it doesn't in logstash).
How can I filter the exceptions correctly?
You can multiline before grok, for example java exceptions:
multiline {
type => %sometype
pattern => "(^\s)"
what => previous
}
So this will append all lines that starts with whitespace to previous. And after that you can use grok filter.
Oh, and you can mutate to avoid '\n' symbols after multiline:
mutate {
gsub => ["message", "\n", " "]
}
After that you are ready to filter multiline message.