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How about no grep and zabbix?
or
ELK based metrics and alerts.
Vladimir Pavkin
QIWI Conf #3
Scala Developer
gettopical.com
Plan
ELK stack components
ELK setups
Basic usage (grep)
Advanced usage (alerts, metrics)
Da heck is ELK?
Elasticsearch
Logstash
Kibana
Logstash
Inputs
1+
Filters
0+
Outputs
1+
• raw data
• various formats
• enriched events
• standard formats
Logstash inputs
file, syslog, log4j
http, tcp, udp
rabbitmq
twitter, rss
…
Logstash filters
grok
geoip
drop, clone, mutate, split
…
Logstash outputs
stdout, file
elasticsearch
rabbitmq
http, tcp, udp
…
Logstash transformation example
127.0.0.1 - - [11/Dec/2013:00:01:45 -0800]
"GET /xampp/status.php HTTP/1.1" 200 3891
"http://cadenza/xampp/navi.php" "Mozilla/5.0 (Macintosh;
Intel Mac OS X 10.9; rv:25.0) Gecko/20100101 Firefox/25.0"
Logstash transformation example
{
"message" : "127.0.0.1 - - [11/Dec/2013:00:01:45 -0800] "GET /xampp/status.php
HTTP/1.1" 200 3891 "http://cadenza/xampp/navi.php" "Mozilla/5.0 (Macintosh;
Intel Mac OS X 10.9; rv:25.0) Gecko/20100101 Firefox/25.0"",
"@timestamp" : "2013-12-11T08:01:45.000Z",
"@version" : "1",
"host" : "cadenza",
"clientip" : "127.0.0.1",
"path" : "/xampp/status.php",
"response" : "200",
// ...
}
Elasticsearch
Distributed data storage, optimized for text
search.
Is managed/queried through HTTP REST API.
Based on open-source Apache Lucene
project.
Elasticsearch vocab
Document - data unit used for indexing
and searching. Contains fields. (JSON)
Field - a part of a Document, has a
name and a value.
Term - the unit of search. A word we
look for in text
Elasticsearch inverted index
Documents:
1 => How about no grep
2 => How about no zabbix
Index:
how => <1>, <2>
about => <1>, <2>
zabbix => <2>
...
Elasticsearch query DSL
message:exception
log_level:(ERROR OR INFO)
stack_trace:”Out of memory”
_exists_:body
date:[now-1h TO now]
age:(>=10 AND <20)
wildcards (*, ?)
regex search
fuzzy search (Levenshtein)
proximity search
boosting weights
Elasticsearch query DSL
Even more power with JSON query DSL:
{
"query_string" : {
"fields" : [“message", “stack_trace"],
"query" : “exception AND fatal"
}
}
Elasticsearch clustering
Just easy as hell
Kibana
Converts these:
{
"message" : "127.0.0.1 - - [11/Dec/2013:00:01:45 -0800] "GET /xampp/status.php
HTTP/1.1" 200 3891 "http://cadenza/xampp/navi.php" "Mozilla/5.0 (Macintosh; Intel
Mac OS X 10.9; rv:25.0) Gecko/20100101 Firefox/25.0"",
"@timestamp" : "2013-12-11T08:01:45.000Z",
"@version" : "1",
"host" : "cadenza",
"clientip" : "127.0.0.1",
"path" : "/xampp/status.php",
"response" : "200",
// ...
}
Kibana
To this:
Kibana timestamp field
Not strings/objects
Events!
ELK Setups
Simple setup (startup mode)
App1
App2
App3
logback
logback
logback
VPN
Single
instance
Logstash
Elastic
search
TCP/UDP
port
http:9200
Kibana
http:5601
Complex setup (QIWI)
App1
VPN
Logstash
logback
RMQ
App2
Logstash
logback
RMQ
RMQ
Elasticsearch
Elasticsearch
Elasticsearch
Kibana
RMQ
RMQ
RMQ
Basic ELK
usage scenarios
1. Search that whole cluster!
Events from all your apps are in one place!
Rocking useful and flexible timeline
Powerful, text oriented search engine
2. Default logback fields
Quickly filter events by:
Host name or IP
Log level, logger name
Search only in stack trace.
3. Customize and save searches
Save frequently used search
Show only specific fields
(e.g. message and host name)
Showtime
Advanced ELK.
Metrics and alerts.
1. Custom fields (search/filter)
Payment event:
{
“user” : “9112223344”,
“amount” : 500.00,
“provider” : 464
}
Log custom fields (JVM)
<appender name="LOGSTASH"
class="net.logstash.logback.appender.LogstashTcpSocketAppender">
<destination>127.0.0.1:4560</destination>
</appender>
<root level="DEBUG">
<!--...-->
<appender-ref ref="LOGSTASH" />
</root>
libraryDependencies +=
"net.logstash.logback" % "logstash-logback-encoder" % "4.5.1"
Log custom fields (JVM)
import net.logstash.logback.marker.Markers._
val fields = Map[String, Any](
"str_field" -> "str_value",
"num_field" -> 666
)
logger.info(appendEntries(fields), "log message");
2. Elastalert
Configured with a set of “rules”
Performs periodical queries to ES
Triggers alerts for matched rules
2. Elastalert rule types
Frequency
Spike
Flatline
Cardinality
Blacklist, Whitelist
Arbitrary query
# rules/500_frequency.yaml
es_host: localhost
es_port: 9200
name: 500 code frequency alert
type: frequency
index: logstash-*
num_events: 50
timeframe:
minutes: 1
alert:
- "email"
email:
- “s.solonin@qiwi.ru"
2. Elastalert alert types
Email
Slack
Jira
Custom shell command
2. Elastalert with custom fields
Any alert you can imagine can be
implemented on custom fields:
Average payment drops below 300 RUB
Processing response latency spike
User A buys something on Herbalife
3. Monitoring and Metrics
Realtime
Lots of aggregations
Beautiful visualizations
Super power with custom fields
Showtime
3. Why so useful?
Tech monitoring (UI and flexibility)
Business metrics (approx.)
Alerts (both tech and business)
Instant market/system reaction
Thanks !

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