Recent changes: As of Elastalert 0.2.0, you must use Python 3.6. Python 2 will not longer be supported.
ElastAlert - Read the Docs.
ElastAlert is a simple framework for alerting on anomalies, spikes, or other patterns of interest from data in Elasticsearch.
ElastAlert works with all versions of Elasticsearch.
At Yelp, we use Elasticsearch, Logstash and Kibana for managing our ever increasing amount of data and logs. Kibana is great for visualizing and querying data, but we quickly realized that it needed a companion tool for alerting on inconsistencies in our data. Out of this need, ElastAlert was created.
If you have data being written into Elasticsearch in near real time and want to be alerted when that data matches certain patterns, ElastAlert is the tool for you. If you can see it in Kibana, ElastAlert can alert on it.
We designed ElastAlert to be reliable, highly modular, and easy to set up and configure.
It works by combining Elasticsearch with two types of components, rule types and alerts. Elasticsearch is periodically queried and the data is passed to the rule type, which determines when a match is found. When a match occurs, it is given to one or more alerts, which take action based on the match.
This is configured by a set of rules, each of which defines a query, a rule type, and a set of alerts.
Several rule types with common monitoring paradigms are included with ElastAlert:
- Match where there are at least X events in Y time" (
frequency
type) - Match when the rate of events increases or decreases" (
spike
type) - Match when there are less than X events in Y time" (
flatline
type) - Match when a certain field matches a blacklist/whitelist" (
blacklist
andwhitelist
type) - Match on any event matching a given filter" (
any
type) - Match when a field has two different values within some time" (
change
type) - Match when a never before seen term appears in a field" (
new_term
type) - Match when the number of unique values for a field is above or below a threshold (
cardinality
type)
Currently, we have built-in support for the following alert types:
- JIRA
- OpsGenie
- Commands
- HipChat
- MS Teams
- Slack
- Telegram
- GoogleChat
- AWS SNS
- VictorOps
- PagerDuty
- PagerTree
- Exotel
- Twilio
- Gitter
- Line Notify
- Zabbix
Additional rule types and alerts can be easily imported or written.
In addition to this basic usage, there are many other features that make alerts more useful:
- Alerts link to Kibana dashboards
- Aggregate counts for arbitrary fields
- Combine alerts into periodic reports
- Separate alerts by using a unique key field
- Intercept and enhance match data
To get started, check out Running ElastAlert For The First Time
in the documentation.
You can either install the latest released version of ElastAlert using pip:
pip install elastalert
or you can clone the ElastAlert repository for the most recent changes:
git clone https://github.com/Yelp/elastalert.git
Install the module:
pip install "setuptools>=11.3"
python setup.py install
The following invocation can be used to run ElastAlert after installing
$ elastalert [--debug] [--verbose] [--start <timestamp>] [--end <timestamp>] [--rule <filename.yaml>] [--config <filename.yaml>]
--debug
will print additional information to the screen as well as suppresses alerts and instead prints the alert body. Not compatible with --verbose
.
--verbose
will print additional information without suppressing alerts. Not compatible with --debug.
--start
will begin querying at the given timestamp. By default, ElastAlert will begin querying from the present.
Timestamp format is YYYY-MM-DDTHH-MM-SS[-/+HH:MM]
(Note the T between date and hour).
Eg: --start 2014-09-26T12:00:00
(UTC) or --start 2014-10-01T07:30:00-05:00
--end
will cause ElastAlert to stop querying at the given timestamp. By default, ElastAlert will continue
to query indefinitely.
--rule
will allow you to run only one rule. It must still be in the rules folder.
Eg: --rule this_rule.yaml
--config
allows you to specify the location of the configuration. By default, it is will look for config.yaml in the current directory.
Available at the ElastAlert Kibana plugin repository.
A Dockerized version of ElastAlert including a REST api is build from master
to bitsensor/elastalert:latest
.
git clone https://github.com/bitsensor/elastalert.git; cd elastalert
docker run -d -p 3030:3030 \
-v `pwd`/config/elastalert.yaml:/opt/elastalert/config.yaml \
-v `pwd`/config/config.json:/opt/elastalert-server/config/config.json \
-v `pwd`/rules:/opt/elastalert/rules \
-v `pwd`/rule_templates:/opt/elastalert/rule_templates \
--net="host" \
--name elastalert bitsensor/elastalert:latest
Read the documentation at Read the Docs.
To build a html version of the docs locally
pip install sphinx_rtd_theme sphinx
cd docs
make html
View in browser at build/html/index.html
See config.yaml.example for details on configuration.
Examples of different types of rules can be found in example_rules/.
-
example_spike.yaml
is an example of the "spike" rule type, which allows you to alert when the rate of events, averaged over a time period, increases by a given factor. This example will send an email alert when there are 3 times more events matching a filter occurring within the last 2 hours than the number of events in the previous 2 hours. -
example_frequency.yaml
is an example of the "frequency" rule type, which will alert when there are a given number of events occuring within a time period. This example will send an email when 50 documents matching a given filter occur within a 4 hour timeframe. -
example_change.yaml
is an example of the "change" rule type, which will alert when a certain field in two documents changes. In this example, the alert email is sent when two documents with the same 'username' field but a different value of the 'country_name' field occur within 24 hours of each other. -
example_new_term.yaml
is an example of the "new term" rule type, which alerts when a new value appears in a field or fields. In this example, an email is sent when a new value of ("username", "computer") is encountered in example login logs.
So you've managed to set up ElastAlert, write a rule, and run it, but nothing happens, or it says 0 query hits
. First of all, we recommend using the command elastalert-test-rule rule.yaml
to debug. It will show you how many documents match your filters for the last 24 hours (or more, see --help
), and then shows you if any alerts would have fired. If you have a filter in your rule, remove it and try again. This will show you if the index is correct and that you have at least some documents. If you have a filter in Kibana and want to recreate it in ElastAlert, you probably want to use a query string. Your filter will look like
filter:
- query:
query_string:
query: "foo: bar AND baz: abc*"
If you receive an error that Elasticsearch is unable to parse it, it's likely the YAML is not spaced correctly, and the filter is not in the right format. If you are using other types of filters, like term
, a common pitfall is not realizing that you may need to use the analyzed token. This is the default if you are using Logstash. For example,
filter:
- term:
foo: "Test Document"
will not match even if the original value for foo
was exactly "Test Document". Instead, you want to use foo.raw
. If you are still having trouble troubleshooting why your documents do not match, try running ElastAlert with --es_debug_trace /path/to/file.log
. This will log the queries made to Elasticsearch in full so that you can see exactly what is happening.
If you got logs that had X query hits, 0 matches, 0 alerts sent
, it depends on the type
why you didn't get any alerts. If type: any
, a match will occur for every hit. If you are using type: frequency
, num_events
must occur within timeframe
of each other for a match to occur. Different rules apply for different rule types.
If you see X matches, 0 alerts sent
, this may occur for several reasons. If you set aggregation
, the alert will not be sent until after that time has elapsed. If you have gotten an alert for this same rule before, that rule may be silenced for a period of time. The default is one minute between alerts. If a rule is silenced, you will see Ignoring match for silenced rule
in the logs.
If you see X alerts sent
but didn't get any alert, it's probably related to the alert configuration. If you are using the --debug
flag, you will not receive any alerts. Instead, the alert text will be written to the console. Use --verbose
to achieve the same affects without preventing alerts. If you are using email alert, make sure you have it configured for an SMTP server. By default, it will connect to localhost on port 25. It will also use the word "elastalert" as the "From:" address. Some SMTP servers will reject this because it does not have a domain while others will add their own domain automatically. See the email section in the documentation for how to configure this.
There is a setting called realert
which is the minimum time between two alerts for the same rule. Any alert that occurs within this time will simply be dropped. The default value for this is one minute. If you want to receive an alert for every single match, even if they occur right after each other, use
realert:
minutes: 0
You can of course set it higher as well.
By setting realert
, you will prevent the same rule from alerting twice in an amount of time.
realert:
days: 1
You can also prevent duplicates based on a certain field by using query_key
. For example, to prevent multiple alerts for the same user, you might use
realert:
hours: 8
query_key: user
Note that this will also affect the way many rule types work. If you are using type: frequency
for example, num_events
for a single value of query_key
must occur before an alert will be sent. You can also use a compound of multiple fields for this key. For example, if you only wanted to receieve an alert once for a specific error and hostname, you could use
query_key: [error, hostname]
Internally, this works by creating a new field for each document called field1,field2
with a value of value1,value2
and using that as the query_key
.
The data for when an alert will fire again is stored in Elasticsearch in the elastalert_status
index, with a _type
of silence
and also cached in memory.
You can use the field alert_text
to add custom text to an alert. By setting alert_text_type: alert_text_only
, it will be the entirety of the alert. You can also add different fields from the alert by using Python style string formatting and alert_text_args
. For example
alert_text: "Something happened with {0} at {1}"
alert_text_type: alert_text_only
alert_text_args: ["username", "@timestamp"]
You can also limit the alert to only containing certain fields from the document by using include
.
include: ["ip_address", "hostname", "status"]
If you are using type: frequency
, you can set the option attach_related: true
and every document will be included in the alert. An alternative, which works for every type, is top_count_keys
. This will show the top counts for each value for certain fields. For example, if you have
top_count_keys: ["ip_address", "status"]
and 10 documents matched your alert, it may contain something like
ip_address:
127.0.0.1: 7
10.0.0.1: 2
192.168.0.1: 1
status:
200: 9
500: 1
The aggregation
feature will take every alert that has occured over a period of time and send them together in one alert. You can use cron style syntax to send all alerts that have occured since the last once by using
aggregation:
schedule: '2 4 * * mon,fri'
There are several ways to potentially speed up queries. If you are using index: logstash-*
, Elasticsearch will query all shards, even if they do not possibly contain data with the correct timestamp. Instead, you can use Python time format strings and set use_strftime_index
index: logstash-%Y.%m
use_strftime_index: true
Another thing you could change is buffer_time
. By default, ElastAlert will query large overlapping windows in order to ensure that it does not miss any events, even if they are indexed in real time. In config.yaml, you can adjust buffer_time
to a smaller number to only query the most recent few minutes.
buffer_time:
minutes: 5
By default, ElastAlert will download every document in full before processing them. Instead, you can have ElastAlert simply get a count of the number of documents that have occured in between each query. To do this, set use_count_query: true
. This cannot be used if you use query_key
, because ElastAlert will not know the contents of each documents, just the total number of them. This also reduces the precision of alerts, because all events that occur between each query will be rounded to a single timestamp.
If you are using query_key
(a single key, not multiple keys) you can use use_terms_query
. This will make ElastAlert perform a terms aggregation to get the counts for each value of a certain field. Both use_terms_query
and use_count_query
also require doc_type
to be set to the _type
of the documents. They may not be compatible with all rule types.
The only aggregation supported currently is a terms aggregation, by setting use_terms_query
.
You can use timestamp_field
to change which field ElastAlert will use as the timestamp. You can use timestamp_type
to change it between ISO 8601 and unix timestamps. You must have some kind of timestamp for ElastAlert to work. If your events are not in real time, you can use query_delay
and buffer_time
to adjust when ElastAlert will look for documents.
When using type: flatline
, ElastAlert must see at least one document before it will alert you that it has stopped seeing them.
ElastAlert does not currently support stateful alerts or resolve events.
Currently, the only way to set a warning threshold is by creating a second rule with a lower threshold.
ElastAlert is licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0
Read the documentation at Read the Docs.
There is now a must_not
field which behaves similarly to the filter field, only excludes hits.
A cron scheduler is added. This works by running jobs based on a cron scheduler rather than the default interval scheduling. To use this, instead of defining "run_every" in the rule, use cron_schedule. See the below example.
cron_schedule: "0 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23 * * *"
Format is: minute (0-59), hour (0-23), day of month (1-31), month (1-12), day of week (MON-SUN)
Fields are separated by space, values separated by comma, * for all values
notice that cron_schedule is currently only supported for use_count_query uses.