Sherlock: Anomaly Detector

CI Coverage Status GPL 3.0

Maven Package [version 1.7 onwards]

Download [version <=1.6]

Table of Contents

Introduction to Sherlock

Sherlock is an anomaly detection service built on top of Druid. It leverages EGADS (Extensible Generic Anomaly Detection System) to detect anomalies in time-series data. Users can schedule jobs on an hourly, daily, weekly, or monthly basis, view anomaly reports from Sherlock's interface, or receive them via email.


  1. Timeseries Generation
  2. EGADS Anomaly Detection
  3. Redis database
  4. UI in Spark Java

Detailed Description

Timeseries Generation

Timeseries generation is the first phase of Sherlock's anomaly detection. The user inputs a full Druid JSON query with a metric name and group-by dimensions. Sherlock validates the query, adjusts the time interaval and granularity based on the EGADS config, and makes a call to Druid. Druid responds with an array of time-series, which are parsed into EGADS time-series.

Sample Druid Query:

  "metric": "metric(metric1/metric2)", 
  "aggregations": [
      "filter": {
        "fields": [
            "type": "selector", 
            "dimension": "dim1", 
            "value": "value1"
        "type": "or"
      "aggregator": {
        "fieldName": "metric2", 
        "type": "longSum", 
        "name": "metric2"
      "type": "filtered"
  "dimension": "groupByDimension", 
  "intervals": "2017-09-10T00:00:01+00:00/2017-10-12T00:00:01+00:00", 
  "dataSource": "source1", 
  "granularity": {
    "timeZone": "UTC", 
    "type": "period", 
    "period": "P1D"
  "threshold": 50, 
  "postAggregations": [
      "fields": [
          "fieldName": "metric1", 
          "type": "fieldAccess", 
          "name": "metric1"
      "type": "arithmetic", 
      "name": "metric(metric1/metric2)", 
      "fn": "/"
  "queryType": "topN"

Sample Druid Response:

[ {
  "timestamp" : "2017-10-11T00:00:00.000Z",
  "result" : [ {
    "groupByDimension" : "dim1",
    "metric(metric1/metric2)" : 8,
    "metric1" : 128,
    "metric2" : 16
  }, {
    "groupByDimension" : "dim2",
    "metric(metric1/metric2)" : 4.5,
    "metric1" : 42,
    "metric2" : 9.33
  } ]
}, {
  "timestamp" : "2017-10-12T00:00:00.000Z",
  "result" : [ {
    "groupByDimension" : "dim1",
    "metric(metric1/metric2)" : 9,
    "metric1" : 180,
    "metric2" : 20
  }, {
    "groupByDimension" : "dim2",
    "metric(metric1/metric2)" : 5.5,
    "metric1" : 95,
    "metric2" : 17.27
  } ]
} ]

EGADS Anomaly Detection

Sherlock calls the user-configured EGADS API for each generated time-series, generates anomaly reports from the response, and stores these reports in a database. Users may also elect to receive anomaly reports by email.

Redis Database

Sherlock uses a Redis backend Redis to store job metadata, generated anomaly reports, among other information, and as a persistent job queue. Keys related to Reports have retention policy. Hourly job reports have retention of 14 days and daily/weekly/monthly job reports have 1 year of retention.

Sherlock UI

Sherlock's user interface is built with Spark. The UI enables users to submit instant anomaly analyses, create and launch detection jobs, view anomalies on a heatmap, and on a graph.

Building Sherlock

A Makefile is provided with all build targets.

Building the JAR

make jar

This creates sherlock.jar in the target/ directory.

How to run

Sherlock is run through the commandline with config arguments.

java -Dlog4j.configuration=file:${path_to_log4j}/ \
      -jar ${path_to_jar}/sherlock.jar \
      --version $(VERSION) \
      --project-name $(PROJECT_NAME) \
      --port $(PORT) \
      --enable-email \
      --failure-email $(FAILURE_EMAIL) \
      --from-mail $(FROM_MAIL) \
      --reply-to $(REPLY_TO) \
      --smtp-host $(SMTP_HOST) \
      --interval-minutes $(INTERVAL_MINUTES) \
      --interval-hours $(INTERVAL_HOURS) \
      --interval-days $(INTERVAL_DAYS) \
      --interval-weeks $(INTERVAL_WEEKS) \
      --interval-months $(INTERVAL_MONTHS) \
      --egads-config-filename $(EGADS_CONFIG_FILENAME) \
      --redis-host $(REDIS_HOSTNAME) \
      --redis-port $(REDIS_PORT) \
      --execution-delay $(EXECUTION_DELAY) \
      --timeseries-completeness $(TIMESERIES_COMPLETENESS)

CLI args usage

args required default description
--help - false help
--config - null config
--version - v0.0.0 version
--egads-config-filename - provided egads-config-filename
--port - 4080 port
--interval-minutes - 180 interval-minutes
--interval-hours - 672 interval-hours
--interval-days - 28 interval-days
--interval-weeks - 12 interval-weeks
--interval-months - 6 interval-months
--enable-email - false enable-email
--from-mail if email enabled from-mail
--reply-to if email enabled reply-to
--smtp-host if email enabled smtp-host
--smtp-port - 25 smtp-port
--smtp-user - smtp-user
--smtp-password - smtp-password
--failure-email if email enabled failure-email
--execution-delay - 30 execution-delay
--valid-domains - null valid-domains
--redis-host - redis-host
--redis-port - 6379 redis-port
--redis-ssl - false redis-ssl
--redis-timeout - 5000 redis-timeout
--redis-password - - redis-password
--redis-clustered - false redis-clustered
--project-name - - project-name
--external-file-path - - external-file-path
--debug-mode - false debug-mode
--timeseries-completeness - 60 timeseries-completeness
--http-client-timeout - 20000 http-client-timeout
--backup-redis-db-path - null backup-redis-db-path
--druid-brokers-list-file - null druid-brokers-list-file


Prints commandline argument help message.


Path to a Sherlock configuration file, where the above configuration may be specified. Config arguments in the file override commandline arguments.


Version of sherlock.jar to display on the UI


Path to a custom EGADS configuration file. If none is specified, the default configuration is used.


Port on which to host the Spark application.


Number of historic data points to use for detection on time-series every minute.


Number of historic data points to use for detection on hourly time-series.


Number of historic data points to use for detection on daily time-series.


Number of historic data points to use for detection on weekly time-series.


Number of historic data points to use for detection on monthly time-series.


Enable the email service. This enables users to receive email anomaly report notifications.


The handle's FROM email displayed to email recipients.


The handle's REPLY TO email where replies will be sent.


The email service's SMTP HOST.


The email service's SMTP PORT. The default value is 25.


The email service's SMTP USER.


The email service's SMTP PASSWORD.


A dedicated email which may be set to receive job failure notifications.


Sherlock periodically pings Redis to check scheduled jobs. This sets the ping delay in seconds. Jobs are scheduled with a precision of one minute.


A comma-separated list of valid domains to receive emails, e.g. 'yahoo,gmail,hotmail'. If specified, Sherlock will restrict who may receive emails.


The Redis backend hostname.


The Redis backend port.


Whether Sherlock should connect to Redis via SSL.


The Redis connection timeout.


The password to use when authenticating to Redis.


Whether the Redis backend is a cluster.


Name of the project to display on UI.


Specify the path to external files for Spark framework via this argument.


Debug mode enables debug routes. Ex. '/DatabaseJson' (shows redis data as json dump). Look at for more details.


This defines minimum fraction of datapoints needed in the timeseries to consider it as a valid timeseries o/w sherlock ignores such timeseries. (default value 60 i.e. 0.6 in fraction)


HttpClient timeout can be configured using this(in millis). (default value 20000)


Backup redis DB at given file path as json dump of indices and objects. Backup is done per day at midnight. Default this parameter is null i.e. no buckup. However, BGSAVE command is run at midnight to save redis local dump.


Specify the path to an access control list file of permitted druid broker hosts for querying. Format: :,:... (default null i.e any host is allowed)


Jigar Patel, [email protected]

Jeff Niu, [email protected]


Josh Walters, [email protected]

Stephan Stiefel, Stephan3555


Code licensed under the GPL v3 License. See LICENSE file for terms.