Edge Delta Agent Settings

Global Pipeline configuration options.

Overview

There are a number of global settings you can configure in the Pipeline configuration v3 yaml file. These are contained in the settings section.

Pipeline configuration v2 uses the settings described in the v2 Agent Settings section.

Example

version: v3

settings:
  tag: prod
  log:
    level: debug
  persisting_cursor_settings:
    path: /var/edgedelta/pos
    file_name: cursor_file.json
    flush_interval: 1m
  archive_flush_interval: 5m
  archive_max_byte_limit: "16MB"
  source_discovery_interval: 5s
  anomaly_tolerance: 0.1
  anomaly_confidence_period: 1m
  skip_empty_intervals: false
  only_report_nonzeros: false
  anomaly_coefficient: 10.0
  item_buffer_flush_interval: 5s
  item_buffer_max_byte_limit: 1MiB
  multiline_max_size: 250
  multiline_max_byte_size: "10KB"
  max_incomplete_line_buffer_size: "10KB"
  metric_column_opts:
    drop_columns:
    - name: docker_id
      metric_categories:
      - incoming_outgoing
    - name: labels.*
      exceptions:
      - labels.app.value
      - labels.somefield.*

Parameters

anomaly_coefficient

The anomaly_coefficient parameter multiplies the final anomaly score by between 0 and 100. The higher the coefficient the higher the anomaly score will be. The default is 10. It can be set at the node level and/or dimension group level for some log_to_metric nodes. It is optional.

settings:
  tag: prod
  anomaly_coefficient: 12

anomaly_confidence_period

The anomaly_confidence_period parameter defines the period for which to ignore anomaly score calculations after a source is found. This helps prevent noise associated with a new source. It is defined with a duration and the default is 30m. It can be set at node level and/or dimension group level for some log_to_metric nodes. It is optional.

settings:
  tag: prod
  anomaly_confidence_period: 1m

anomaly_tolerance

The anomaly_tolerance parameter configures anomaly sensitivity. When anomaly_tolerance is non-zero, anomaly scores are better handled in edge cases better where the standard deviation is small. The default is 0.01. It can be set at node level and/or dimension group level for some log_to_metric nodes. It can also be set in the global agent settings. It is optional.

nodes:
  - name: <node name>
    type: log_to_metric
    pattern: <regex pattern>
    anomaly_tolerance: 0.03
settings:
  tag: prod
  anomaly_tolerance: 0.2

archive_flush_interval

The archive_flush_interval parameter defines the interval at which logs are flushed and send to archive destinations. The default value is 30m. It is optional.

settings:
  tag: prod
  archive_flush_interval: 30m

archive_max_byte_limit

The archive_max_byte_limit parameter defines the maximum bytes to buffer in memory until triggering an archive flush. When either archive_flush_interval or archive_max_byte_limit is reached, the agent flushes the buffered raw logs to configured archive destinations. The default byte size limit is 16MB. It is optional.

settings:
  tag: prod
  archive_max_byte_limit: "16MB"

item_buffer_flush_interval

The item_buffer_flush_interval parameter defines the interval after which item buffers will flush their contents. It is specified as a duration and the default is 5s.

settings:
  tag: prod
  item_buffer_flush_interval: 5s

item_buffer_max_byte_limit

The item_buffer_max_byte_limit parameter defines the size limit that will trigger an item buffer flush. It is specified as a string and the default is 1MiB.

settings:
  tag: prod
  item_buffer_max_byte_limit: 2MiB

log

The log parameter configures the severity level down to which the agent should populate its own log file. You use this log file to troubleshoot the agent itself. The configured level and more severe levels will be included. It is optional. Less severe levels will increase the log volume.

You specify one of the following levels in increasing order of severity:

  • debug
  • info
  • warn
  • error
  • fatal
settings:
  tag: prod
  log:
    level: debug

max_incomplete_line_buffer_size

The max_incomplete_line_buffer_size parameter defines maximum data that can be kept in a buffered line separator. This is useful when receiving JSON formatted and large inputs. When a single line is larger than 10KB, the line_pattern parameter can be used to separate inputs into valid JSON objects. It is specified as a string and the default value is 10KB.

settings:
  tag: prod
  max_incomplete_line_buffer_size: "20KB"

metric_column_opts

THe metric_column_opts parameter defines options for metric columns. Currently only column dropping (drop_columns)is supported. The drop_columns parameter defines metric columns that will not be sent to metric outputs. This can be used to reduce high cardinality issues. It supports prefix matching with a wildcard * as terminating character.

settings:
  tag: prod
  metric_column_opts:
    drop_columns:
    - name: docker_id
      metric_categories:
      - incoming_outgoing
    - name: labels.*
      exceptions:
      - labels.app.value
      - labels.somefield.*

multiline_max_size

The multiline_max_size parameter defines the multiline buffer size in length. You increase the maximum line number for overflow cases where all buffered lines are otherwise dumped as single line. It is specifies as an integer and is optional.

settings:
  tag: prod
  multiline_max_size: 250

multiline_max_byte_size

The multiline_max_byte_size parameter defines the multiline buffer size in bytes. Increase this maximum byte limit for overflow cases where all buffered lines are dumped as single line. It is specified as a data size string and the default is 10KB. It is optional.

settings:
  tag: prod
  multiline_max_byte_size: "20KB"

only_report_nonzeros

The only_report_nonzeros parameter configures the agent to only report non zero statistics. It is a Boolean value and the default is true. It can be set at node level and/or dimension group level for some log_to_metric nodes. It is optional.

settings:
  tag: prod
  only_report_nonzeros: false

persisting_cursor_settings

The persisting_cursor_settings parameter configures persisting cursor for environments where no data can be lost during agent restarts. It is optional.

  • path is the folder where the cursor file will be created.
  • file_name is the name of the cursor file.
  • flush_interval is the interval after which the file will be saved to from memory.
settings:
  tag: prod
  persisting_cursor_settings:
    path: /var/edgedelta/pos
    file_name: cursor_file.json
    flush_interval: 1m

skip_empty_intervals

The skip_empty_intervals parameter skips empty intervals so the anomaly scores are calculated based on rolling history of non-zero intervals. It is a Boolean value and the default is true. It can be set at node level and/or dimension group level for some log_to_metric nodes. It is optional.

settings:
  tag: prod
  skip_empty_intervals: true
nodes:
  - name: <node name>
    type: log_to_metric
    pattern: <regex pattern>
    skip_empty_intervals: true

source_discovery_interval

The source_discovery_interval parameter configures the duration after which source discovery is invoked. The default value is 5s and it is optional.

settings:
  tag: prod
  source_discovery_interval: 5s

tag

The tag parameter labels the environment in which the agent is installed to help identify it, for example prod_us_west_2_cluster. A custom value is recommended. It is specified as a string and is required.

settings:
  tag: prod_us_west_2_cluster