Glossary of terms used in application


By Agentless we regroup all the solutions available to send logs to a remote endpoint by directly calling it within your applications.

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An Alert

An alert is fired when a metric goes above or below a pre-defined value. In, this is defined on time series focused on a specific metric aggregated over a size of time bucket that evolves during time.
To illustrate this, some alerts can:

  • Notify me whenever a specific error occurs
  • Notify me whenever a throughput is lower than expected
  • Notify me whenever the CPU usage is too high for more than 15 minutes
  • And so on...

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An Attribute

An attribute comes from the attribute-value pairs from your raw JSON event.

It can be used to define Fields or Metrics for faceting or analytical purposes.

Attribute Remapping

Sometimes attributes are not named as you want because application are using different standards. Remapping an attribute consists in changing its name so 2 different datasets can be compared together.

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Calculated Metric

A Calculated metric can be either a Filtered metric or a Formula metric

  • Formula metrics allow you to combine different metrics / filtered metrics / other formula metrics with a formula.
    Find more information on how to create/edit a formula metric here

  • Filtered metrics are actually providing filtered aggregation of any regular metric. This is then the combination of a metric (an attribute and an aggregation function) and a context filter (a set of filters, search etc...).
    Find more information on how to create/edit a filtered metric here

Calculated metrics can be use as regular metrics in a widget


Columns are specific field values from a raw-event. They can either be displayed in the event list on the explore view or be request from the output API
Find more informations for the event list here
Find more informations for the output API here

Filter Context

The filtecontext is a (combination of) filter(s) on a given widget or on a dashboards.

Contextual Panel

The Contextual panel is there to provide extra details over some analytics or a raw log. It opens up any time you click on parts of a widget.
Just click on a raw-event or on some analytics (cell of table).

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Dashboards are single paged, real-time, clickable views. They show multiple widgets or alerts so you can:

  • Correlate different signals side by side
  • Get a bird eye view on a specific problem you want to monitor
  • Do top to bottom analysis by applying filters simply by clicking over analytical widgets

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Event list

The Event list or Drillthrough is the default widget for the exploration view.
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A Field is a dimension defined analytical or filtering purposes. It contains values extracted from raw attributes.

A field helps you to break down your datasets over user(s) or appname(s) while metrics provide aggregated information like Count, Memory usage, etc...

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Filter can be use to slice your data pool in order to focus on a specific context. They can be either applied:


A group is a set of Fields, Tag Sets and Metrics. It helps the user to quickly find the Fields & Metrics of interest depending on what is the current focus.

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Log shipper

A log shipper is a software that can "ship" logs from one of your host to a remote destination.
(eg: Rsyslog, FluentD, Syslog-ng, logstash ...)

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A metric is a numerical value associated to an aggregation method. It can be aggregated in a widget

Find more information on how to create/edit a metric here
Find more information on how to use a metric here

Parsing Extension

When you log format isn't standard or doesn't belong to the provided parsing library, you can define your own parsing rules. Input parsers are applied on every log entry that is submitted to
They are really useful to extract tokens from semi-structured messages and to re-use them as fields or metrics.

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A pipeline is a set of processors used to Enrich your data after it went to the Parsing phase.

Find more here


A Processor describe an action done on a raw event attribute.

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Raw Event

A Raw event corresponds to a event sent to your's platform. It generally contains multiple attributes and is represent as a JSON-like object.

The search Bar

The search bar aims at giving our users the full flexibility to quickly isolate a structured or unstructured dataset of events. The search query language is based on the Lucene query string.

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The Side Menu

The Side Menu or menu bar refers to the left panel of the application:
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Tag & Tag Set

Contrary to values which are directly extracted from existing attributes, a tag is applied to a log if a provided boolean query matches this log. In tags are regrouped in Tag sets.

A Tag in a Tag Set is just a way to quickly retrieve important subsets in your logs. So you won't have to enter complex search queries all the time.

Tag Sets are also very useful to create meaningful groups which can be used in any analytical view (eg URL groups, Machine groups, environments, response time buckets, etc....).

From the analytical point of view: Fields and Tag sets look like the same in the exploration view. But differences in their implementation allow you to enrich your logs in the best way that fit your needs.

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The exploration view

The exploration view is the main part of the application where you can:

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The Timeline

The timeline is where you easily define your time range of interest for the exploration view.
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Time Horizon

The Time horizon is the time range displayed by the whole timeline.
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Time Selector

The time selector represents the selected time range displayed in your analytical widgets. By default, the time selector is equal to the time horizon and so it is usually invisible as its lower and upper bounds stick to the time horizon's bounds.
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Top sentence

The Top sentence refers to the sentence present on top of analytics on the explore view.

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A widget is a way to display datasets.
It can be an Event List or an Analytics such as:

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Glossary of terms used in application

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