Events to Metrics in Chronologics

Study Notes

Events to Metrics Overview

Events to Metrics allows users to turn logs or spans into metrics, making it easy to hold onto data for a long time without incurring high costs.
Metrics are very easy to retain and can be queried in a very performant way across long periods of time.
This feature unlocks historical reporting capabilities without the need for expensive indexing.

Prerequisites

A metrics bucket needs to be set up in order for Events to Metrics to work.
The metrics bucket can be set up in the Data Flow section, inside the Archive section.

Benefits

Events to Metrics enables huge cost savings while retaining key information over a long period of time.
The power of Chronologics lies in the ability to convert logs and traces into metrics without indexing, resulting in significant cost savings.

Converting Logs to Metrics

In the Log Explore view, users can filter logs by a specific field, such as HTTP response took Ms.
A query can be run to capture the field, and then an event to metrics category can be defined to capture the field.
The metric series will start generating from the particular field when the "Save" button is clicked.
The resulting metrics can be visualized in a custom dashboard.

Converting Spans to Metrics

Spans can be converted into metrics in a similar way to logs.
Users can extract the duration field from a span and generate metrics from it.
The resulting metrics can be visualized in a custom dashboard.

Creating an Event to Metrics Feature

To create an event to metrics feature, users need to hover over Data Flow, go to Events to Metrics, and click on "New Event to Metric".
The first step is to enter basic details, such as the name and description of the event to metric.
Users can then choose between logs and spans, and enter a query to filter the data.
Metric fields can be defined, and labels can be added to the metrics.

Metric Fields

Up to 10 different metric fields can be defined.
Metric fields can be used to generate different metric series, such as maximum, minimum, and average.
Advanced options allow users to customize the metric fields, such as adding histograms or aggregations.

Labels

Labels are essentially values that can be added to metrics.
Labels can be used to query and slice the data.
Users need to be aware of the implications of adding labels, as they can affect the number of permutations.

Permutations

Permutations refer to the different combinations of unique values for labels.
The number of permutations can quickly increase if multiple labels are added.
A graph is available to show the number of permutations per day, helping users to understand the impact of adding labels.

Best Practices

It is recommended to make specific queries to avoid slowdowns.
Users should be aware of the implications of adding labels and permutations.
It is important to think about how the data will be used and define labels accordingly.### Permutations
Permutations can quickly increase exponentially, making it possible to reach the 10 million permutations per account limit
It is essential to carefully consider labels with unique values and how they impact permutation metrics

Managing Permutations

Use the Matrix permutations graph to understand the impact of labels on permutations
Allocate a daily permutation budget (e.g., 1100, 1200, etc.) to avoid reaching the limit
Consider the permutation budget when adding labels, and evaluate whether they are necessary or can be optimized

Event to Metrics Configuration

Configure events to metrics, setting the query, scope, and severities for logs
Set services and actions for given spans
Configure different values in the metrics fields (limited to 10 metric fields per program to metrics)

Metric Permutations and Labels

Metric permutations are crucial, and their impact should be monitored
The number of metric permutations can be viewed in the dashboard
Labels can significantly affect permutations, making it essential to balance the number of labels and high cardinality labels with the permutation budget

Benefits of Custom Dashboards

Cost-effective: storing data in object storage in the cloud account
Prerequisite: having the metrics archive set up
No additional cost impact: generate data without incurring extra costs
Provides powerful, high-performance historical perception of data

Description

Learn about the Events to Metrics feature in Chronologics, which allows users to convert logs and spans into metrics, enabling cost-effective historical reporting and data analysis. This feature provides a powerful way to retain data without incurring high costs. Discover how to set up and configure Events to Metrics, and understand the benefits of using custom dashboards.

Events to Metrics in Chronologics

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Questions and Answers

What is the main advantage of using Events to Metrics?

What is a prerequisite for using Events to Metrics?

How are logs converted to metrics in Events to Metrics?

What can be visualized in a custom dashboard in Events to Metrics?

How are spans converted to metrics in Events to Metrics?

What is the benefit of using Chronologics?

What is the first step in creating an event to metrics feature?

What is the maximum number of metric fields that can be defined?

What do labels essentially represent in metrics?

What can be done to avoid reaching the 10 million permutations per account limit?

What is a recommended practice when creating events to metrics?

What is a benefit of using custom dashboards?