The Great Logging Crusade: How a Simple Text File Can Change the World
Tags: debugging, logging, programmertools, softwareengineering
Published: 2023-01-10 01:14:40

---
title: The Great Logging Crusade: How a Simple Text File Can Change the World
published: true
date: 2023-01-09 14:08:55 UTC
tags: Debugging,Logging,ProgrammerTools,SoftwareEngineering
canonical_url: https://techdevblog.io/the-great-logging-crusade-how-a-simple-text-file-can-change-the-world/
---

 ![The Great Logging Crusade: How a Simple Text File Can Change the World](https://techdevblog.io/content/images/2023/01/image_5-3.jpg)

Welcome to our guide on logging best practices! In this guide, we will cover a variety of topics related to logging, including:

- The importance of logging
- How to format logs
- How to improve their readability
- How to make them prettier

We will also discuss a few popular libraries, frameworks, and tools for different programming languages and platforms that can help you implement these best practices in your own projects.

## The Importance of Logging

Logging is an essential part of software development and maintenance that allows developers to track the behaviour of their code and identify issues that may arise. Proper logging can help you:

- Troubleshoot problems more efficiently
- Understand how your code is being used
- Make informed decisions about how to improve your application

In addition to these benefits, logging can also help you:

- Monitor the performance of your code
- Detect security breaches or other malicious activity
- Meet regulatory or compliance requirements

Ignoring or neglecting logging can have nefarious consequences, such as:

- a lack of information and context on hard to reproduce bugs,
- misunderstanding of the code's behaviour by misleading developers with inaccurate, incomplete or useless log message,
- generally increased debugging times, leading to increased downtime and user frustration.

Therefore, it is important to give proper attention to logging in your projects and not treat it as a mere afterthought.

## Common Logging Pitfalls

While logging is an important aspect of software development, it is often overlooked or implemented poorly in many projects. Here are a few common pitfalls to avoid when implementing logging:

- Neglecting to log important events or information: Without sufficient logging, it can be difficult to understand the context of an issue or identify the root cause of a problem.
- Using vague or generic log messages: Log messages should be clear and descriptive, providing specific, actionable information about what is happening in your code. Using vague or generic messages like "error" or "warning" can make it more difficult to understand the context of a log message and identify the root cause of an issue.
- Lack of consistency in log format: It is important to use a consistent format for your log messages to make them easier to read and parse. This might include using a specific syntax or structure for your log messages, such as including the log level (e. g. "debug", "info", "warning", etc.) at the beginning of each message. Inconsistent log formats can make it difficult to extract and analyze relevant information from your logs.
- Not using appropriate log levels: Different log levels (e.g. "debug", "info", "warning", etc.) are used to indicate the severity of a log message. By using the appropriate log level for each message, you can more easily filter and prioritize your logs based on their importance. Using the wrong log level for a message can make it harder to understand the context and significance of the message.
- Neglecting to use log filtering and aggregation tools: There are a variety of tools available that can help you filter and aggregate your logs to make them easier to read and analyze. By neglecting to use these tools, you may miss important log messages or have a harder time understanding the context of a problem.

## Formatting Logs

Now that we've covered the importance of logging and some common pitfalls to avoid, let's turn our attention to formatting logs. Proper formatting is crucial to making your logs clear, concise, and easy to understand. Here are a few tips for formatting your logs effectively:

- Use clear, descriptive log messages: Your log messages should clearly and concisely describe what is happening in your code. Avoid using vague or generic messages like "error" or "warning." Instead, provide specific, actionable information that will help you understand the context of the log message.
- Include relevant information: In addition to a descriptive log message, you should also include any relevant information that may help you understand the context of the log message. This might include the date and time of the log message, the location in your code where the log message was generated, and any relevant variables or data.
- Use a consistent format: It's important to use a consistent format for your log messages to make them easier to read and parse. This might include using a specific syntax or structure for your log messages, such as including the log level (e.g. "debug", "info", "warning", etc.) at the beginning of each message.

## Improving Readability

In addition to formatting your logs effectively, there are a few other things you can do to improve their readability:

- Use appropriate log levels: Different log levels (e.g. "debug", "info", "warning", etc.) are used to indicate the severity of a log message. By using the appropriate log level for each message, you can more easily filter and prioritize your logs based on their importance.
- Use log filtering and aggregation tools: There are a variety of tools available that can help you filter and aggregate your logs to make them easier to read and analyze. For example, you might use a tool like Logstash or Splunk to search and filter your logs, or a tool like [Datadog](https://www.datadoghq.com), [Loggly](https://www.loggly.com) or [sumo Logic](https://www.sumologic.com) to aggregate and visualize your logs.
- Use log visualization tools: Visualization tools can help you make sense of large volumes of log data by displaying it in an easy-to-understand graphical format. Some popular log visualization tools include [Grafana](https://grafana.com) and [Kibana](https://www.elastic.co/kibana/).

## Making Logs Prettier

While the primary goal of logging is to provide useful information about the behavior of your code, there's no reason your logs can't also be visually appealing! Here are a few tips for making your logs prettier:

- Use color coding: Many logging libraries and tools support the use of color coding to make it easier to differentiate between different log levels and types of messages. For example,
- Use ASCII art: ASCII art is a fun and creative way to make your logs more visually interesting. You might use ASCII art to decorate your log messages, or to create custom log levels or icons. Just be sure to use ASCII art sparingly, as it can make your logs more difficult to read if overused.
- Use log templates: Some logging libraries and tools support the use of log templates, which allow you to specify the layout and format of your log messages using placeholders. This can be a useful way to create a consistent, visually appealing look for your logs.

## Libraries & Frameworks

Now that we've covered some best practices for logging, let's take a look at a few popular libraries, frameworks, and tools for different programming languages and platforms:

### Python

- Python's built-in logging library is a popular choice for logging in Python applications. It provides a flexible and powerful logging system that supports a variety of log levels, handlers, and formatting options.
- The [loguru](https://github.com/Delgan/loguru) library is another popular choice for logging in Python. It is designed to be simple and lightweight, and offers a number of convenience features such as automatic log formatting and integration with popular logging frameworks like [structlog](https://www.structlog.org/en/stable/).
- The[ structlog](https://www.structlog.org/en/stable/) library is a structured logging library for Python that allows you to specify the structure of your log messages using a simple API. This can be useful for generating logs that are easier to parse and analyze.

### JavaScript

- The [winston](https://github.com/winstonjs/winston) library is a popular choice for logging in [Node.js](https://nodejs.org) applications. It supports a wide range of log levels, transports (e.g. console, file, HTTP), and formatting options.
- The [bunyan](https://github.com/trentm/node-bunyan) library is another popular logging library for [Node.js](https://nodejs.org). It is designed to be fast and easy to use, and supports log message serialization and rotation.
- The [debug](https://github.com/debug-js/debug) library is a small utility for debugging [Node.js](https://nodejs.org) and browser applications that, amongst other things, allows you to enable and disable debug messages on a per-module basis.

### Java

- The [Log4j](https://logging.apache.org/log4j/2.x/) library ([be careful to use an up-to-date version](https://theconversation.com/what-is-log4j-a-cybersecurity-expert-explains-the-latest-internet-vulnerability-how-bad-it-is-and-whats-at-stake-173896)) is a popular choice for logging in Java applications. It supports a variety of log levels, appenders (e.g. console, file, database), and formatting options.
- The [SLF4J](https://www.google.com/search?client=safari&rls=en&q=SLF4J&ie=UTF-8&oe=UTF-8) library is a simple facade for logging in Java that allows you to use a variety of different logging implementations (e.g. [Log4j](https://logging.apache.org/log4j/2.x/), java.util.logging) without changing your code.
- The [Logback](https://logback.qos.ch) library is a fast, flexible logging library for Java that is designed to be a successor to [Log4j](https://logging.apache.org/log4j/2.x/). It offers a number of advanced features such as automatic log rotation and support for multiple log formats.

### Log Filtering, Aggregation & Visualisation Tools

#### Log Filtering Tools

Here is a list of popular log filtering tools that can help you identify and analyze:

##### Open-Source Tools

- [Elasticsearch](https://www.elastic.co): [Elasticsearch](https://www.elastic.co) is an open-source search and analytics engine that allows you to search, filter, and analyze your logs. It is often used in conjunction with other open-source tools such as [Logstash](https://www.elastic.co/logstash/) and [Kibana](https://www.elastic.co/kibana/).
- [Kibana](https://www.elastic.co/kibana/): [Kibana](https://www.elastic.co/kibana/) is an open-source data visualization and exploration platform that allows you to search, filter, and visualize your logs. It is often used in conjunction with other open-source tools such as [Elasticsearch](https://www.elastic.co) and [Logstash](https://www.elastic.co/logstash/).

##### SaaS Tools

- [Datadog](https://www.datadoghq.com): [Datadog](https://www.datadoghq.com) is a cloud-based monitoring and analytics platform that allows you to search, filter, and visualize your logs. It offers a variety of features such as real-time alerting, dashboarding, and integrations with other tools and platforms.
- [Logz.io](https://logz.io): [Logz.io](https://logz.io) is a cloud-based log analytics platform that allows you to search, filter, and analyze your logs in real-time. It offers a range of features including machine learning-based analytics, real-time alerting, and integrations with other tools and platforms.
- [Logentries](https://logentries.com): [Logentries](https://logentries.com) is a cloud-based log analytics platform that allows you to search, filter, and visualize your logs in real-time. It offers a variety of features such as alerting, dashboarding, and integrations with other tools and platforms.

#### Log Aggregation Tools

Here is a list of popular log aggregation tools that can help you collect and combine logs from multiple sources:

##### Open-Source Tools

- [Logstash](https://www.elastic.co/logstash/): [Logstash](https://www.elastic.co/logstash/) is an open-source log collection and processing pipeline that allows you to collect and combine logs from multiple sources. It is often used in conjunction with other open-source tools such as Elasticsearch and Kibana.
- [Fluentd](https://www.fluentd.org): [Fluentd](https://www.fluentd.org) is an open-source log collection and processing daemon that allows you to collect and forward logs from a variety of sources. It is designed to be lightweight and scalable, and offers a range of features such as log routing and filtering, and integrations with popular tools and platforms.
- [Graylog](https://www.graylog.org): [Graylog](https://www.graylog.org) is an open-source log management platform that allows you to collect, search, and visualize your logs. It offers a range of features including real-time alerting, dashboarding, and integrations with other tools and platforms.

##### SaaS Tools

- [Mezmo](https://www.mezmo.com): [Mezmo](https://www.mezmo.com) (formerly LogDNA) is a cloud-based log management platform that allows you to collect, search, and visualize your logs in real-time. It offers a range of features such as alerting, dashboarding, and integrations with other tools and platforms.
- [LogRhythm](https://logrhythm.com): [LogRhythm](https://logrhythm.com) is a cloud-based log management and analytics platform that allows you to collect, search, and visualize your logs. It offers a variety of features such as real-time alerting, dashboarding, and integrations with other tools and platforms.
- [Logz.io](https://logz.io): [Logz.io](https://logz.io) is a cloud-based log analytics platform that allows you to collect, search, and visualize your logs in real-time. It offers a range of features including machine learning-based analytics, real-time alerting, and integrations with other tools and platforms.

#### Log Visualization Tools

Here is a list of popular log visualization tools that can help you make sense of large volumes of log data:

##### Open-Source Tools

- [Grafana](https://grafana.com): [Grafana](https://grafana.com) is an open-source data visualization and monitoring platform that allows you to create custom dashboards to visualize your data. It supports a variety of data sources including logs, and offers a range of features such as alerting and integration with other tools and platforms.
- [Kibana](https://www.elastic.co/kibana/): [Kibana](https://www.elastic.co/kibana/) is an open-source data visualization and exploration platform that allows you to search, filter, and visualize your logs. It is often used in conjunction with other open-source tools such as [Elasticsearch](https://www.elastic.co) and [Logstash](https://www.elastic.co/logstash/).
- [Prometheus](https://prometheus.io): [Prometheus](https://prometheus.io) is an open-source monitoring and alerting platform that allows you to collect and visualize your log and metric data. It offers a range of features such as real-time alerting, dashboarding, and integrations with other tools and platforms.

##### SaaS Tools

- [Splunk](https://www.splunk.com): [Splunk](https://www.splunk.com) is a popular data analysis and visualization platform that allows you to search, filter, and visualize your log data. It offers a variety of features including real-time alerting, dashboarding, and integrations with other tools and platforms.
- [Datadog](https://www.datadoghq.com): [Datadog](https://www.datadoghq.com) is a cloud-based monitoring and analytics platform that allows you to search, filter, and visualize your logs. It offers a variety of features such as real-time alerting, dashboarding, and integrations with other tools and platforms.
- [Logz.io](https://logz.io): [Logz.io](https://logz.io) is a cloud-based log analytics platform that allows you to search, filter, and analyze your logs in real-time. It offers a range of features including machine learning-based analytics, real-time alerting, and integrations with other tools and platforms.

## Conclusion

In conclusion, logging is an essential practice that allows you to understand the behavior of your code and troubleshoot problems.

There are several best practices that can help you make the most of your logs, including using clear, descriptive log messages, including relevant information, and using a consistent format.

In addition, using appropriate log levels, log filtering and aggregation tools, and log visualization tools can help you improve the readability and usefulness of your logs, and using consistent formats can make them easier to both read and parse.

Finally, there are a variety of libraries, frameworks, and tools available for different programming languages and platforms that can help you implement logging best practices in your projects.

We hope this guide has provided you with a useful overview of logging best practices and some popular tools and libraries for different programming languages and platforms. Happy logging!

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