Organizing custom metrics for effective application monitoring
Tags: java, kotlin, oop, architecture
Published: 2023-10-13 08:37:44

## Disclaimer

This article represents my perspective on this solution, thus any suggestions, fixes, or discussions will be highly appreciated.

## The short story

In many projects I've been a part of, I've witnessed the challenges caused by disorganized metrics. Team members often struggled to discern which metrics were actively in use, especially in projects lacking a well-architected structure. In such cases, it wasn't uncommon to encounter classes like 'MetricService,' which aggregated static methods for various counters without any logical organization. To address these issues, I propose the approach described below to effectively organize this crucial aspect of application monitoring.

## The intro

In the world of backend development, metrics are the eyes and ears of your application. They provide critical insights into its performance, allowing you to spot issues, optimize code, and ensure a seamless user experience. However, when metrics are scattered and disorganized, they become more of a headache than a helpful tool. In this article, we'll explore the challenges of disorganized metrics and present a practical solution: organizing all your metrics within a dedicated package and using a dedicated enum.

### The importance of well-organized metrics

Metrics are essential in understanding the heartbeat of your backend application. They serve as early warning systems, helping you detect and diagnose issues promptly. Well-organized metrics offer several key advantages:

* _Clarity_: metrics should be self-explanatory. Organized metrics make it clear what is being monitored, reducing confusion during troubleshooting.
* _Efficiency_: accessing and analyzing metrics is significantly faster when they are neatly organized. This streamlines the debugging process.
* _Scalability_: as your application grows, so does the number of metrics. An organized system makes it easier to manage a large number of metrics.

Dealing with disorganized metrics can lead to a range of problems:

* _Confusion_: it's challenging to make sense of metrics when they have vague or inconsistent names. This can lead to mistakes and delays in issue resolution.
* _Time-consuming analysis_: scouring through countless metrics to find the relevant ones wastes valuable time, especially during critical incidents.
* _Maintenance nightmares_: as your application evolves, so do the metrics. Without proper organization, maintenance becomes a nightmare.

### The solution: dedicated package and enums

To overcome these challenges, I propose a two-fold solution:

1. _Dedicated packages for metrics_: create a dedicated package or namespace for metrics. This isolates them from other parts of your codebase, enhancing clarity.
2. _Dedicated enums for categories_: use an enum to categorize and label your metrics. This adds a layer of organization and makes metrics more self-explanatory.

Organizing metrics in this way offers numerous advantages:

* _Clear hierarchy_: metrics grouped within packages and categorized by enums create a clear hierarchy that simplifies navigation and comprehension.
* _Easy maintenance_: when new metrics are added, or existing ones are modified, it's much easier to manage and update them when they're organized.
* _Enhanced collaboration_: team members can quickly understand and work with metrics, which fosters better collaboration.

## The implementation

1. _Create dedicated package_: designate a package, directory, or folder in your codebase for metrics. For example, `com.project.util.metric`.

2. _Utilize enums_: create an enum for metric categories: `Metric`. This can include also categories like `BusinessMetric`, `ApiMetric` and so on.

```java
@Getter
@RequiredArgsConstructor
public enum Metric {

    METRIC_ONE("metric.one"),
    METRIC_TWO("metric.two");

    private final String name;

}
```

3. _Consistent naming_: ensure that all metrics follow a consistent naming convention, and use the enum values as labels:

```java
@Getter
@RequiredArgsConstructor
public enum Label {

    STATUS("status"),
    TYPE("type");

    private final String name;

}
```
```java
@Getter
@RequiredArgsConstructor
public enum Value {

    SUCCESS("success"),
    FAILURE("failure");

    private final String name;

}
```

4. _Documentation_: document your metrics and their categories. This provides a reference for your team and future developers. If you use Maven use it: [Apache Maven Javadoc Plugin](https://maven.apache.org/plugins/maven-javadoc-plugin/#apache-maven-javadoc-plugin).

5. _Clear architecture_: avoid the temptation to lump all your counters into a monolithic 'god' class. This can lead to uncontrolled growth and make code reading and maintenance a cumbersome task. Instead, if a specific class uses certain metrics, place those counters within that class for better organization and maintainability.


## Conclusion

In the world of backend development, organized metrics are not just a luxury but a necessity. Well-structured metrics offer clarity, efficiency, and scalability, making your life as a developer much easier. By using dedicated packages and enums, you can transform metrics from a headache into a valuable asset in your toolbox. Implement this strategy, and you'll be well on your way to mastering the art of organized metrics.

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