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  • Writer's pictureViacheslav Miroshnychenko

Navigating through metrics in Distributed Systems

In the ever-evolving world of software engineering, the success of a project often hinges on more than just coding skills or cutting-edge technology. It's the ability to measure, understand, and apply key metrics throughout the development lifecycle that truly sets apart high-performing teams and robust software architectures. In this comprehensive exploration, we dive into the crucial metrics that drive success in software architecture, especially in the context of distributed systems.


In the realm of software architecture, understanding and utilizing metrics is fundamental. Metrics provide valuable insights into various aspects of distributed systems. They guide in tracking essential elements and help in maintaining robust performance and reliability.

Key metric groups include:

  1. DORA Metrics: Originating from the DevOps Research Assessment, these metrics focus on deployment frequency, change lead time, incident count, and recovery metrics. They are vital for assessing and improving deployment practices and service resilience.

  2. SRE Metrics: This set includes Service Level Indicators (SLIs), Service Level Objectives (SLOs), Service Level Agreements (SLAs), error budgets, and metrics related to toil-work. These are crucial for maintaining service reliability and meeting performance standards.

  3. Additional Metrics: These encompass flow time, flow distribution, and metrics surrounding pull requests. They are instrumental in understanding the efficiency of development workflows and the overall health of the software development process.

These metrics collectively form a comprehensive framework for monitoring and improving software architecture in distributed systems. They serve as a checklist for deploying services into production, ensuring each aspect of the system is optimized for peak performance.


In exploring advanced concepts of software architecture, particularly in the context of distributed systems, a fascinating resource is the book "Software Architecture: The Hard Parts." Within its scope, an intriguing article stands out, focusing on a mathematical model for gauging the maintainability of codebases. This model is an innovation of a developer associated with Sonargraph, a tool adept at monitoring maintainability metrics in various programming languages, including Python 3, Java, and C/C++/C#.

The article delves deep into the nuances of software maintenance, highlighting the pivotal role of tracking coupling and cyclical dependencies. It draws a clear distinction between two fundamental types of system segmentation: the horizontal, which aligns with the layered architectural style, and the vertical, which is more aligned with business functions. The discussion reveals that the vertical segmentation often poses more intricate challenges, prompting the author to introduce a sophisticated metric for assessing the Maintainability Level. This metric is based on the degree of interconnectivity among software components.

Moreover, the author navigates through the complex mathematics underpinning this metric, offering insights into improving it. This exploration is not just an academic exercise but a practical guide for software development firms aiming to enhance their understanding and management of software maintainability. It underscores the critical balance between system complexity and maintainability, providing a framework for developers to achieve optimal software design and architecture. This understanding is crucial in a landscape where efficient, maintainable, and scalable software solutions are the keystones of successful technology ventures.


In the realm of software architecture, event storming serves as a pivotal strategy for delving into the core of a system's business logic. This innovative approach aids in meticulously organizing various components like commands, events, and other crucial elements into well-defined domains. Such organization is instrumental in shaping and refining the metrics that gauge a system's efficiency and cohesiveness.

The article in question illuminates how event storming can be effectively utilized to evaluate key aspects of a system, such as its coupling, cohesion, and overall modularity. This evaluation draws inspiration from the venerable Chidamber & Kemerer object-oriented metrics suite, a set of principles established in 1994. Building upon these foundational concepts, the article introduces a suite of four Domain-Driven Design (DDD) metrics, each serving a distinct purpose in assessing the system's architecture:

  1. Weighted Events per Microservice (WEM): This metric casts light on the intricacy and depth of a service or context, determined by the volume and nature of the events it encompasses.

  2. Coupling Between Microservices (CBM): It measures the interdependencies and interactions among various microservices, providing insights into the system's interconnectedness.

  3. Response for Microservices (RFM): This parameter quantifies the events that are set in motion by other events, offering a perspective on the system's reactive complexity.

  4. Lack of Cohesion in Events (LCE): Focused on the ReadModel, this metric evaluates the data essentials for event execution, highlighting the synergy within the system components.

The exploration in the article suggests that refining and expanding these metrics could pave the way for advanced automated tools tailored for meticulous system quality evaluation. Moreover, the article nods to the influential work "Fundamentals of Software Architecture", which advocates the application of the Lack of Cohesion of Methods (LCOM) metric. This metric is seen as a potential fitness function within software applications, showcasing a progressive blend of traditional and modern architectural methodologies.

This confluence of time-tested and contemporary strategies underscores the dynamic and evolving landscape of software architecture, where innovative metrics and models continually reshape our understanding and capabilities in designing robust, efficient, and cohesive systems.


As we wrap up our exploration of the essential metrics in software architecture, it's clear that the integration of these metrics into our daily practices is more than just a technical necessity; it's a strategic imperative. The DORA metrics, SRE metrics, and the additional metrics we've discussed, along with the innovative approaches to maintainability and microservices metrics, are not just tools but roadmaps guiding us towards excellence in software development and architecture.

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