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Distributed Systems Monitoring: The Essential Guide

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Distributed systems offer many advantages, such as improved scalability and availability, but they can also be more challenging to manage. As an IT professional, you are responsible for keeping distributed systems running smoothly and efficiently. To do this, you need to monitor distributed systems effectively. This guide introduces the essential concepts of distributed systems monitoring and what you need to know to monitor one effectively. It covers identifying key performance indicators (KPIs), understanding system behavior, and best practices for distributed systems monitoring.

This essential guide will better equip you to monitor your distributed systems effectively and help keep them running smoothly. Understanding key concepts such as KPIs and system behavior will enable you to detect issues before they cause serious problems.

Importance of Distributed Systems Monitoring

You need to monitor distributed systems ensuring every stakeholder will know how they’re doing. Distributed systems are complex, often consisting of many components working together to function correctly. It can therefore make monitoring these systems a challenge. To effectively monitor a distributed system, understanding the various components and how they work together is vital.

One of the critical concepts in distributed systems monitoring is identifying key performance indicators. These are measurements that track a system’s health and measure its performance. Understanding system behavior involves understanding how the system works and how its components interact. This knowledge can help you detect issues.

Components of a Distributed System

A distributed system is a system in which the components are distributed across multiple physical or logical locations.


The hardware of a distributed system can be divided into two categories: physical and virtual. Physical hardware includes servers, storage, and networking equipment. Virtual hardware is software that simulates physical hardware, including virtual machines and cloud instances.

The physical and virtual hardware of a distributed system can be divided further into the following categories:

  1. Servers: The backbone of a distributed system responsible for running the applications.
  2. Storage: Primary storage stores operational data, whereas secondary storage stores less frequently used data.
  3. Networking equipment: Switches, routers, and firewalls that connect the servers, storage, and cloud instances.
  4. Cloud instances: Virtual machines or containers that run in the cloud and are used to create a distributed system.


The software of a distributed system can be divided into the following categories:

  1. Operating system: The software that manages the hardware and provides a platform for applications to run.
  2. Application: The software that runs on top of the operating system and provides the system’s functionality.
  3. Databases: A collection of data that applications can access. It can be divided into two categories, relational and NoSQL databases. Relational databases are traditional databases utilizing a table structure to store data. NoSQL databases are newer databases that use a variety of data structures, such as key-value pairs, to store data.

Important Metrics to Track

There are a few essential metrics to track when monitoring a component of a distributed system:

  1. Response time is the time it takes for the system to process a request. You can use this metric to identify bottlenecks.
  2. Throughput is the number of requests the system can process per unit of time. You can use this metric to identify overloaded components.
  3. Error rate is the number of errors that occur in the system per unit of time. You can use this metric to identify issues.

Types of Distributed Systems Monitoring

There are two main types of distributed systems monitoring: application-level monitoring and infrastructure-level monitoring. Both types are crucial for effectively managing a distributed system.

Application-Level Monitoring

Application-level monitoring focuses on the performance of the system’s software. You can use this type of monitoring to detect issues such as slow response times or errors.

Infrastructure-Level Monitoring

Infrastructure-level monitoring focuses on the hardware and software. You can use this type of monitoring to detect issues such as overloaded servers or network latency. You can also perform different types of monitoring on a distributed system. You can monitor the hardware, software, and networks. Monitoring the hardware means ensuring the system’s physical components are working correctly. It includes things like servers, storage devices, and other equipment.

Monitoring the software means making sure the application is working correctly. It includes databases, web servers, and other types of software.

Implementing Distributed Systems Monitoring

Once you’ve decided to implement distributed systems monitoring, there are a few steps you need to take.

  1. Define the KPIs you want to track. This is the first step in setting up a distributed systems monitoring infrastructure. There are a few things to consider when defining KPIs. First, you need to decide what metric you want to track. Second, you need to choose how often you wish to collect data.
  2. Set up the monitoring infrastructure. While setting up the monitoring infrastructure, you need to decide which tools you want to use and then deploy the monitoring infrastructure.
  3. Collect and analyze data from the distributed system. Once the monitoring infrastructure is in place, you need to collect and analyze data from the distributed system and utilize the resulting data to troubleshoot issues or improve performance.

How Logging Can Help You  Manage Distributed Systems

Logging is a type of data collection you can use for distributed systems monitoring. Logs can contain information about system events, such as when a user logs in or an error occurs. This information can help you understand system behavior and detect issues.

There are two main types of logs: system logs and application logs. The operating system generates system logs that contain information about system events. An important distinction to remember is software generates application logs. You can use both types in distributed systems monitoring. System logs can detect issues such as system errors or resource utilization. Application logs can detect issues such as application errors or slow response times.

Logging is a valuable tool for distributed systems monitoring, but it can be challenging to collect and manage log data. Log data can be voluminous, and it can be challenging to extract useful information from it.

Below is a list of capabilities logging provides to assist with efficiently running distributed systems:

  • Logging provides a record of system events that you can use for troubleshooting.
  • It can help you identify, diagnose, and fix errors.
  • It can help you understand how your system is performing and help you optimize it.

Logging Best Practices for Distributed Systems

There are a few things you can do to make logging easier.

  1. Use a log management tool. A log management tool can help you to collect and manage log data. A tool such as Loggly can be used to index and search log data.
  2. Set up alerts. You can set up alerts, so you’re notified when a specific event occurs or when a threshold is reached.
  3. Use log aggregation. You can use log aggregation to collect log data from multiple servers. This can be useful if you have an extensive distributed system.


Keeping a distributed system operational requires constant monitoring. IT professionals can identify issues before they become problems using KPIs and tracking system behavior. This ensures the system continues to operate smoothly. Loggly® provides log management and analytics platforms to help IT professionals troubleshoot and optimize their distributed systems. It comes with a free thirty-day trial.

This post was written by Tarun Telang. Tarun is a software engineering leader with over 16 years of experience in the software industry with some of the world’s most renowned software development firms like Microsoft, Oracle, BlackBerry, and SAP. His areas of expertise include Java, web, mobile, and cloud. He’s also experienced in managing software projects using Agile and Test Driven Development methodologies.