DevOps

Monitoring DevOps: Types, Practices, and Tools

Monitoring DevOps: Types, Practices, and Tools

Monitoring is one of the most important concepts in DevOps. It is a fundamental aspect that goes beyond just graphs showing the state of your product. Monitoring is a general term for collecting data about the behavior of a digital solution (platforms, infrastructure, applications).

DevOps monitoring involves overseeing the entire development lifecycle, ensuring data protection, and quickly responding to and resolving errors. It encompasses various levels such as cloud services monitoring, infrastructure monitoring, abstraction level monitoring (e.g., containers), and application monitoring. Through monitoring, DevOps teams can ensure that their systems operate efficiently, stably, and securely, thereby delivering a high-quality end product.

Monitoring in DevOps is like the dashboard of a plane; a cloud architect needs a clear view of every system’s performance and potential issues. Just as a pilot relies on instruments to navigate safely, we rely on continuous monitoring to ensure smooth and efficient operations in the cloud.

Roman Burdiuzha, Cloud Architect | Specializing in DevOps & Cloud Solutions

Why Monitoring is Complex?

Monitoring is the interpretation of information about your digital solution in the form you desire. The possibilities are limitless. This variability makes it a rather complex task. Determining what to monitor, what truly matters for the project, requires DevOps engineers to:

  • Identify what to monitor,
  • Determine what to display,
  • Define how to execute these tasks.

The most critical question is not how to monitor, but what to monitor.

monitoring in devops real life example

Types of Monitoring

At each level, a system has its own set of metrics. For instance, at the cloud level such as AWS, there are metrics for account status, organizational structure—user counts, service instances, virtual machines, policies, and IP addresses—all meticulously recorded. Each service incurs charges, necessitating expense monitoring.

Moving down a level to infrastructure—virtual machines, for example—they have processors, memory, disk usage, etc. This information is logged—how much memory is used, processor load, and network traffic. For instance, a network adapter might handle 1 gigabit per second, and its interface load is measured accordingly.

Next is the abstraction level. Take Docker, where multiple instances of an operating system are launched to run a specific app. Docker provides virtual metrics for memory, CPU usage, and more.

Then there’s the application level. Consider an application running on Java. In Java, there’s a Java Virtual Machine (JVM) that processes code. The JVM has its metrics—allocated memory, actual memory usage, worker threads, and so forth.

There are also custom-based metrics; for example, an application might track errors occurring and log their frequency per second.

In essence, monitoring involves tracking the state of a solution across these levels to ensure optimal performance, efficiency, and reliability.

Types of devops Monitoring

Cloud Level Monitoring ( AWS, Azure, Google Cloud, other)

Observes and manages the performance, availability, and health of cloud resources and services provided by cloud platforms like AWS, Azure, and Google Cloud.

Infrastructure Level Monitoring 

  1. Server Monitoring
  2. Network Monitoring
  3. Database Monitoring
  4. Storage Monitoring

Tracks the performance, availability, and health of physical and virtual infrastructure components, including servers, networks, databases, and storage systems.

Abstraction Level Monitoring

Monitors the performance and health of abstraction layers such as containers (e.g., Docker) and orchestration systems (e.g., Kubernetes), as well as virtual machines.

  1. Container Monitoring (e.g., Docker)
  2. Orchestration Monitoring (e.g., Kubernetes)
  3. Virtual Machine Monitoring

Application Level Monitoring

Focuses on tracking the performance, availability, and user interactions of applications, providing insights into response times, error rates, and transaction flows.

  1. Application Performance Monitoring (APM)
  2. Transaction Tracing
  3. User Experience Monitoring

Three Pillars of Monitoring

Logs – Logs record events with timestamps, creating a chronology of processes occurring within the system.

Metrics – Metrics demonstrate resource usage levels or behaviors that can be collected in systems.

Traces – Traces illustrate the journey of a user through the entire application stack.

best practices for log collection in devops monitorinf

Best Practices for Log Collection

  1. Ensure maximum standardization of logs.
  2. Avoid collecting confidential information to prevent data leaks.
  3. Configure real-time alerts.
  4. Optimize your log retention policy.

Monitoring Tools

Grafana and Prometheus are among the most widely used, free, and open-source solutions. These tools together create a solid foundation for a robust and reliable monitoring stack, ensuring high-quality analysis.

  • Grafana: This powerful visualization tool displays data from various sources in customizable dashboards, making it easier to understand and act on complex metrics.
  • Prometheus: A leading open-source monitoring and alerting toolkit, known for its reliability and scalability in gathering and querying metrics.
  • Grafana Loki: A log aggregation system that integrates smoothly with Grafana, allowing for comprehensive log management and analysis.

devops monitoring tools

Other notable tools in the monitoring ecosystem include:

Datadog: A comprehensive monitoring and analytics platform that provides visibility into your entire tech stack, from infrastructure to applications.

New Relic: An observability platform that offers detailed insights into application performance, helping to quickly identify and resolve issues.

The key to effective monitoring is not just in the tools used but in determining what to monitor. Identifying the critical metrics that matter most to your project is essential. This approach ensures that you are not overwhelmed with data but are focused on the information that will help you maintain and improve your systems’ performance and reliability.

By leveraging these tools and practices, you can create a monitoring setup that provides actionable insights, helping you to quickly respond to issues, optimize performance, and ensure the overall health of your digital solutions.

Take a look at these Monitoring projects in the portfolio of Gart Solutions.

Centralized Monitoring for a B2C SaaS Music Platform:
We introduced a real-time monitoring framework for both infrastructure and applications by leveraging AWS CloudWatch and Grafana for a globally distributed music platform. This approach enabled seamless, region-wide scalability, improved system transparency, and reduced operational interruptions. The result was a cost-efficient, intuitive monitoring system designed to support the platform’s continuous growth and expansion efforts. To the case.

Monitoring Solutions for Scaling a Digital Landfill Platform: for the elandfill.io platform, we engineered a robust monitoring system that was successfully scaled across several nations, including Iceland, France, Sweden, and Turkey. This solution enhanced the accuracy of methane emission forecasting, improved landfill management practices, and simplified adherence to regulatory standards. The cloud-agnostic architecture offered the client flexibility in selecting their preferred cloud service provider, ensuring adaptability and freedom of choice. To the case.

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FAQ

What is monitoring in DevOps?

Monitoring in DevOps refers to the continuous tracking of systems, applications, and infrastructure to ensure optimal performance, availability, and security. It involves collecting and analyzing data to detect anomalies, identify issues, and provide insights for proactive management.

Why is monitoring important in DevOps?

Monitoring is crucial because it allows teams to detect and resolve issues before they impact users. It ensures system reliability, improves performance, and supports continuous delivery by providing real-time feedback on the health of the environment.

What are the key components of a monitoring system in DevOps?

Key components include metrics collection, logging, alerting, and visualization. Metrics track system performance, logging captures detailed records of events, alerting notifies teams of issues, and visualization helps in understanding data trends and anomalies.

What are some best practices for implementing monitoring in a DevOps environment?

Best practices include defining clear metrics and KPIs, setting up comprehensive logging, establishing alerting thresholds, using dashboards for visualization, and continuously refining monitoring strategies based on feedback and evolving needs.

Can monitoring be automated, and what are the benefits?

Yes, monitoring can be automated using tools and scripts to collect data, trigger alerts, and perform predefined actions. Automation improves efficiency, reduces human error, and ensures consistent monitoring across complex environments.
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