What Is DevOps Monitoring and How to Implement It in Your Organization

Software companies today often face two significant challenges —  delivering at speed and innovating at scale. And DevOps helps address these challenges by imbibing automation throughout the software development lifecycle (SDLC) to develop and deliver high-quality software.

Continuous Integration and Continuous Deployment (CI/CD) is the critical component of automation in a DevOps practice. It automates code builds, testing, and deployment so businesses can ship code changes faster and more reliably. However, one must continuously monitor their CI/CD pipeline to realize the DevOps promise.

So, what is monitoring in DevOps, and how can businesses leverage it to tap optimal DevOps potential? Let's dig deep…

What Is DevOps Monitoring?

At its core, DevOps methodology is a data-driven approach. The ability to continuously improve the software quality completely relies on understanding how the code performs, what issues it introduces, and where to find improvement opportunities. This is where DevOps monitoring comes into the picture.

DevOps monitoring is the practice of tracking and measuring the performance and health of code across every phase of the DevOps lifecycle, from planning, development, integration, and testing to deployment and operations. It facilitates a real-time, easy-to-consume, single-pane-of-glass view of your application and infrastructure performance. You can find significant threats early and fix them before they become a headache. DevOps monitoring gleans valuable data about everything from CPU utilization to storage space to application response times. Real-time streaming, visualizations, and historical replay are some key aspects of DevOps monitoring.

What Is the Importance of DevOps Monitoring for Business Organizations?

DevOps monitoring empowers business organizations to track, identify, and understand key metrics such as deployment frequency and failures, code error count, the cycle time of pull requests, rate of change failure, mean time to detect (MTTD), mean time to mitigate (MTTM), and mean time to remediate (MTTR). These valuable insights enable you to proactively identify the application or infrastructure issues and resolve them in real-time. Monitoring also optimizes the DevOps toolchain by identifying opportunities for automation.

Here are some of the key benefits that highlight the importance of DevOps monitoring for business organizations:

1. High Visibility

The Continuous Integration/Continuous Deployment (CI/CD) facilitated by DevOps enables frequent code changes. However, the increased pace of code changes makes the production environments increasingly complex. Moreover, introducing microservices and micro front-ends into the modern cloud-native ecosystem leads to various workloads operating in production, each with varying operational requirements of scale, redundancy, latency, and security. As a result, greater visibility into the DevOps ecosystem is crucial for teams to detect and respond to issues in real-time. This is where continuous monitoring plays a key role. 

DevOps monitoring gives a real-time view of your application performance as you deploy new versions of code in various environments. So you can identify and remediate issues earlier in the process and continue to test and monitor the subsequent code changes. Monitoring helps you validate new versions in real-time to ensure they are performing as planned, so you can confidently release new deployments.

2. Greater Collaboration

The core principle of DevOps is to enable seamless collaboration between the development and operations teams. However, a lack of proper integration between the tools can impede coordination between different teams. This is where DevOps monitoring comes in. You can leverage continuous monitoring to get a complete, unified view of the entire DevOps pipeline. You can even track commits and pull requests to update the status of related Jira issues and notify the team.

3. High Experimentation

The ever-evolving customer needs demand businesses to constantly experiment in order to optimize their product line through personalization and optimized conversion funnels. Teams often run hundreds of experiments and feature flags in the production environments, making it difficult to identify the reason for any degraded experience. Moreover, the increasing customer demand for uninterrupted services and applications can add vulnerabilities to applications. Continuous monitoring can help you easily monitor the experiments and ensure they work as expected.

4. Manage Changes

Typically, most production outages are triggered by frequent code changes. Therefore, it is imperative to implement change management, especially for mission-critical applications, such as banking and healthcare applications. One needs to determine the risks associated with changes and automate the approval flows based on the risk of the change. And a comprehensive monitoring strategy can help you deal with these complexities. You only need a set of rich, flexible, and advanced monitoring tools.

5. Monitoring Distributed Systems

Businesses often deal with distributed systems composed of many smaller, cross-company services. So, teams need to monitor and manage the performance of the systems they build and that of dependent systems. DevOps monitoring empowers you to deal with this dependent system monitoring with ease.

6. Shift-Left Testing

Testing, when shifted left. i.e., when performed at the beginning of the software development lifecycle, it can significantly improve the code quality and reduce the test cycles. However, shift-left testing can be implemented only when you can streamline monitoring of the health of your pre-production environments and implement it early and frequently. Continuous monitoring also enables you to track user interactions and maintain application performance and availability before it is deployed to production environments.

Benefits of Unified Monitoring and Analytics

Unified monitoring and analytics help your DevOps teams to gain complete, unparalleled, end-to-end visibility across the entire software lifecycle. However, unifying monitoring data, analytics, and logs across your DevOps CI/CD ecosystem can be challenging and complex. 

Types of DevOps Monitoring

Infrastructure monitoring

Every IT business must set up and maintain an IT infrastructure in order to deliver products and services in a seamless and efficient manner. Typically, IT infrastructure includes everything that relates to IT, such as servers, data centers, networks, storage systems, and computer hardware and software. And DevOps monitoring helps in managing and monitoring this IT infrastructure, which is termed Infrastructure Monitoring.

Infrastructure Monitoring collects the data from the IT infrastructure. It analyzes it to derive deep insights that help in tracking the performance and availability of computer systems, networks, and other IT systems. It also helps in gleaning real-time information on metrics such as CPU utilization, server availability, system memory, disk space, and network traffic. Infrastructure Monitoring covers hardware monitoring, OS monitoring, network monitoring, and application monitoring.

Some of the popular Infrastructure Monitoring Tools are:

• Nagios
• Zabbix
• ManageEngine OpManager
• Solarwinds
• Prometheus

Application Monitoring

Application monitoring helps DevOps teams track runtime metrics of application performance, like application uptime, security, and log monitoring details. Application Performance Monitoring (APM) tools are used to monitor a wide range of metrics, including transaction time and volume, API and system responses, and overall application health. These metrics are derived in the form of graphical figures and statistics, so that DevOps teams can easily evaluate the application performance.

Some of the popular application monitoring tools are:

• Appdynamics
• Dynatrace
• Datadog
• Uptime Robot
• Uptrends
• Splunk

Network Monitoring

Network monitoring tracks and monitors the performance and availability of the computer network and its components, such as firewalls, servers, routers, switches, and virtual machines (VMs). Typically, the network monitoring systems share five important data points, namely, discover, map, monitor, alert, and report. Networking monitoring helps identify network faults, measure performance, and optimize availability. This enables your DevOps teams to prevent network downtimes and failures.

Some of the popular NMS tools are:

• Cacti
• Ntop
• Nmap
• Spiceworks
• Wireshark
• Traceroute
• Bandwidth Monitor

Difference Between DevOps Monitoring and Observability

DevOps teams often use monitoring and observability interchangeably. While both concepts play a crucial role in ensuring the safety and security of your systems, data, and applications, monitoring and observability are complementary capabilities and are not the same. Let's understand how both concepts are different:

The differences between monitoring and observability depend on whether the data collected is predefined or not. While monitoring collects and analyses predefined data gleaned from individual systems, observability collects all data produced by all IT systems.

Monitoring tools often use dashboards to display performance metrics and other KPIs, so DevOps teams can easily identify and remediate any IT issues. However, metrics can only highlight the issues your team can anticipate, as they are the ones that create the dashboards. This makes it challenging for DevOps teams to monitor the security and performance posture of the cloud-native environments and applications as the issues are often multi-faceted and unpredictable.

On the other hand, observability tools leverage logs, traces, and metrics collected from the entire IT infrastructure to identify issues and proactively notify the teams to mitigate them. While monitoring tools provide useful data, DevOps teams need to leverage observability tools to get actionable insights into the health of the entire IT infrastructure and detect bugs or vulnerable attack vectors at the first sign of abnormal performance. However, observability doesn’t replace monitoring; rather, it facilitates better monitoring.

The Best DevOps Monitoring Tools

DevOps monitoring tools enable DevOps teams to implement continuous monitoring across the DevOps application development lifecycle and identify potential errors before releasing the code to production. However, you need to select the monitoring tools that best suit your business objectives so that you can achieve quality products with minimal costs. Here are some of the best DevOps monitoring tools available in the market:

The Top 10 DevOps Monitoring Tools:

1. Splunk

Splunk is the most-sought after monitoring tool when it comes to machine-generated data. In addition to monitoring, this popular tool is also used for searching, analyzing, investigating, troubleshooting, alerting, and reporting machine-generated data. Splunk complies with all the machine-generated data into a central index that enables DevOps teams to glean required insights quickly. The enticing aspect of Splunk is that it does not leverage any database to store its data; instead, it uses indexes for data storage. The tool helps in creating graphs, dashboards, and interactive visualizations, so your team can easily access data and find solutions to complex problems.

Some of the key features of Splunk are:

• Real-time data processing.
• The tool accepts input data in various formats, including CSV and JSON.
• The tool allows you to easily search and analyze a particular result.
• The tool allows you to troubleshoot any performance issue.
• You can monitor any business metrics and make an informed decision.
• You can incorporate Artificial Intelligence into your data strategy with Splunk.

2. Datadog

Datadog is a subscription-based SaaS platform that enables continuous monitoring of servers, applications, databases, tools, and services. This tool helps you foster a culture of observability, collaboration, and data-sharing, so you can get quick feedback on operational changes and improve development velocity and agility. 

Some of the key features of Datadog are:

• Extensible instrumentation and open APIs.
• Autodiscovery for automatic configuration of monitoring checks.
• Monitoring-as-code integrations with configuration management and deployment tools.
• Easily customizable monitoring dashboards.
• 80+ turn-key integrations.
• Get health and performance visibility of other DevOps tools. 

3. Consul

HashiCorp’s Consul is an open-source monitoring tool to connect, configure, and secure services in dynamic infrastructure. The tool enables you to create a central registry that tracks applications, services, and health statuses in real-time. The Consul's built-in UI or the APM integrations enable DevOps teams to monitor application performance and identify problem areas at the service level. The topology diagrams in the Consul UI help you visualize the communication flow between services registered in your mesh.

Some of the key features of Consul are:

• The perfect tool for modern infrastructure.
• It provides a robust API.
• Easy to find services each application needs using DNS or HTTP.
• Supports multiple data centers.

4. Monit

Monit is an open-source DevOps monitoring tool. It is used for managing and monitoring Unix systems. Your team can leverage Monit for monitoring daemon processes such as those started at system boot time from /etc/init/, For instance, Sendmail, apache, sshd, and MySQL. The tool can also be used for running similar programs, files, directories, and filesystems running on localhost and tracking the changes, such as size changes, timestamp changes, and checksum changes. Moreover, you can also use Monit for monitoring general system resources on localhosts, such as CPU usage, memory usage, and average load.

Some key features of Monit are:

• The tool conducts automatic maintenance and repair.
• It also executes insightful actions during any event.
• The tool has built-in network tests for key Internet protocols, such as HTTP and SMTP.
• It is used to test programs or scripts at certain times.
• Monit is an autonomous system that does not rely on any plugins or special libraries to run.
• The tool easily compiles and runs on most flavors of Unix.

5. Nagios

Nagios is one of the most popular DevOps monitoring tools. It is an open-source tool and is used for monitoring all mission-critical infrastructure components, including services, applications, operating systems, systems metrics, network protocols, and network infrastructure. The tool facilitates both agent-based and agentless monitoring, making it easy to monitor Linux and Windows servers. With Nagios, your DevOps teams can monitor all sorts of applications, including Windows applications, UNIX applications, Linux applications, and Web applications.

Some key features of Nagios are:

• The tool supports hundreds of third-party addons so that you can monitor virtually anything, all in-house and external applications, services, and systems.
• Simplifies log data sorting process.
• Offers high network visibility and scalability.
• Provides complete monitoring of Java Management Extensions.

6. Prometheus

Prometheus is an open-source monitoring toolkit primarily developed for system monitoring and alerting. The tool collects and stores the metrics information along with the timestamp at which it is recorded. Optional key-value pairs called labels are also stored with the metric information. The Prometheus tool ecosystem comprises multiple components, including the main Prometheus server for storing time series data, client libraries for instrumenting application code, a push gateway for handling short-lived jobs, and an alert manager for handling alerts. 

Some of the key features of the Prometheus tool are:

• The tool facilitates special-purpose exporters for services like StatsD, HAProxy, and Graphite.
• Supports Mac, Windows, and Linux.
• Facilitates monitoring of containerized environments such as Dockers and Kubernetes.
• Easily integrates with configuration tools like Ansible, Puppet, Chef, and Salt.
• The tool does not rely on distributed storage.
• The Prometheus tool supports multiple modes of graphing and dashboarding.

7. Sensu

Sensu by Sumo Logic is a monitoring-as-code solution for mission-critical systems. This end-to-end observability pipeline enables your DevOps and SRE teams to collect, filter, and transform monitoring events and send them to the database of their choice. With a single Sensu cluster, you can easily monitor tens of thousands of nodes and quickly process over 100M events per hour. The tool facilitates enterprise-grade monitoring of production workloads, providing true multi-tenancy and multi-cluster visibility into your entire infrastructure.

Some of the key features of the Sensu tool are:

• The tool supports external PostgreSQL databases, allowing you to scale Sensu limitlessly.
• Sensu’s inbuilt etc., handles 10K connected devices and 40K agents/clusters.
• The tool offers declarative configurations and a service-based approach to monitoring.
• Easily integrates with other DevOps monitoring solutions like Splunk, PageDuty, ServiceNow, and Elasticsearch.

8. Sematext

Sematext is a one-stop solution for all your DevOps monitoring needs. Unlike other monitoring tools which offer only performance monitoring or only logging, or only experience monitoring, Sematext offers all the monitoring solutions that your DevOps team needs to troubleshoot their production and performance issues and move faster. With Sematext, your DevOps teams can monitor application performance, logs, metrics, real users, processes, servers, containers, databases, networks, inventory, alerts, events, and APIs. You can also do log management, synthetic monitoring, and JVM monitoring, among many other operations.

Some of the key features of the Sematext tool are:

• The tool empowers you to map and monitor your entire infrastructure in real-time.
• Sematext provides better visibility for DevOps teams, System Admins, SREs, and Bizops.
• The tool offers fully managed Elasticsearch and Kibana, so you don’t need to spend on highly expensive Elasticsearch expert staff and infrastructure.
• The tool allows you to set up your free account in less than ten mins.
• Seamtext makes integration with external systems a breeze.

9. PagerDuty

PagerDuty is an operations performance monitoring tool that enables your DevOps teams to assess the reliability and performance of the applications. The tool keeps your DevOps team connected with their code in production, leverages machine learning technology to identify issues, and alerts the team to address the errors as early as possible. That means your DevOps team spends less time responding to the incidents and has more time for building and innovating.

Some of the key features of the PagerDuty tool are:

• PagerDuty comes with an intuitive alerting API, making it an excellent, easy-to-use incident response and alerting system.
• If an alert does not respond within the predefined time, the tool will auto-escalate by the originally established SLA.
• The tool supports data collection through a pull model over the HTTP.
• PagerDuty works as autonomous single server nodes with no dependency on distributed storage.
• It is a robust GUI tool for scheduling and escalation policy.
• The tool also supports multiple modes for dashboards and graphs.

10. AppDynamics

AppDynamics is one of the most popular application performance monitoring tools available in the market. As a continuous monitoring tool, AppDynamics helps monitor your end users, applications, SAP, network, database, and infrastructure of both cloud and on-premises computing environments. With this tool, your DevOps team can easily gain complete visibility across servers, networks, containers, infrastructure components, applications, end-user sessions, and database transactions, so they can swiftly respond to performance issues.

Some of the key features of the AppDynamics tool are:

• The tool seamlessly integrates with the world’s best technologies, such as AWS, Azure, Google Cloud, IBM, and Kubernetes.
• AppDynamics leverages machine learning to deliver instant root-cause diagnostics.
• The tool supports hybrid environment monitoring.
• Cisco full-stack observability with AppDynamics.
• The tool comes with a pay-per-use pricing model.

DevOps Monitoring Use-cases: Real Examples of How Enterprises Use Monitoring Tools

There’s no question the DevOps monitoring tools enable your DevOps team to automate the monitoring processes across the software development lifecycle. The monitoring tools enable your DevOps teams to identify code errors early, run code operations efficiently, and respond to code changes in usage rapidly. However, one must implement monitoring tools effectively to ensure complete success. Here are some prominent DevOps monitoring use cases that you can leverage to achieve DevOps success:

Git Workflow Monitoring

DevOps teams often encounter recurring codebase conflicts as a result of multiple developers working on the same project functionality simultaneously. Git enables your DevOps teams to manage and resolve conflicts, including commits and rollbacks. So, when you monitor your Git workflows, you can easily keep the code conflicts and ensure consistent progress in your project.

Code Linting

Code linting tools help your DevOps team analyze the code for style, syntax, and potential issues. With these tools, your DevOps team can ensure that they are adhering to the coding best practices and standards. Code linting enables you to identify and address code issues before they trigger runtime errors and other potential performance issues. With linting tools, you can ensure that your code is clean and consistent.

Distributed Tracing

Your DevOps teams need to be distributed tracing to streamline the monitoring and debugging processes of the microservices applications. Distributed tracing helps your team in understanding how applications interact with each other through APIs, making it easier to identify and address application performance issues.

Continuous Integration/Continuous Deployment (CI/CD) Logs

With CI/CD pipelines becoming the prominent element of the DevOps ecosystem, monitoring them is imperative for DevOps success. The continuous integration (CI) logs help ensure that your code builds are running smoothly. Otherwise, the logs inform you about the errors or warnings in your code builds. So, monitoring the CI logs helps identify the potential issues in your build pipeline and address them proactively. Likewise, the continuous deployment (CD) logs inform you about the overall pipeline health and status. So, monitoring the CD logs helps your DevOps teams easily troubleshoot any failed deployments and repair potential issues.

Configuration Management Changelogs

Configuration management changelogs help DevOps teams to gain deep visibility into the system’s health and important changes —  both manual and automated. So, monitoring these logs empowers your team to track the changes made to the system, identify the unauthorized changes and rectify the issues. 

Code Instrumentation

Code instrumentation is the process of adding code to an application. This process enables you to collect data about the application's performance and its operations route. This is crucial for tracing stack calls and knowing the contextual values. So, monitoring this code instrumentation results empowers you to measure the efficiency of your DevOps practices and gain visibility into the potential gaps, if any. It also helps you identify bugs and improve testing.

Best Practices to Nail DevOps Monitoring

Just like the adoption of DevOps itself, implementing a robust DevOps monitoring model needs a strategic combination of culture, process, and tooling. Though you can take inspiration from how your competitors are adopting DevOps monitoring, the right model you adopt must be on par with your unique organizational needs and SDLC. Here are some best practices that help you nail DevOps monitoring:

Know What to Monitor

Knowing what to monitor is half the battle won. So, even before you start implementing your DevOps monitoring strategy, it is crucial to know what needs to be monitored. Your monitoring objectives should focus on the server’s performance, vulnerabilities, user activity, and application logs.

Define Development Goals

Your DevOps monitoring strategy must be anchored with fixed development goals. These objectives help you understand how well your DevOps monitoring strategy is performing. A most sought-after method to ensure meeting the objectives is to track each sprint duration and measure the time taken to identify, document, and rectify the issues. Leveraging machine learning technology to automate configuration processes helps you save significant time and avoid manual errors.

Monitor User Activity

Monitoring user activity is one of the most important monitoring types. It helps you in tracking unusual requests, multiple login attempts, logging from unknown devices, and any suspicious user activity like a developer trying to access the admin account. By monitoring user activity, you can ensure that the right user is accessing the right resources. This process helps in preventing potential threats to the system and mitigate cyberattacks.

Choose the Right Monitoring Tools

Selecting the right set of DevOps monitoring tools from a rich choice of tooling available in the DevOps ecosystem is an arduous task. Picking the precise tool that is most suitable for your SDLC and your application’s infrastructure starts with an evaluation process. It primarily involves understanding the tool's features and functionality so you can easily assess whether it is best suited for application or infrastructure monitoring or not. So, here are some questions you need to ask to evaluate the DevOps monitoring tool: 

Does the tool integrate easily? Ensure that the monitoring tool easily integrates with your DevOps pipeline and your broader technology stack. This helps you atomate actions and alerts with ease.

Does the tool offer something new? The DevOps monitoring tools that glean a rich amount of data are a cut above the rest. However, more data demands more attention, uses more storage and needs more management. So, select monitoring tools that pave way for new avenues of monitoring rather than those that provide normal benefits.

Does the tool offer a unified dashboard? Your DevOps ecosystem comprises many services, libraries, and products working together. So, a DevOps monitoring tool that offers a unified dashboard helps you gain complete, real-time visibility across the DevOps lifecycle and make it easier to identify issues and gaps.

Does the tool integrate alerts with your existing tooling? Your DevOps monitoring tools must enable your DevOps teams to respond quickly to alerts and notifications. Check whether the tool supports alerting directly or integrates with your existing notification tools. Also, ensure that the tooling you're evaluating integrates with your organization's existing reporting and analytics tools.

What type of audit logs does the tool provide? Understanding the current state of your system is important, especially when something goes south. The action-by-action record provided by the audit logs enables you to understand what has happened, identify which process or person is responsible, analyze the root cause, and provide a basis for learning the gaps in the system. So, what type of audit logs does your tool provide, and how do they provide crucial information? 

What are the tool’s data storage needs? DevOps monitoring tools generate massive amounts of data. So, it is important to understand the storage needs of the tool and the cloud storage costs to keep useful history without storing data beyond its useful life.

What types of diagnostics does the tool offer? Check whether the monitoring tool alerts you to symptoms or helps you in diagnosing the underlying issue. Choose comprehensive tools, such as application performance monitoring platforms, to understand what's happening in complex scenarios, such as several asynchronous microservices working together.