Today's software developers often face two major challenges - rapid delivery and large-scale innovation. DevOps helps address these challenges by introducing automation in the software development lifecycle (SDLC) to develop and deliver high-quality software.

Continuous Integration (CI)/Continuous Deployment (CD) is a key component of automation in DevOps practices. It automates code builds, testing, and deployment so businesses can deliver code changes faster and more reliably. However, their continuous integration (CI)/continuous deployment (CD) pipeline must be continuously monitored to deliver on the DevOps promise.

So, what is monitoring in DevOps, and how can businesses use it to maximize DevOps potential? Here's a deep dive…

1. What is DevOps monitoring?

At the heart of the DevOps methodology is a data-driven approach. The ability to continuously improve software quality relies entirely on understanding how the code performs, what problems it introduces, and where opportunities for improvement can be found. This is where DevOps monitoring plays an important role.

DevOps monitoring is the practice of tracking and measuring the performance and health of code at each stage of the DevOps lifecycle, from planning, development, integration, and testing to deployment and operations. It facilitates a real-time, easy-to-use single-pane-of-glass view of application and infrastructure performance. The benefit is that major threats can be detected early and addressed before they become a headache. DevOps monitoring collects data on everything from CPU utilization to storage space to application response times. Live streaming, visualization, and historical playback are some of the key aspects of DevOps monitoring.

2. What is the importance of DevOps monitoring to business organizations?

DevOps monitoring enables business organizations to track, identify and understand key metrics such as deployment frequency and failures, code bug counts, cycle times for pull requests, change failure rates, mean time to detect (MTTD), mean time to mitigate (MTTM) and mean time to remediate (MTTR). These valuable insights enable organizations to proactively identify application or infrastructure issues and resolve them in real time. Monitoring can also optimize the DevOps toolchain by identifying opportunities for automation.

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

1. High visibility

Continuous Integration (CI)/Continuous Deployment (CD) enabled by DevOps supports frequent code changes. However, the increased rate of code change has made production environments increasingly complex. Additionally, the introduction of microservices and microfrontends in a modern cloud-native ecosystem results in running a variety of workloads in production, each with different operational requirements in terms of scale, redundancy, latency, and security. Therefore, increasing visibility into the DevOps ecosystem is critical for teams to detect and respond to issues in real time. This is where continuous monitoring plays a key role.

DevOps monitoring provides a real-time view of application performance as new versions of code are deployed in different environments. As a result, problems can be identified and fixed early in the process, and subsequent code changes can continue to be tested and monitored. Monitoring can help organizations validate new releases to ensure they perform as planned, so new deployments can be released with confidence.

2. Strengthen collaboration

A core principle of DevOps is to enable seamless collaboration between development and operations teams. However, lack of proper integration between tools hinders coordination between different teams. This is where DevOps monitoring comes in. Continuous monitoring can be leveraged to gain a complete and unified view of the entire DevOps pipeline. Commits and pull requests can even be tracked to update the status of related Jira issues and notify the team.

3. Highly experimental

Changing customer demands require organizations to continually try to optimize their product lines through personalization and optimized conversion funnels. Organizations' teams often run hundreds of experiments and feature flags in production, making it difficult to pinpoint the cause of any degraded experiences. Additionally, the increasing demand from customers for uninterrupted services and applications may increase the vulnerability of applications. Continuous monitoring can help organizations monitor experiments and ensure they are working as expected.

4. Manage Changes

Typically, most production outages are triggered by frequent code changes. Therefore, change management must be implemented, especially for mission-critical applications such as banking and healthcare applications. One needs to identify the risks associated with the change and automate the approval process based on the risk of the change. A comprehensive monitoring strategy can help organizations deal with these complexities, requiring only a rich, flexible, and advanced set of monitoring tools.

5. Monitor distributed systems

Organizations often deal with distributed systems consisting of cross-company services of many sizes. Consequently, an organization's teams need to monitor and manage the systems they build and the performance of related systems. DevOps monitoring enables organizations to easily handle this dependent system monitoring.

6. Shift left testing

The left shift test is to test when moving to the left. When performed at the beginning of the software development lifecycle, it can significantly improve code quality and reduce testing cycles. However, shift-left testing can only be achieved when organizations simplify monitoring the health of pre-production environments and implement it early and often. Continuous monitoring also enables organizations to track user interactions and maintain application performance and availability before deploying the application into production.

3. The benefits of unified monitoring and analysis

Unified monitoring and analytics can help an organization's DevOps teams gain complete end-to-end visibility across the entire software lifecycle. However, unifying monitoring data, analytics and logs in a DevOps continuous integration (CI)/continuous deployment (CD) ecosystem can be challenging and complex.

DevOps Monitoring Types

infrastructure monitoring

Every IT business must build and maintain IT infrastructure to deliver products and services in a seamless and efficient manner. Typically, IT infrastructure includes everything related to IT, such as servers, data centers, networks, storage systems, and computer hardware and software. DevOps monitoring helps to manage and monitor this IT infrastructure, which is known as infrastructure monitoring.

Infrastructure monitoring collects data from IT infrastructure. It helps track the performance and availability of computer systems, networks, and other IT systems by analyzing data to gain insights. It also helps in collecting real-time information on metrics like CPU utilization, server availability, system memory, disk space, and network traffic. Infrastructure monitoring includes hardware monitoring, operating system monitoring, network monitoring, and application monitoring.

Some popular infrastructure monitoring tools are:

Nagios
Zabbix
ManageEngine OpManager
Solarwinds
Prometheus

application monitoring

Application monitoring helps DevOps teams track runtime metrics of application performance such as application uptime, security and log monitoring details. Application performance monitoring (APM) tools are used to monitor a wide range of metrics, including transaction times and volumes, API and system responsiveness, and overall application health. These metrics are available in the form of graphs and statistics so DevOps teams can easily assess the performance of the application.

Some popular application monitoring tools are:

Appdynamics
Dynatrace
Datadog
Uptime Robot
Uptrends
Splunk

Network Monitoring

Network monitoring is used to track and monitor the performance and availability of computer networks and their components such as firewalls, servers, routers, switches, and virtual machines. Typically, network monitoring systems share 5 important data points, namely Discovery, Mapping, Monitoring, Alerting and Reporting. Network monitoring helps identify network faults, measure performance, and optimize availability. This enables an organization's DevOps team to prevent network downtime and failures.

Some popular NMS tools are:

Cacti
Ntop
Nmap
Spiceworks
Wireshark
Traceroute
Bandwidth Monitor

4. The difference between evOps monitoring and observability

DevOps teams often use monitoring and observability interchangeably. While both concepts play a vital role in ensuring the security of systems, data, and applications, monitoring and observability are complementary capabilities, not the same. Let's understand the difference between these two concepts:

The distinction between monitoring and observability depends on whether the data collected is predefined or not. Monitoring collects and analyzes predefined data collected from various systems, Observability collects all data generated by all IT systems.

Monitoring tools often use dashboards to display performance metrics and other KPIs, so DevOps teams can easily identify and correct any IT issues. Metrics, however, can only highlight issues that the organization's team can foresee, as they are the issues creating the dashboard. This makes it difficult for DevOps teams to monitor the security and performance health of cloud-native environments and applications, as these issues are often multifaceted and unpredictable.

Observability tools, on the other hand, utilize logs, traces, and metrics collected from across the IT infrastructure to identify issues and proactively notify teams to mitigate them. While monitoring tools provide useful data, DevOps teams need to leverage observability tools to gain actionable insights into the health of the entire IT infrastructure and detect vulnerabilities or vulnerable attack vectors at the first sign of performance anomalies. However, observability does not replace monitoring, rather it contributes to better monitoring.

5. The best DevOps monitoring tools

DevOps monitoring tools enable DevOps teams to achieve continuous monitoring of the entire DevOps application development lifecycle and identify potential bugs before releasing code to production. However, organizations need to choose the monitoring tool that best suits their business goals in order to obtain a high-quality product with minimal cost. Here are some of the top 10 best DevOps monitoring tools in the market:

1.Splunk

Splunk is the most popular monitoring tool for machine-generated data. In addition to monitoring, this popular tool is used to search, analyze, investigate, troubleshoot, alert, and report on machine-generated data. Splunk consolidates all machine-generated data into a central index, enabling DevOps teams to quickly glean the insights they need. The allure of Splunk is that it doesn't utilize any database to store data; instead, it uses indexes to store data.

The tool helps create graphs, dashboards, and interactive visualizations so an organization's teams can easily access data and find solutions to complex problems.

The main features of Splunk are as follows:

Real-time data processing.
Accepts input data in various formats, including CSV and JSON.
Allows for easy searching and analysis of specific results.
Allows to troubleshoot any performance issues.
Any business metric can be monitored and informed decisions can be made.
AI can be combined with Splunk into a data strategy.

2.Datadog

Datadog is a subscription-based SaaS platform that enables continuous monitoring of servers, applications, databases, tools, and services. This tool can help organizations foster a culture of observability, collaboration, and data sharing so that rapid feedback on operational changes can be obtained and development speed and agility increased.

Some of the key features of Datadog are:

Extensible detection and open API.
Autodiscover automatic configuration of monitoring checks.
Code monitoring integration with configuration management and deployment tools.
Easily customizable monitoring dashboard.
80+ turnkey integrations.
Get health and performance visibility into other DevOps tools.

3. Consul

Consul by Hashi is an open source monitoring tool for connecting, configuring and securing services in dynamic infrastructure. The tool enables organizations to create a central registry that tracks the state of applications, services, and health in real time. Consul's built-in user interface (UI) or APM integration enables DevOps teams to monitor application performance and identify problem areas at the service level. The topology map in the Consul user interface helps organize and visualize the flow of communication between services registered in the mesh.

Some of the main features of Consul are listed below:

A handy tool for modern infrastructure.
Provides a robust API.
Easily find the services each application needs using DNS or HTTP.
Support for multiple data centers.

4. Prompt

Monit is an open source DevOps monitoring tool. It is used to manage and monitor Unix systems. An organization's team can leverage Monit to monitor daemon processes such as those started from /etc/init/ at system startup, such as Sendmail, apache, sshd, and MySQL. The tool can also be used to run similar programs, files, directories, and filesystems running on the local host and track changes such as size changes, timestamp changes, and checksum changes. Additionally, you can use Monit to monitor general system resources on your localhost, such as CPU usage, memory usage, and load average.

Some key features of Monit are:

Automatic maintenance and repair.
Take insightful action at any event.
The tool has built-in web tests for key Internet protocols such as HTTP and SMTP.
Used to test a program or script at a specific time.
Monit is an autonomous system that does not depend on any plugins or special libraries to function.
Easy to compile and run on most Unix flavors.

5.Nagios

Nagios is one of the most popular DevOps monitoring tools. It is an open-source tool for monitoring all mission-critical infrastructure components, including services, applications, operating systems, system metrics, network protocols, and network infrastructure. The tool facilitates agent-based and agentless monitoring, making it easy to monitor Linux and Windows servers. Using Nagios, an organization's DevOps team can monitor a variety of applications, including Windows applications, Unix applications, Linux applications, and Web applications.

Some of the key features of Nagios are as follows:

Hundreds of third-party plugins are supported so virtually anything can be monitored, all internal and external applications, services and systems.
Simplify the log data sorting process.
Provides high network visibility and scalability.
Provides complete Java management extension monitoring.

6. Prometheus

Prometheus is an open source monitoring toolkit, mainly used for system monitoring and alerting. The tool collects and stores metrics along with the timestamp at which it was recorded. Optional key-value pairs called tags are also stored in the metrics. The Prometheus tooling ecosystem consists of multiple components, including the main Prometheus server for storing time-series data, a client library for instrumenting application code, a push gateway for handling short-lived jobs, and an alert manager for handling alerts.

Some key features of Prometheus tools are:

Facilitates special purpose exports for services like StatsD, HAProxy, and Graphite.
Mac, Windows and Linux operating systems are supported.
It is convenient to monitor container environments, such as Dockers and Kubernetes.
Easily integrate configuration tools such as Ansible, Puppet, Chef and Salt.
The tool does not rely on distributed storage.
Prometheus tools support 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 an organization's DevOps and SRE teams to collect, filter and transform monitoring events and send them to the database of their choice. Using a single Sensu cluster, organizations can easily monitor tens of thousands of nodes and quickly process over 10 billion events per hour. The tool facilitates enterprise-level monitoring of production workloads, providing true multi-tenant and multi-cluster visibility across the entire infrastructure.

Some key features of the Sensu tool are:

Support for external PostgreSQL databases allows organizations to scale Sensu infinitely.
Sensu's built-in, handles 10,000 connected devices and 40,000 brokers/cluster.
Provides declarative configuration and service-based monitoring methods.
Easily integrate with other DevOps monitoring solutions like Splunk, PageDuty, ServiceNow, and Elasticsearch.

8.Sematext

Sematext is a one-stop solution for all DevOps monitoring needs. Unlike other monitoring tools that only provide performance monitoring, logging or experience monitoring, Semattext provides all the monitoring solutions DevOps teams need to solve their production and performance issues and speed up their progress. Using Semtext, an organization's DevOps team can monitor application performance, logs, metrics, real users, processes, servers, containers, databases, network, inventory, alerts, events and APIs. Organizations can also perform log management, synthetic and JVM monitoring, and many others.

Some key features of Sematext tools are:

Enables organizations to map and monitor their entire infrastructure in real time.
Sematext provides better visibility for DevOps teams, sysadmins, SREs and Bizops.
Provides fully managed Elasticsearch and Kibana, so organizations don't need to spend on expensive Elasticsearch expert staff and infrastructure.
Allows organizations to set up free accounts in less than ten minutes.
Seamtext makes integration with external systems a breeze.

9.PagerDuty

PagerDuty is an operational performance monitoring tool that enables an organization's DevOps team to assess application reliability and performance. The tool keeps an organization's DevOps team connected to code in production, using machine learning techniques to identify issues and alert teams to fix bugs early. This means that an organization's DevOps teams spend less time responding to incidents and more time building and innovating.

Some of the main 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 is not responded to within a predefined time, the tool will automatically escalate according to the originally established SLA.
Data collection via pull model over HTTP is supported.

PagerDuty works as an independent server node and does not depend on distributed storage.

This is a robust GUI tool for scheduling and escalating policies.
Multiple modes for dashboards and charts are also supported.

10.AppDynamics

AppDynamics is one of the most popular application performance monitoring tools on the market. As a continuous monitoring tool, AppDynamics can help monitor an organization's end users, applications, SAP, network, database, and infrastructure of cloud and on-premise computing environments. With this tool in place, an organization's DevOps teams can easily gain complete visibility across servers, networks, containers, infrastructure components, applications, end-user sessions, and database transactions so they can quickly respond to performance issues.

Some key features of AppDynamics tools are:

Seamlessly integrate with the world's best technologies such as AWS, Azure, Google Cloud, IBM and Kubernetes.
AppDynamics leverages machine learning to provide immediate root cause diagnosis.
Supports mixed environment monitoring.
Features Cisco full-stack observability with AppDynamics.
Adopt a pay-per-use pricing model.

6. DevOps monitoring use cases: real examples of how enterprises use monitoring tools

There is no doubt that DevOps monitoring tools enable an organization's DevOps team to automate the monitoring process throughout the software development lifecycle. These monitoring tools enable an organization's DevOps team to identify code errors early, run code operations efficiently, and respond quickly to code changes in use. However, monitoring tools must be used effectively to ensure complete success. Here are some prominent DevOps monitoring use cases that organizations can leverage for DevOps success:

Monitor Git workflow

DevOps teams often experience recurring codebase conflicts due to multiple developers working on the same project functionality concurrently. Git enables an organization's DevOps teams to manage and resolve conflicts, including commits and rollbacks. So, when monitoring Git workflows, it's easy to keep track of code conflicts and ensure consistent progress on projects.

code detection

Code instrumentation tools help DevOps teams analyze code for style, syntax, and potential issues. With these tools in place, an organization's DevOps team can ensure they follow coding best practices and standards. Code instrumentation enables organizations to identify and resolve code issues before they trigger runtime errors and other potential performance issues. Using instrumentation tools, organizations can ensure that code is clean and consistent.

distributed tracing

An organization's DevOps team needs distributed tracing to simplify the monitoring and debugging process of microservices applications. Distributed tracing helps an organization's teams understand how applications interact with each other through APIs, making it easier to identify and resolve application performance issues.

Continuous Integration (CI)/Continuous Deployment (CD) logs

As continuous integration (CI)/continuous deployment (CD) pipelines become important elements of the DevOps ecosystem, monitoring them is critical to DevOps success. Continuous integration (CI) logs help ensure that code builds run smoothly. Otherwise, the logs will inform the organization of errors or warnings in the build of the code. Therefore, monitoring continuous integration (CI) logs can help identify potential issues in your build pipeline and resolve them proactively. Likewise, continuous deployment (CD) logs inform the health and status of the entire pipeline. Therefore, monitoring Continuous Deployment (CD) logs can help DevOps teams easily troubleshoot any failed deployments and fix potential issues.

Configuration Management Changelog

Configuration management change logs help DevOps teams gain insight into system health and important changes (both human and automated). Therefore, monitoring these logs enables the organization's teams to track changes made to the system, identify unauthorized changes and correct problems.

code instrumentation

Code insertion is the process of adding code to an application. This process enables organizations to collect data on the performance of applications and their routes of operation. This is essential for tracing stack calls and understanding scene values. Therefore, monitoring this code instrumentation results enables organizations to measure the effectiveness of DevOps practices and understand potential gaps, if any. It also helps organizations identify bugs and improve testing.

7. Identify best practices for DevOps monitoring

Like adopting DevOps itself, implementing a robust DevOps monitoring model requires a strategic mix of culture, process, and tooling. While organizations can take inspiration from the way their competitors have adopted DevOps monitoring, the right model an organization adopts must align with its unique organizational needs and software development life cycle (SDLC). Here are some best practices that can help organizations better monitor DevOps:

know what to monitor

Knowing what to monitor is half the battle. Therefore, even before starting to implement a DevOps monitoring strategy, it is crucial to understand what needs to be monitored. An organization's monitoring goals should focus on server performance, vulnerabilities, user activity, and application logs.

Clear development goals

An organization's DevOps monitoring strategy must be anchored by fixed development goals. These goals help organizations understand how well their DevOps monitoring strategies are performing. The most popular way to ensure that goals are achieved is to track each Sprint duration and measure the time spent identifying, documenting and correcting issues. Automating the configuration process with machine learning techniques can help organizations save a lot of time and avoid human errors.

Monitor user activity

Monitoring user activity is one of the most important types of monitoring. It can help organizations track unusual requests, multiple login attempts, logins from unknown devices, and any suspicious user activity such as developers trying to access administrative accounts. By monitoring user activity, organizations can ensure that the correct users are accessing the correct resources. This process helps prevent potential threats to the system and mitigates cyber attacks.

Choose the right monitoring tool

Selecting the right set of DevOps monitoring tools from the plethora of tools available in the DevOps ecosystem is a daunting task. Selecting the precise tool that best fits the software development life cycle (SDLC) and application infrastructure begins with the evaluation process. It mostly involves understanding a tool's features and capabilities in order to easily assess whether it's best for application or infrastructure monitoring. So, when evaluating DevOps monitoring tools, here are some questions to ask:

Is the tool easy to integrate? Make sure the monitoring tool can easily integrate with the DevOps pipeline and wider tech stack. This can help organizations easily generate actions and alerts.
Does the tool offer something new? DevOps monitoring tools that collect massive amounts of data are better than others. However, more data requires more attention, uses more storage space, and requires more management. Therefore, choose monitoring tools that pave the way for new monitoring avenues, rather than those that provide normal functionality.
Does the tool provide a unified dashboard? An organization's DevOps ecosystem consists of many services, libraries, and products that work together. Therefore, DevOps monitoring tools that provide a unified dashboard can help organizations gain completeness, real-time visibility across the entire DevOps lifecycle, and identify issues and gaps more easily.
What type of audit logs does the tool provide? It is important to know the current state of the system, especially if something goes wrong. The action-by-action record provided by audit logs enables organizations to understand what happened, determine which process or person is responsible, analyze root cause, and provide a basis for understanding gaps in the system. So, what types of audit logs does an organization's tools provide, and how do they provide critical information?
What are the data storage needs of the tools? DevOps monitoring tools generate a lot of data. Therefore, it is important to understand the storage requirements and cloud storage costs of the tool in order to preserve a useful history without exceeding its useful life.
What types of diagnostics does the tool provide? Check to see if the monitoring tool alerts you to issues or helps your organization diagnose basic issues. Choose a comprehensive tool, such as an application performance monitoring platform, to understand what's happening in complex scenarios, such as multiple asynchronous microservices working together.

8. Expansion - DevOps capabilities of low-code platforms

The JNPF rapid development platform integrates DevOps capabilities, rapid deployment, and easy operation and maintenance. Experience the official website: www.jnpfsoft.com/?csdn DevOps provides a Jenkins-based CI/CD pipeline, supports automated workflows, including Binary-to-Image (B2I) and Source-to-Image (S2I), etc., to improve delivery capabilities.

【Application scenario】

Automatically check out code, test, analyze, build, deploy and publish

Out-of-the-box CI/CD pipeline

Easy to integrate into your SCM, support GitLab/GitHub/BitBucket/SVN
Graphical editing panel design to create CI/CD pipelines without writing Jenkinsfile
Integrate SonarQube for source code quality analysis
Supports dependency caching for faster builds and deployments
Dynamically build Agents and automatically create Pods as needed

【Help developers】

Freed from tedious YAML editing work, allowing developers to focus on business development

Provide developers with a wizard-style user experience, reducing the learning curve for getting started with cloud-native technology stacks
Built-in commonly used automated deployment environment, providing a customized container runtime environment for application (Java/NodeJs/Python/Go) deployment
Provides out-of-the-box tool sets to help developers quickly build code into runnable container images, improving development efficiency
Provide application store and application life cycle management, shorten the application launch cycle

What is DevOps monitoring and how can it be implemented in an organization?