DevOps monitoring tools: How to drive DevOps efficiency

DevOps monitoring tools automate the collection and analysis of data for agile software development. Here's why it's important for DevOps teams today.

With the world’s increased reliance on digital services and the organizational pressure on IT teams to innovate faster, the need for DevOps monitoring tools has grown exponentially.

In fact, the Dynatrace 2023 CIO Report found that 78% of respondents deploy software updates every 12 hours or less. 54% reported deploying updates every two hours or less.

This demand for rapid innovation is propelling organizations to adopt agile methodologies and DevOps principles to deliver software more efficiently and securely. The DevOps approach breaks up projects into modular components that development teams build in parallel by working closely with operations and business stakeholders. DevOps aims to move applications more quickly into production by releasing new builds frequently — often several times per day — and incorporating constant feedback and testing, both during development and after software is deployed.

But when and how does DevOps monitoring fit into the process? And how do DevOps monitoring tools help teams achieve DevOps efficiency?

What is DevOps monitoring?

DevOps monitoring is an observability practice that creates a real-time view of the status of applications, services, and infrastructure in pre-production and production environments.

DevOps monitoring tools enable teams to collect, analyze, and visualize data to ensure the smooth operation of software applications and infrastructure in a DevOps environment. The process involves monitoring various components of the software delivery pipeline, including applications, infrastructure, networks, and databases.

Also known as continuous monitoring, DevOps monitoring enables development and operations teams to detect and respond to problems quickly. The goal is to help teams respond to slowdowns, outages, and freezes before they become major problems for users. DevOps monitoring also typically involves high levels of automation that can enable self-healing before IT personnel step in.

Why DevOps monitoring is important—and challenging

DevOps monitoring is important to help teams achieve greater efficiency in their software development lifecycles. In addition, monitoring DevOps processes provide the following benefits:

• Improve system performance. Monitoring provides a clearer, more consistent picture of DevOps system performance and overall health. The result is faster and more data-driven decision making.
• Help systems meet SLAs. DevOps monitoring also gives developers and operations teams the data they need to successfully meet service-level agreements (SLAs).
• Provide metrics for improved site reliability. Monitoring also creates a baseline for continuous improvement in DevOps systems and processes, which bolsters site reliability.

However, DevOps monitoring has its challenges. Because every DevOps environment is unique and varied, teams often use many different tools at every stage of the SDLC. Moreover, most organizations use a combination of cloud-based and on-premises infrastructure. As a result, they use different tools for monitoring. These conditions can lead to the following challenges:

• Data silos. The more tools and platforms teams use, the greater the likelihood of developing data silos.
• Missed insights. This profusion of tools at different stages means teams across the organization—such as developers, site reliability engineers, and security professionals—can have difficulty sharing data and insights.
• Lost efficiency. Lack of cohesion also means DevOps efficiency can suffer as teams have to manually piece together how one system affects another.

Different types of DevOps monitoring and why they’re important

Because DevOps spans the entire SDLC from pre-production to production, DevOps monitoring includes the following four areas:

1. Application performance monitoring

Application performance monitoring tracks the availability and performance of applications in the field. It examines metrics like response times, application programming interface availability, and page load times to flag problems that affect the user experience.

2. Infrastructure monitoring

Infrastructure monitoring reviews servers, storage, network connections, virtual machines, and other data center elements that support applications. It looks at variables like central processing unit utilization rates, available bandwidth, and disk space usage to detect problems early.

3. Network monitoring

Network monitoring analyzes network traffic logs to look for anomalies such as high bandwidth usage, packet flow, and atypical patterns that might indicate a cyberattack.

4. User experience monitoring

Also known as synthetic monitoring, user experience monitoring is a practice and technology that simulates the actions users might take when using an application. User experience monitoring generates simulated behavior patterns across different scenarios, such as geography, device type, and time of day. The result is that teams can identify issues that don’t necessarily show up in other types of monitoring.

Because every DevOps environment is unique, exactly how organizations implement these monitoring types will differ depending on architecture and tools. The challenge is being able to integrate the data from these disparate monitoring efforts into insights that enable teams to automate more DevOps processes.

DevOps monitoring use cases

The goal of DevOps monitoring is to improve software quality and make processes more efficient and automatable. Common DevOps monitoring use cases include the following:

• Detect and remediate errors before they affect users. By pinpointing issues earlier in the SDLC, teams can fix problems before software is released to production. Early detection enables teams to deliver more reliable software and seamless user experiences.
• Increase system uptime. DevOps monitoring also helps teams meet their SLAs for system uptime. When the market demands five-nines uptime (a system that is up 99.999% of the time), teams need full-stack observability and pinpoint precision to meet it.
• Increase software supply chain security. As teams integrate application security into DevOps for DevSecOps, monitoring provides an organization-wide view of security issues as they occur. This view enables teams to understand software vulnerabilities and risks in the context of pre-production and production environments.
• Create a developer-operations feedback loop. An enemy of efficient DevOps is data silos that can develop because of disparate toolsets and separate teams. DevOps monitoring can improve cross-team collaboration by bringing data together in one place where both development and operations teams can gain and share new insights.
• Enable progressive delivery. DevOps monitoring allows teams to reduce the risk of failed releases by delivering new features and updates in a controlled and incremental manner. Monitoring tools allow development teams to validate key quality, performance, and functional criteria are met through the gradual introduction of new changes to production. This helps minimizes failure and improve customer satisfaction
• Enhance user experience and boost business credibility. Using real user monitoring (a performance monitoring process centered on a user’s interaction with an application), teams can gain full visibility into how users experience digital transactions across web, mobile, and custom apps. Factors such as page load times, process flows, and real-time user surveys quickly gauge user satisfaction and business impact in real time.

Advanced observability advances DevOps monitoring

DevOps monitoring is essential for delivering software efficiently, securely, and reliably. By equipping teams with the insights they need to proactively identify code issues before they escalate, DevOps monitoring tools help organizations keep up with the accelerating pace of digital transformation. But to overcome the challenges of an ever-lengthening toolchain, it helps to take an observability platform approach to DevOps monitoring.

Powered by AI and intelligent automation, Dynatrace’s scalable and comprehensive observability platform advances organizations on their DevOps monitoring initiatives. Dynatrace enables teams to build highly integrated DevOps toolchains with observability, security, and AI at the core to help further accelerate delivery speed, improve code quality, and increase DevOps throughput.

The Dynatrace platform also enables teams to monitor logs generated by applications, servers, and infrastructure components. This centralized view enables teams to gather even more insight into errors, security issues, and operational inefficiencies.

Ultimately, using the platform as a single source of truth can break down silos and increase collaboration and trust within teams.