Thanks to the efforts of DevOps teams, rapid application and feature development are increasing the pace of innovation and having an increasing impact on business revenue. Top-performing DevOps teams are key contributors to year-over-year revenue growth of 25 percent or more, according to Enterprise Management Associates (EMA), thus increasing the value of IT. Application performance monitoring (APM), when used throughout the development life cycle, is a significant contributor to the success of these top-performing DevOps organizations.

APM: Not Just for Production Anymore

Frequent application changes, virtual environments, complex infrastructures, distributed data and cloud services are making production apps more difficult to support. We all know that it is cheaper to catch and fix bugs and performance problems earlier in the development process. Yet, 70 percent of organizations still use a collection of disconnected, manual troubleshooting processes, and they rank this manual troubleshooting as the single biggest bottleneck in their continuous delivery pipeline. According to EMA research, “APM solutions can substantially mitigate the challenges generated by high rates of production change.”

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Which of the following best describes how you currently monitor and manage systems across your hybrid cloud environment?(Required)

Multiple separate tools for different environments

Multiple separate tools for different monitoring and management functions

Single consolidated dashboard

Custom built monitoring and management solution

No full monitoring and management solution

Don’t know

How valuable would it be for your monitoring and management solution to incorporate predictive analytics to help you identify and address system issues that are critical and not waste time or effort working through all the data and “noise” that is not critical?(Required)

Extremely valuable

Moderately valuable

Somewhat valuable

Slightly valuable

Not valuable

How do you most typically address potential system issues BEFORE they impact your operations?(Required)

Automated workflows and playbooks to remediate potential issues as soon as they are detected

An orchestrated response process that leverages automation, AI, and human expertise to rapidly respond to potential issues

Advanced monitoring tools such as predictive analytics and anomaly detection to proactively identify and address potential issues

Respond to issues as they arise, using manual processes and troubleshooting techniques

A combination of automated remediation, orchestrated response, and/or proactive monitoring to address potential system issues

Don’t know

Other

What methods does your organization use to control and monitor cloud/IT spending?(Required)

Centralized procurement processes

Pre-approved budget thresholds

Automated cost monitoring tools

Department-level spending controls

Regular cost audits and reviews

Cloud cost optimization platform

Approval workflows for resource provisioning

Native financial operations tools provided by the cloud provider

No formal controls in place

Don’t know

Other

Please specify:

Which methods do you rely on most to detect security vulnerabilities in your systems?(Required)

Automated scanning tools

Manual assessments

Vendor notifications

Threat modeling (for early detection)

None of these

Don’t know

Other

Please specify:

What are the TWO most common ways you prioritize vulnerabilities to address within your environment?(Required)

Based on potential impact

Based on exploitability

Regulatory compliance requirements

Based on CVSS scores

Risk-based analysis of multiple factors

First-in-first-out approach

No formal prioritization process

Don’t know

How do you typically handle system updates and security patches?(Required)

Automated updates and patches

Manually review and apply updates and patches on a regular schedule

A combination of automation and manual review

Apply updates and patches on an as-needed basis.

Outsourced update and patch management

No defined process

Don’t know

Other

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Say, for example, a piece of code is running slowly during development or QA. The assumption that it’s the code’s fault triggers a rewriting process that doesn’t ultimately solve the problem, delays feature delivery and may introduce new issues. Details available from APM show that an underlying dependency, such as the Java Virtual Machine, is becoming saturated by a completely different process—details that are very difficult to correlate with silo-based tools and manual processes.

There is a saying that you can’t manage what you don’t measure. While many organizations use APM to measure the performance of production environments, shifting application performance monitoring left into the development environment enhances application performance and stability. Using APM throughout the development life cycle helps teams track down elusive performance problems, enabling earlier debugging of performance bottlenecks, higher confidence of achieving production SLAs and enhanced insight into feature adoption.

Earlier Debugging of Bottlenecks

Using multiple, domain-specific performance monitoring tools ends up trapping critical information in different silos. Consequently, troubleshooting potential issues is very resource-intensive, requiring experts from multiple domains to analyze the outputs and correlate the results into something actionable. Developers are pulled into production troubleshooting more often, slowing the pace of innovation and delivery. Mean times to repair get longer and longer, impacting SLAs and overall user experience.

Testing application performance during development, using the same tools that monitor the production application, helps identify bugs and bottlenecks when they are cheaper and easier to fix. Analytic features trace transactions from user to back-end, detecting potential load problems. Real-time, code-level diagnostics understand dependencies and watch all components, including containers and microservices, exposing code, SQL, networks, system resources and web services to detailed evaluations. Barriers between silos become transparent, improving communications and reducing time to resolution of issues that cross team or department boundaries.

Higher Confidence of Achieving SLAs in Production

Performing QA tests with unintegrated legacy tools is still a common practice in many organizations. These tools are often tied to physical concepts such as servers and networks, not the highly transient and virtualized production environment of clouds, services and VPNs. As a result, teams struggle to get a clear picture of potential issues under real-world conditions. Developers again get pulled into production troubleshooting, working to reconcile development and QA data and results with the production APM system.

Including application performance monitoring during automated load testing gives DevOps a better prediction of code behavior in production. Performance analytics that cross all infrastructure components quickly validate the desired production SLAs. REST APIs make it faster and easier to collect and analyze APM data, thereby improving collaboration between teams during troubleshooting. Some APM tools can automate the correlation of logs to application activity, removing the need for manual correlation and speeding problem identification and resolution. Overall, instead of guessing at the relationship between testing and production performance, application performance monitoring provides better simulation of real-world conditions, improving confidence and reducing time to deployment.

Enhanced Insight into Feature Adoption

Deploying apps more often, with better performance and stability, only leads to enhanced digital experiences if customers like and use the new features. Users do not always behave as expected, even with thoroughly researched enhancements. Focusing on metrics such as availability and response time, while important, means missing out on useful information. Without understanding the details of end user adoption, IT is unable to quantify a new feature’s contribution to revenue, productivity, satisfaction and other valuable business objectives.

Continuously monitoring user experience is essential to getting timely insights on usage trends, response times and overall user satisfaction. For instance, identifying high- and low-performing features or the most- and least-used capabilities enables better road map planning. For applications with a broad and global user base, segmenting by different groups or geographies can help pinpoint local problems (e.g., within a particular country or a subset of users), which helps DevOps teams fine-tune their apps in even the most distributed and challenging of environments. And by viewing detailed performance graphs of critical transactions, teams can quickly understand financial and productivity impacts, helping them prioritize open support tickets and application optimization efforts. Overall, user experience monitoring helps shift the DevOps team from a reactive to a proactive approach to ensuring performance.

Managing the Digital Experience

Customers and employees have high expectations of their digital experiences that must keep pace with their changing needs. DevOps practices help address these evolving customer expectations. But while frequent releases are great for the business, they are often hard on IT.

To be successful, DevOps must strike a balance between velocity and stability. However, delivering the combination of innovation, performance, and availability is a significant challenge for IT. Puppet’s “2017 State of DevOps” report states that stability (mean time to recovery and change failure rates) varies significantly between top-performing and lower-performing organizations, and it is only getting worse. Increasingly complex environments, containers, microservices and other dynamic components are difficult to monitor with traditional performance monitoring techniques.

The performance benefits enjoyed by the leading organizations are substantial. According to the Puppet report, these top-performing firms spend 22 percent less time on rework or unplanned work, deployments are 46 times more frequent, and mean times to repair 96 times faster. The inevitable result is faster innovation, better responsiveness to user issues and significantly higher customer satisfaction with the digital experience.

Integrated application performance monitoring is an essential tool that enables collaboration across IT specialties, reducing or eliminating the finger pointing and other unproductive behaviors that show up all too often in organizations with operational silos. In addition, APM improves visibility across highly dynamic infrastructures, making it possible to quantify financial impact over time and across releases. Lastly, when issues do arise, APM can help rapidly troubleshoot complex issues in production, often before they negatively impact the business or user’s digital experience.

Application performance monitoring in DevOps is the modern choice of innovative organizations that want to deliver the best digital experiences to their customers, without having to choose between speed and quality.

— Steve Brar