Principle #3: Actionable Intelligence

See into the future. With more accuracy.

Gaining Insights in Massively Scalable Environments

Containerized applications create an exponential increase in alerts and the number of metrics that can be tracked. More complexity means more monitoring to help gain a clear perspective of performance across the entire system.

With so much data, teams are challenged to separate the noise from the insights needed to optimize performance. With complex dependencies, finding the root cause of problems is like trying to find a “needle in a haystack of needles.”

Container monitoring reduces the number of alerts so that you can focus on the most critical alerts. At the same time, these critical alerts can also display actionable information and the workflows needed to quickly address a problem.

Today, even more intelligent alerts, using machine learning and analytics, are being developed for container monitoring solutions to help predict problems with even greater precision. By learning application performance behavior, these solutions can set baselines dynamically to prevent noise and false alarms. By using predictive analytics to identify problems and anomalies, teams can become more proactive in addressing more complex container issues, helping offset any serious performance issues.

"54% of surveyed IT organizations’ biggest challenge when monitoring new application is alert correlation or noise reduction."

Source: TechValidate. TVID: 360-731-B7C

Power Digital Performance With a New Model for Application Performance Management

CA Technologies

“Monitoring Reset for Containers”

Chapter from Container Monitoring and Management eBook

Monitoring used to be as simple: check to see if a computer was still running. Cloud-based application environments, of course, have changed all that. Monitoring is far more complex, and requires much more time and effort. Today’s users often want a solution that not only reduces the time needed to set up a monitoring tool, but the amount of time needed to predict or pinpoint problems in their stack.

Read this chapter now to learn more about:

  1. The ephemeral nature of containers

  2. Proliferation of objects, services and metrics to track

  3. Services as the new focal point of monitoring

  4. The diversity of end-user groups that perform monitoring

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See the 4 Principles of
Container Monitoring in Action

Containers are the fast-growing class of tools, growing at an annual clip of 40%.

Source: Container Technology Market to Grow 40% a Year, Analysts Predict. ZDNet, 17 Jan. 2017

Learn More about Container Monitoring

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Accelerating the Application Lifecycle with Microservices, Docker Containers 
and End-To-End Visibility of the User Experience

View solution brief >

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Monitoring Microservices? Consider Noise Cancellation

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CA APM Docker Monitoring

View data sheet >



Read Next: Principle #4

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