What is Container Monitoring? Tools and Best Practices
Container monitoring improves visibility into microservices - based architecture with metrics that help assess, evaluate, and alert on the health and performance of your containerized environment.
What is container monitoring?
Container monitoring is a solution that improves the visibility of containerized applications by collecting, tracking, and displaying metrics that offer real-time insight into container performance.
Container monitoring tools are a critical element of an effective application performance management (APM) strategy. Modern microservices architectures have played an important role in simplifying the development lifecycle by supporting DevOps strategies, but that ease came at the cost of visibility. Getting a clear view of highly distributed environments is challenging but essential for optimal troubleshooting and performance monitoring.
Why is container monitoring important?
Container monitoring supports the overall health of your application and reduces MTTR of performance issues by providing data that enables you to be proactive in avoiding system outages. The ability to automate alerting, monitor time-series data, and implement changes without increasing risk protects the user experience and, ultimately, business outcomes.
Developing a comprehensive understanding of your IT infrastructure through the aggregation and visualization of data allows you to optimize functionality and pinpoint the root cause of performance issues more efficiently.
How do you monitor container applications?
Monitoring container environments can seem challenging, since application infrastructure consists of a collection of microservices versus a monolithic tech stack. These modular components are each developed, deployed, and managed independently which makes monitoring more complex.
An effective container monitoring solution accounts for each layer of an IT stack and collects key metrics such as CPU usage, CPU limit, memory utilization, and memory limit. Features like real-time streaming logs, transaction tracing, and observability provide critical information that helps IT teams scale up or down as needed. The aggregate of collected data is reported through dashboards and visualization systems so that it can be shared and analyzed with relevant teams.
Performance monitoring for two of the most popular container platforms, Docker and Kubernetes, requires request counts and latency metrics if a container runs an HTTP server. Memory and CPU ratios for the cluster itself must also be collected for accurate Kubernetes and Docker monitoring.
What are best practices for container monitoring?
Container monitoring is a collection of techniques that improve visibility into a microservices architecture. Consider the following as you implement your container monitoring system:
Streamline individual container metrics
Containers add more layers to application performance monitoring because now it is not only the physical hosts that need monitoring, but also the services they run and the associated containers. Manually checking error logs or reviewing reports for anomalies is inefficient and time-consuming. The cumbersome nature of such a task would result in important information getting lost in an abundance of less relevant data.
Streamline your container monitoring system with tools that provide top-level metrics with the option to drill down into the performance of individual containers.
Automate service discovery
Containerized environments are always evolving. Services are added and removed, containers move between hosts, instances are added and removed by autoscaling, and auto replication and failover result in ever-changing architecture.
Automating service discovery ensures that monitoring isn't disrupted without requiring you to manually track dependencies and connect services with each change. Service discovery also makes it easier to scale clusters of containers more accurately.
Leverage tools for real time monitoring
Due to the ephemeral nature of containers, data has a tendency to lose its value as it ages. Monitoring tools that include an effective data visualization system streamline analysis with a graphical interface that makes dramatic changes or anomalies easier to spot than it would be while reading countless lines of log data.
Advanced monitoring solutions pair a machine learning algorithm with automated alerting to make sure incidents are quickly, accurately, and appropriately reported to the right people.
How AppDynamics Helps
AppDynamics simplifies container monitoring with an out-of-the-box end-to-end monitoring solution that offers a single pane of glass perspective of all monitored containers and application code. Modernize traditional tech stacks or develop cloud-native microservices architecture within the same interface for seamless application monitoring that helps pinpoint the root cause of performance issues while also correlating application performance and user experience with business outcomes. Improve your application and the bottom line of your business with a comprehensive performance monitoring solution that consolidates your system's data into actionable insights.
Hear from our customers
"With AppDynamics, we gain better visibility into how microservices interface with the rest of the components of our application, the ability to proactively troubleshoot emerging issues, and the increased velocity to resolve issues faster than ever."
Nuno Pereira, CTO, iJET