Have you used Gmail or YouTube? If yes, did you ever asked, “how the applications like Gmail, YouTube, or even a simple search engine run?”
Google runs all its tools on “Linux container technologies”. This container technology eases development and facilitates quick deployment in production. The applications have their ecosystem in a container that maintains the separation of concern.
Working on containers the focus on extra features is evitable. The prominent features like providing a consistent environment, running anywhere in an isolation environment make it easier to work on any given platform.
As the number of containers and their replica grows, there is a need for an orchestrated container system to automate, maintain, placement, scaling, and monitoring it.
The Kubernetes acts as an orchestrated system that exhibits advantages like availability, auto-scaling, an extensive and flexible ecosystem.
Why monitoring is essential?
Kubernetes manages application by creating abstractions like pods, and services. If there are multiple containers involved for your process monitoring Kubernetes becomes an essential task.
Let’s know the importance of the architecture of Kubernetes before we move into the importance of Kubernetes monitoring. The client-server architecture of Kubernetes includes the master node and Kubernetes node. The master node is installed in the master machine whereas, the Kubernetes nodes are in multiple Linux machines. Master Machine’s components of Kubernetes:
The master machines contain,
- Etcd :Etcd contains configuration information that is used by each node in the cluster. It contains the distributed key values store accessible to all.
- API Server: It provides an interface to communicate different tools and libraries.Kubeconfig exposes Kubernetes API and server-side tools used for communication.
- Controller Manager: The control manager regulates the state of the cluster to perform tasks. It acts as a daemon that collects and sends the information to the API server, creates the shared state, and changes it to the desired state from its current state.
- Scheduler: It distributes the workload among the cluster nodes. The available nodes are used and by allocating the pods of the overloaded nodes.
2) Node Components: The Node components communicate with Kubernetes master components contains,
- Docker: Docker assists in running the applications in encapsulation containers in isolated light-weighted compartments.
- Kubelet Service: This service sends and receives information from the control plane service. Reading configuration information from etcd, communicating with master components, managing network rules, port forwarding, maintaining a state of work, and node server are its main functions.
- Kubernetes Proxy Service: A proxy server running on each node, it manages nodes, volumes, secrets.
Some tools used for Monitoring
Monitoring becomes complex when we have a Kubernetes with multiple components. The four layers namely, applications, hosts running, containers and Kubernetes layer needs to be monitored and analyzed.
1) Use monitoring tools to monitor the applications that are running in dynamically based on schedule policy. The tools like Kubernetes dashboard, Prometheus, Jaeger, Kubewatch, Weave Scope, EFKstack are used to monitor the Kubernetes clusters.
2) Monitor the containerized applicationsdistributed across multiple data centers and data centers. Collect and aggregated the data from all the data centers and cloud providers.
3) Resource metrics are used to track the various measurements like actively deployed pods, resource matrices like disk I/O, memory usage, CPU usage, container-native matrix, and application matrix.
4) Labeling these metrics using Kubernetes labels and correlating it with the events of containers will assist you in monitoring and optimum usages of Kubernetes and its clusters monitoring the Kubernetes clusters.
Orchestrating the multiple containers is the job of Kubernetes. The monitoring of Kubernetes becomes essential as the number of containers increases. These several ways of monitoringKubernetes cluster eliminates bottleneck and elevates the performance of containers, as you work on the applications.