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What are the six Kubernetes monitoring tools? I believe many inexperienced people are at a loss about this. Therefore, this article summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.

Guide: monitoring can help you ensure that your Kubernetes application runs smoothly and troubleshoot any problems that may arise. Prometheus is a popular open source monitoring tool that many companies use to monitor their IT infrastructure. However, there are many other monitoring tools available. Six alternative methods of Kubernetes Prometheus monitoring are introduced.

What is Prometheus?

Prometheus is an open source monitoring system originally built on SoundCloud. It is designed to monitor multidimensional data collection and query. The Prometheus server has its own independent unit that does not rely on network storage or external services. Therefore, Prometheus does not require a large number of other infrastructure or software.

The main advantages of Prometheus include tight integration with Kubernetes, many available exporters and libraries, and fast query languages and API. The main disadvantages of Prometheus include simplified, constrained data models, limited granularity of pull-based models, and lack of encryption.

The following list reviews six ways to monitor Kubernetes in addition to Prometheus. Each tool has its own advantages and disadvantages. Let's review the main functions of each tool.

1.Grafana

Grafana is an open source platform for visualization, monitoring and analysis of metrics. The main focus of Grafana is time series analysis. Grafana can display analyzed data through a variety of graphic options, including line charts, heat maps, and bar charts. You will receive an alert when the monitored metrics exceed a predefined threshold.

The main features include:

Alerts-you can obtain alerts through different channels, including SMS, email, Slack, or PagerDuty. If you prefer other channels of communication, you can use some code to create your own notifier.

Dashboard templates-with templating, you can create dashboards that can be reused for multiple use cases. For example, you can use the same dashboard for the production server and the test server.

Provisioning-you can use scripts to automate everything in Grafana. For example, you can automatically start Grafana and new Kubernetes clusters using scripts that contain IP address, server, and data source presets.

Comments-used for data association when an error occurs. You can manually create comments by adding text to the drawing, or you can get data from any data source.

2.cAdvisor

CAdvisor can collect, process, and export information about the performance and resource usage of running containers. CAdvisor has native support for Kubernetes because it is integrated into the Kubelet binaries.

Its main functions include:

Auto Discovery-automatically discovers all containers in a given node and collects statistics, including memory, CPU, network, and file system usage.

Storage plug-ins-export statistics to different storage plug-ins, such as Elasticsearch and InfluxDB.

Overall computer usage-provides overall computer usage by analyzing the "root" container on the computer.

Web-UI-you can view metrics on Web-UI, which displays real-time information about all containers on your computer.

3.Fluentd Fluentd

Fluentd Fluentd separates the data source from the back-end system by providing a unified logging layer between the two. The logging layer allows you to collect multiple types of logs generated.

The main features include:

JSON data structure-enables you to unify all aspects of log data processing, such as buffering, filtering and outputting logs across different sources.

Pluggable architecture-the flexible plug-in system allows you to extend the functionality of Fluentd by connecting multiple data sources and outputting them.

System resources-the instance runs on 30MB to 40MB memory and can handle 13000 events per second. If you need more memory, you can use Fluent Bit lightweight transponders.

Reliability-supports file-based buffering and memory buffering to prevent data loss on the node. In addition, you can set up Fluentd to support high availability and strong failover.

4.Jaeger

Jaeger is an open source tool for monitoring traffic between distributed services such as Kubernetes. Jaeger uses distributed tracing to trace the paths of service requests through different microservices. You can then see the request flow visually. Distributed tracking is a method of managing and observing micro-services, which runs as part of the service grid.

The main features include:

High scalability-designed for no single point of failure (SPOF) and scalable according to business needs.

Multiple storage options-supports two open source NoSQL databases, Elasticsearch and Cassandra. Jaeger also provides simple memory storage for testing.

Cloud native deployment-supports different configuration methods, including environment variables, command line options, and configuration files. Kubernetes templates, Kubernetes operators, and Helm diagrams support Kubernetes deployment.

Monitoring-the Jaeger backend component exposes Prometheus metrics and logs by default.

5.Telepresence

Telepresence is an open source tool that runs a single service locally while connecting it to a remote Kubernetes cluster. Telepresence deploys a two-way network agent in Pod that collects data for Kubernetes environments, including TCP connections, environment variables, and volumes.

The main features include:

Compatibility-both Linux and Mac OS with native OS packages are available.

Development Workflow-provides you with a rapid development workflow for multi-container applications developed on Kubernetes. You can run it when you proxy the local Docker container to the cluster.

Debug the Kubernetes service locally-when there is a bug in the temporary cluster, you want to run the service locally. Telepresence allows you to debug services locally.

Connect to a remote Kubernetes cluster-you can access the remote cluster from a local process. With this access, you can use local tools on your laptop to communicate with processes within the cluster.

6. Zabbix

Zabbix is designed to monitor a large number of network parameters and the health of servers, and provides many data visualization and reporting capabilities based on stored data. Small organizations with a small number of servers and large enterprises with multiple servers can use Zabbix to monitor the IT infrastructure.

The main features include:

Elastic threshold-you can define elastic problem thresholds, also known as triggers. These triggers are based on values in the back-end database.

Real-time visualization-you can use the built-in drawing feature to view monitored projects immediately.

Automatic discovery-provides a variety of ways to automate the management of large environments, such as Kubernetes. You can automatically add and remove file systems and network interfaces in your organization.

Network Discovery-enables you to periodically scan external services or Zabbix agents in the network and take predefined actions when discovered.

Distributed monitoring-provides an effective way to monitor distributed infrastructure using Zabbix agents. You can use an agent to collect data locally and then report the data to the server.

Conclusion

Prometheus is an open source tool for monitoring Kubernetes workloads. It is locally integrated as the default monitoring tool in Kubernetes, including the built-in alert manager. However, you should also consider using other monitoring options for your Kubernetes environment to complement and improve the Kubernetes functional experience.

After reading the above, have you mastered which of the six Kubernetes monitoring tools are? If you want to learn more skills or want to know more about it, you are welcome to follow the industry information channel, thank you for reading!

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