Distributed computing and orchestration have solved many problems, but they also have created new challenges. A Kubernetes cluster may look to a user to be a single machine, but it consists of a collection of independent nodes and numerous connected services.
Kubernetes is the de facto industry standard for container orchestration, with more than 58K stars on GitHub and over 2,200 contributors from around the world. While addressing some of the major issues with managing distributed microservices, it also created several new ones. It should come as no surprise that when questioned, engineers name monitoring as one of the biggest barriers to using Kubernetes. After all, it has never been simple to monitor distributed environments, and Kubernetes only makes things more difficult. The development of numerous open-source monitoring tools for Kubernetes to aid in problem-solving is also not surprising.
These tools exist to solve different problems pertaining to Kubernetes monitoring. Some help with logs, others with metrics. Some are data collectors while others provide an interface for operating Kubernetes from a birdseye view. This variety and depth attest to the strength of Kubernetes as an ecosystem and community, and in this article, we’ll take a look at the Top 5 of the most popular tools for Kubernetes monitoring.
Table of contents:
- The ELK stack
- Fluentd/Fluent Bit
There are many open-source time-series databases available today, including Graphite, InfluxDB, and Cassandra, but none are as well-liked among Kubernetes users as Prometheus. Prometheus, which started out as a SoundCloud project and is now a part of CNCF (Cloud Native Computing Foundation), has become the open-source de-facto standard for monitoring Kubernetes.
In a nutshell, Prometheus's multi-dimensional data model, PromQL (the Prometheus querying language), built-in alerting features, a pull vs. push approach, and, of course, the always expanding community are what set it apart from other time-series databases. The two projects are now tightly connected, allowing users to quickly operate Prometheus on top of Kubernetes using the Prometheus Operator. These differentiators make Prometheus a great option for Kubernetes users.
The pros of Prometheus are Kubernetes-native, simple to use, and has a huge community of contributors while the cons are it has challenges at scale and storage problems.
An open-source, cross-platform online application for interactive visualization and analytics is called Grafana. When connected to supported data sources, it offers charts, graphs, and alerts for the web. It is extendable using a plug-in architecture. A licensed Grafana Enterprise version with additional features is also available as a self-hosted installation or an account on the Grafana Labs cloud service. Using interactive query builders, end users may design sophisticated monitoring dashboards. The front end and back end of Grafana are each composed of TypeScript and Go code, respectively.
There are a number of reasons Grafana is so popular, its ability to integrate with a long list of data sources being one of them. Grafana is extremely robust, featuring a long list of capabilities such as alerts, annotations, filtering, data source-specific querying, visualization and dashboarding, authentication/authorization, cross-organizational collaboration, and plenty more.
Grafana is also super easy to set up on Kubernetes — there are numerous deployment specifications that include a Grafana container by default and there are plenty of Kubernetes monitoring dashboards for Grafana available for use.
Pros are a Large ecosystem of developers, rich visualization capabilities, and altering, while cons are that Grafana is not optimized for Kubernetes Log management.
- The ELK stack
The ELK Stack is undoubtedly the most popular open-source monitoring tool for Kubernetes logs. ELK, which stands for Elasticsearch, Logstash, and Kibana, also contains a fourth part called Beats, which are little data shippers. Together, the stack's components offer a complete and potent logging solution for Kubernetes. Each component in the stack handles a separate stage of the logging process.
Logstash is capable of aggregating and processing logs before sending them on for storage Elasticsearch will function well even when storing and searching through millions of pages because it was built to be scalable. The analysis interface required by users to interpret the data is brilliantly provided by Kibana.
It is simple to deploy each component of the stack into a Kubernetes environment. The components can be run as pods utilizing a variety of deployment options or helm charts. Metricbeat and Filebeat both add Kubernetes metadata to the documents and can be set up as daemon sets.
Pros of the ELK stack are huge community, ease to deploy and use in Kubernetes, and also rich analysis capabilities that it comes with while cons are ELK stack is difficult to maintain at a scale
- Fluentd/Fluent Bit
Another well-liked tool utilized by Kubernetes users for log aggregation and processing is Fluentd. Fluentd, a unified logging layer written in Ruby, was developed as a one-stop component that can gather data from many sources, combine the disparately formatted data into JSON objects, and route it to various output destinations. The ELK moniker has been superseded by the EFK Stack because Fluentd is so commonly used.
Fluentd owes its popularity among Kubernetes users to Logstash’s fallacies, especially those performance-related. Design-wise — performance, scalability, and reliability are some of Fluentd’s more outstanding features. Adding new inputs or outputs is relatively simple and has little effect on performance. Fluentd uses disk or memory for buffering and queuing to handle transmission failures or data overload and supports multiple configuration options to ensure a more resilient data pipeline.
Pros of Fluentd are the huge plugin ecosystem, performance, and reliability while the con of Fluentd is to difficulty in its configuration.
Kubewatch, as the name suggests, keeps a close eye out for particular Kubernetes events and sends notifications about these events to a variety of endpoints, including Slack and PagerDuty. More specifically, when you ask kubewatch to watch certain Kubernetes resources, such as daemon sets, deployments, pods, replica sets, replication controllers, services, secrets, and configuration maps, it will search for changes made to those particular resources. Using helm or a custom deployment, kubewatch is simple to set up and deploy.
Pros of Kubewatch are the support of multiple endpoints, easy to deploy while the con is that it just provides an overview of metrics rather than alerts and rich visualizations.
In this article, we saw an in-depth understanding of open-source tools for monitoring Kubernetes. We saw the top 5 tools to monitor Kubernetes, such as Prometheus, Grafana, the ELK stack, Fluentd, and Kubewatch.