[Republished from Turbonomic.com]
It’s widely accepted that the standard for creating cloud native applications is Kubernetes, and while this software has solved key challenges, it has also introduced new complications. It didn’t take long before operators realized that monitoring a Kubernetes environment is one of the top obstacles that comes along with using this software. With the rise of Kubernetes came a new wave of monitoring tools to help overcome these challenges. Choosing the right monitoring toolkit for you and your team’s Kubernetes environment is a challenge in itself as each tool covers a different specialty, from logging to metrics to data collectors and much more.
This blog will unpack some tips on which Kubernetes monitoring tool is best for you.
Why is Kubernetes Monitoring Important?
Running Kubernetes adds an extra layer of complexity to your environment that has led operators to learn that traditional monitoring tools and processes can’t stand up to the level required. Traditional monitoring tools created for monitoring hosts, VMs, or physical machines are unable to scale to the level of complexity within a Kubernetes environment. A single point of failure can destroy hours of countless work due to the increasing entanglement of countless applications communicating with one another. Hence, the creation of specific tools and processes to monitor your Kubernetes environment.
Here is our list of the top open-source tools that we have seen deployed to monitor Kubernetes in many organizations. You may even have some already in your organization and didn’t know they were up to the job.
Kubernetes Monitoring Tools
Out of the Box: Kubernetes Offerings
Kubernetes has many out of the box offerings for you to use along with their software. The kube-state-metrics and dashboards are provided to you by KaaS distribution. These kube-state-metrics can provide insight into your cluster through metrics alone, dashboards, or an alerting pipeline.
These offerings are great for monitoring a smaller scope Kubernetes environment but once your organization decides to expand their cloud native environment you will need a tool that can help you operate at scale.
Prometheus is a standalone open-source monitoring and alerting system. The software is most commonly used for data collection with your Kubernetes clusters. In order to monitor your environment, you need to collect data, along with the visualization of that data. Prometheus solves the problem of data collection. It was designed to be a quick set up, provide value immediately, and be straightforward and easy to operate. And while the ease and simplicity of Prometheus is one of its benefits, it is also one of its trade-offs.
Originally designed at the beginning of the cloud-native journey when most organizations were starting their dally with microservices, the pain and problems with Prometheus becomes prominent as your organization inevitably scales up your microservice infrastructure. A substantial amount of overhead management is required to stand up numerous Prometheus instances. Prometheus allows you to collect data, but not to visualize it or bring everything together and operate at scale. The pain grows as your infrastructure grows and is not only felt by the team who manages the software, but also by the end users. Besides the increased need for overhead management, some other areas of the Prometheus management breakdown include...
- Reduced productivity for developers
- Decreased ability to diagnose upstream and downstream issues due to siloed data
- Loss of real-time visibility
Grafana is an open-souring visualization and analytics solution. The software allows you to query,visualize and alert on metrics no matter where they are stored. In short, Grafana presents teams what their users are really doing, not just what they say they are doing. But since Grafana is a visualization tool it does not have the native capability to aggregate data from multiple sources. This leads to a limited ability to correlate data across numerous data types.
Where Prometheus was created to collect your data, Grafana was created to help you visualize that data. And while both tools are good at their specific job, they cannot do much more. Even working together, you still need another tool that can give you one common data model and allow you to operate at scale.
Kibana is a free open fronted application that sits on top of the Elastic stack. The software provides search and data capabilities to its users. On top of that, Kibana secures Elastic stack clusters through monitoring and managing by acting as the user interface. Similar to Grafana, Kibana allows for the visualization of your data; however, Kibana only supports Elastic stack as a data source. Grafana is not bound to one data source and can be used with the data source you prefer. The major limitation with Kibana is that it must be configured and run with an Elastic node of the same version number. Kibana is also affected by any and all limitations that the Elastic stack is affected by.
Kibana and Grafana’s main goal is to make it easy to visualize and alert on their data, and they both do that well. But the common theme, which I’m sure you can guess, is it’s not enough to operate at scale and ensure your applications will always perform.
Graphite, quite simply, is an open-source data logging and graphing tool. Compared to Prometheus, Graphite is less complicated as it has fewer features. And the two aspects it performs precisely is that it can store numeric time series data and render graphs of the collected data. Graphite will not collect your data as its data collection is passive. This means that your applications that send their data to Graphite need to be configured to send the data to Graphite’s carbon component.
Again, Graphite does the job it was created to perform well, but that’s all it does. Regardless of the combination of Kubernetes monitoring tools you are utilizing if you are not assuring performance of your applications by preventing issues from arising in the first place, you will forever be reactive.
Kubernetes Monitoring Tools Do Not Assure Performance
You have inevitably tried some of these solutions or have looked at some commercial monitoring products which are slowly catching up to the cloud-native architectures. These tools were created to solve a single problem, exceedingly well, but that’s about it. Previously, monitoring tools were the most effective way to fix issues within your environment like bottlenecks, but with Turbonomic’s application resource management capabilities you will never have to wait for an issue to arise again. A new approach is needed, and that is Turbonomic ARM.
Making the jump from monitoring to performance assurance is where the proverbial rubber really hits the road. This is where our engineering team, some amazing customers, and Kubernetes operators are working hand-in-hand to bring the best of “traditional” monitoring data together with full-stack analytics that are used to drive real performance-focused and automatable actions for your Kubernetes environment.
Instead of relying on reactive monitoring tools that alert you to issues within your environment after they occur, our software will prevent them from occurring in the first place. Turbonomic in conjunction with your Kubernetes monitoring tools will create an unstoppable force. Our software will automatically assure your applications performance at scale by resourcing each layer of your stack, continuously.
By the way, if you’re considering what you need when running your mission-critical applications on Kubernetes, be sure to check out this blog Kubernetes Management: It’s All About the Application or download our free white paper below.
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