Kubernetes is revolutionizing application development because it is designed for ease of use, flexibility and scalability. In spite of these compelling advantages, however, troubleshooting Kubernetes problems can be a formidable challenge. Once you are alerted to an error, just knowing where to begin can even be overwhelming.
Imagine you are developing an app in a Kubernetes-based development environment and you get an alert for a container error that you do not recognize. First, you ask your colleagues if they have seen this before. Next, you search multiple blogs to see what other developers are saying about this error. Maybe you check multiple dashboards and logs; try to dig up any information you can find. The whole process can take hours and involve multiple teams. Ultimately, you end up back at the command line, trying to solve a problem that you do not really understand. Does this frustrating scenario sound familiar? This is a hit-or-miss approach to Kubernetes troubleshooting that does not benefit the development process or the business.
The bottom line is that Kubernetes is very complex—significantly more complicated than traditional development environments—because there are thousands of moving parts, any one of which could be part of the problem. In this environment, there is no way a developer can manually figure out everything that is going on or solve every issue that arises.
The following are just a few examples of the many hard-to-troubleshoot Kubernetes errors you may encounter:
- Pods pending
- CPU throttling
- Node pressure
Troubleshooting any one of these errors could put you behind schedule by hours or even days. Even an application performance management (APM) tool is not enough to enable you to diagnose the error quickly. While APM may alert you to the issue, you still have to search multiple other dashboards and resources and go into the command line to identify and resolve the problem. Notwithstanding the help of a respected APM solution, troubleshooting a Kubernetes error is still a lengthy and laborious process.
For all these reasons, it may be tempting to simply ignore an error and hope the issue will go away. To avoid the time-consuming troubleshooting process, some developers will simply start a new container and assume the error was a configuration mistake that is now corrected. That may be the case in some instances, but in other cases the problem is still there, hidden away, only to arise later in the application life cycle, resulting in even more costly complications.
Development Challenges Lead Directly to Business Problems
Every error matters because every application problem has the potential to blow up into a major business problem. First, consider the time and resources spent on the remediation of a mysterious infrastructure issue. In the end, this results in higher operational costs that eat away at IT budgets. By accelerating troubleshooting and reducing mean-time-to-resolve (MTTR), you maximize your company’s investment in its most important asset: People.
Second, the time spent investigating a Kubernetes error takes away from valuable hours that you could spend improving performance, optimizing the application, or innovating new features and capabilities—the critical factors that differentiate your application from the competition.
Finally, and maybe most importantly, the longer it takes to find a solution to a Kubernetes issue, the greater the impact it can have on application availability and performance, which adversely affects the end-user experience. In the digital economy, an application that delivers a negative user experience is a dire concern for any business because it can ultimately reduce customer retention, revenue and market share and even damage brand reputation.
Must-Have Capabilities For Your Kubernetes Monitoring Solution
Kubernetes development requires a solution designed to simplify and accelerate troubleshooting so you can get on with more important tasks.
The following are must-have capabilities you should look for when choosing a Kubernetes monitoring system.
Universal dashboard: You should not have to toggle between multiple tools to identify and rectify a Kubernetes error. The right monitoring system will provide a universal view of all the information you need to remediate the problem including alerts, events, logs, performance, capacity and utilization for clusters, namespaces, workloads and pods.
Detailed explanation: An error does not do much good if you do not know what it means. A Kubernetes monitoring solution should explain the meaning of any error, along with the context and potential causes.
Easy navigation: An optimal monitoring tool will enable easy navigation across different levels, pods, containers and namespaces, so you can focus on exploring the root cause of an issue, rather than how to use the troubleshooting tools.
Pinpointing: A complete monitoring system can pinpoint exactly where you are having trouble—even if there are multiple sources—enabling you to quickly drill down to each potential source for more details.
Prioritization: In cases where multiple entities could be the cause of the error, the right monitoring system provides a comprehensive list of all possible sources and prioritizes them so you know where to look first.
Secure access: Security teams are often concerned about providing broad access to command-line tools, and for good reason—overly permissive Kubernetes pod policies can put the company at great risk. Consequently, a Kubernetes monitoring solution should provide you with quick access to all the data you need without compromising security.
Actionability: The ideal monitoring system should propose recommended solutions to the problem, with actionable sets of steps for remediation.
Kubernetes errors are a normal part of software development and IT operations. Situations arise and they must be solved in a timely and cost-effective manner to keep the business up and running. There is no reason to put the development process on hold while you try to figure out the meaning behind an error. With the right monitoring solution, you can accelerate troubleshooting by as much as 10X—which means less time searching and more time for innovation.