Tackling the Top 5 Kubernetes Debugging Challenges
Bugs are inevitable and typically occur as a result of an error or oversight. Learn five Kubernetes debugging challenges and how to tackle them.
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Cloud-native technologies like Kubernetes enable companies to build software quickly and scale effortlessly. However, debugging these Kubernetes-based applications can be quite challenging due to the added complexity of building service-oriented architectures (microservices) and operating the underlying Kubernetes infrastructure.
Bugs are inevitable and typically occur as a result of an error or oversight made during the software development process. So, in order for a business to keep pace with app delivery and keep their end users happy, developers need an efficient and effective way to debug. This involves finding, analyzing, and fixing these bugs.
This article highlights five Kubernetes debugging challenges and how to tackle them.
#1. Slow Dev Loop Due To Building and Re-Deploying Containers
When a development team adopts a cloud-native technology like Kubernetes, their developer experience is significantly altered as they’ll now be expected to carry out extra steps in the inner dev loop. Instead of coding and seeing the result of their code changes immediately, as they used to when working with monolithic environments, they now have to manage external dependencies, build containers, and implement orchestration configuration (e.g., Kubernetes YAML) before they can see the impact of their code changes.
There are several ways to tackle this Kubernetes debugging challenge:
- The first one is for you to develop services locally and focus on unit tests over end-to-end tests but this was painful when a service/web application has authentication requirements and dependencies on databases.
- Another way to solve this is to use a tool called DevSpace which will automate your build and deployment steps, thereby making it faster.
- And finally, you can also utilize a CNCF tool called Telepresence to connect your local development environment to a remote Kubernetes cluster, thereby making it possible to access these external dependencies in the remote Kubernetes cluster and test them against the service being developed locally for an instant feedback loop.
#2. Lack of Visibility in the End-to-End Flow of a Distributed Application
Another debugging challenge when working with Kubernetes is having full visibility of the end-to-end flow of your application because there are often just too many services. And without full visibility, it’s difficult to identify and fix a bug.
Ideally, you should be able to get cross-service visibility into what is calling what, what is timing out, etc. To tackle this, you need to utilize tools that make observability and tracing more seamless. For example, tools OpenTelemetry, Jaeger, and Grafana Tempo can help you get the necessary information to reproduce errors. The goal here is to get as much information as possible, and when you do, you’d be able to fix bugs in real-time and ultimately improve the overall performance of your application.
#3. Inability To Attach a Debugger to the Code
One of the most important things a developer needs is the ability to attach a debugger to their code, and working with Kubernetes doesn’t make this easy. Yes, things like print/log statements work, but they are nowhere near as good as being able to put a debugger on something and step through the code, especially if it’s a new code base that a user isn’t familiar with.
Two possible ways to tackle this Kubernetes debugging issue are to:
- Develop locally and find ways to mock or spin up local instances of dependencies.
- Ensure code is unit testable and focus on those because they are easier to write tests for and easy to throw a debugger on.
#4. Complicated Setup for Performing Integration Testing With a Local Change
Cloud-native applications are often composed of various microservices. More often than not, these microservices work interdependently and communicate with each other to process larger business requests.
As an example, a timeline service for a social media application may need to talk to a user profile service to determine a user's followers and, at the same time, may need to talk to an authentication service to determine the authentication state of a user. Because of this multi-directional, service-to-service communication that happens between microservices, it is crucial to perform integration testing on microservices before deploying any changes because unit testing alone doesn't always provide guarantees about the behavior of the application in the target environment.
Performing integration testing in this context naturally involves running multiple services and connecting to (potentially remote) middleware and data stores. This requires techniques and tooling that present multiple challenges. These challenges include having limited resources and inconsistent data between production and non-production environments; managing distinct configurations for separate environments; and difficulties associated with managing service versioning, releases, and deployment cycles.
#5. Reproducing an Issue That Only Happens in Prod/Staging
Sometimes, it can be very complex to reproduce a bug that happened in production or staging locally. At this point, your mocks or existing values will not be sufficient.
You’d think to yourself, how can I actually reproduce this issue? How can I get to the root of the problem faster? Well, an open-source tool called Telepresence is usually my go-to when facing the K8s debugging challenge — The tool allows you to access remote dependencies as if they were running locally and reroute traffic from remote to local services.
This means you’d get to debug them in real-time, reproduce these issues, and push a fix to your preferred version control and CI/CD pipeline faster.
Most organizations insist that any important delivery of software goes through multiple iterations of testing, but it’s important to remember that bugs are inevitable. Having the ability to debug applications effectively is one of the best techniques for identifying, understanding, and fixing bugs. Container technology, such as Kubernetes, provides many benefits for software developers but also introduces app debugging challenges. Fortunately, there are multiple ways to address these challenges easily.
If there are other Kubernetes debugging techniques that you’d like to share, please mention them in the comment section.
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