Troubleshooting Kubernetes- Using the Shift-left approach

Effective troubleshooting in Kubernetes involves understanding the basic problem, managing the problem, and ensuring that the problem does not recur in the future. Kubernetes today is the standard container management tool and it is predicted that it will stay in that position in the coming years too. ‘Kubernetes has emerged as the foremost container orchestration platform and close 50 percent of organizations surveyed have already adopted Kubernetes in 2021.’

In this article, we attempt to explain the shift-left approach in a simple fashion.

Kubernetes provides a neat abstraction between the infrastructure layer and applications. This allows developers to quickly develop, deploy, and also operate their applications.

Kubernetes contains a set of APIs all of which work together. If your work involves deploying simple applications and executing them, then Kubernetes will do it for you. 

Kubernetes works to scale your applications whenever required, restart applications that have stopped working in case they have stopped working because of an issue, and direct user requests to those services that are healthy and working.

Read our blog “Kubernetes Health Checks: Some things you need to know”.

It is known to everyone that a high level of automation can get your entire system stuck at times because of very small problems. As an example, a field that is wrongly configured in the Kubernetes configmap could spread over to hundreds of instances when the application is running and bring it to a standstill. Therefore, you have to be careful and alert when you deploy/operate Kubernetes applications. 

In addition, the modern cloud-native applications that are developed are complex, and so there is a need to troubleshoot and debug them frequently. Kubernetes’ default setup is not always the best platform for this activity. In this blog post, we will discuss the shift-left paradigm that makes it easy for Kubernetes to troubleshoot.

The Kubernetes Lifecycle

At this point, it is important to discuss the lifecycle and critical milestones of a Kubernetes application.

Lifecycle management in software applications is comprehensive and includes management of various aspects that include project management as a whole and which can be further split into release management, requirements, architecture, programming, testing, maintenance, change management, continuous integration, etc. This is tantamount to managing all the teams of a large enterprise. However, the Kubernetes application lifecycle is very simple and organized into three phases: Day 0, Day 1, and Day 2.  

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Day 0: Design Phase

This phase involves making decisions related to your Kubernetes platform and the requirements of the application. You can keep the following important points in mind:

• Kubernetes platforms: whether on public cloud, private cloud, or on-premise
• Infrastructure requirements with respect to networking, storage, monitoring
• Cloud service integrations and security features
• Integration to CI/CD/GitOps

Day 1: Design Phase

In this next phase, you have to consider how to deploy the application to Kubernetes clusters. The main to be considered in this phase are:

• Deployment strategies at the application level, such as blue/green or A/B 
• Resource and cost optimization for multi-cloud and multi-cluster deployment strategies 
• Staged application deployments along with their environment requirements: test, staging, and production stages
• Security, trackability, and visibility of the deployments you are going to make

Day 2: Design Phase

A majority of the microservices team members focus on Day 0 and Day 1 phases and pay less attention to the most difficult part of Kubernetes applications: the operation. In the Day 2 phase, as all the applications have already been designed and deployed to the cluster, the job that remains is maintaining the infrastructure and keeping the systems alive and working. Here are the commonly recurrent problems you usually encounter and have to manage during this phase: 

• SLA levels and how to achieve them
• Troubleshooting guides/playbooks 
• Overall application visibility and their statuses via monitoring and alerting
• Tracking and taking necessary steps for proper resource usage and utilization 
• Access control to Kubernetes clusters and applications
• Backup and restoration of Kubernetes clusters, configurations, and application data, such as database disks

Managing Kubernetes lifecycles helps you to bring focus on the existing problems and move to the production stage with more robust applications, clusters, and, of course, the correct mindset. The following section discusses the shift-left paradigm and how it can be applied to the Kubernetes lifecycle. We have also attempted to list down some relevant best practices.

Shift-Left in DevOps

When using the shift-left approach, you focus on working on problems that may occur at a later stage in the SDLC even if you are in the early stages of software development. This approach encourages you to shift your mindset to the priorities required in the previous step. 

At the start, you have to start designing your application’s architecture keeping in mind the deployment characteristics of your cloud provider. You also have to deploy your applications in a manner that they are easy to operate and troubleshoot. In short, the shift-left approach enables the SDLC to become a more coherent set of processes. 

For the shift-left approach to Kubernetes, all applications have to be tested on Day 0, keeping in mind the fact that they will be deployed to the clusters on Day 1. The applications have to be positively deployed on Day 1, without forgetting the fact that the applications will operate and you will troubleshoot them on Day 2. 

Read our blog : How Kubernetes Works to Support Microservices Architecture

In the present times, there are very few DevOps engineers to help the developers. The ratio is estimated to be around 1:10 to 1:12. Therefore, developers have to dive deep into operational tasks and troubleshoot applications running in the clusters. The shift-left paradigm becomes a useful aid when you use Kubernetes in production in cases where the underlying problems are related to applications or the infrastructure.

In the absence of a perfect tool to apply the shift-left approach rules, best practices are essential. Here is a brief run on the existing best practices.  

Kubernetes Best Practices for Left-Shift

Taking into consideration the stages of the SDLC for Kubernetes, given below are methods of applying the shift-left approach by using a list of best practices. 

Day 0: Design Phase

In this phase, it is crucial for you to consider how to deploy and operate applications that will run in Kubernetes clusters. For this you have to:

1. Consider integration points paying attention to the cloud
2. Reduce the number of dependency libraries to a minimum
3. Use container images that are testable
4. Design troubleshooting APIs as first-class citizens (APIs will be consumed by client applications)

Day 1: Design Phase

In this stage, you will be creating application environments that are easy to operate and troubleshoot.

• Deploy with staged environments for testing, staging, and production
• Enable logging and tracing to capture transient information
• Integrate troubleshooting tools into container images
• Enable the use of metadata, such as labels and annotations

Day 2: Design Phase

Operation is the final phase of the lifecycle, but not the end-of-life for SDLC. In this stage, it is important for you to create an environment that is easy to both operate and troubleshoot so that future applications can be easily developed and deployed. For this:

• Using namespaces to isolate applications can be of help
• Onboard the whole team to ensure that everyone has access to Kubernetes clusters
• It pays to create alerts, notifications, and support levels 

conclusion

The use of best practices will likely help you to improve your Kubernetes lifecycle management. While these tips can (and will) help minimize the chances of things breaking down if carried out diligently and regularly. 

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