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Given its open-source benefits, Kubernetes has quickly emerged as a go-to choice for container orchestration for all developers.
Although Kubernetes is one of the best solutions for microservice application delivery issues, it comes with a slew of challenges and roadblocks for developers. Some of these challenges are technological, while others are unique to Kubernetes.
It is critical to address these challenges because failure to do so may result in various operational and management issues.
This article will look at some of the most common Kubernetes challenges teams face worldwide and their solutions.
What is Kubernetes?
Kubernetes simplifies application management by automating container management operational tasks and including built-in commands for deploying applications, rolling out application changes.
The following are notable Kubernetes challenges and its solution:
Challenge #1: Security
Due to its complexity and vulnerability, security is one of Kubernetes’ most difficult challenges. It can obstruct identifying vulnerabilities if not properly monitored. It is difficult to detect vulnerabilities when multiple containers are deployed. This makes it simple for hackers to gain access to the system.
Use Separate Containers
The private key is hidden for maximum security when you use regulated interaction to separate a front-end and a back-end container.
Challenge #2: Networking
Traditional networking approaches do not work well with Kubernetes. As a result, the difficulties you face grow in tandem with the size of the deployment. Complexity and multi-tenancy are two examples of issues.
- Kubernetes becomes more complicated when deployed across multiple cloud infrastructures. The same happens when mixed workloads from different architectures, such as Virtual Machines (VMs) and Kubernetes, are used.
- Static IP addresses and ports on Kubernetes cause similar issues. Implementing IP-based policies is difficult because pods use an infinite number of IPs in a workload.
- When multiple workloads share the same resources, multi-tenancy issues arise. If resources are allocated incorrectly, other workloads in the same environment suffer.
The Container Network Interface (CNI) plug-in assists developers in resolving networking issues. It enables Kubernetes to integrate seamlessly into the infrastructure and access applications on various platforms.
You can also use service mesh to solve this problem. A service mesh is an infrastructure layer embedded in an app and handles network-based intercommunication through APIs.
These solutions enable smooth, fast, and secure container communication, resulting in seamless container orchestration.
Challenge #3: Interoperability
Interoperability, like networking, can be a significant Kubernetes issue. Communication between apps can be difficult when enabling interoperable cloud-native apps on Kubernetes. It also impacts cluster deployment because the app instances it contains may have issues running on individual nodes in the cluster.
Kubernetes performs better in production than in development, QA, or staging. Furthermore, migrating to an enterprise-class production environment introduces numerous performance, governance, and interoperability complexities.
- The API, user interface, and command line are all the same
- Fuel interoperability for manufacturing issues
- Increase portability between offers and providers by enabling interoperable cloud-native apps via the Open Service Broker API
- Use collaborative projects from multiple organizations (Google, Red Hat, SAP, and IBM) to provide services for cloud-native apps
Challenge #4: Storage
Kubernetes presents storage challenges for larger organizations, particularly those with on-premises servers. One reason for this is that all of their storage infrastructure is managed on-premises rather than in the cloud. This can lead to vulnerabilities and memory issues.
Even if the infrastructure is managed by a separate IT team, it is difficult for a growing business to manage the storage. Storage was viewed as a challenge by 54% of companies deploying containers on on-premises servers.
Moving to a public cloud environment and reducing reliance on local servers is the long-term solution to storage issues. Other alternatives to using temporary storage include:
This term refers to the volatile temporary storage attached to the instances during their lifetime, including data such as cache, session data, swap volume, buffers, etc.
Stateful applications, such as databases, can be linked to storage volumes. They can also be used after the individual container’s life has expired.
Persistent volume claims, storage, classes, and stateful sets can be used to solve storage and scaling issues.
Challenge #5 Scaling
Over time, every organization strives to broaden the scope of its operations. They will, however, be at a significant disadvantage if their infrastructure is not scale-ready. Even though Kubernetes microservices are complex and generate a large amount of data when deployed, diagnosing and fixing any problem can be difficult.
The density of applications and the dynamic nature of the computing environment exacerbate the problem for some businesses, such as:
- Managing multiple clouds, clusters, designated users, or policies can take time and effort.
- Installation and configuration are difficult.
- Variations in user experience based on the environment
Another scaling issue is that the Kubernetes infrastructure may conflict with other tools. Expansion is a difficult task when there are errors in the integration.
There are several approaches to scaling in Kubernetes. You can scale the horizontal pod autoscaler using the autoscaling or v2beta2 API versions, which allow you to specify multiple metrics.
Monitoring Solutions that Manage Kubernetes Complexities
To manage the complexities of Kubernetes observability, you must first understand what to look for in a monitoring solution. While several open-source Kubernetes monitoring solutions are available, you must create and install several individual components before you can meaningfully monitor the cluster.
Several traditional IT monitoring tool providers have also introduced Kubernetes monitoring solutions, but many of them need to be designed specifically for Kubernetes.
As a result, organizations must do more tuning and spend more time identifying problems, determining what is causing them, and determining how to fix them.
When comparing Kubernetes monitoring options, keep the following points in mind.
- Maintains a consistent user experience while automatically adjusting to changes.
- Provides ready-to-use tools made specifically for Kubernetes
- Knows which metrics are crucial to pay attention to while handling a lot of data
- Comprised of a unified monitoring platform with correlative data
Kubernetes has a lot to offer modern cloud-based applications, but enterprises must adopt a new monitoring strategy to fully profit from it. Traditional monitoring techniques are insufficient to understand cluster health and resource allocation because Kubernetes has new observability challenges. Understanding the challenges associated with Kubernetes monitoring will help you find a solution that will maximize the benefits of your Kubernetes implementation. Despite the complexity of Kubernetes monitoring, your solution should not be either.