The official web-based UI for Kubernetes is known as the Kubernetes dashboard. The Kubernetes dashboard displays information about the Kubernetes cluster and the individual resources that are operating inside it.
As such, it is a crucial piece of the Kubernetes puzzle since it allows DevOps and Kubernetes administrators to observe and control the monitoring and operational elements of their Kubernetes clusters.
The dashboard provides the following features, which is pretty much exhaustive:
- A high-level overview of the Kubernetes cluster
- Install apps on your Kubernetes clusters
- Get an overview of the apps that are now executing
- Investigate those applications
- Get an overview of the resources that are active in the cluster
- Kubernetes resources can be created, modified, updated, and deleted
- Information about the current condition of the Kubernetes resources in the cluster
- Basic resource measurements, such as resource use for particular Kubernetes objects
There was a time when the Kubernetes Dashboard was the only thing available. This dashboard is the default choice for anyone who wishes to monitor a Kubernetes cluster, although there have been several alternatives built over the years that are worth investigating.
Kubernetes is obviously not for everyone. For one, unless you want to develop a complex solution for a large audience, then there’s no point using Kubernetes.
If you want to develop a simple website, you will find it more reasonable to use other alternatives as Kubernetes is known to be complex and capable of reducing productivity.
We’ll look at some of the alternative Kubernetes dashboards in this article.
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Best Kubernetes Dashboard Alternatives
- 1. k8dash
- 2. Konstellate
- 3. Kubernator
- 4. Kubricks
- 5. Octant AI
- 6. Weave Scope
- 7. Kubernetes Operational View
- 8. Kubernetes Resource Report
- 9. Kubevious
- 10. Rancher
So you’ve established your first k8dash cluster. Congratulations! Now, how do you use the device? Deployments, replica sets, stateful sets, pods, and ingress.
Getting Kubernetes up and running might feel like a daunting task in and of itself, but does day two of operations have to be just as difficult? Kubernetes is a fantastic yet complicated system. The learning curve can be challenging.
Furthermore, the basic Kubernetes dashboard has limited functionality. An alternative to the Kubernetes dashboard is k8dash, which is highly powerful but only suitable for advanced users. Can you expect everyone in your business to become k8dash wizards if you become one?
Since its release in March 2019, k8dash has gotten over 625 GitHub stars and downloaded over 1 million times on DockerHub. For many businesses, k8dash is an essential component of Kubernetes operations.
The Indeed Engineering group approved the k8dash project in May of 2020. We’re pleased about the increased visibility this will bring to the project.
The k8dash project’s central premise is low operational complexity. As a result, k8dash may be installed fast with a few hundred lines of YAML. K8dash only runs one service. There is no need for databases or caches. This includes AuthN/AuthZ through OIDC.
If you’re already using OIDC to protect your cluster, k8dash makes it simple to extend this to your dashboards: just specify a few environment variables, and you’re good to go. There is no need for any additional authentication proxies or other complex setups.
Cluster visualization and management
K8dash allows you to see the current state of all of your cluster’s moving pieces, including namespaces, nodes, pods, and deployments.
Real-time charts reveal underperforming resources. The user-friendly interface eliminates most of the behind-the-scenes complications and aids in flattening your Kubernetes learning curve.
You may manage your cluster elements from the dashboard and change resources using k8dash’s YAML editor.
K8dash takes advantage of the Kubernetes API and offers context-aware API documentation. With k8dash, you can see pod logs and even SSH straight into a running pod through a terminal right in your browser.
K8dash also interacts with Metrics Server, allowing you to see CPU/RAM use in real-time. This visualization assists you in understanding how effectively your services are performing.
Kubernetes promises greater resource efficiency through bin packing as it lowers the complexity of running hundreds or even thousands of microservices over an abstract compute pool.
Nevertheless, most businesses fail to achieve this promise because it is difficult to determine whether services are over-provisioned. The simple UI of k8dash removes the guesswork from determining how well services are supplied.
You don’t need to refresh websites to monitor the current condition of your cluster because k8dash is a real-time dashboard. Instead, you can see charts, graphs, and tables alter in real-time when you roll out a deployment.
You may monitor the addition and removal of nodes in your cluster and be notified when new nodes become fully operational.
Alternatively, just watch a stream of Kubernetes cluster-wide events as they occur.
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This is a user interface for creating, editing, and managing the relationship of Kubernetes resources. Complex YAML may be simply created and exported as Kustomize templates or Helm charts.
You may use the editor to import the YAML you already have or to build resources from one of the templates. Once you’ve established some resources, you may easily link them by dragging a line between them.
Konstellate can search for any possible connections and present you with a list of alternatives. After you’ve created your application, you may clone it in a new workspace and modify it there.
- Warn users if no connection types are available
- Implement Export YAML
- Implement Import Helm + Kustomize
- Update Add/Remove buttons on the editor
- Auto-populate required fields in resource templates
- Add tree view into YAML spec
- Packaging as electron/docker image + local file system sync
- Tie Konstellate into running clusters + kubectl plugin
- Enable GitOps flow
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Kubernator displays all items in your cluster, including custom resource definitions, in a simple, code-focused UI (CRDs). They are categorized according to namespace and object type.
You may change the YAML code, remove the object, and create a new one in the editing area. As seen in the screenshot, the editor is ready to offer suggestions, show modifications, and provide many more capabilities to please any administrator.
It also provides an RBAC viewer, which displays a schema of all roles and bindings: One limitation of Kubernator is that it is a client-side-only application.
It communicates directly with the Kubernetes API. This implies that you can only utilize it by running a kubectl proxy; there is no way to use an ingress.
You can address this on the Helm chart by adding a container with kubectl to the pod and some ingress rules to route the API queries to that container.
The navigation tree displays the types of items, which are organized by namespaces and the objects themselves.
All API groups are retrieved, resulting in a list of versions and endpoints for each group. Then, Kubernator loads a list of resources for all groups and performances, followed by a list of objects for each known resource. Namespaces groups objects to display the tree.
Kubernator makes many API calls; thus, it actively caches their replies in the browser’s local storage to improve loading speeds in subsequent usage, e.g., API groups and Swagger schemas are only refreshed when the cluster is updated.
When the relevant type or namespace is opened, the resources are restored.
Multiple API Versions
Every group retrieves its resources using all API versions, not just the preferred one, and then combines the resources into a single list based on the priority of the versions.
This means that we may access objects using multiple API versions. Furthermore, when a new object is created, an API endpoint is automatically selected depending on the value of the apiVersion field in its description.
The names of tabs reflect the position of the current object in the navigation tree (object. namespace object. kind object).
The tab color for new items is green, whereas the tab color for changed and unsubmitted objects is red. Local changes are preserved even if the tab is closed and reopened.
All extra and read-only fields are automatically removed when an object is cloned, as defined in the associated Swagger scheme.
Available actions include: opening a new tab and copying the current item; closing all tabs; reloading, saving, or deleting the current object; and switching the currently active tab to the left/right neighbor.
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Kubricks is an Electron app that provides developers with simple graphs of current cluster deployment. It enables the user to visualize cluster resources and their interconnections and render resources to indicate problems conditionally.
Furthermore, a few requirements must be satisfied to use the Kubricks app effectively. You should have a Kubernetes cluster deployed and a kubectl context configured (i.e., GKE, Minikube)
Cluster View is similar to how Kublet interacts with resources housed on individual nodes. This view’s primary purpose is to display pods that are hosted on a specific node. Persistent volumes that are configured as part of a pod are also displayed.
Traffic View mimics how Kube-proxy routes incoming requests to different pods via services. This view renders services using specified pods and highlights port mapping issues.
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Octant AI is a game-changing solution to project cost forecasting that combines the power of AI with a tried-and-true economic model.
What exactly is Octant AI Predict? Octant AI Predict is a proprietary artificial intelligence software solution developed by Endeavour Programme to optimize project results.
Octant AI Predict learns prior project performance from historical data and tailor-made machine learning algorithms to produce more accurate, impartial, and timely forecasts for project management choices.
It delivers dynamic cost and time predictions from project inception through project completion, aligning with the standard project review procedure.
Visualize relationships between components in a Kubernetes cluster graphically. To demonstrate workload performance, the state of each object is indicated by color.
It consolidated status and configuration information in a single page derived from the output of various kubectl commands.
For debugging applications, send a local port to a running pod with a single button and port forward numerous pods across namespaces.
View log streams of pod and container activities for troubleshooting and monitoring without having to open numerous terminals.
Workloads may be organized using label filtering for inspecting clusters with many items in a namespace.
Easily switch between namespaces or contexts across clusters. Multiple kubeconfig files can also be used.
Users can utilize a highly flexible plugin system to offer extra functionality through gRPC. Authors of plugins can add components on top of existing views.
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Weave Scope is a Docker and Kubernetes visualization and monitoring solution. Weave scope would be beneficial in analyzing network bottlenecks, debugging CPU use, and resolving memory leaks in microservices-based architecture.
It gives a top-down view of your program and your complete infrastructure, allowing you to detect any problems with your distributed containerized software as it is deployed to a cloud provider in real-time.
Weave Scope is made up of two parts: the app and the probe. The probe’s goal is to determine information about the host on which it is executing. This data is delivered to the app in the form of a report. The software converts probe reports into several visuals (ex. Topologies).
Drill down Views
Scope displays Pods, Replica Sets, Deployments, and associated Services on clusters for a Kubernetes-running program. You can see Processes, Containers, Orchestrators, and Hosts for containerized microservices operating in the cloud.
Real-time Contextual metrics
When you click on a node, you will be sent to a comprehensive panel with other stats about that node. You may dig down from the detailed discussion on processes inside your container to the hosts that your containers operate on.
Troubleshoot / Manage Containers
When you click on a container, pod, or host, the controls pane appears, from which you may pause, restart, stop, and remove without leaving the Scope browser window.
If more debugging is necessary, terminal windows may be created from any container or host, allowing you to interact with your app and run any UNIX command to identify problems.
Weave offers simple operands, allowing you to discover processes that are using a specific amount of memory or nodes that are using an excessive amount of CPU.
Nodes may be filtered by CPU and memory consumption to discover containers consuming the most excellent resources quickly.
If you’re running an app in Kubernetes, you may filter it by namespace and container state, which might be running, paused, contained, or uncontained.
Graphic / Table Mode
Views can be shown in both graphic and table modes. Graphical mode is more beneficial when you need a fast visual overview of your software.
Table mode displays data like the resources utilized by processes, containers, and hosts, among other things.
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The goal of a typical Kubernetes Operational View is straightforward: it offers a unified operational view for many clusters.
If you like, you may also use it for a single cluster. Installation is clear; you may run it in a Docker container and connect using a kubectl proxy, or you can run it within your Kubernetes cluster.
You may use the latter for my test scenario and install it using the official stable helm chart if you want.
CLUSTERS is the primary variable you may want to change. This allows you to define a list of Kubernetes API server URLs separated by commas. Use this to populate the dashboard display with numerous clusters that you have access to.
Keep in mind that the tool only requires read-only access to the cluster if you install it manually.
There are several open-source logging programs available. To gather and analyze logs from our containers, we used Graylog, an outstanding logging tool, and Apache Kafka, a messaging system. The containers transmit logs to Kafka, which then forwards them to Graylog for indexing.
When there is a mistake, Kubernetes performs an outstanding job of recovering. Kubernetes will restart pods if they crash for any reason. End users are unlikely to detect an issue when Kubernetes is replicated.
Kubernetes recovery works so effectively that we’ve seen instances when our containers crashed many times a day due to a memory leak, with no one (including us) knowing.
Datastores and Kubernetes
When operating a data store like MongoDB or MySQL, you almost certainly want the data to remain durable. Containers lose data when they restart by default.
This is acceptable for stateless components, but it is not appropriate for a persistent data store. To cope with continuous data, Kubernetes includes the idea of volumes.
In the majority of installations, the data storage is also duplicated. Mongo generally operates in a Replica Set, whereas MySQL may be in primary/replica mode.
This raises a few issues. First and foremost, each node in the data store’s cluster must be backed by a separate volume. Attempting to write to the same disk will result in data corruption.
When it comes to expenses, there are two sides to the story. An etcd cluster, as well as a master node, are necessary to operate Kubernetes. While these are not inherently expensive components to run, the overhead can be significant in minimal installations.
It’s usually preferable to utilize a hosted solution for these sorts of deployments, such as Google’s Container Service.
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Kubernetes Resource Report is software that manages, grows, and maintains multi-container workloads in desired states automatically.
Modern software is increasingly being deployed as fleets of containers, often known as microservices. A complete application may consist of several containers, each of which must interact in specific ways.
The Kubernetes Resource Report displays the monetary amount of possible savings, for example, “You may potentially save 321.99 USD every month by optimizing resource demands and minimizing slack.”
The potential savings are determined by multiplying the cluster costs (the total of all node costs plus any additional configured expenses) by the applicable share per application/team by the number of resource requests.
The use of resources is another significant measure of how well your Kubernetes environment is optimized. Ideally, operations teams would like to maximize the percentage of resources utilized by pods as a fraction of total resources available on the cluster.
The cluster autoscaler is a free and open-source utility for resizing individual clusters depending on resource requirements and use. When a pod fails to operate on a cluster owing to resource constraints, the cluster autoscaler adds nodes to that cluster. It can also eliminate underused nodes.
Horizontal pod autoscaling
This is a Kubernetes feature that automatically uses resource utilization data to add or delete pod replicas from Kubernetes replication controllers.
Replica sets, deployments, and replication controllers are examples of these. HPA scales are based on Kubernetes metrics such as CPU and user-specified metrics.
Vertical pod autoscaling
Vertical pod autoscaling was also recently implemented by Kubernetes (VPA). The vertical pod autoscaler (currently in beta) serves two purposes: it automates reserving pod resources and improving cluster resource usage.
Kubevious is open-source software that offers a graphical interface for Kubernetes. Kubevious consolidates all settings essential to the application into a single location.
This saves operators a lot of time by removing the need to search up settings and delve through selectors and labels. Kubevious is compatible with all Kubernetes distributions.
Kubevious is a project management tool that may be utilized at any stage of the project.
Detect Configuration Errors
Kubernetes adheres to a decoupled idea of configuration. When connecting components, mistakes and errors are all too common.
Kubevious detects a wide range of setup problems, much more like missing ports, label misapplication, etc. The red circle shows the number of mistakes within the subtree.
Kubevious includes the ability to assist organizations requiring additional rules and built-in checks (such as label mismatch, missing port, misused or overused objects, etc.).
It accomplishes this by allowing Kubernetes operators to set their own rules and enabling businesses to implement DevOps best practices without modifying their existing release procedures.
Identify Blast Radius
Kubernetes configuration is highly reusable. A minor modification can have unintended consequences.
Kubevious detects standard settings and presents additional items that are dependent on them. A single glance is all that is required to recognize the ripple effects of a given modification.
Optimize Resource Usage
Determine how many resources are consumed by each container, pod, deployment, daemonset, namespace, and so on.
Kubevious generates absolute resource request figures and relative use per node, namespace, and cluster as a whole. Determine which apps consume the most resources inside the namespace.
Rancher is an intuitive interface that offers a single point of contact for all clusters and centralized policy controls and monitoring.
With the press of a button, end users may quickly deploy new clusters. Furthermore, the platform provides users with several advantages such as easy setup of networking and storage drivers, repeatable deployments of bespoke environments, etc.
Again, maintaining and deploying apps is simple—the public catalog contains over 90 popular Docker applications, and Helm is integrated by default.
Rancher has quickly become the platform of choice for running containers in production, with over 60 million downloads and enterprise-class support.
- Included Kubernetes Distribution
- Monitoring and Logging
- Connect Containers
- Included Mesos Distribution
- Infrastructure Management
- Docker App Catalog
- Manage Disks
- Deploy Load Balancers
- Included Docker Swarm Distribution
An incredible number of alternatives are available to assist Kubernetes developers and operators in navigating this new paradigm of container orchestration.
You should consider them in three categories: do they run as Kubernetes, do they test as well as Kubernetes, and do the code in a Kubernetes-aware manner?
All three of these categories can lead you to well-maintained open-source software that will help you become a better YAML herder, just like everyone else.
K8dash checks these three categories and that is why it is our top Kubernetes Dashboard alternative this year.
Tom loves to write on technology, e-commerce & internet marketing.
Tom has been a full-time internet marketer for two decades now, earning millions of dollars while living life on his own terms. Along the way, he’s also coached thousands of other people to success.