The benefits of using Kubecost on Kuberenetes

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Kubecost provides comprehensive cost analysis on Digital Ocean Managed Kubernetes clusters. This tool is designed to help optimize your Kubernetes cluster and ensure valuable resources are not wasted.

In this guide, we’ll review some of the benefits of using Kubecost on Digital Ocean Managed Kubernetes clusters, and provide some tips on getting started.

What is Kubecost?

Kubecost is an open-source cost analytics solution for monitoring and optimizing the cost of cloud deployments on Kubernetes. The product helps users understand the linked cost of different aspects of their Kubernetes infrastructure across multiple cloud providers and the underlying data center environment. Kubecost also enables users to drill down into more detailed information, providing a way to experiment with infrastructure and application optimization, quickly identify unnecessary spending, and monitor usage patterns over time.

The benefits of using Kubecost include:

  • Cost control: The ability to control and optimize cloud spend over time.
  • Actionable metrics: Distributing granular Kubernetes spending data across all your cloud providers gives you insight into your current spend and enables you to allocate resources accordingly.
  • Comparative analysis: Through insights into your AWS vs GCP or Azure spends, you can make informed decisions when adding new services or optimizing existing ones, ensuring that your resources are used optimally.
  • Cost visualization & trends tracking: A thorough overview of your cloud spends gleaned from charts that allow for easy comparison of past versus present usage and cost fluctuations.

What is Digital Ocean Managed Kubernetes?

Digital Ocean Managed Kubernetes (also known as Digital Ocean Kubernetes or DOKS) is a fully-managed Kubernetes service that enables developers to easily launch and orchestrate containers on DigitalOcean’s cloud platform.

With DOKS, users can access powerful clusters optimized for running containerized applications in production environments. In addition, with a managed service like DOKS, users don’t need to worry about the complexities associated with operating and maintaining cluster infrastructure or managing clustered applications.

The DOKS offering also lets users take advantage of features like seamless scaling capabilities, comprehensive monitoring, plus automated backup and recovery services so teams can focus on building instead of worrying about uptime. Leveraging these capabilities helps speed development and quickly move projects through the pipeline. Additionally, integrated cost management tools offer insight into usage permitting spending optimization efforts resulting in substantial cost savings over time.

Thanks to its intuitive user interface, fine-grained authorization controls, and rolling updates, any team can confidently manage their Kubernetes cluster.

Benefits of Kubecost

Kubecost is a great tool to help you optimize and manage your Kubernetes clusters. It tracks usage of your Kubernetes clusters, gives you detailed insights into your cluster, and alerts you when usage is trending too high.

This section will explore the benefits of using Kubecost on Kubernetes, from cost saving to better visibility.

Increased visibility into Kubernetes resource usage

Kubecost provides its users with increased visibility into Kubernetes resource usage, enabling them to efficiently manage workloads and identify opportunities for optimization. Using Kubecost, teams can easily track their utilization of various K8s resources including CPU, memory, network, and storage at the pod level. This ensures teams can make data-driven decisions to keep their infrastructures running smoothly.

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Additionally, Kubecost’s interactive interface allows users to quickly pinpoint where resources are being wasted and uncover hidden system inefficiencies that could be causing higher than expected costs or performance degradation. With high-level cost forecasting and monitoring capabilities, Kubecost provides its users with the essential tools to optimize their budgets on Kubernetes infrastructure.

Cost savings from optimizing resource usage

Kubecost provides detailed cost breakdowns and cost analytics for Kubernetes deployments, enabling organizations to see all their expenses associated with running their applications in Kubernetes. Kubecost helps identify underutilized resources, resulting in reduced cloud costs and a more efficient use of resources. The intuitive dashboard makes it easy to visualize where costs are incurred allowing you to quickly identify opportunities for cost savings.

Kubecost also provides detailed insights on how resources are used over time, historical trends, daily estimated cloud spend amounts, and predictions for future expenditure levels so that users can make informed decisions when optimizing resource usage. Additionally, Kubecost can recommend reducing Kubernetes-specific operational costs with strategies such as auto scaling and cluster management optimizations.

With the help of the Kubecost platform, organizations can find the right balance between price and performance while creating more predictable operations and reducing business risk associated with unplanned infrastructure cost increases.

Ability to customize cost models

Kubecost allows users to customize cost models for their Kubernetes infrastructure. This allows users to more accurately identify where costs are coming from and make appropriate programmatic or manual adjustments. Additionally, this allows users to better understand the various resource usages across their environments so they can take proactive steps to optimize spending.

Kubecost also provides users with an amazing assortment of filters, offering convenient granularity when it comes to refining cost models with specific criteria. In addition, it offers multiple visualization approaches such as node-by-node analysis and workload versus resource ratio that help users confidently make informed decisions. Not only that, but these capabilities are factored into API calls, for resources to be dynamic and user friendly.

In the modern era of cloud infrastructure used within Kuberenetes infrastructures, Kubecost offers a comprehensive array of features that go above and beyond traditional tools offered for cost optimization and analytics within any cloud environment – empowering its users to gain more insight on consumption patterns within their respective environments as well as providing suggestions on further savings opportunities.

Getting Started with Kubecost on Digital Ocean Managed Kuberenetes

Kubecost is a tool that allows users to optimize their cloud costs and usage on Digital Ocean Managed Kuberenetes. With Kubecost, you can get complete visibility into your Kubernetes resources and track how much each resource consumes.

Let’s explore how to start with Kubecost on Digital Ocean Managed Kuberenetes.

Setting up the Kubecost Operator

To set up the Kubecost Operator on Digital Ocean’s Managed Kubernetes service, the following steps must be taken:

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1. Log into your DigitalOcean account and create a Kubernetes cluster. Make sure you select the ‘Kubernetes with clusters’ plan when creating the cluster so that Kubecost is included in the deployment.

2. Install the Kubecost Operator to provision and deploy Kubecost as part of your DigitalOcean Managed Kubernetes service. You can do this by running the following command in your terminal: `kubectl apply -f`

3. After installation, your Kubecost installation page appears within 30 seconds, prompting you to configure some basic settings related to cost acquisition and analysis tools such as Prometheus exporter.

  • i) Enter a project name that represents your main Kubernetes deployment
  • ii) Specify an idx (short for index) which indicates what type of environment you’re running within DigitalOcean
  • iii) Enter any additional digital metrics integration keys needed for data collection, such as GCE or AWS IAM keys
  • iv) Add additional resources or customized flags required for specific workloads upon request
  • v) Provide a URL endpoint of where pricing information will be collected from
  • vi) Configure any alert preferences

4. Once configured, save your settings and execute the deploy command by running `kubectl apply -f kubecost-installYAML`. You can find more detailed instructions on how to configure various options at

Configuring Kubecost on Digital Ocean Managed Kubernetes

Kubecost is a platform for cost optimization, visualization, and budgetary control of Kubernetes clusters. It provides:

  • Real-time visibility into resource utilization.
  • Cost baseline control.
  • Predictive insights to help you optimize your cloud costs.

Configuring Kubecost on Digital Ocean Managed Kubernetes (DOMK) is straightforward and can be done in the following steps:

1. Access the Kubernetes page of Digital Ocean by navigating to Manage > Clusters on the top panel. By clicking on your cluster name in the list, you’ll be shown information about your Kubernetes cluster. In this page, copy API token from “Access token” section as we need it in next steps.

2. Install Kubecost CLI with command below:

“curl -sL | bash”

3. After installing Kubecost CLI ,Login with command below :

“kubectl kubecost login –nkube-system –context $(kubectl config current-context)”

Replace YourDigitalOceanAPIToken with Access Token which you had copied previously in Step 1

4. To view(check) all relevant metrics of your clusters like resource usage, try using ‘promql’ flag of kubectl command as follows :

“kubectl kubecost promql ‘sum(container_cpu_usage_seconds_total{clusterName = “”})”

where should be replaced by actual Cluster Name which you can find out by going to Manage > Clusters page under top panel of Dashboard page . or use one from the search bar (on top right of dashboard ) once you have searched for your cluster name.

You can generate rich metrics out of these which will further help you optimize and monitor cost through Kubecost.

Accessing Kubecost on Digital Ocean Managed Kubernetes

Getting started with Kubecost on Digital Ocean Managed Kubernetes is straightforward. To access the Kubecost user interface, you must create a Kubernetes Service Account and configure credentials on your DigitalOcean account.

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First, ensure your DigitalOcean account is linked with an existing Kubernetes cluster running version 1.17 or later. Then, select a service account in the service accounts page of your DigitalOcean Managed Kubernetes cluster settings.

Next, add roles to grant permissions to the newly created service account:

  • Storage admin role allows users to view and add storage classes;
  • cluster-admin role lets users access all components of a cluster;
  • view role grants read-only access to objects;
  • edit role grants permission for systems to write data within a given namespace;
  • prometheus prometheus/unified operator can be used if they would like to use open source Prometheus or Grafana as their visualization provider;
  • node exporter allows users to export related node metrics like CPU/RAM consumption.

Finally, after granting appropriate roles and permissions, scroll down in the settings page until you see “Kubecost Service Accounts” section which will give you a Kubecost URL link that you can use with your browser and begin using Kubecost with your managed cluster.


Kubecost is a powerful tool for managing cost and utilization for Kuberbetes clusters. It can provide visibility into areas of high cost, underutilized resources, poor deployment practices, etc. Implementing Kubecost allows for optimizing time and money spent on Kubernetes at the source or cloud level, making projects more efficient and cost-effective.

Overall, Kubecost provides insight into the financial aspects of running Kubernetes clusters and operations. It also supports enterprise goals such as optimizing spend across multiple clouds while ensuring optimal performance, security and reliability. In addition, by leveraging Kubecost’s advanced metric analysis capabilities, organizations can gain greater transparency into their clusters to identify potential issues earlier in the process and make well-informed decisions when allocating resources. This information can then be used to optimize resource allocation while reducing total spend on Kubernetes infrastructure.