> For the complete documentation index, see [llms.txt](https://arpit-1.gitbook.io/cost-visibility/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://arpit-1.gitbook.io/cost-visibility/cost-visibilty/cost-breakdown.md). # cost breakdown While the **Overview** section gives you a quick summary of overall spending, the **Cost Breakdown** page lets you analyze deeper into where those costs come from. It helps you analyze costs within a selected category (**Clusters**, **Applications**, **Environments**, or **Projects**), for a specific time range. ![Figure 1: Cost Breakdown Overview](/files/25223876b2603db0836ace268a355bc335df2111) At the top of the **Cost Breakdown** page, you can apply filters in the top-right corner to adjust the view. Selecting the right filters helps you to focus on the most relevant cost information for your preferred analysis. For example, you might want to analyze your most recent infrastructure spend across production clusters. In that case, you can set the Cluster Scope filter to `Production` and select a Time Range of Last 30 Days. This will give you a focused view of active workloads and recent spending trends, without including cost from other clusters. {% hint style="success" %} #### Use Case Imagine your team is reviewing this month’s cloud spends and wants to focus only on production clusters. You open the Cost Breakdown page, set the **Cluster Scope** to `Production`, choose your preferred Currency, and adjust the Time Range to Last 30 Days. Instantly, the data updates to show just the relevant costs, providing you a clear picture of active environments and helps you spot any unusual spending patterns. With these quick filters, your team can focus on costs within the defined scope, ensuring the analysis stays relevant to your current objective. {% endhint %} | Filter | Description | | ----------------- | ------------------------------------------------------------------------------------------------------------------------------------------------- | | **Cluster Scope** | Choose whether to view costs across all clusters or environments, or limit the view to only production or non-production clusters or environments | | **Currency** | Displays all cost values in the currency of your choice. | | **Time Range** | Defines the time range for data displayed | ## Inspecting Different Categories For the chosen category type (**Clusters**, **Applications**, **Environments**, or **Projects**), the page shows the following: For example, if you select the Cluster category, you can view the total cost across all clusters, the recommended cost based on actual usage, and the potential savings if resources were optimized. This gives you a quick, high-level view of how efficiently each cluster is utilizing its allocated resources. {% hint style="success" %} #### Use Case Imagine your team is analyzing monthly infrastructure expenses for multiple clusters. You notice that the **Total Cost** for one cluster is significantly higher than the others. When you check the **Recommended Cost**, it’s much lower, showing that this cluster is over-provisioned. The Potential Savings metric confirms this, showing how much of your current spend could be reduced by aligning resource allocation with actual usage. With this insight, your team adjusts resource requests to improve overall cost efficiency without impacting performance. By the next billing cycle, costs come down, while the performance remains stable. {% endhint %} | Field | Description | | --------------------------- | ------------------------------------------------------------------------------------------------ | | **Total Cost** | The actual spend for the selected category type (e.g., all clusters). | | **Recommended Cost** | The estimated cost calculated from actual resource usage instead of allocated capacity | | **Potential Savings** | The percentage of your current spend that could be reduced | | **Monthly Savings** | The estimated savings for one month based on the difference between allocated and used resources | | **Annual Savings** | The projected savings over a year based on the same calculation | | **Top 10 Costly Resources** | A ranked list of 10 highest cost resources of the selected category | You will also find a complete list of all the resources for the selected category at the bottom, helping you identify where most of your spending is concentrated. For example, if you’re viewing the Environment category, the list displays each environment along with its CPU, Memory, Storage, GPU, and Network costs. You can quickly compare environments and identify which ones have higher spend or greater potential savings. {% hint style="success" %} #### Use Case Suppose you’re reviewing costs within the **Environment** category. As you go through the list, you notice one environment's **Total Cost** is higher than others. You look across its row and notice that both **CPU Cost** and **Memory Cost** are also on the higher side. The Potential Savings column then shows a clear opportunity to optimize usage within that environment. With this focused view, you get a clearer understanding of where your resources are being used most and which environments might need attention, all from a single, organized view. You can then check the detailed view for those environments to investigate further. {% endhint %} Each row in the list shows the following for the specific resource of the selected category: | Field | Available For Categories | Description | | ---------------------- | ------------------------ | ---------------------------------------------------------------------------------------------- | | **Provider** | Clusters | Shows the cloud provider or infrastructure source for each cluster | | **Type** | Clusters, Environments | Shows whether each cluster or environment is **Production** or **Non-Production** | | **Applications Count** | Environments, Projects | Shows the number of applications linked to each environment or project | | **Environments** | Applications | Shows the number of environments where each application is deployed | | **Memory Cost** | All categories | Shows the cost of memory usage for each resource in the selected category | | **CPU Cost** | All categories | Shows the cost of CPU usage for each resource in the selected category | | **Storage (PV) Cost** | All categories | Shows the cost of persistent volume (storage) usage for each resource in the selected category | | **GPU Cost** | All categories | Shows the cost of GPU usage for each resource in the selected category | | **Network Cost** | All categories | Shows the cost of network usage for each resource in the selected category | | **Total Cost** | All categories | Shows the total cost of each resource | | **Potential Savings** | All categories | Shows the cost and percentage of your current spend that could be saved for each resource | {% embed url="" %} ### Inspecting Specific Resource Clicking on any resource in the Cost Breakdown list opens its detailed cost breakdown view. Based on the category you will see the following: For example, after identifying a high-cost Environment in the previous section, you can click on that environment to open its detailed breakdown. In the detailed breakdown view of the environment, you can see which Applications contribute most to its total cost, and how resource types (like CPU, Memory, and Storage) are distributed. {% hint style="success" %} #### Use Case Continuing from the earlier scenario, you open the detailed cost breakdown for the environment that showed unusually high costs. In the **Top 10 Costly Applications** section, one application clearly dominates the cost chart. You then look at the **Cost Breakdown by Resource Kind** graph, where it becomes clear that most of this cost comes from Memory usage. Investigating further, you confirm that a recent update introduced higher memory requests for that application. This explains the cost spike you noticed earlier. With this insight, your team can review and right-size resource allocations to keep the environment’s cost under control while maintaining stable performance. {% endhint %} | Field | Available For Categories | Description | | ----------------------------------- | ---------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Total Cost** | All categories | Shows the overall cost for the selected resource, along with a cost trend graph for the chosen time range | | **CPU** | All categories | Shows the total spend on CPU resources, along with the potential savings | | **Memory** | All categories | Shows the total cost for memory resources, along with the potential savings | | **Storage** | All categories | Shows the total cost for persistent volume (storage), along with potential savings | | **GPU** | All categories | Shows the total cost for GPU resources, along with potential savings | | **Top 10 costly namespace** | Cluster | A ranked list of 10 highest cost namespaces within a specific cluster | | **Top 10 costly application** | Environments & Projects | A ranked list of 10 highest cost applications within a specific environment or project | | **Top 10 costly deployment** | Applications | A ranked list of 10 highest cost deployments within a specific application | | **Cost Breakdown by Namespace** | Clusters | Shows the distribution of costs across namespaces within the selected cluster. Each bar represents a namespace, segmented by CPU, Memory, GPU, Storage, and Network costs. Helps identify which namespaces are responsible for most cost inside a cluster | | **Cost Breakdown by Application** | Clusters, Projects, & Environments | Shows the cost distribution across applications in the selected category. Each bar represents an application, segmented by CPU, Memory, GPU, Storage, and Network costs | | **Cost Breakdown by Resource kind** | All categories | Shows the costs broken down by Kubernetes resource types (e.g., Pod, Deployment, StatefulSet, Job, DaemonSet, Rollout, Container). Each bar represents a resource kind, segmented by CPU, Memory, GPU, Storage, and Network costs | | **Cost Breakdown by Deployment** | Applications | Shows the distribution of costs across deployments within the selected application. Each bar represents a deployment, segmented by CPU, Memory, GPU, Storage, and Network costs | {% embed url="" %} ### Custom Views **Custom Views** allows you to define your own filtered view of cluster costs. Instead of looking at costs for the entire cluster, you can create a focused view based on propagated tags (for example, filter by team, environment, or application tag). For example, if your production workloads are labeled with `environment=production`, you can create a custom view to track cost of production workloads only. By creating a custom view with: **Key**: `environment`\ **Operator** : `:`\ **Value** : `production` This helps you quickly analyze how much your production workloads are costing without manually filtering every time. As long as your workloads have the right labels, Devtron automatically groups and updates the data in your custom view, giving you a consistent and focused view of your use case. {% hint style="success" %} #### Use Case Imagine your organization runs workloads for multiple teams — frontend, backend, and logistics — all within the same cluster. Each team’s workloads have propagated tags (labels) (for example, workloads of the logistics team have `team=logistics` propagated tag). Your team often needs to check the monthly cloud spend for the logistics workloads. Instead of applying filters every time, you create a custom view once using that label. Now, whenever you open Cost Visibility, you simply select the “Logistics Team View” from the sidebar to instantly see total cost, usage patterns, and potential savings specific to that team. Because the workloads are already labeled, the data stays accurate and your analysis remains consistent, saving time and effort each time you review costs. {% endhint %} This feature is available only under the Clusters category. **Note:** Custom Views are dependent on propagated tags (labels). If tags are not mentioned and propagated in the workloads, some resources may not appear in the view. Ensure that you have added and propagated tags for the workloads you want to include in the custom view. #### Creating a Custom View {% stepper %} {% step %} ### Go to Cost Breakdown (Cluster) Go to **Cost Visibility** → **Cost Breakdown** → **Cluster**. {% endstep %} {% step %} ### Add Custom View In the sidebar, click the `+` icon next to **Custom Views**. {% endstep %} {% step %} ### Enter Details Enter a **Name** and an optional **Description** for your view. {% endstep %} {% step %} ### Define Filters Enter one or more label-based filters using **Key**, **Operator**, and **Value**. {% endstep %} {% step %} ### Apply Click Apply Changes. Once applied, a Custom View works just like any other category breakdown in Cost Visibility. {% endstep %} {% endstepper %} ### Filters | **Field** | **Description** | | ------------ | -------------------------------------------------------------------------------- | | **Key** | The label key applied to your Kubernetes resources (for example, `app`, `team`). | | **Operator** | Defines the comparison logic between the key and value. | | **Value** | The label value to match against (for example, `logistics`, `prod`). | ### Operators | **Operator** | **Meaning** | **Example** | | ------------ | ------------------- | -------------------------------------------------------------------------- | | `:` | Equals to | `app : frontend` → selects resources where `app=frontend`. | | `!:` | Not Equals To | `team !: dev` → excludes resources with `team=dev`. | | `~:` | Contains | `name ~: api` → selects resources where label contains `api`. | | `!~` | Not Contains | `app !~: test` → excludes resources where label contains `test`. | | `<~` | Contains Prefix | `env <~: prod` → selects resources where label starts with `prod`. | | `!<~` | Not Contains Prefix | `env !<~: staging` → excludes resources where label starts with `staging`. |