Deep Kubernetes Visibility for FinOps

Get a complete understanding of your Kubernetes application costs, drill into clusters and nodes to isolate Kubernetes pods that have been overprovisioned with memory or CPU, and rightsize their resources

Do you understand your Kubernetes application costs?

Kubernetes drives service agility and portability, but it also has one significant disadvantage: it is far more difficult to understand just how much each K8s-based application costs. Shared resources create challenges with cost allocation, cost visibility, and resource optimization.

Unlike non-containerized environments — where a solid mapping/tagging strategy allows you to estimate the costs for each application — Kubernetes enables multiple applications to run on each node, so traditional FinOps cost allocation no longer applies. As Kubernetes environments grow in complexity, costs quickly spiral if an effective optimization strategy isn’t in place.

Analyze your level of Kubernetes visibility

Gaining visibility into your container cost and usage data is the first step to controlling and optimizing Kubernetes costs.

When considering whether you have enough visibility to understand your application’s costs, ask yourself:

  1. Can you explain K8s costs and report on them accurately?
  2. Are your engineering teams accountable for the resources they provision?
  3. How do you allocate costs for shared and common K8s services?
  4. Can you report on the cost of individual containers on the clusters that your teams are operating?
  5. Can you calculate cost at the pod level? What about per pod label or namespace?
  6. For each dollar you invest in K8s, do you know how much revenue you generate?
  7. Is your team regularly reviewing policies and practices related to containerized cloud financial governance?
  8. Can you identify opportunities to optimize cloud resource utilization regularly?

Get deep Kubernetes visibility

No other cloud cost management platform provides granular insight into your Kubernetes deployments like Anodot. Track your spending and usage across clusters with detailed reports and dashboards. With Anodot’s powerful algorithms and multidimensional filters, you can analyze your performance in depth and identify underutilization at the node and pod level.

Anodot provides FinOps teams with comprehensive visibility, optimization, and forecasting capabilities in a single, focused tool that drives multicloud and K8s ROI. Avoid the shock of a high cloud bill, detect cost anomalies, and identify ways to further optimize your Kubernetes costs.

Allocate K8s costs accurately

Allocating Kubernetes costs isn’t an easy task. Most Kubernetes clusters are shared services with applications run by any number of teams. This means there’s no direct cost of a specific container. Additionally, FinOps teams must break down costs by compute, storage, data transfer, shared cluster costs, waste, and choose between request, limit or actual usage allocation models.

With Anodot, FinOps teams can accurately allocate K8s spend including shared cluster costs and waste; analyze their cost and usage by cost centers; and perform full allocation across K8s and traditional workloads.

Optimize your Kubernetes environment

Once you have comprehensive K8s visibility and can allocate your costs accurately, your next priority is to continuously look for ways to optimize your Kubernetes clusters, nodes and pods. Many parameters impact a node’s price including the operating system, processor vendor, processor architecture, instance generation, CPU and memory capacity and ratio, and the pricing model.

Anodot provides a shared source of cost visibility and cost optimization recommendations, making continuous improvement a scalable task for multi-stakeholder teams. With Anodot, FinOps teams can fine-tune Kubernetes resource allocation — allocating the correct amount of resources per cluster, namespace/label, node, pod, and container.