Containers on AWS
Kubernetes Cost Allocation
nOps Kubernetes Cost Allocation & Optimization Solution delivers deep, comprehensive, real-time analysis and cost insights to maximize cost benefits with minimal interruption.

Lightweight Kubernetes Modules Provide Real-Time Analysis and Cost Insights
To understand the cost impact of your services in Kubernetes, we deploy our lightweight Kubernetes modules. Our lightweight agent can be easily deployed and maintained in your environment and forwards relevant details to our data platform for real-time analysis and cost insights. We correlate cluster metrics with cost, usage, pricing, and savings programs data to deliver the deepest and most comprehensive insights at the container, pod, node, and cluster levels.
Pod Insights
We collect and aggregate by labels or drill into specific pod replicas or containers to see how they contribute to cost or create waste. These insights allow the team to make decisions about profiling, load testing, and tuning based on impact. Both pod and node-level insights can be sorted by cost, RAM, or CPU utilization making it extremely simple to prioritize optimization based on opportunity and impact.


Cluster Node Insights
nOps also provides Cluster node insights so that we can make decisions about how to tune our instance type selections. We can quickly look at average node utilization over time and, again, prioritize our actions based on either cost impact or the largest rightsizing opportunities.
Pod Details & Recommendations
Now that we’re no longer flying blind on our EKS clusters, taking action becomes very easy. At nOps, we’ve started with conservative resource thresholds for our production environments — because we’ve got a constant stream of real-time tuning data, we can easily project the impact of new capabilities and ever-increasing load.
nOps pod recommendations give you the exact parameters to confidently tune your pod resource requests and limits.


Workload Configuration Insights & Recommendations
nOps also gives teams control over configuration insights and recommendations so that targeted recommendations can be tuned to meet the operational and business requirements of your workloads.
Through integration with both Jira and Gitlab, tuning goes on auto-pilot as we ticket, approve changesets, and rollout optimizations without interruption to our critical feature delivery timelines.
Pod Optimization
Keeping your pods tuned eliminates waste in your cluster by freeing up space for pods to scale on existing cluster nodes — and helps your team to exact immediate benefit with very low overhead.
Once your configuration house is in order, we can go further by limiting replicas based on the utilization patterns that nOps can give you at both the replica and container level. You can select any time window from the last 10 minutes to the last month, and investigate historical trends for ephemeral resources.


Node Details and Recommendations
By identifying the waste in cluster nodes, nOps makes it very easy is to understand the impact of node selection. Pod insights help organize pods by either compute or memory optimization. The node insights show where there are opportunities to rightsize nodes in a cluster.
Cluster Node RI Coverage
nOps rightsizing recommendations help to continuously optimize node instance type selection. This ensures that we are taking advantage of the latest in EC2 technologies and reducing waste in our environment.
For steadier state workloads, we increase our savings by taking advantage of nOps advanced reserved instance capacity capabilities. nOps not only recommends reserved instance purchases that map to our cluster nodes but also helps to see, graphically, how much coverage we have for the dominant instance types.
