As organizations scale their cloud usage on AWS, keeping tabs on daily spending—and reacting quickly to cost fluctuations—can be an ongoing challenge. Setting up a Cost and Usage Report (CUR), dissecting cost drivers, and implementing remedial steps often demand manual effort and specialized knowledge. DagKnows addresses this pain point head-on by offering an AI Agent and pre-built workflows that automate these tasks from end to end. Below are some key highlights from our AWS FinOps offering:
1. Deep-Dive into AWS EC2 Other and more of such notorious Cost Categories
The Challenge: AWS has hundreds of usage types (e.g., NatGateway-Bytes, DataTransfer-Regional-Bytes, CPUCredits:t3, etc.) that can contribute unexpected cost overhead. Attempting to parse them manually filter by filter in the AWS console is a time sink.
DagKnows’ Solution: We automatically map these cost categories into an at-a-glance visualization. For example, if you reduce the number of EKS cluster nodes, you might inadvertently increase Inter-AZ data transfer. Our tasks highlight all usage types for EC2 (or CloudWatch, or AWS Config) in a single view—so you can see if data transfer-regional or NAT Gateway data processed usage soared in ways you didn’t anticipate also helping with application structuring insights. Eg. Use affinity/anti-affinity rules or placement groups to deploy frequently communicating services within the same AZ, minimizing inter-AZ data transfer costs.
Here’s a snippet of EC2 Other usage categories from our analytics:
"USE2-NatGateway-Bytes": 237.9115381087,
"USE2-EBS:VolumeUsage.gp3": 469.1074017308,
"USE2-DataTransfer-Regional-Bytes": 678.1990997336,
...In real-world terms, this kind of breakdown can save large accounts thousands of dollars over time by shining a light on “stealth cost drains” that often slip under the radar.
We can do this analysis for any service—like EC2 Other, a “notorious” cost category in EC2 that lumps together everything from elastic IP charges, EBS volume/snapshots charges to cross-AZ data transfer. Similarly, AWS CloudWatch could see a surge of streaming logs or generating custom metrics inflates your bill. Come find all these answers, and more, simply by having a chat with DagKnows. [Schedule a demo]
2. Identifying Top 50 Cost Movers
The Challenge: Even after you know your cost breakdown, how do you spot the largest changes over a short window? Often, you want to see which resource ARNs specifically jumped 20% in cost from, say, three days ago to two days ago or last 2 days.
DagKnows’ Solution: A specialized “Top 50 Resource Movers” task focuses on resources that have changed the most in absolute dollars and in percentage. AWS Cost Explorer doesn’t directly provide a resource-level short-term deltas feature. By hooking into the CUR data we previously set up, we can highlight, for example, a single NAT Gateway or RDS instance whose daily cost soared and then drill down deeper into it.
For large teams, scanning 150–200 cost categories to find that one outlier is impractical. Our automation isolates it in seconds.
3. Optional Remediation for Cost Surges—Without Extra AWS Services
The Challenge: Even if you see a cost spike, action may require an automation runbook or custom AWS Lambda functions deployed as solutions. That means more time and potential overhead.
DagKnows’ Solution: We offer the ability to set up an optional remediation workflow. If a cost threshold is exceeded, you can automatically trigger a correction (e.g., shutting down or resizing an instance)—all within DagKnows. No separate AWS Config rules or paid Lambda deployments are needed. This saves management from the “context switching” trap, letting them handle investigation and resolution within one platform.
4. AI-Driven Insights: “Drill Down” with Natural Language
On top of these curated tasks, DagKnows features an agentic AI layer. Rather than manually building queries, you can ask:
“Drill down into the EC2 Other cost category and tell me the top usage types driving cost?”
In response, the system sorts the data, surfaces top line items, and can plot a chart. This level of guided analysis is a game changer, letting teams glean insights quickly in plain English—no advanced SQL or external BI tools required.
Conclusion
As FinOps maturity grows, the ability to see daily service-by-service changes, automatically set up cost usage pipelines, pinpoint outliers at the resource level, and take immediate action on cost anomalies can mean the difference between massive monthly overages and a well-managed AWS bill. DagKnows provides these workflows and more, allowing you to unify cost tracking, dynamic alerting, and optional remediation in one cohesive experience.
If your team struggles with manual AWS cost management or wants to see immediate ROI from a more robust FinOps practice, consider exploring DagKnows’ End-to-End Cost Tracking and Management offering. It’s designed to cut down the complexity, reduce wasted spending, and arm you with the timely insights needed to stay in control of cloud costs—without rummaging through a dozen AWS consoles every day.
Ready for a simpler FinOps experience? Reach out to us or explore our DagKnows documentation to learn more about building these workflows and unlocking AI-driven, single-click cost management for AWS.
