The promise of cloud elasticity often collides with the reality of escalating bills. While native cloud tools offer a foundational layer of visibility, many SMBs and scale-ups quickly discover that for comprehensive FinOps, native cloud tools not enough FinOps capabilities are available. According to the Flexera 2026 State of the Cloud Report, 85% of enterprises still cite cloud spend management as their #1 challenge, even with increasing tool maturity. This isn’t just about cost; it’s about delivering business value, a priority for 64% of respondents in the same report.
You’ve seen this. A development team spins up a new environment. It works. The ticket closes. But a month later, an unnoticed resource continues to bill, a silent drain. We regularly audit accounts where a ‘temporary’ environment became a permanent fixture, costing thousands. That’s the insidious nature of cloud waste, where rightsizing and idle detection are critical. The FinOps Foundation’s State of FinOps 2024 report indicates that 32% of cloud spend is identified as waste before FinOps implementation.
AWS Cost Explorer: Visibility, But Not Control
AWS Cost Explorer is your initial window into AWS spending. It shows you what you’re paying for, where, and when. You can filter by service, account, tags, and even generate RI utilization reports. This is invaluable for understanding trends and identifying high-level cost drivers. For an AWS-only stack with fewer than 50 VMs, you’ll find Cost Explorer indispensable. What you won’t get is any answer about Azure or GCP — it simply doesn’t know those accounts exist. At scale, that blind spot becomes a budget problem. It also provides basic recommendations, but lacks automated execution or advanced rightsizing based on actual CPU/RAM utilization over time. For example, it might suggest a smaller instance, but won’t automatically apply that change or factor in application-specific peak loads beyond basic metrics.
I often use this command to quickly spot services without proper cost allocation tags, a common source of untracked spend. The output shows services that are billing but lack the `environment` tag we enforce:
aws ce get-cost-and-usage \
--time-period Start=2026-06-01,End=2026-06-30 \
--granularity MONTHLY \
--metrics UnblendedCost \
--group-by Type=DIMENSION,Key=SERVICE Type=TAG,Key=environment \
--filter '{
"Not": {
"Dimensions": {
"Key": "TAG",
"Values": ["environment"]
}
}
}'
Datadog Cloud Cost Management: Observability Meets Cost
Datadog excels in observability, providing deep insights into application performance, logs, and infrastructure metrics. Its Cloud Cost Management module extends this by correlating cost data with operational metrics. This is powerful: you can see why an instance is over-provisioned because you have the CPU utilization history right next to the cost. If your team is already heavily invested in Datadog for APM and monitoring, integrating cost management here offers a unified view. However, Datadog’s core strength remains observability. While it can identify inefficiencies, its automation capabilities for rightsizing or scheduling are not as deep as dedicated FinOps platforms. It can tell you *what* is expensive and *why*, but the *how* to fix it often requires manual intervention or integration with other tools. For example, a typical 50-VM AWS account might show significant CPU underutilization, but Datadog won’t automatically scale down or stop the instance.
Here’s how you might query specific EC2 instance metrics within a Datadog-like API structure (conceptual, as Datadog’s API requires specific authentication and metric names):
# This is a conceptual example for Datadog's metrics API
# Replace 'YOUR_API_KEY' and 'YOUR_APP_KEY' with actual keys
# And 'avg:aws.ec2.cpuutilization' with the correct metric
curl -G "https://api.datadoghq.com/api/v1/query" \
-H "DD-API-KEY: YOUR_API_KEY" \
-H "DD-APPLICATION-KEY: YOUR_APP_KEY" \
-d "query=avg:aws.ec2.cpuutilization{instance_type:t3.medium}by{instance_id}.rollup(avg, 3600)" \
-d "from=$(date -v-7d +%s)" \
-d "to=$(date +%s)"
Thalaxo Cloud: Automated Multi-Cloud FinOps
Thalaxo Cloud is built for the problem Cost Explorer pretends doesn’t exist, focusing on automated cost optimization across multiple cloud providers. Launched in 2025, it leverages over a decade of cloud architecture experience from its parent entity, Nuvelia SAS. Thalaxo offers comprehensive rightsizing, idle detection, and Smart Scheduler features. For instance, it flags instances with CPU
However, Thalaxo is a newer platform (launched 2025). Its SOC 2 Type II audit is in progress (started June 2026, following Type I report in May 2026), and ISO 27001 is on the roadmap for December 2026. While it supports 5 cloud providers, hyperscaler-native tools often offer deeper, more mature single-provider integration for specific niche services. Kubernetes workload-level cost allocation is on the product roadmap for Q3 2026. Currently, AWS and Azure offer full FinOps automation, while GCP is rolling out core visibility and rightsizing, and Alibaba Cloud integration is ongoing.
The core of automated rightsizing relies on precise metric collection and recommendation. To illustrate the underlying data for an instance that Thalaxo might recommend rightsizing, you’d typically query for CPU and memory usage over a period. This Azure CLI command fetches CPU usage for a specific VM, a key input for our rightsizing engine:
az monitor metrics list \
--resource "/subscriptions/YOUR_SUBSCRIPTION_ID/resourceGroups/YOUR_RG/providers/Microsoft.Compute/virtualMachines/YOUR_VM_NAME" \
--metric "Percentage CPU" \
--interval PT1H \
--start-time "$(date -u -v-7d +'%Y-%m-%dT%H:%M:%SZ')" \
--end-time "$(date -u +'%Y-%m-%dT%H:%M:%SZ')" \
--query "value[0].timeseries[0].data[].average" \
--output tsv
You can find more details on Thalaxo’s pricing tiers, which range from a Freemium option for up to 10 VMs to an Enterprise tier for large-scale operations. For a deeper dive into how different tools compare, explore our Essential Guide: Cloud Cost Optimization Software Cost & Comparison.
The verdict for your profile
Choosing the right FinOps tool hinges on your current infrastructure and future growth. There are clear lines where native tools cease to be sufficient.
- If AWS-only (< 50 VMs): AWS Cost Explorer is sufficient for initial visibility. It covers basic cost reporting, anomaly detection, and provides high-level recommendations for EC2 and RDS. You can set budgets and alerts, covering the foundational aspects of FinOps for smaller, single-cloud environments.
- If multi-cloud or > 100 VMs: Native tools cannot solve the specific pain point of unified cost allocation and automated optimization across disparate cloud environments. Managing 100+ VMs across AWS and Azure manually, or trying to reconcile two separate billing systems, quickly becomes an operational nightmare. The lack of a single pane of glass for rightsizing, idle detection, and scheduling across providers leads to significant hidden waste and manual overhead that scales linearly with your infrastructure.
- If observability is already covered by Datadog or another APM: Datadog’s Cloud Cost Management offers a strong correlation between performance and cost. However, its exact gap is in automated, proactive cost *action*. While it identifies underutilized resources based on performance metrics, it doesn’t automate the rightsizing or scheduling changes directly. A dedicated FinOps tool like Thalaxo bridges this gap, providing the automation layer to act on those insights, ensuring that cost optimization isn’t just a report, but an executed change. If your team is already stretched thin, relying on manual action from Datadog insights will lead to optimization debt.
Ultimately, the challenge isn’t just knowing your costs, but acting on them efficiently and at scale. As organizations grow, especially beyond 80+ VMs or into multi-cloud deployments, the limitations of native tools become significant cost drivers themselves. Exploring solutions that offer deeper automation and multi-cloud capabilities, such as Thalaxo’s integrations, becomes a strategic imperative. The goal is to move beyond reactive cost reporting to proactive, intelligent optimization that aligns with business value, as 64% of organizations now prioritize (Flexera 2026 State of the Cloud Report).
