We're evaluating CSPM tools and resource consumption is a primary concern. Our team runs a lot of data pipelines, so overhead on our cloud infrastructure matters.
From a pure data perspective, which one generally has a lighter footprint in terms of agent requirements, network calls, and storage for findings? I'm particularly interested in the scanning and data collection mechanics.
I'm a cloud platform engineer at a mid-sized e-commerce company, and my team manages about 400 VMs and containers across AWS and GCP, handling heavy nightly batch workloads. We've run Tenable's VM scanner and Prisma Cloud's agent in test environments, so I've seen the load impact firsthand.
Here's a side-by-side on footprint:
* **Agent CPU/Memory:** Prisma Cloud's Defender is the heavier agent. In our tests, it consistently used 0.5-1 vCPU core and 1-1.5GB RAM at idle, with periodic spikes during image scans. Tenable's Nessus scanner is lighter at steady-state (under 0.2 vCPU, ~500MB RAM), but it's not a real-time daemon; it runs intensive scans on a schedule, which can still momentarily spike a host.
* **Network Calls & Data Volume:** Prisma Cloud wins on network efficiency for continuous monitoring. It pushes small, batched findings in near real-time. Tenable, by design, is a network scanner that initiates bulk requests during its scan windows; if you run a full credentialed scan of a large subnet, it can generate significant in/outbound traffic for a short period, which can affect network-sensitive pipelines.
* **Storage for Findings:** Tenable stores its raw scan data (`.nessus` files) locally on the scanner node, which can grow to tens of GBs if you don't prune. Prisma Cloud's findings are metadata sent to its SaaS console, so local storage impact is negligible - it's just log rotation on the agent.
* **Deployment & Control:** This is the clincher. Prisma's Defender is a persistent service you install across all hosts, which adds overhead to every instance. Tenable typically uses a few central scanner nodes that probe other systems over the network, so the footprint is concentrated, not pervasive. However, that means Tenable can miss ephemeral or containerized assets unless you tightly manage scan frequency.
My pick depends on your scanning model. For a classic, scheduled vulnerability assessment of stable infrastructure, Tenable is less of a pervasive resource hog. For continuous, real-time cloud security posture (containers, serverless, IaaS) where catching drift immediately matters, Prisma Cloud's distributed overhead is the trade-off.
To make the call clean, tell us what matters more: scheduled, comprehensive scans of known assets, or real-time drift detection across a dynamic environment including containers?
Infrastructure as code is the only way
You cut off mid-sentence on storage. Tenable's raw scan data *is* the storage hog. It's a massive database of vuln states over time. Prisma Cloud findings are smaller, more transactional.
But your CPU comparison misses a critical point. It's the classic batch vs streaming trade-off. A momentary spike during a nightly scan can be catastrophic if it lines up with your data pipeline windows. A constant, predictable overhead is often easier to plan around.
What's your scan frequency? If you're scanning nightly, the Tenable spike likely coincides with your batch workloads. That's the worst possible timing.
If it's not a retention curve, I don't care.
You've quantified the agent footprint, but you're comparing a continuous monitor to a scheduled scanner. That's an apples-to-airplanes comparison.
The more relevant resource question isn't idle CPU, it's the total compute tax on your environment. A constant 0.5 vCPU draw from Prisma Cloud adds up to a predictable, always-on overhead you can account for in your instance sizing. Tenable's "lighter" agent is a sleeper cell that detonates on a schedule. If that scan window overlaps with your nightly batch processing, even a 20-minute spike can cause cascading pipeline failures. Which is more expensive: a predictable tax or an unpredictable, system-crippling audit?
You need to correlate your scan schedules with your pipeline SLA windows. If you can scan entirely outside of them, Tenable's model might be tolerable. If your batch windows are near-continuous, Prisma's steady hunger is the lesser evil.
Attribution is a lie, but we need the lie.
You're asking about the pure data footprint. The comments above are spot on about CPU, but you specifically called out storage for findings.
Tenable's database is huge because it keeps a full historical record of every vulnerability state. Prisma Cloud findings are more like events - they come in, get processed, and the storage is for the current posture plus a short audit trail.
For network calls, Prisma is more chatty with continuous checks, but the payloads are small. Tenable is quiet until the scheduled scan, then it dumps everything at once.
So "lighter" depends: Prisma is a steady, predictable drip. Tenable is a flood at intervals. Which is worse for your data pipelines?
metrics not myths
Totally agree with your framing of the tax vs. the bomb. That's exactly it.
One nuance I'd add from our trial: "predictable" overhead depends heavily on your host churn. With Prisma, that constant 0.5 vCPU draw applies to *every* instance you spin up. In a dynamic environment where you're constantly scaling batch workers up and down, you're paying that tax across your entire fleet, 24/7. That's a real, quantifiable cost.
With Tenable, if you can tightly control your scan windows and your pipeline hosts are ephemeral, you can sometimes dodge the bullet entirely by not scanning certain workloads. It's a scheduling nightmare, but the resource cost isn't baked into every single VM's baseline.
So it's not just about overlapping with batch windows, but whether your infrastructure is static or fluid.
Another trial, another spreadsheet