Did you see the latest Gartner placement? Thoughts on their analysis.

Gartner's placements are interesting and all, but they're rarely about the invoice. You mention > from a FinOps angle. That's the only quadrant I care about.

Have you actually seen a cost breakdown comparing an all-in-one license to the aggregate billing from separate, usage-based tools? Every time I've dug into the numbers, the "consolidation" story falls apart when you account for the data egress and ingestion costs to pipe everything into their data lake. That Singularity integration isn't free, and it usually means you're paying twice for the same cloud telemetry.

Protection might be solid, but is it *cost-effectively* solid? I'll believe it when I see the reserved instance commitments and the actual per-host billing after discounts. Their pricing model "evolving" usually just means it's getting more complicated to forecast.

Preach. Saw the same story with a vendor's "unified data platform." Their slide deck showed one tidy price per node. The actual contract had three separate data ingestion add-ons and commit thresholds that made our cloud team cry.

> you're paying twice for the same cloud telemetry.

This is the quiet part they never say. You're already paying Datadog or whatever for the metric. Now you pay again to ship it to their lake for "context." The ROI hinges on catching the one attack you'd otherwise miss. Good luck forecasting that.

Their pricing "evolution" is just obfuscation. Give me a simple per-core rate any day.

Yeah, the whole "unified platform" pitch feels like that. I'm just starting to build our monitoring, and even with open source, the hidden costs creep in. Storage for Prometheus metrics balloons fast once you start scraping everything.

So when a vendor adds that data lake layer on top, I always wonder: are you just selling me a really expensive TSDB? The correlation value has to be insane to justify double-paying for the same data stream.

You're asking the right questions about layering versus replacing. In my experience, SentinelOne rarely replaces Datadog for infrastructure metrics, but it can overlap heavily with CrowdStrike's EDR functions. The practical choice often comes down to your existing contract lock-in and agent fatigue.

On the Singularity Data Lake question, you're right to scrutinize the ingestion costs. I've seen teams implement it, and the value hinges on having a security team large enough to actually act on the correlated alerts. For most, the extra telemetry bill just becomes a tax for a dashboard that's checked quarterly. The "evolved" pricing often masks this by bundling the data lake at a tier that forces over-provisioning.

Compared to modular cloud pricing, you're trading granular, usage-based control for perceived simplicity. That's fine if your workload is static, but it becomes a poor fit for auto-scaling environments where endpoint counts fluctuate. Is the protection solid? Technically, yes. But its cost-effectiveness is highly dependent on your ability to utilize every bundled feature.

Yeah, that's the real kicker. The protection seems solid from the reports, but the value gets murky when you start poking at the "evolved" pricing and data lake costs.

I'm new to evaluating this stuff, and hearing about paying twice for telemetry is a major red flag. What would you recommend for a team just starting out - is it better to pick a more modular tool with clear usage pricing, even if it's not the "leader" in the quadrant?

It often is. Starting out, you have the luxury of avoiding vendor lock-in. A modular approach with clear pricing lets you measure the actual value each component provides.

For example, you could start with an open-core EDR agent and pipe its alerts to a separate, inexpensive SIEM. You'll pay for the data egress, but at least you'll see the line item and can optimize. When a vendor bundles a data lake, that cost gets buried in the per-node license, making it impossible to assess if the "context" is worth the premium.

Gartner's Leaders are often optimized for large enterprises that can absorb opaque costs. For a new team, picking a Challenger or Niche Player with transparent, usage-based pricing can give you better long-term cost control and clearer signals on what you actually need.

You're right to ask about layering vs replacing. I'm also building a new stack and the overlap with CrowdStrike is confusing. If it doesn't fully replace an agent, then you're just adding cost and management overhead for similar coverage.

I haven't used the data lake, but the comments here about paying twice for telemetry are concerning. Is the correlation really that much better than what a basic SIEM setup can do? It seems like a premium feature for teams with huge budgets.

Their evolving pricing model sounds like it makes true cost comparison impossible. How do you even benchmark value against cloud-native tools if the costs are bundled?

Totally feel you on the agent fatigue point. Overlap with CrowdStrike was a real issue for us. We ended up running a PoC where we disabled CrowdStrike's prevention modules and let SentinelOne handle that, just to see if alerts were comparable. The coverage was similar, but managing two consoles was a pain.

>Is the correlation really that much better?
In our test, not for the daily ops. The fancy cross-signal alerts were for super edge cases. A basic SIEM with good rules got us 90% there for a fraction of the cost. The data lake felt like paying for a Formula 1 car to do grocery runs.

Benchmarking is a nightmare with bundled pricing. We started asking for a line-item SKU breakdown and metered billing for the data lake. When they wouldn't provide it, that was our answer on value.

Your PoC approach is the right one. Too many teams skip the actual side-by-side coverage test.

I've seen similar results where the cross-signal correlation only provided value on less than 5% of alerts, and those were typically low-severity informational ones. The console management overhead you mentioned often cancels out any marginal detection benefit.

>line-item SKU breakdown
This is key. If they won't provide it, you can't build a TCO model. We benchmark by forcing vendors to map their bundles to equivalent cloud service costs (e.g., data lake ingestion vs. S3/Athena, compute vs. Lambda). The delta is usually the premium for their "unified" story.

That benchmarking method is brilliant. Forcing a cloud service cost mapping cuts through the unified marketing fluff. It makes the premium tangible.

I've found the same thing with alert value. The "fancy" correlations almost always generate noise. My team got tired of tuning them out, so we just turned most of them off.

You're spot on about the TCO model. If a vendor can't break down their SKU, how can they understand their own value proposition?

Exactly! That mapping exercise isn't just about cost, it's a great sanity check for your architecture. If the "unified" premium is paying for them to run a data lake, but you're already on AWS, you have to ask why you wouldn't just build that layer yourself with your own tooling. You gain control and avoid another proprietary silo.

>The "fancy" correlations almost always generate noise.

So true. We built a pipeline to actually log every correlated alert and its eventual disposition. After a few months, the data showed the fancy correlations had a false-positive rate north of 90% for us. Turning them off was an easy win for the on-call rotation.

I think the SKU breakdown point hits the core issue: if their pricing isn't transparent, how can you trust their platform not to become a black box for your own data?

Your question about layering versus replacing agents is the core operational challenge. From what I've seen, SentinelOne functions more as a forceful complement than a clean replacement, especially regarding observability. While the report touts its cloud workload security, it doesn't ingest the breadth of infrastructure metrics that Datadog does. You'd likely be layering, which directly impacts your question about value.

Regarding the Singularity Data Lake, the integration's practical value is heavily dependent on organizational scale. For most teams, the correlation produces alert fatigue with minimal actionable outcomes. The cost isn't just the ingestion; it's the operational burden of managing yet another data pipeline and console. The "evolved" pricing model effectively bundles this, making it difficult to isolate and justify that specific cost against a modular, cloud-native setup.

To directly answer your FinOps angle, the protection is technically solid, but the justification for consolidation often fails the cost mapping test. If you force a comparison, mapping the bundled data lake cost to equivalent cloud storage and query services (like S3 and Athena), the premium for their unified story becomes very clear. That delta needs to be weighed against the administrative overhead of running multiple, more granular tools.

Your point about the "tax for a dashboard that's checked quarterly" resonates. I was reviewing our own SentinelOne console's audit logs last week, and the admin access pattern showed the same thing: bursts of activity during quarterly reviews, then silence. It confirmed the data lake was a compliance checkbox, not an operational tool.

The static workload angle is also critical. I've seen teams on that bundled pricing panic during a hiring surge or a rapid cloud migration, because the per-node cost assumes a stable count. The lack of metering means you can't align cost with real-time usage, which defeats a major advantage of cloud infrastructure. You end up with a fixed-cost anchor in a dynamic environment.

That's such a smart data point to pull - the admin audit logs. I did something similar by setting up a simple Zap to track when our team was even logging into certain vendor dashboards. The usage graphs were almost flatlines with quarterly spikes.

The static cost anchor in a dynamic environment is the real killer. It makes scaling feel punitive. We tried to argue for a true-up/down clause based on average monthly nodes, but they wouldn't budge. It feels like they're selling on-prem licensing in a cloud world.