Everyone pushing Exabeam for MSSPs talks "value" and "efficiency." Let's talk real numbers. Our multi-tenant deployment for 30 clients burned nearly $250k/year in pure infra costs *before* Exabeam licensing.
* The data ingestion tax is brutal. More logs = more hot storage = more compute for parsing. Our AWS bill for the SIEM pipeline alone jumped 40%.
* Their "cloud-scale" architecture? Runs on oversized, on-demand instances "for stability." Their own docs recommend i3.4xlarge for a mid-sized deployment. That's ~$1.2k/month per node before you store a single byte.
* Managed service? You still pay for the underlying cloud waste.
For an MSSP, the math is critical:
```python
# Simplified cost per client (50GB/day)
compute = 4 # vCPUs per client avg
storage_hot = 50 * 30 * 0.10 # 50GB/day, 30 days, $0.10/GB
storage_warm = 50 * 335 * 0.025 # 335 days archive
monthly_infra_per_client = (compute * 0.08 * 720) + storage_hot + storage_warm # ~$365
```
Now multiply by 100 clients. That's $36.5k/month *just for infra they orchestrate*. Add their premium licensing.
Is it worth it? Only if your operational savings from their automation exceed this + the license. For us, it didn't. We built our own correlation engine on spot instances and saved 60%.
Show the math.
show the math
Hi user400, that breakdown is painfully familiar. I'm Brian Lee, an IT operations lead at a manufacturing-focused MSP with about 40 clients in the logistics and industrial space. We've been running Exabeam Cloud in a multi-tenant setup for two years, managing our own ingestion pipelines before handing logs off to their S3 bucket.
**1. Multi-Tenant MSSP Cost & Performance Realities**
**True Infrastructure Ownership:** Your numbers are correct. Even with their Cloud, you're paying for your own ingestion, and they orchestrate expensive compute for correlation. For our ~8TB/day total volume, we saw a consistent 35-45% AWS premium layered over our baseline pipeline costs, just for the instances they spun up. Their "efficiency" doesn't apply to the cloud resources they control.
**The 80/20 Rule of Automation:** Their UEBA and automated timelines are good, maybe 80% of the value. But that last 20% - tuning for client-specific apps or non-standard auth sources - requires the same level of analyst effort as any other SIEM. The promised analyst efficiency gain only materializes if your clients have very common, well-supported tech stacks.
**Deployment and Integration Friction:** The initial connector deployment is straightforward for universal sources like AD or Office 365. The real effort, about 2-3 weeks per client for us, is in normalizing the custom data - proprietary manufacturing SCP logs, warehouse management systems - to feed their behavioral analytics engine properly. Out-of-the-box parsers often failed here.
**Where It Clearly Wins (For Some):** For pure compliance-driven MSSPs with clients on standardized, cloud-heavy stacks (Azure, AWS, SaaS), the automated report generation and incident timelines drastically cut manual work. If you can map 90% of a client's logs to their supported parsers, one analyst can probably handle triple the number of clients compared to a barebones ELK stack.
**2. Vendor Responsiveness & Scaling Pain**
Support for technical issues is generally responsive within SLAs. The real challenge is scaling discussions. When we wanted to re-architect our data routing to lower the ingestion tax before it hit their system, the conversation immediately shifted to their professional services team and a five-figure engagement. Their model optimizes for you sending everything, not for you being efficient upstream.
**My pick:**
We're actually moving off Exabeam for clients where custom log sources are more than 30% of their volume. The math only works if your client base is homogenous. If your 30 clients all use the same core stack (e.g., all on Microsoft 365, Fortinet, and CrowdStrike), Exabeam's automation can justify the cost. If you have a mix of legacy, on-prem, and niche SaaS, the tuning burden and infrastructure overhead will erase the savings. Tell us what percentage of your clients' log sources are considered "standard" versus custom, and what your primary driver is - compliance reporting or actual threat hunting.
The 80/20 rule you mention on automation is exactly where our ROI calculation fell apart. The promised 1:200 analyst-to-endpoint ratio assumes you're not spending those saved hours on custom parsing and tuning. For an MSSP with diverse clients, that assumption is false.
Your point about **True Infrastructure Ownership** is critical, and it extends to Reserved Instances. Even if you commit to a 1 or 3-year term on the underlying i3 instances they dictate, you're absorbing the risk of client churn. That reservation becomes a stranded cost if a client leaves, which makes the per-client margin even thinner.
Have you quantified the actual analyst time spent on that last 20% of tuning per client? We found it nearly erased the platform's efficiency gains for anyone outside a standardized compliance package.
Your bill is too high.