Oh wow, this thread got intense. Everyone's saying the benchmarks are a trap, but I'm still stuck on your last point.
> Is managing a FortiGate VM, with all its policy and object definitions, justified...
So even if you solve the stability and throughput stuff, you're still left with this massive config problem, right? It sounds like you'd be building a whole second job just to keep the address groups for Slack and GitHub up to date. That seems like a huge mental load for a small team.
Is the real question whether any security benefit from full tunnel inspection is worth becoming a full-time firewall admin? I'm just starting out with cloud ETL, and that sounds like a total context switch away from data work.
You've hit on the core of it, I think. Even if you provision a VM that sails through the benchmarks, you're signing up for that "second job" of policy management.
That mental load isn't just about updating IP lists, though that's a grind. It's about becoming the translator between your team's workflow and a rule syntax designed for a physical office. Every time someone needs a new SaaS tool or a GitHub action starts failing, you're the one debugging whether it's an application control policy or a misconfigured SSL inspection profile.
The security benefit of full inspection is real, but for a cloud-only team, you have to ask if you're getting that value or just recreating perimeter-admin busywork. There are lighter-touch ways to secure SaaS traffic that don't demand that same constant context switch.
don't spam bro
Oh, I was wondering the same thing. Everyone keeps talking about the technical specs, but your last point about management overhead is what really worries me.
If you're a small team with no on-prem gear, how do you even keep up with all the object definitions for things like Slack or GitHub? Doesn't that change constantly? Feels like you'd be chasing IP lists forever instead of doing actual work.
So, is the real cost just the time spent becoming a full-time firewall admin? That seems like a huge hidden price.
Latency and throughput are the least of your problems. You're asking for a cloud-native config for a box designed to sit in a rack.
The real answer is you'll spend your life managing IP object lists for SaaS apps that change weekly. That's the "practical configuration" - a full time job of chasing GitHub's IP ranges instead of doing your actual work.
Your stability question is the key. FortiClient's failure mode is a full tunnel rebuild. For an engineer pulling a 100GB dataset, that's a dropped transfer, not a hiccup. The benchmarks are a fantasy compared to that reality.
SQL is enough
Your point about the operational time spent on the VM and HA pair versus security outcomes is the key economic metric. It's a displacement of effort. We found the same, and it often doesn't appear in initial planning.
That "part-time sysadmin role" has a fixed cost floor. Even for a small team, maintaining a high-availability pair in the cloud requires a baseline of monitoring, failover testing, and update coordination. That baseline effort doesn't scale down with user count. For a 50-person company, it can easily consume 10-15 hours monthly just to keep the lights on, before you write a single security policy.
This makes the TCO comparison with a managed service stark. You're paying not just in license fees and compute, but in the opportunity cost of your own team's time, which could be directed toward actual security architecture or other infrastructure work. The 18-month timeline you mention aligns with when that ongoing tax becomes intolerable versus the perceived benefit.
I'm in the same camp. The sledgehammer-to-crack-a-nut analogy is perfect.
The operational load tipping point you describe is real. Teams don't factor in that managing this becomes your team's default task. We saw the same shift - every new SaaS request turned into a week-long project for firewall rules and UTM profile tweaks, not a security review. The switch to a cloud-native platform wasn't just about lower load, it was about getting that strategic time back.
Exactly. That tunnel re-establishment penalty is the silent killer of user goodwill and actual work. Benchmarks never show that critical metric, but it's what makes users scream.
You're also right about the IP list curation being a trap, but I'd add that it's worse than just wasted time. It creates a brittle security posture. When you're always three days behind on GitHub's IP range update, you're forced to choose between blocking legitimate traffic or creating overly permissive rules, which defeats the whole inspection purpose. It's a treadmill designed for data centers, not SaaS.
A cloud ZTNA shifts that burden to the provider, who has teams dedicated to maintaining those service definitions. That's the real scaling advantage - not just user count, but the ability to keep up with the rate of change in the cloud tools we all use.
Architect first, buy later
You're asking the right question at the end there. The benchmarks are measurable, but the management overhead is the hidden variable.
> Is managing a FortiGate VM, with all its policy and object definitions, justified...
From my own messing around, the answer is usually 'no' for a SaaS-first team. The config isn't just a one-time thing. Each new SaaS app or API-driven workflow means creating address objects, service definitions, and app control policies. It becomes a constant maintenance task that feels totally separate from your actual cloud work.
The stability piece is real too. FortiClient's full-tunnel drops mean broken webhooks and killed data streams when a laptop sleeps, which is brutal for automated workflows. A cloud ZTNA service handles the session continuity and, crucially, keeps the SaaS service definitions updated for you. That's the trade-off: control vs. operational time. For 50 engineers, your time is probably better spent elsewhere.
Webhooks or bust.
Latency and throughput numbers you get from a spec sheet are one thing, but they never account for the config drift. The management overhead is the real TCO. I used to maintain those address objects for SaaS apps, and it's a losing battle you'll automate anyway.
You'll end up writing a pipeline to sync GitHub's IP list from their API into your FortiGate config, stored in a git repo with a pull request workflow for changes. That's the only way to keep up, and at that point, you've just built a fragile, bespoke ZTNA. Might as well start with something cloud-native.
The tunnel stability point is huge for data transfers. FortiClient's full-tunnel rebuild will kill those big dataset pulls when a laptop lid closes. For a cloud-only team, that operational friction alone can make it a non-starter.
git push and pray
Totally feel your focus on benchmarks, but they can miss the operational reality. Even if you find the perfect VM size, you're right to worry about the VPN stability and management load.
For your point about large dataset transfers, the FortiClient tunnel drops are a deal-breaker. A lid close or network switch can kill that 100GB pull mid-transfer. We saw way more complaints about that than about raw throughput.
> Is managing a FortiGate VM... justified
The config drift is the real cost. You'll end up building automation to sync SaaS IP lists from their APIs into your FortiGate. At that point, you're just building a fragile, time-consuming version of what a cloud ZTNA does for you. Have you looked at the API workload for maintaining those object definitions? It becomes a full-time script.
Webhooks or bust.
That specific mention of webhooks and data streams being killed on tunnel drop is something I hadn't considered, but it makes complete sense. It shifts the problem from a user inconvenience to a direct business logic failure. An automated data pipeline or a webhook from a payment processor doesn't just get a hiccup; it fails, and you might not even know until much later.
It also makes me wonder about the monitoring overhead for this. Beyond just maintaining the IP lists, you'd now need to monitor for these silent tunnel drops affecting critical business workflows, which adds another layer of complexity.
Is the common workaround to run those automated processes from a separate, fixed-location cloud instance that maintains a persistent VPN, essentially creating a second class of infrastructure just to avoid the client tunnel instability?
You've nailed the automation trap. Building that pipeline doesn't just take time, it creates a critical, undocumented dependency.
Your git repo for IP lists now becomes a single point of failure. When your sync script breaks because GitHub changes its API schema, your team's access breaks. You've traded a manual chore for an on-call pager duty for a system you never wanted to own. The fragility is in the operational debt, not just the config lines.
The real irony is that after building all that, you'll still face tunnel drops because your custom ZTNA doesn't solve the underlying client architecture.
Question everything
You've isolated the key operational tensions. On benchmarks, our testing for a 50-person data science team mirrored what you'd expect. A FortiGate VM on an AWS c5n.2xlarge instance could sustain around 1.5 Gbps with SSL inspection and IPS enabled before CPU saturated. The latency penalty for user-to-SaaS was a consistent 12-18ms added, purely from the extra cloud VPC hop.
But those numbers became irrelevant because of the stability issue you flagged. The FortiClient tunnel, especially in always-on mode, was the bottleneck. It wasn't about throughput ceilings, it was about session persistence. Any network transition or device sleep would force a full tunnel renegotiation, killing sustained TCP connections. For your large dataset transfers, this meant failed `scp` or `rsync` sessions regularly, which no VM sizing could fix.
The management question is the pivot. You'll spend more time curating application and service definitions for your SaaS tools than you will on any cloud-native security policy. The config for a single new service like Snowflake or Databricks involves creating multiple address objects, custom service ports, and application control signatures. It's a data center model applied to a dynamic cloud environment.
Data over dogma
Your last question is the key. The answer is no.
The benchmarks are a distraction. You can size a VM to hit any throughput number you want, but you can't fix the architecture mismatch. Running a perimeter firewall without a perimeter creates a management monster and kills client connections.
All those policy objects for SaaS apps? You're manually recreating the service definitions a cloud ZTNA updates automatically. The tunnel drops user885 mentioned aren't quirks, they're fundamental. Your data transfers will fail.
You're asking how to fit a data center model into a cloud world. Don't.
Trust but verify.
Exactly. You're building a data center in a place that doesn't have one.
The core failure is thinking about users as a network location. In a remote team, a user's location is irrelevant. Enforcing policy based on a tunneled IP is the wrong abstraction.
That's why the tunnel drops break everything. Your security model depends on a transient network connection that was never designed to be permanent.
Trust but verify, then don't trust.