Alright, let's get this over with. The migration is done, the consultants have finally left our Slack channels, and I've had six months to watch this new shiny thing run in production. Everyone was screaming about ForgeRock's "legacy complexity" and how Ping was the cloud-native savior. So we drank the Kool-Aid, signed the enterprise agreement that probably requires my firstborn as collateral, and here we are.
Let's be clear: Ping Identity *works*. Our SSO flows are functional, the dashboard has prettier graphs, and the SaaS admin console is indeed less of an immediate headache than ForgeRock's AM configuration files scattered across a dozen servers. But before you start your own migration to escape the ForgeRock jungle, let's talk about the trade-offs we've measured, because the marketing slides sure won't.
First, the supposed "cost savings" from reduced operational overhead. It's a shell game. Our ForgeRock cluster ran on a handful of c5.2xlarge instances we could rightsize, stop, or drill into with any APM tool we wanted. Ping's "cloud-native" model means we're now paying a premium per user per month, and our bill scales linearly with users we onboard, not with actual compute we can optimize. Our finance team is now getting monthly invoices that look like a mortgage statement. Try explaining to them why "outsourcing the headache" costs 40% more year-over-year. The operational overhead didn't vanish; it just transformed from a capex infrastructure problem into an ever-growing, unpredictable opex line item.
Then there's the "simplicity." Sure, you don't edit XML files in Ping. Instead, you get to learn their proprietary expression language for policy decisions and data transformations. Want to do a custom claim mapping based on a call to an external API? In ForgeRock, I'd write a bit of Groovy or Java. In Ping, I'm writing something like this in their policy editor:
```
# Their expression language feels like a weird hybrid...
if (subject.getAttribute("department") != null && subject.getAttribute("department").equals("Engineering")) {
action = "PERMIT";
} else {
action = "DENY";
}
```
It's not hard, but it's yet another vendor-specific DSL to maintain. And debugging these flows when something goes wrong? The observability is locked inside their dashboard. I can't just `grep` logs or pipe them into Splunk with the same granularity. I have to rely on *their* log export features, which add latency and filter fields. For an engineer used to owning the full stack, it feels like having your hands tied.
The biggest failure mode we've encountered so far isn't technical—it's procedural. With ForgeRock, a config change went through a Git review, a CI/CD pipeline, and was deployed to our nodes. Ping's "deployment" is often a point-and-click in the admin console or a call to their (admittedly decent) APIs. This has led to at least two "oops" moments where an admin made a direct change in production that wasn't recorded in our IaC. We're now trying to enforce discipline using Terraform for *everything*, but their provider, while comprehensive, lags behind new features. So you're stuck choosing between stability and using the latest Ping feature.
So, is it better? For reducing the immediate cognitive load on a team that doesn't want to specialize in identity servers, maybe. But don't for a second believe you're moving to something "simpler" or "cheaper." You're trading one form of complexity (infrastructure and open config) for another (financial model and vendor-locked abstractions). The question you need to ask isn't "which product is better?" It's "which set of problems would my team rather have?"
Now, if you'll excuse me, I need to go argue with our account rep about why our non-human service accounts shouldn't be counted at the same rate as human users.
-- cynical ops
Your k8s cluster is 40% idle.
1. I'm a procurement lead for a global fintech with about 3k employees. I handle the vendor side of our IAM stack, which currently runs PingFederate and PingDirectory on-prem to serve our external customer portal, after we evaluated both platforms.
2. Core comparison:
**The Real Cost Model:** Ping's per-user/month licensing is a predictable bleed, but it's the professional services that get you. Our migration required 40% more consulting hours than the Ping sales rep estimated because their out-of-the-box connectors needed so much customization. ForgeRock's perpetual license hurt upfront, but its overhead was a fixed, predictable ops team headcount.
**Operational Control vs. Illusion:** You called it on the APM tools. With ForgeRock, I could trace a performance issue down to a specific thread pool in a specific JVM. With Ping's cloud service, my visibility ends at their API gateway. I get a support ticket, not a root cause. Their SLA credits are a joke, maxing out at 10% of the monthly fee for an outage.
**Where Ping Actually Wins (Narrowly):** Developer experience for simple, greenfield SaaS apps. If your use case is purely SAML/OIDC for a handful of modern apps, a Ping SaaS setup can be configured by a mid-level engineer in an afternoon. ForgeRock's AM console feels like a legacy cockpit by comparison.
**The Flexibility Trap:** ForgeRock's complexity is its superpower for edge cases. We had a bizarre requirement for a step-up auth flow that involved a legacy mainframe. Building a custom node in ForgeRock's AM was painful but possible. Ping's support team's answer was "that's not a standard pattern" and a $50k quote for "potential custom development."
3. My pick: I'd only recommend Ping if you're a mid-market company with a simple, cloud-only app portfolio and zero legacy systems. If you have complex auth workflows, hybrid infrastructure, or need deep performance control, stick with ForgeRock and invest in upskilling your team. Tell us your annual user growth rate and how many non-standard authN/authZ flows you have.
Your free trial ends today.
> "With Ping's cloud service, my visibility ends at their API gateway."
This is the part that always gets under my skin. We're heavy into Metabase and Looker for our internal dashboards, and I've been trying to build a decent monitoring layer for our Ping setup. The API gateway logs are a black box - you get the request/response timestamps but zero insight into what the Ping engine itself is doing during that time. ForgeRock at least gave you JMX metrics you could pipe into a Grafana dashboard.
I've found a semi-workaround: pushing Ping's audit logs into a cheap data pipeline (we use Fivetran into BigQuery) and then building custom SQL queries to spot latency patterns. It's not real-time, but it's better than nothing. Still, you're essentially reverse-engineering their performance from the outside. 40% more consulting hours sounds about right - we had to eat almost the same delta on our migration because the "built-in" connectors for our legacy LDAP needed custom scripts.
Curious if you've looked at PingDirectory's monitoring capabilities at all? We're still on-prem with that piece, and I'm wondering if the hosted version gives you any more rope for root cause analysis.
Data doesn't lie, but dashboards sometimes do.
>the bill scales linearly with users we onboard, not with actual compute
This is the killer feature for them, not you. It incentivizes them to make onboarding frictionless while you watch the meter run. Our finance team had a collective heart attack when we auto-provisioned a test cohort of 500 users and forgot to decommission them for a month. The "cloud-native" tax hits different.
For us, the real trade-off was observability. You can't run chaos experiments or meaningful canary deployments when you can't instrument the guts of the thing. It's like doing surgery with oven mitts on.
Oh, the "premium per user per month" is the real kicker, isn't it? You're not paying for compute, you're paying for the privilege of having your own cost structure become a scaling nightmare. I saw a team provision a batch of service accounts for a new microservices mesh and their annual forecast blew up overnight. The sales rep called it "predictable scaling." I call it a hostage situation.
The fun part is when you try to correlate that linear cost with actual performance. Your bill doubles, but can you prove your user experience improved? Or that their multi-tenant box isn't just getting noisier? Of course not. The APM black box ensures you can't.
The professional services creep is so real. We hit the exact same wall. Our "accelerator" package turned into a never ending customization project because their OOTB connector for our legacy HR system just...didn't. The fixed ops headcount for ForgeRock is a great point - you budget for those FTE salaries and move on. With Ping, it's like the project never truly ends, you just switch from implementation consultants to premium support retainer fees.
That thread pool visibility hit home too. Had a latency spike last quarter and all Ping support could say was "the backend is healthy." Had to triangulate the issue ourselves by adding synthetic transactions from three different regions and correlating it with their status page events. Felt like detective work just to get a vague "network latency in the region" non-answer.
cost first, then scale