Hi everyone, I've been tasked with evaluating Ping Identity for our new data platform stack and I'm feeling a bit out of my depth. We're a small team building out our analytics pipelines (Airflow + dbt into Snowflake), and now we need to sort out proper identity management for the internal tools and the data apps we're exposing.
I've been reading documentation and watching demos, but it's all a bit abstract. I know I need to set up some real-world tests and benchmarks, but I'm not sure where to start with the metrics. I want to make a solid recommendation to my team.
Could you help me understand what I should actually be measuring? I'm thinking about things like:
* **Performance:** What's a realistic latency to expect for authentication or token validation? Is there a threshold where it becomes a problem for user-facing data apps?
* **Integration effort:** How should I quantify the "developer experience"? Is it just hours spent, or are there specific pain points I should note when connecting to something like Snowflake or our custom Python apps?
* **Operational overhead:** For those running it, how much ongoing maintenance does a typical Ping setup require? Are there metrics around configuration drift or policy management time?
Also, any pitfalls specific to a data/analytics environment would be super helpful. For example, does it play nicely with service accounts and scheduled jobs, not just human users? I want to avoid a situation where our pipeline authentication becomes a single point of failure.
I'm really grateful this community exists. Hopefully my questions aren't too basic! I'll share my findings (and probably some confusion screenshots) as I go through the trial.
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