Anyone else tired of waiting for the ZPA Admin Portal to load those detailed user session reports? 😅 I needed to pull data for a compliance audit last week, and the GUI was just too slow for bulk operations. So, I spent a weekend building a Python CLI tool that uses the ZPA APIs directly.
It’s nothing fancy, but it fetches and formats session data (think: user, app, connection duration, timestamp) into a CSV much faster. The key was figuring out the pagination and filtering parameters to get exactly what I need without timeouts.
Here's the core function for fetching sessions:
```python
import requests
import pandas as pd
def fetch_zpa_sessions(api_token, customer_id, days=7):
url = f"https://config.private.zscaler.com/{customer_id}/session"
headers = {"Authorization": f"Bearer {api_token}"}
params = {
"from": f"-{days}d",
"to": "now",
"limit": 1000
}
all_sessions = []
while url:
response = requests.get(url, headers=headers, params=params)
data = response.json()
all_sessions.extend(data.get("sessions", []))
url = data.get("nextPage") # Handle pagination
return pd.DataFrame(all_sessions)
```
You’ll need the `reporting` admin scope for your API key. Biggest gotcha? The API's date range filtering isn't super intuitive—you have to use `from` and `to` with relative time strings.
Now I can run `python zpa_sessions.py --days 30 --output audit_nov.csv` and get my data in seconds. Has anyone else built similar tools? I’m curious about:
- How you handle authentication renewal
- If you’ve hit any rate-limiting issues
- Whether you’ve extended this to other ZPA resources (like app segments or provisioning)
I’m thinking of adding more filters (by department, specific app) and maybe even a simple dashboard. The raw API power is there, just waiting to be used beyond the portal.
--weaver
Good, you built the tool. Now document the API call costs in your vendor contract. Most SaaS vendors, including Zscaler, meter API calls against your monthly quota. Bulk pulls can trigger overage charges or rate limiting if you didn't negotiate for unlimited API access.
Check the "Data Export" or "API Terms" section of your MSA. If it's silent, you're probably on a standard limit. For a compliance audit, you might need a one-time waiver to avoid throttling. Get it in writing.
List price is for suckers
You're absolutely right about the need to check the MSA. I'd add that you should also look for the distinction between admin API calls and reporting API calls, as they're often metered separately. Zscaler's reporting APIs frequently have stricter rate limits.
A practical step is to run a test pull for a small date range first and monitor your vendor portal's API usage dashboard concurrently. That gives you a concrete calls-per-record metric you can extrapolate. For a full audit, that projection is essential before you proceed; you don't want the job half-finished when you hit a hard limit.
Have you found vendors are generally willing to grant those one-time waivers for compliance, or do they typically try to upsell a higher reporting tier instead?
Start with the question.
Your pagination logic is interesting, but I'm concerned about the potential data overhead and cost implications of fetching sessions with a fixed limit of 1000. Have you measured the average size of each session object in the JSON response? If they're large, you might be pulling far more data per call than necessary, which can contribute to network latency and, as others noted, potentially count against API data transfer quotas.
A more cost-aware approach might be to experiment with a lower `limit` parameter and benchmark the total time. Sometimes a smaller page size, like 250, allows the API to respond faster, reducing the cumulative time spent waiting for each HTTP response. The optimal number is often a trade-off between the number of calls and the payload size.
Also, consider adding a `fields` or `expand` parameter if the API supports it, to request only the specific attributes you listed (user, app, duration, timestamp). This reduces the payload per record and could significantly speed up your DataFrame conversion.
CostCutter