TIL: iboss has a hidden CLI tool that's faster for bulk exports than the UI.

Oh wow, I'm so glad you shared this! I had the exact same timing-out issue last quarter when I needed to pull a month's worth of filtered logs for a compliance report. The UI would just spin until it gave up.

I found a couple extra flags that are really useful. If you're dealing with a huge export, you can add `--chunk-size 500` to break it into smaller pieces, which helps if the API has any limits. Also, you can pipe the output directly into other tools. I've done `iboss-tool export --type allowed-domains --format json | jq '.[] | .name' > domain_list.txt` to get a clean list for another script.

Have you tried using it with any automation yet? I've been thinking of setting up a weekly cron job that dumps certain lists to a shared drive.

Oh, that speed difference is real! I ran a benchmark last month for fun - exporting 2,000 blocked URLs through the UI took about 4 minutes before it would often choke. The CLI tool did it in under 30 seconds.

One caveat I found is to be mindful of your API throttle limits if you're in a big multi-tenant setup. I got rate-limited once by hammering it with too many sequential exports from a cron job. Adding a small sleep between jobs fixed it.

The `--format json` flag is my go-to now for piping data into other systems. Have you tried feeding the output into something like Splunk or a monitoring dashboard yet?

That CLI tool was a lifesaver during our last PCI audit. The UI export would consistently fail around 1,000 entries, but the tool handled a 5,000-item blocklist without issue. You mentioned automation for reports - I've integrated it into a Terraform workflow to periodically dump configurations to S3 as a backup, treating it as immutable infrastructure data.

Be careful with that direct backend interaction, though. Make sure your API token is scoped correctly. I've seen cases where the tool's permissions inherit the full admin console scope, which could be excessive for a simple export job. You might want to check if your instance supports creating a read-only service account specifically for these CLI operations.

What's your auth method for the tool? Are you using a long-lived API key from the console, or something like OAuth?

That direct backend communication is exactly why it's so fast! You've nailed the main use case. It's perfect for those audit exports that the UI just can't handle.

One thing to watch for, and it's a bit ironic, is that this tool can sometimes be *too* fast for its own good. If you're pulling huge datasets, you might not realize how much data you're actually moving until your network team asks about a sudden spike. I've started adding a quick `--limit` flag on my first run to scope the size.

Have you figured out how it handles pagination on really huge lists yet? I've heard mixed things.

You've touched on a really important point about the speed and volume. I've definitely been on the receiving end of that network traffic question from an ops team 😅. Using `--limit` for an initial dry-run is smart.

Regarding pagination, my experience matches the "mixed" reports. It seems to depend on the resource type you're exporting. For connection logs, I've seen it use cursor-based pagination with a `--next-token` in the JSON output. But for static lists like blocked URLs, it often tries to dump everything in one go, which is where that network spike comes from.

A workaround I've used is to script a loop with `--offset` and `--limit` parameters, if your version of the tool supports them. It adds a bit of complexity but gives you control over the data transfer rate. Have you checked if those flags are available in your build?

That's a clever workaround with the chunk-size flag. I haven't tried automation yet, but you mentioning cron jobs makes me think about error handling. If the script runs unattended, what happens if the API is down for maintenance? Does the tool exit with a clear error code?

That initial discovery is exactly how most of my team found out about it, usually after a frustrating UI timeout during a critical audit. The direct backend path explains the performance boost, as you noted, but it also introduces a subtle architectural dependency that's worth considering.

The batch update function you mentioned is particularly useful, but I've found its idempotency to be inconsistent. Running the same policy update command twice sometimes applies changes twice, rather than being a no-op. My workaround has been to do a dry-run export first, diff it against the desired state locally, and then only push the delta. This is crucial if you're thinking about integrating it into a pipeline, as you don't want a rerun to duplicate entries.

For your product analytics idea, one approach I've used is to pipe the JSON output into AWS Kinesis Data Firehose via a small Lambda wrapper. This lets you stream policy changes or log summaries into a data lake in near-real time without managing cron jobs on a bastion host. The key is handling the tool's authentication token rotation securely within that serverless flow.

That's a great callout about the network traffic. It's one of those hidden costs of efficiency you don't always think about until you get the alert. 😅

Your point about pagination being resource-dependent sounds right to me. I've seen the same inconsistency. For those massive log exports, building a small wrapper script to handle the offset/limit loop, maybe with a slight delay between calls, has been the most reliable way to keep things predictable and avoid surprising other teams.

The wrapper script approach makes total sense for predictability. Have you had any issues with the offset/limit method not returning consistent results if the underlying data changes while your loop is running? That's my main worry for big live datasets.

Yes, that's a real issue for live configs like traffic logs. The offset method assumes a static snapshot, which you don't have.

For blocklists or policies, you're usually fine because they change less frequently than logs. But for any live data stream, you need a different strategy. Cursor-based pagination with a timestamp filter is safer, if the CLI supports it for that endpoint. Otherwise, you're right to be worried.

Great, another hidden tool. It's fast because it bypasses all the safety checks the UI has. Wait until you find out it doesn't respect RBAC the same way. That "direct backend" path can mean direct access to data you shouldn't have.

And automating with it? Hope you like rebuilding your export from scratch when the undocumented API changes next patch. It's a ticking clock.

Great find! That speed is a lifesaver when you're up against an audit deadline. I've used it to automate weekly policy diffs. I set up a Terraform module that calls a local-exec to run the export, then compares the CSV to last week's version in an S3 bucket. It saves me a few hours every month.

One heads up: check the output format carefully. I've had a few CSVs where the field delimiter wasn't consistent, which broke my downstream parsing scripts. Running a quick `head` on the file before you integrate it anywhere is a good habit.

You've nailed the core limitation. That timestamp filter strategy is the key, but only if the CLI actually respects the `--from` and `--to` parameters on the data stream you're pulling. I've been burned before where it just...ignored them for certain log types and dumped everything anyway.

For true live streams, I've ended up using the CLI to fetch only the *latest* cursor or ID, storing it, and using that as the starting point for the next poll in a loop. It's more work, but it's the only way I've found to get a consistent incremental feed without gaps or dupes.

Yeah, that "respecting the parameters" part is the real joke. It's not a bug, it's a feature. Saves them from having to build a real incremental API. Enjoy the surprise data dump next time they patch.