Wait, you said you set the update source to a local server. Did you configure any fallback to the cloud CDN if that local server goes down? I saw a comment earlier that mentioned an outage from that exact scenario.
Containers are magic, but I want to know how the magic works.
>Did you configure any fallback to the cloud CDN
You can't. The sensor config is a one-shot setting. It's local server or cloud, not both.
We scripted a daily check for the local server. If it's down, we push a config change to flip the fleet to cloud source, then flip it back when the local server is restored. It's another piece of orchestration you have to build yourself.
Benchmarks don't lie.
Staggering updates and setting a local source is the right first step. But you've got two key gaps to close.
That hash-based allow list for your internal tool is fragile. Every new build breaks it. Consider creating a dedicated directory for that tool, then using a broader path-based exclusion in your dev/test policy. It's a smaller, more controlled blast radius than a global hash you have to constantly update.
Also, confirm your local server has enough storage for multiple sensor versions. If it only caches the latest build and a host on an older version checks in, it'll still pull from the cloud. That could defeat your bandwidth plan for those lagging endpoints.
ship early, test often
Wait, so the API call you added for the hash allow list counts against the rate limit too, right? That's another thing for a script to trip over.
Setting the local update source is smart, but I'm nervous about the 'one-shot setting' thing someone mentioned. What happens if that local server has a hiccup during an update? Does it just fail quietly?
Integrating the kextstat check as a policy pre-stage is a clever automation. You might consider extending that script to also capture the specific incompatible kext's bundle identifier and version, not just a binary pass/fail. Logging that detail to the ticket can save hours during the diagnostic phase, especially when dealing with vendor-specific drivers that have frequent minor updates.
Adding CPU wait time to Grafana is a solid move. When you implement that, set your baseline from a sample of known-clean systems first. We found that the absolute value is less informative than the delta from that baseline; a 15% increase in `IOWAIT` on an older MacBook Air was our threshold for a warning. It caught several outdated virtualization kexts that the basic compatibility list missed.
> Logging that detail to the ticket
This is the way. We use the kext bundle ID as the primary ticket tag. Makes it trivial to group issues and see if a particular driver is a common offender across the fleet.
That baseline delta for CPU wait is crucial. Our threshold was 10%, but the key was monitoring the slope, not just the breach. A slow creep over a week usually meant a background service loading more junk, not a direct conflict.
YAML all the things.
You've addressed the immediate network and policy issues, but that hash-based allow list is going to become a maintenance burden. Every time that internal tool is rebuilt, you'll need to update the hash, and that's an API call that also contributes to your rate limit fatigue.
Consider a path exclusion for its install directory in your dev/test policy instead. It's a broader permission, but it's static and won't require constant API updates.
sub-100ms or bust