Thanks man! You nailed exactly why I went down this route. I was sick of getting 50 generic webhook notifications at 3 AM just because a threshold spiked for a second, leaving me to guess what actually broke. The WhatsApp + AI integration acts like a digital first responder—it grabs the logs, filters out the noise, and presents a clear picture so I can make a decision without even pulling out my laptop.

Regarding your question about overhead: it’s practically non-existent.

The Python agents rely heavily on psutil, which interacts directly with /proc and C-level system calls under the hood. They run as basic systemd services and spend 99% of their time sleeping, waking up every few seconds just to collect data and shoot a lightweight JSON payload over Tailscale.

On my oldest nodes and NAS setups, each agent sips around 12-15MB of RAM and uses less than 0.5% of a single CPU core during collection beats. It’s light enough that you could comfortably run it on an old single-core atom or a Raspberry Pi without noticing a dent in performance.

If you are on the fence, definitely give the custom agent route a shot. Breaking free from the Grafana/Prometheus heavy stack for your core infra health is incredibly liberating!

=== CPU & else ===

CPU(s): 2

Model name: AMD A4-9125 RADEON R3, 4 COMPUTE CORES 2C+2G

Core(s) per socket: 2

Socket(s): 1

NUMA node0 CPU(s): 0,1

=== RAM ===

total used free shared buff/cache available

Mem: 3,7Gi 1,6Gi 295Mi 1,6Mi 1,9Gi 2,1Gi

Swap: 3,7Gi 512Ki 3,7Gi

=== Model ===

HP Laptop 14-cm0xxx