In macOS, we can use inbuilt Activity Monitor or third party apps like Stats to check the live CPU/RAM usage. But, we can't track the historical CPU & memory usage. sar, atop can track the historical CPU & memory usage. But, they are not available for macOS.

Netdata

Netdata¹ is an open source observability tool that can monitor CPU, RAM, network, disk usage. It can also track the historical data.

Unfortunately, it is not stable on macOS. I tried installing it on multiple macbooks, but it didn't work. I raised an issue² on their GitHub repository and the team mentioned that macOS is a low priority for them.

Glances

Glances³ is a cross-platform monitoring tool that can monitor CPU, RAM, network, disk usage. It can also track the historical data.

We can install it using Brew or pip.

$ brew install glances

$ pip install glances

Once it is installed, we can monitor the resource usage using the below command.

$ glances

Glances can log historical data to a file using the below command.

$ glances --export-csv /tmp/glances.csv

In addition to that, it can log data to services like influxdb, prometheus, etc.

Let's install influxdb and export stats to it.

$ brew install influxdb
$ brew services start influxdb
$ influx setup

$ python -m pip install influxdb-client

$ cat glances.conf
[influxdb]
host=localhost
port=8086
protocol=http
org=avilpage
bucket=glances
token=secret_token

$ glances --export-influxdb -C glances.conf

We can view stats in the influxdb from Data Explorer web UI at http://localhost:8086.

Glances provides a prebuilt Grafana dashboard⁴ that we can import to visualize the stats.

From Grafana -> Dashboard -> Import, we can import the dashboard using the above URL.

Conclusion

In addition to InfluxDB, Glances can export data to ~20 services. So far, it is the best tool to log, track and view historical CPU, RAM, network and disk usage in macOS. The same method works for Linux and Windows as well.

Introduction

Zscaler is a cloud-based security service that provides secure internet access via VPN. Unfortunately, Zscaler does not provide a command-line interface to connect to the VPN. We can't use AppleScript to automate the connectivity as well.

Automating Zscaler Connectivity

Once Zscaler is installed on macOS, if we search for LaunchAgents & LaunchDaemons directories, we can find the Zscaler plist files.

$ sudo find /Library/LaunchAgents -name '*zscaler*'
/Library/LaunchAgents/com.zscaler.tray.plist


$ sudo find /Library/LaunchDaemons -name '*zscaler*'
/Library/LaunchDaemons/com.zscaler.service.plist
/Library/LaunchDaemons/com.zscaler.tunnel.plist
/Library/LaunchDaemons/com.zscaler.UPMServiceController.plist

To connect to Zscaler, we can load these services.

#!/bin/bash

/usr/bin/open -a /Applications/Zscaler/Zscaler.app --hide
sudo find /Library/LaunchAgents -name '*zscaler*' -exec launchctl load {} \;
sudo find /Library/LaunchDaemons -name '*zscaler*' -exec launchctl load {} \;

To disconnect from Zscaler, we can unload all of them.

#!/bin/bash

sudo find /Library/LaunchAgents -name '*zscaler*' -exec launchctl unload {} \;
sudo find /Library/LaunchDaemons -name '*zscaler*' -exec launchctl unload {} \;

To automatically toggle the connectivity, we can create a shell script.

#!/bin/bash

if [[ $(pgrep -x Zscaler) ]]; then
    echo "Disconnecting from Zscaler"
    sudo find /Library/LaunchAgents -name '*zscaler*' -exec launchctl unload {} \;
    sudo find /Library/LaunchDaemons -name '*zscaler*' -exec launchctl unload {} \;
else
    echo "Connecting to Zscaler"
    /usr/bin/open -a /Applications/Zscaler/Zscaler.app --hide
    sudo find /Library/LaunchAgents -name '*zscaler*' -exec launchctl load {} \;
    sudo find /Library/LaunchDaemons -name '*zscaler*' -exec launchctl load {} \;
fi

Raycast is an alternative to default spotlight search on macOS. We can create a script to toggle connectivity to Zscaler.

#!/bin/bash

# Required parameters:
# @raycast.schemaVersion 1
# @raycast.title toggle zscaler
# @raycast.mode silent

# Optional parameters:
# @raycast.icon ☁️

# Documentation:
# @raycast.author chillaranand
# @raycast.authorURL https://avilpage.com/

if [[ $(pgrep -x Zscaler) ]]; then
    echo "Disconnecting from Zscaler"
    sudo find /Library/LaunchAgents -name '*zscaler*' -exec launchctl unload {} \;
    sudo find /Library/LaunchDaemons -name '*zscaler*' -exec launchctl unload {} \;
else
    echo "Connecting to Zscaler"
    /usr/bin/open -a /Applications/Zscaler/Zscaler.app --hide
    sudo find /Library/LaunchAgents -name '*zscaler*' -exec launchctl load {} \;
    sudo find /Library/LaunchDaemons -name '*zscaler*' -exec launchctl load {} \;
fi

Save this script to a folder. From Raycast Settings -> Extensions -> Add Script Directory, we can select this folder, and the script will be available in Raycast.

We can assign a shortcut key to the script for quick access.

Conclusion

Even though Zscaler does not provide a command-line interface, we can automate the connectivity using the above scripts.

Introduction

Activity Watch¹ is a cross-platform open-source time-tracking tool that helps us to track time spent on applications and websites.

At the moment, Activity Watch doesn't have any feature to show screen time alerts. In this post, we will see how to show screen time alerts using Activity Watch.

Python Script

Activity Watch provides an API to interact with the Activity Watch server. We can use the API to get the screen time data and show alerts.

import json
import os
from datetime import datetime

import requests


def get_nonafk_events(timeperiods=None):
    headers = {"Content-type": "application/json", "charset": "utf-8"}
    query = """afk_events = query_bucket(find_bucket('aw-watcher-afk_'));
window_events = query_bucket(find_bucket('aw-watcher-window_'));
window_events = filter_period_intersect(window_events, filter_keyvals(afk_events, 'status', ['not-afk']));
RETURN = merge_events_by_keys(window_events, ['app', 'title']);""".split("\n")
    data = {
        "timeperiods": timeperiods,
        "query": query,
    }
    r = requests.post(
        "http://localhost:5600/api/0/query/",
        data=bytes(json.dumps(data), "utf-8"),
        headers=headers,
        params={},
    )
    return json.loads(r.text)[0]


def main():
    now = datetime.now()
    timeperiods = [
        "/".join([now.replace(hour=0, minute=0, second=0).isoformat(), now.isoformat()])
    ]
    events = get_nonafk_events(timeperiods)

    total_time_secs = sum([event["duration"] for event in events])
    total_time_mins = total_time_secs / 60
    print(f"Total time: {total_time_mins} seconds")
    hours, minutes = divmod(total_time_mins, 60)
    minutes = round(minutes)
    print(f"Screen Time: {hours} hours {minutes} minutes")

    # show mac notification
    os.system(f"osascript -e 'display notification \"{hours} hours {minutes} minutes\" with title \"Screen TIme\"'")


if __name__ == "__main__":
    main()

This script² will show the screen time alerts using the Activity Watch API. We can run this script using the below command.

$ python screen_time_alerts.py

We can set up a cron job to run this script every hour to show screen time alerts.

$ crontab -e
0 * * * * python screen_time_alerts.py

We can also modify the script to show alerts only when the screen time exceeds a certain limit.

Conclusion

Since Actvity Watch is open-source and provides an API, we can extend its functionality to show screen time alerts. We can also use the API to create custom reports and dashboards.