Adding Benchmark section to our documentation page

.github/workflows/download_svgs.yml

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+name: Download SVGs
+
+on:
+  workflow_dispatch: # You can trigger the workflow manually, or set it on a schedule.
+
+jobs:
+  download-svgs:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+
+      - name: Set up Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: '3.x'  # Use Python 3.x
+
+      - name: Install dependencies
+        run: |
+          pip install requests
+
+      - name: Run download_svgs.py
+        env:
+          MUNIN_USERNAME: ${{ secrets.MUNIN_USERNAME }}
+          MUNIN_PASSWORD: ${{ secrets.MUNIN_PASSWORD }}
+        run: |
+          python3 /scripts/download_svgs.py

docs/src/benchmarks/index.md

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+---
+title: Benchmarks
+sidebar_position: 10
+---
+
+# Benchmarks
+
+This section contains performance benchmarks for ThinEdge.io, including detailed CPU and memory usage for key processes, measured on a device running in the OSADL QA Farm.
+
+## Hardware Information
+
+The following hardware and software specifications describe the environment in which these benchmarks are measured. The device runs ThinEdge.io and its associated plugins for data collection.
+
+| Component      | Specification                                                 |
+|----------------|---------------------------------------------------------------|
+| **Processor**  | Quad-core ARM Cortex-A72 (ARM v8)                             |
+| **Memory**     | 1.8 GB RAM                                                    |
+| **Operating System** | Debian GNU/Linux 12 (bookworm)                          |
+| **MQTT Broker**| Mosquitto (v2.0.18)                                           |
+| **Firmware**   | ThinEdge.io (v1.1.2)                                          |
+| **Plugins Used** | `tedgecpuprocent`, `memory`, `tedge-agent`, `tedge-mapper`  |
+
+> The device is a Raspberry Pi 4 Model B Rev 1.5, a member of the OSADL QA Farm, which continuously collects data on performance and resource consumption.
+
+## CPU Run-time Consumption of Key ThinEdge.io Tasks
+
+In this section, we monitor the CPU usage of the most critical ThinEdge.io tasks: `mosquitto`, `tedge-agent`, and `tedge-mapper`. These tasks are essential for device-to-cloud communication, and their performance is crucial for the overall efficiency of the system.
+
+### Graph of CPU Usage
+
+Below is a visual representation of the CPU consumption by the main ThinEdge.io processes over the past month.
+
+![CPU Usage](./tedgecpuprocent-month.svg)
+
+For each process, the graph shows:
+- **Command Name (comm)**: The name of the task running on the device.
+- **CPU Usage (cuc)**: The percentage of CPU time utilized by each process.
+
+
+The graph allows you to visually track CPU performance trends and identify potential bottlenecks in the system.
+
+### Detailed Metrics
+
+The following table provides a detailed description of the CPU consumption of measured tasks:
+
+| Task                 | Description                                                    |
+|----------------------|----------------------------------------------------------------|
+| `mosquitto`          | Handles MQTT communications between devices and cloud          |
+| `tedge-agent`        | Coordinates device management, software updates, and telemetry |
+| `tedge-mapper_c8y`   | Converts telemetry data into the format required by cloud      |
+| `tedge-mapper-colle` | Converts telemetry data into the format required               |
+
+> Note: The values in this table are updated dynamically once per month.
+
+
+## Memory Usage
+
+In this section, we monitor the memory consumption of key ThinEdge.io components to ensure efficient performance and to view how the system memory is being utilized.
+
+### Graph of Memory Usage
+
+Below is a visual representation of the memory consumption of ThinEdge.io tasks over the past month.
+
+![Memory Usage](./tedgemem-month.svg)
+
+### Monitored Metrics:
+- **Mosquitto Memory Usage**: Tracks the memory consumed by the mosquitto process, which manages MQTT messages and connections.
+- **Tedge-Agent Memory Usage**: Tracks the memory consumed by the tedge-agent process, which handles software updates, configurations, and telemetry operations.
+- **Tedge-Mapper Memory Usage**: Tracks the memory consumed by the tedge-mapper process, which converts telemetry data between MQTT and other protocols (e.g., Cumulocity, AWS). For multi-instance tedge-mapper, each instance is tracked individually.
+
+For each metric, the graph shows the current and historical values, allowing you to monitor how memory is utilized by the system.
+
+### Detailed Metrics
+
+The following table provides a description of memory usage metrics:
+
+| Metric                   | Description                                                                 |
+|--------------------------|-----------------------------------------------------------------------------|
+| **Mosquitto Memory**     | Memory used by the mosquitto process, which manages MQTT messages and connections. |
+| **Tedge-Agent Memory**   | Memory used by the tedge-agent process, responsible for software updates, configurations, and telemetry operations |
+| **Tedge-Mapper Memory**  | Memory used by the tedge-mapper process, which converts telemetry data between MQTT and other protocols (e.g., Cumulocity, AWS). Each instance of tedge-mapper is monitored individually if multiple instances exist |
+
+
+> The values in this table are updated dynamically once per month.
+
+By monitoring these metrics, we can ensure that the system is using memory efficiently, and we can detect potential memory leaks or bottlenecks in the system's operation.
+
+---
+
+This section now contains all relevant memory metrics for ThinEdge tasks, helping you track and analyze how resources are allocated and used by mosquitto, tedge-agent, and tedge-mapper over time. These benchmarks are crucial for maintaining optimal performance of ThinEdge.io components and ensuring efficient memory usage across the system.