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niloysh committed Nov 14, 2024
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6 changes: 6 additions & 0 deletions README.md
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Expand Up @@ -22,6 +22,7 @@ The figure above shows the conceptual architecture of Monarch. Monarch is design
- [Step 1: Deploy a 5G Network with Network Slicing Support](#step-1-deploy-a-5g-network-with-network-slicing-support)
- [Step 2: Verify Network Slice Deployment](#step-2-verify-network-slice-deployment)
- [Quick Start](#quick-start)
- [Detailed Deployment Guide](#detailed-deployment-guide)
- [Visualizing network slices KPIs using Monarch](#visualizing-network-slices-kpis-using-monarch)
- [Citation](#citation)
- [Contributions](#contributions)
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After deploying the 5G network, ensure that two network slices have been successfully configured by performing a [ping test to verify connectivity](https://github.com/niloysh/open5gs-k8s?tab=readme-ov-file#step-5-test-connectivity). This step confirms that the network is functioning correctly and is ready for Monarch deployment.

# Quick Start
To quickly set up the Monarch system, follow these steps:

```bash
git clone https://github.com/niloysh/5g-monarch.git
cd 5g-monarch
./deploy-all.sh
```
This script will deploy all core and external components needed for Monarch in a single step.

## Detailed Deployment Guide
For a step-by-step deployment process, including individual component setup and configuration, refer to the [deployment slides](https://niloysh.github.io/5g-monarch/slides.pdf).

# Visualizing network slices KPIs using Monarch

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4 changes: 2 additions & 2 deletions labs/lab3/README.md
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Expand Up @@ -24,7 +24,7 @@ We can query our metrics using Thanos Querier's HTTP API.
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# Using the Thanos HTTP API with Python (2/3)

1. Open [exercise.py](exercise.py): This file contains a skeleton of code for **Tasks 1 through 3**.
1. Open `labs/lab3/exercise.py`: This file contains a skeleton of code for **Tasks 1 through 3**.
2. Structure of the Exercise Code:
- `query_prometheus`: Sends a Prometheus query to the Thanos HTTP API.
- `parse_numeric_value_from_prometheus_response`: Parses numeric results from the API response.
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**Task**:
- Task 3 of [exercise.py](exercise.py) dives deeper into composing slice-level metrics, specifically focusing on calculating resource utilization for slice 1 (with `SNSSAI=1-000001`).
- Task 3 of `labs/lab3/exercise.py` dives deeper into composing slice-level metrics, specifically focusing on calculating resource utilization for slice 1 (with `SNSSAI=1-000001`).
- You'll combine multiple queries to determine memory usage, providing a practical understanding of how to build KPIs from various metric sources.

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