Add all assessment files
هذا الالتزام موجود في:
21
common-qabilah/qabilah-profile.txt
Normal file
21
common-qabilah/qabilah-profile.txt
Normal file
@@ -0,0 +1,21 @@
|
||||
Name: Mohamed Wael
|
||||
|
||||
Track: SRE Internship
|
||||
|
||||
GitHub Repository:
|
||||
ghaymah-exam-mohamed-wael-sre
|
||||
|
||||
Qabilah Profile:
|
||||
https://qabilah.com/profile/moxwael
|
||||
|
||||
Skills:
|
||||
- Linux
|
||||
- Docker
|
||||
- Kubernetes
|
||||
- AWS
|
||||
- Terraform
|
||||
- GitHub Actions
|
||||
- Prometheus
|
||||
- Grafana
|
||||
- Python
|
||||
- Monitoring
|
||||
15
q1-deploy-monitor/Dashboard
Normal file
15
q1-deploy-monitor/Dashboard
Normal file
@@ -0,0 +1,15 @@
|
||||
FROM python:3.12-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
COPY requirements.txt .
|
||||
|
||||
RUN pip install --no-cache-dir -r requirements.txt
|
||||
|
||||
COPY . .
|
||||
|
||||
RUN chmod +x start.sh
|
||||
|
||||
EXPOSE 5000
|
||||
|
||||
CMD ["./start.sh"]
|
||||
111
q1-deploy-monitor/dashboard.html
Normal file
111
q1-deploy-monitor/dashboard.html
Normal file
@@ -0,0 +1,111 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>SRE Dashboard</title>
|
||||
|
||||
<style>
|
||||
|
||||
body{
|
||||
font-family:Arial,Helvetica,sans-serif;
|
||||
background:#f4f4f4;
|
||||
margin:30px;
|
||||
}
|
||||
|
||||
h1{
|
||||
text-align:center;
|
||||
color:#333;
|
||||
}
|
||||
|
||||
table{
|
||||
width:100%;
|
||||
border-collapse:collapse;
|
||||
background:white;
|
||||
box-shadow:0 2px 6px rgba(0,0,0,.15);
|
||||
}
|
||||
|
||||
th{
|
||||
background:#1976d2;
|
||||
color:white;
|
||||
padding:12px;
|
||||
}
|
||||
|
||||
td{
|
||||
padding:10px;
|
||||
text-align:center;
|
||||
border-bottom:1px solid #ddd;
|
||||
}
|
||||
|
||||
tr:nth-child(even){
|
||||
background:#f9f9f9;
|
||||
}
|
||||
|
||||
</style>
|
||||
|
||||
</head>
|
||||
|
||||
<body>
|
||||
|
||||
<h1>API Monitoring Dashboard</h1>
|
||||
|
||||
<table>
|
||||
|
||||
<thead>
|
||||
|
||||
<tr>
|
||||
|
||||
<th>Timestamp</th>
|
||||
<th>Status</th>
|
||||
<th>Response Time</th>
|
||||
|
||||
</tr>
|
||||
|
||||
</thead>
|
||||
|
||||
<tbody id="table-body">
|
||||
|
||||
</tbody>
|
||||
|
||||
</table>
|
||||
|
||||
<script>
|
||||
|
||||
async function loadData(){
|
||||
|
||||
const response = await fetch("/metrics");
|
||||
|
||||
const data = await response.json();
|
||||
|
||||
const table = document.getElementById("table-body");
|
||||
|
||||
table.innerHTML = "";
|
||||
|
||||
data.reverse().forEach(item=>{
|
||||
|
||||
const parts = item.split("|");
|
||||
|
||||
table.innerHTML += `
|
||||
|
||||
<tr>
|
||||
|
||||
<td>${parts[0]}</td>
|
||||
<td>${parts[1]}</td>
|
||||
<td>${parts[2]}</td>
|
||||
|
||||
</tr>
|
||||
|
||||
`;
|
||||
|
||||
});
|
||||
|
||||
}
|
||||
|
||||
loadData();
|
||||
|
||||
setInterval(loadData,30000);
|
||||
|
||||
</script>
|
||||
|
||||
</body>
|
||||
</html>
|
||||
13
q1-deploy-monitor/health-check.sh
Normal file
13
q1-deploy-monitor/health-check.sh
Normal file
@@ -0,0 +1,13 @@
|
||||
#!/bin/bash
|
||||
|
||||
URL="http://localhost:5000/health"
|
||||
|
||||
STATUS=$(curl -s -o /dev/null -w "%{http_code}" "$URL")
|
||||
|
||||
if [ "$STATUS" -eq 200 ]; then
|
||||
echo "Healthy"
|
||||
exit 0
|
||||
else
|
||||
echo "Unhealthy"
|
||||
exit 1
|
||||
fi
|
||||
123
q2-postmortem/postmortem-report.md
Normal file
123
q2-postmortem/postmortem-report.md
Normal file
@@ -0,0 +1,123 @@
|
||||
# Incident Postmortem Report
|
||||
|
||||
## Incident Summary
|
||||
|
||||
On 27 July 2026, an application deployed on the Ghaymah platform experienced repeated **OOMKilled** events, resulting in approximately **45 minutes of downtime**. During this period, users were unable to access the service because the application pods kept restarting after exceeding their memory limit.
|
||||
|
||||
---
|
||||
|
||||
# Timeline
|
||||
|
||||
| Time | Event |
|
||||
|------|-------|
|
||||
| 10:00 | A new application version was deployed. |
|
||||
| 10:08 | Memory usage began increasing steadily. |
|
||||
| 10:12 | The first pod was terminated with an **OOMKilled** event. |
|
||||
| 10:15 | Kubernetes automatically restarted the pod. |
|
||||
| 10:18 – 10:40 | The application entered a restart loop as multiple pods were repeatedly OOMKilled. |
|
||||
| 10:42 | The SRE team investigated pod events, logs, and resource metrics. |
|
||||
| 10:45 | Memory limits were increased temporarily, and the application's memory usage was reviewed. |
|
||||
| 10:47 | A new healthy pod started successfully. |
|
||||
| 10:55 | The service was fully restored and became available to users again. |
|
||||
|
||||
---
|
||||
|
||||
# Root Cause
|
||||
|
||||
The application gradually consumed more memory than the Kubernetes memory limit that had been configured for the container. Once the limit was exceeded, Kubernetes terminated the container with an **OOMKilled** event.
|
||||
|
||||
Although Kubernetes restarted the pod automatically, the application continued to exceed its memory limit after each restart. This created a restart loop that kept the service unavailable until the memory issue was addressed.
|
||||
|
||||
---
|
||||
|
||||
# Impact
|
||||
|
||||
- Approximately **45 minutes** of service downtime.
|
||||
- Multiple pod restarts due to repeated **OOMKilled** events.
|
||||
- Users experienced failed requests and service unavailability.
|
||||
- Increased operational effort to investigate and restore the application.
|
||||
|
||||
---
|
||||
|
||||
# Resolution
|
||||
|
||||
The incident was resolved by:
|
||||
|
||||
- Investigating Kubernetes pod events and application logs.
|
||||
- Identifying excessive memory consumption.
|
||||
- Increasing the container memory limit temporarily.
|
||||
- Restarting the affected pods.
|
||||
- Verifying that the application returned to a healthy state.
|
||||
|
||||
---
|
||||
|
||||
# Recommendations
|
||||
|
||||
To reduce the likelihood of similar incidents:
|
||||
|
||||
- Configure appropriate CPU and memory requests and limits.
|
||||
- Enable Horizontal Pod Autoscaler (HPA).
|
||||
- Create alerts for high memory utilization.
|
||||
- Monitor pod restart counts and OOMKilled events.
|
||||
- Perform load testing before deploying new releases.
|
||||
- Review application memory usage regularly to identify potential memory leaks.
|
||||
|
||||
---
|
||||
|
||||
# Auto-Scaling Policy for Ghaymah Platform
|
||||
|
||||
To prevent similar incidents, the platform should automatically scale the application based on resource utilization.
|
||||
|
||||
## Horizontal Pod Autoscaler (HPA)
|
||||
|
||||
- Minimum replicas: **2**
|
||||
- Maximum replicas: **10**
|
||||
|
||||
### Scaling Rules
|
||||
|
||||
- Scale out when CPU utilization exceeds **70%**.
|
||||
- Scale out when memory utilization exceeds **75%**.
|
||||
- Scale in only after resource utilization remains below **40%** for several minutes to avoid frequent scaling.
|
||||
|
||||
This policy helps distribute incoming traffic across multiple pods before any single container reaches its memory limit.
|
||||
|
||||
---
|
||||
|
||||
# Early Detection Using Ghaymah Monitoring
|
||||
|
||||
The issue can be detected before it causes downtime by continuously monitoring application and Kubernetes metrics.
|
||||
|
||||
## Key Metrics
|
||||
|
||||
- Container memory usage
|
||||
- Memory utilization percentage
|
||||
- CPU utilization
|
||||
- Pod restart count
|
||||
- OOMKilled events
|
||||
- API response time
|
||||
- HTTP 5xx error rate
|
||||
- Application availability
|
||||
|
||||
## Alerting Rules
|
||||
|
||||
Create alerts when:
|
||||
|
||||
- Memory utilization exceeds **80%** for more than 5 minutes.
|
||||
- A pod restarts more than **3 times** within 10 minutes.
|
||||
- An **OOMKilled** event occurs.
|
||||
- API response time exceeds the defined threshold.
|
||||
- Service availability drops below the expected level.
|
||||
|
||||
## Dashboard
|
||||
|
||||
A monitoring dashboard should display:
|
||||
|
||||
- CPU usage
|
||||
- Memory usage
|
||||
- Running pods
|
||||
- Pod restart count
|
||||
- Request rate
|
||||
- Response time
|
||||
- Active alerts
|
||||
|
||||
With these metrics and alerts in place, the operations team can detect abnormal memory growth early and take corrective action before users are affected.
|
||||
86
q3-cicd/workflow.yml
Normal file
86
q3-cicd/workflow.yml
Normal file
@@ -0,0 +1,86 @@
|
||||
name: Build & Deploy to Ghaymah
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
|
||||
jobs:
|
||||
build-and-push:
|
||||
name: Build and Push Docker Image
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: Checkout Source Code
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Build Docker Image
|
||||
run: |
|
||||
docker build -t ghaymah-app:${{ github.sha }} .
|
||||
|
||||
# Login to Ghaymah Container Registry
|
||||
# Store credentials as GitHub Secrets
|
||||
- name: Login to Ghaymah Registry
|
||||
run: |
|
||||
echo "${{ secrets.GHAYMAH_REGISTRY_PASSWORD }}" | docker login ${{ secrets.GHAYMAH_REGISTRY }} \
|
||||
-u "${{ secrets.GHAYMAH_REGISTRY_USERNAME }}" \
|
||||
--password-stdin
|
||||
|
||||
- name: Tag Docker Image
|
||||
run: |
|
||||
docker tag ghaymah-app:${{ github.sha }} \
|
||||
${{ secrets.GHAYMAH_REGISTRY }}/ghaymah-app:${{ github.sha }}
|
||||
|
||||
- name: Push Docker Image
|
||||
run: |
|
||||
docker push \
|
||||
${{ secrets.GHAYMAH_REGISTRY }}/ghaymah-app:${{ github.sha }}
|
||||
|
||||
deploy-staging:
|
||||
name: Deploy to Staging
|
||||
needs: build-and-push
|
||||
runs-on: ubuntu-latest
|
||||
environment: staging
|
||||
|
||||
steps:
|
||||
- name: Checkout Repository
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Install Ghaymah CLI
|
||||
run: |
|
||||
curl -sSl https://cli.ghaymah.systems/install.sh | bash
|
||||
|
||||
- name: Login to Ghaymah
|
||||
run: |
|
||||
gy auth login --token "${{ secrets.GHAYMAH_API_TOKEN }}"
|
||||
|
||||
- name: Deploy to Staging
|
||||
run: |
|
||||
gy resource app launch
|
||||
|
||||
deploy-production:
|
||||
name: Deploy to Production
|
||||
needs: deploy-staging
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
# Configure this environment in GitHub:
|
||||
# Settings → Environments → production
|
||||
# Add Required Reviewers to enable manual approval.
|
||||
environment:
|
||||
name: production
|
||||
|
||||
steps:
|
||||
- name: Checkout Repository
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Install Ghaymah CLI
|
||||
run: |
|
||||
curl -sSl https://cli.ghaymah.systems/install.sh | bash
|
||||
|
||||
- name: Login to Ghaymah
|
||||
run: |
|
||||
gy auth login --token "${{ secrets.GHAYMAH_API_TOKEN }}"
|
||||
|
||||
- name: Deploy to Production
|
||||
run: |
|
||||
gy resource app launch
|
||||
ثنائية
q4-scalability/architecture.png
Normal file
ثنائية
q4-scalability/architecture.png
Normal file
ملف ثنائي غير معروض.
|
بعد العرض: | الارتفاع: | الحجم: 1.4 MiB |
66
q4-scalability/calculations.md
Normal file
66
q4-scalability/calculations.md
Normal file
@@ -0,0 +1,66 @@
|
||||
# Scalability Design
|
||||
|
||||
## 1. Architecture
|
||||
|
||||
The application is deployed on a Kubernetes cluster hosted on Ghaymah Cloud.
|
||||
|
||||
Incoming traffic is distributed through a Ghaymah Load Balancer across multiple application containers. The application stores persistent data using Ghaymah Block Storage, which is mounted as a Persistent Volume.
|
||||
|
||||
---
|
||||
|
||||
## 2. Required Number of Containers
|
||||
|
||||
### Given
|
||||
|
||||
- Incoming traffic = **15,000 requests/second**
|
||||
- One container handles = **500 requests/second**
|
||||
- Safety margin = **30%**
|
||||
|
||||
### Step 1
|
||||
|
||||
Base number of containers
|
||||
|
||||
15000 / 500 = 30 containers
|
||||
|
||||
### Step 2
|
||||
|
||||
Add 30% capacity
|
||||
|
||||
30 × 1.3 = 39 containers
|
||||
|
||||
### Final Answer
|
||||
|
||||
**39 containers**
|
||||
|
||||
---
|
||||
|
||||
## 3. Cold Start Strategy
|
||||
|
||||
To reduce startup latency for newly created containers:
|
||||
|
||||
- Keep a minimum number of warm replicas running.
|
||||
- Use Kubernetes readiness probes before routing traffic.
|
||||
- Pull container images in advance on cluster nodes.
|
||||
- Use Horizontal Pod Autoscaler (HPA) to scale before traffic reaches peak levels.
|
||||
- Deploy applications with rolling updates to avoid downtime.
|
||||
|
||||
---
|
||||
|
||||
## 4. Using Ghaymah Block Storage
|
||||
|
||||
Ghaymah Block Storage provides persistent storage for stateful workloads.
|
||||
|
||||
Typical use cases include:
|
||||
|
||||
- Databases
|
||||
- PostgreSQL
|
||||
- MySQL
|
||||
- Redis persistence
|
||||
- Application uploaded files
|
||||
- Persistent logs
|
||||
|
||||
Benefits:
|
||||
|
||||
- Data persists even if a container is recreated.
|
||||
- Storage can be attached to new containers.
|
||||
- Reliable and durable storage for production workloads.
|
||||
292
q5-mithal-monitor/dashboard.html
Normal file
292
q5-mithal-monitor/dashboard.html
Normal file
@@ -0,0 +1,292 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>Mithal Monitoring Dashboard</title>
|
||||
|
||||
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
|
||||
|
||||
<style>
|
||||
|
||||
body{
|
||||
font-family:Arial,sans-serif;
|
||||
background:#f4f6f8;
|
||||
margin:30px;
|
||||
}
|
||||
|
||||
h1{
|
||||
text-align:center;
|
||||
color:#333;
|
||||
}
|
||||
|
||||
.cards{
|
||||
display:flex;
|
||||
gap:20px;
|
||||
margin-bottom:25px;
|
||||
}
|
||||
|
||||
.card{
|
||||
flex:1;
|
||||
background:white;
|
||||
padding:20px;
|
||||
border-radius:10px;
|
||||
box-shadow:0 2px 6px rgba(0,0,0,.15);
|
||||
text-align:center;
|
||||
}
|
||||
|
||||
.card h2{
|
||||
margin:0;
|
||||
color:#666;
|
||||
}
|
||||
|
||||
.card p{
|
||||
font-size:28px;
|
||||
margin-top:15px;
|
||||
color:#1976d2;
|
||||
font-weight:bold;
|
||||
}
|
||||
|
||||
.chart-container{
|
||||
background:white;
|
||||
padding:20px;
|
||||
border-radius:10px;
|
||||
box-shadow:0 2px 6px rgba(0,0,0,.15);
|
||||
}
|
||||
|
||||
table{
|
||||
|
||||
width:100%;
|
||||
margin-top:30px;
|
||||
border-collapse:collapse;
|
||||
background:white;
|
||||
box-shadow:0 2px 6px rgba(0,0,0,.15);
|
||||
|
||||
}
|
||||
|
||||
th{
|
||||
|
||||
background:#1976d2;
|
||||
color:white;
|
||||
padding:10px;
|
||||
|
||||
}
|
||||
|
||||
td{
|
||||
|
||||
text-align:center;
|
||||
padding:10px;
|
||||
border-bottom:1px solid #ddd;
|
||||
|
||||
}
|
||||
|
||||
.up{
|
||||
|
||||
color:green;
|
||||
font-weight:bold;
|
||||
|
||||
}
|
||||
|
||||
.down{
|
||||
|
||||
color:red;
|
||||
font-weight:bold;
|
||||
|
||||
}
|
||||
|
||||
</style>
|
||||
|
||||
</head>
|
||||
|
||||
<body>
|
||||
|
||||
<h1>Mithal Monitoring Dashboard</h1>
|
||||
|
||||
<div class="cards">
|
||||
|
||||
<div class="card">
|
||||
|
||||
<h2>Uptime (24h)</h2>
|
||||
|
||||
<p id="uptime">--</p>
|
||||
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
|
||||
<h2>SSL Remaining</h2>
|
||||
|
||||
<p id="ssl">--</p>
|
||||
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
|
||||
<h2>Latest Latency</h2>
|
||||
|
||||
<p id="latency">--</p>
|
||||
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
<div class="chart-container">
|
||||
|
||||
<canvas id="chart"></canvas>
|
||||
|
||||
</div>
|
||||
|
||||
<h2>Last 10 Checks</h2>
|
||||
|
||||
<table>
|
||||
|
||||
<thead>
|
||||
|
||||
<tr>
|
||||
|
||||
<th>Time</th>
|
||||
|
||||
<th>Status</th>
|
||||
|
||||
<th>Latency</th>
|
||||
|
||||
<th>DNS</th>
|
||||
|
||||
<th>Search</th>
|
||||
|
||||
<th>SSL Days</th>
|
||||
|
||||
</tr>
|
||||
|
||||
</thead>
|
||||
|
||||
<tbody id="tableBody">
|
||||
|
||||
</tbody>
|
||||
|
||||
</table>
|
||||
|
||||
<script>
|
||||
|
||||
let chart=null;
|
||||
|
||||
async function refresh(){
|
||||
|
||||
const response=await fetch("/api/data");
|
||||
|
||||
const data=await response.json();
|
||||
|
||||
if(data.length===0)
|
||||
return;
|
||||
|
||||
const last=data[data.length-1];
|
||||
|
||||
document.getElementById("latency").innerHTML=
|
||||
last.latency_ms+" ms";
|
||||
|
||||
document.getElementById("ssl").innerHTML=
|
||||
last.ssl_remaining_days+" days";
|
||||
|
||||
const success=data.filter(x=>x.uptime).length;
|
||||
|
||||
const uptime=((success/data.length)*100).toFixed(2);
|
||||
|
||||
document.getElementById("uptime").innerHTML=
|
||||
uptime+"%";
|
||||
|
||||
const hour=data.slice(-60);
|
||||
|
||||
const labels=hour.map(x=>x.timestamp.substring(11));
|
||||
|
||||
const values=hour.map(x=>x.latency_ms);
|
||||
|
||||
if(chart)
|
||||
chart.destroy();
|
||||
|
||||
chart=new Chart(
|
||||
|
||||
document.getElementById("chart"),
|
||||
|
||||
{
|
||||
|
||||
type:"line",
|
||||
|
||||
data:{
|
||||
|
||||
labels:labels,
|
||||
|
||||
datasets:[{
|
||||
|
||||
label:"Latency (ms)",
|
||||
|
||||
data:values,
|
||||
|
||||
borderWidth:2,
|
||||
|
||||
fill:false
|
||||
|
||||
}]
|
||||
|
||||
},
|
||||
|
||||
options:{
|
||||
|
||||
responsive:true,
|
||||
|
||||
plugins:{
|
||||
|
||||
legend:{
|
||||
display:true
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
);
|
||||
|
||||
const tbody=document.getElementById("tableBody");
|
||||
|
||||
tbody.innerHTML="";
|
||||
|
||||
data.slice(-10).reverse().forEach(item=>{
|
||||
|
||||
tbody.innerHTML+=`
|
||||
|
||||
<tr>
|
||||
|
||||
<td>${item.timestamp}</td>
|
||||
|
||||
<td class="${item.uptime?'up':'down'}">
|
||||
|
||||
${item.uptime?'UP':'DOWN'}
|
||||
|
||||
</td>
|
||||
|
||||
<td>${item.latency_ms} ms</td>
|
||||
|
||||
<td>${item.dns_ms} ms</td>
|
||||
|
||||
<td>${item.search_latency_ms} ms</td>
|
||||
|
||||
<td>${item.ssl_remaining_days}</td>
|
||||
|
||||
</tr>
|
||||
|
||||
`;
|
||||
|
||||
});
|
||||
|
||||
}
|
||||
|
||||
refresh();
|
||||
|
||||
setInterval(refresh,60000);
|
||||
|
||||
</script>
|
||||
|
||||
</body>
|
||||
|
||||
</html>
|
||||
177
q5-mithal-monitor/monitor.py
Normal file
177
q5-mithal-monitor/monitor.py
Normal file
@@ -0,0 +1,177 @@
|
||||
import requests
|
||||
import socket
|
||||
import ssl
|
||||
import json
|
||||
import time
|
||||
import threading
|
||||
from datetime import datetime
|
||||
from flask import Flask, jsonify, send_from_directory
|
||||
|
||||
app = Flask(__name__)
|
||||
|
||||
BASE_URL = "https://mithal.space"
|
||||
SEARCH_URL = "https://mithal.space/search?q=test"
|
||||
|
||||
DATA_FILE = "monitor_data.json"
|
||||
|
||||
CHECK_INTERVAL = 60
|
||||
|
||||
|
||||
def load_data():
|
||||
try:
|
||||
with open(DATA_FILE, "r") as f:
|
||||
return json.load(f)
|
||||
except:
|
||||
return []
|
||||
|
||||
|
||||
def save_data(data):
|
||||
with open(DATA_FILE, "w") as f:
|
||||
json.dump(data, f, indent=4)
|
||||
|
||||
|
||||
def get_latency():
|
||||
start = time.time()
|
||||
|
||||
response = requests.get(BASE_URL, timeout=10)
|
||||
|
||||
latency = round((time.time() - start) * 1000, 2)
|
||||
|
||||
return latency, response.status_code
|
||||
|
||||
|
||||
def get_dns_time():
|
||||
|
||||
start = time.time()
|
||||
|
||||
socket.gethostbyname("mithal.space")
|
||||
|
||||
return round((time.time() - start) * 1000, 2)
|
||||
|
||||
|
||||
def get_ssl_info():
|
||||
|
||||
hostname = "mithal.space"
|
||||
|
||||
context = ssl.create_default_context()
|
||||
|
||||
with context.wrap_socket(
|
||||
socket.socket(),
|
||||
server_hostname=hostname
|
||||
) as s:
|
||||
|
||||
s.settimeout(10)
|
||||
|
||||
s.connect((hostname, 443))
|
||||
|
||||
cert = s.getpeercert()
|
||||
|
||||
expiry = datetime.strptime(
|
||||
cert["notAfter"],
|
||||
"%b %d %H:%M:%S %Y %Z"
|
||||
)
|
||||
|
||||
remaining = (expiry - datetime.utcnow()).days
|
||||
|
||||
return expiry.strftime("%Y-%m-%d"), remaining
|
||||
|
||||
|
||||
def get_search_latency():
|
||||
|
||||
start = time.time()
|
||||
|
||||
response = requests.get(
|
||||
SEARCH_URL,
|
||||
timeout=10
|
||||
)
|
||||
|
||||
latency = round((time.time() - start) * 1000, 2)
|
||||
|
||||
return latency, response.status_code
|
||||
|
||||
def monitor():
|
||||
|
||||
while True:
|
||||
|
||||
try:
|
||||
|
||||
latency, status = get_latency()
|
||||
|
||||
dns = get_dns_time()
|
||||
|
||||
ssl_expiry, ssl_days = get_ssl_info()
|
||||
|
||||
search_latency, search_status = get_search_latency()
|
||||
|
||||
entry = {
|
||||
|
||||
"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
|
||||
|
||||
"uptime": status == 200,
|
||||
|
||||
"status_code": status,
|
||||
|
||||
"latency_ms": latency,
|
||||
|
||||
"dns_ms": dns,
|
||||
|
||||
"ssl_expiry": ssl_expiry,
|
||||
|
||||
"ssl_remaining_days": ssl_days,
|
||||
|
||||
"search_latency_ms": search_latency,
|
||||
|
||||
"search_status": search_status
|
||||
|
||||
}
|
||||
|
||||
data = load_data()
|
||||
|
||||
data.append(entry)
|
||||
|
||||
data = data[-1440:]
|
||||
|
||||
save_data(data)
|
||||
|
||||
print(entry)
|
||||
|
||||
except Exception as e:
|
||||
|
||||
print("Monitoring Error:", e)
|
||||
|
||||
time.sleep(CHECK_INTERVAL)
|
||||
|
||||
|
||||
@app.route("/api/data")
|
||||
def api_data():
|
||||
|
||||
return jsonify(load_data())
|
||||
|
||||
|
||||
@app.route("/")
|
||||
def home():
|
||||
|
||||
return {
|
||||
"message": "Mithal Monitoring API",
|
||||
"dashboard": "/dashboard"
|
||||
}
|
||||
|
||||
|
||||
@app.route("/dashboard")
|
||||
def dashboard():
|
||||
|
||||
return send_from_directory(".", "dashboard.html")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
thread = threading.Thread(target=monitor)
|
||||
|
||||
thread.daemon = True
|
||||
|
||||
thread.start()
|
||||
|
||||
app.run(
|
||||
host="0.0.0.0",
|
||||
port=5002
|
||||
)
|
||||
13
q5-mithal-monitor/monitor_data.json
Normal file
13
q5-mithal-monitor/monitor_data.json
Normal file
@@ -0,0 +1,13 @@
|
||||
[
|
||||
{
|
||||
"timestamp": "2026-07-28 15:09:54",
|
||||
"uptime": true,
|
||||
"status_code": 200,
|
||||
"latency_ms": 1388.97,
|
||||
"dns_ms": 65.85,
|
||||
"ssl_expiry": "2026-09-15",
|
||||
"ssl_remaining_days": 49,
|
||||
"search_latency_ms": 1204.14,
|
||||
"search_status": 200
|
||||
}
|
||||
]
|
||||
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