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Lära Monitoring Blockchain Services | DevOps for Blockchain Applications
Blockchain Foundations with Python

bookMonitoring Blockchain Services

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Monitoring is a crucial aspect of maintaining healthy and reliable blockchain services. By observing key metrics, you can quickly detect issues and ensure nodes remain responsive and available. When monitoring blockchain nodes, focus on metrics such as uptime, which measures how long a node has been operational; response time, which indicates how quickly a node replies to requests; synchronization status, to verify the node is up-to-date with the network; peer count, showing how well-connected the node is; and error rates, which can highlight underlying problems. Consistent tracking of these metrics helps you identify performance bottlenecks, network partitions, or outages before they affect users.

import requests
import time
import logging

logging.basicConfig(filename="node_monitor.log", level=logging.INFO)

NODE_URL = "http://localhost:8545"

def check_node_status():
    try:
        start_time = time.time()
        response = requests.post(NODE_URL, json={
            "jsonrpc":"2.0",
            "method":"web3_clientVersion",
            "params":[],
            "id":1
        }, timeout=5)
        elapsed = time.time() - start_time
        if response.status_code == 200:
            logging.info(f"Node is UP | Response time: {elapsed:.3f} seconds")
            return True, elapsed
        else:
            logging.warning("Node returned non-200 status code.")
            return False, None
    except Exception as e:
        logging.error(f"Node is DOWN | Exception: {e}")
        return False, None

if __name__ == "__main__":
    status, resp_time = check_node_status()
    print(f"Node status: {'UP' if status else 'DOWN'}")
    if resp_time:
        print(f"Response time: {resp_time:.3f} seconds")

To make your monitoring more effective, integrate your Python monitoring scripts with notification services. This way, if a node goes down or a performance metric crosses a threshold, you receive real-time alerts via channels like email, SMS, or chat apps. Integration ensures you can respond promptly to incidents, reducing downtime and improving reliability. Many notification services offer APIs that you can call from Python when an alert condition is detected.

import smtplib
from email.mime.text import MIMEText

ALERT_EMAIL = "admin@example.com"
SMTP_SERVER = "smtp.example.com"
SMTP_PORT = 587
SMTP_USER = "alertbot@example.com"
SMTP_PASS = "yourpassword"

def send_alert(subject, body):
    msg = MIMEText(body)
    msg["Subject"] = subject
    msg["From"] = SMTP_USER
    msg["To"] = ALERT_EMAIL

    with smtplib.SMTP(SMTP_SERVER, SMTP_PORT) as server:
        server.starttls()
        server.login(SMTP_USER, SMTP_PASS)
        server.send_message(msg)

# Reuse check_node_status from the previous code sample
if __name__ == "__main__":
    status, resp_time = check_node_status()
    if not status:
        send_alert(
            subject="Blockchain Node Down",
            body="Alert: The monitored blockchain node is not responding."
        )
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