mackerel_distinguish_filesystem_alert.py

# -*- coding: utf-8 -*-

import requests
import time
import json
from StringIO import StringIO
import re
import sys
import os

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

import logging
logging.basicConfig()
logger = logging.getLogger(__name__)
logger.setLevel(level=logging.INFO)

MACKEREL_APIKEY = os.environ.get("MACKEREL_APIKEY")
#MONITOR_NAME = "Filesystem %"
MONITOR_ID = "2zumT77N8sh"
BASEURL = "https://mackerel.io"
SAVE_FILE = "/tmp/processed_alerts.txt"

SLACK_TOKEN = os.environ.get("SLACK_TOKEN")
SLACK_URL = 'https://slack.com/api/chat.postMessage'

epoch_time = int(time.time())
duration = 60 * 60 * 1
THRESHOLD = 1
ALERT_THRESHOLD = 60 * 60 * 6

def fetch_alert_targets():
    all_alerts = fetch_alerts()
    target_alerts = select_target_alerts(all_alerts)
    processed_alerts = fetch_processed_alerts()
    unprocessed_alerts = select_unprocessed_alerts(target_alerts, processed_alerts)
    save_new_alerts(target_alerts)
    return [alert['hostId'] for alert in unprocessed_alerts]

def fetch_alerts():
    headers = {'X-Api-Key': MACKEREL_APIKEY, 'Content-Type': 'application/json'}
    r = requests.get(BASEURL+"/api/v0/alerts", headers=headers)
    alerts = json.load(StringIO(r.content))

    time.sleep(2.0)
    return alerts['alerts']

def select_target_alerts(all_alerts):
    return [ alert for alert in all_alerts if alert['status'] == 'WARNING' \
        and alert['monitorId'] == MONITOR_ID \
        and alert['type'] == 'host' \
        and 'closedAt' not in alert ]

def fetch_processed_alerts():
    with open(SAVE_FILE, 'r') as f:
        lines = f.readlines()
    logger.debug(lines)
    return lines[0].split(';') if lines else lines

def select_unprocessed_alerts(target_alerts, processed_alerts):
    return [ alert for alert in target_alerts if alert['id'] not in processed_alerts ]

def save_new_alerts(target_alerts):
    os.remove(SAVE_FILE)
    with open(SAVE_FILE, 'w') as f:
        f.writelines(';'.join([ alert['id'] for alert in target_alerts ]))

def prepare_targets(host_ids):
    dat = {}
    for host_id in host_ids:
        host = find_host(host_id)
        if not dat.has_key(host['name']):
            dat[host['name']] = {'id': host['id']}
        meta = host['meta']
        if meta.has_key('filesystem'):
            dat[host['name']]['filesystem'] = meta['filesystem'].keys()
    return dat

def find_host(host_id):
    headers = {'X-Api-Key': MACKEREL_APIKEY, 'Content-Type': 'application/json'}
    r = requests.get("{0}/api/v0/hosts/{1}".format(BASEURL, host_id), headers=headers)
    res = json.load(StringIO(r.content))
    return res['host']

def import_df(metrics, size):
    # {u'metrics': [{u'value': 6.85, u'time': 1450575540}, {u'value': 7.03, u'time': 1450575600}]}
    times = []
    values = []
    for metric in metrics:
        times.append(metric['time'] - (epoch_time - duration))
        values.append(metric['value'])
    df = pd.DataFrame({'time': times, 'value': values})
    #plt.plot(times, values, 'bo')

    model = pd.ols(y=df['value'], x=df['time'], intercept=True)
    #print model
    #plt.plot(model.x['x'], model.y_fitted, 'g-')
    #plt.hlines([size, size * 0.8], times[0], times[-1], linestyles="dashed")
    #plt.show()
    return model

def fetch_metrics(hostid, name, time_from, time_to):
    payload = {'name': name, 'from': time_from, 'to': time_to}
    headers = {'X-Api-Key': MACKEREL_APIKEY}
    r = requests.get(BASEURL+"/api/v0/hosts/"+hostid+"/metrics", params=payload, headers=headers)

    time.sleep(2.0)
    metrics = json.load(StringIO(r.content))
    if metrics.has_key('metrics'):
        return metrics['metrics']
    else:
        return []

def human_readable_size(s):
    s = float(s)
    if s > 10**12:
        return "%.2f TB" % (s / 10**12)
    if s > 10**9:
        return "%.2f GB" % (s / 10**9)
    if s > 10**6:
        return "%.2f MB" % (s / 10**6)
    if s > 10**3:
        return "%.2f MB" % (s / 10**3)
    return "%d B" % s

def human_readable_time(s):
    r = ""
    unit = [("d", 60*60*24),("h", 60*60),("m", 60)]
    for u in unit:
        if s >= u[1]:
            i = int(s / u[1])
            r = r + "%s%s" % (i, u[0])
            s = s - i * u[1]
    return "%s%fs" % (r, s)

def process_targets(dat):
    res = []
    num = 0
    for hostname in dat.keys():
        num = num + 1
        logger.info('fetching %s (%d/%d)', hostname, num, len(dat))
        record = {'hostname': hostname, 'fs': [], 'nearest': sys.maxint}
        if not dat[hostname].has_key('filesystem'):
            continue
        for fs in dat[hostname]['filesystem']:
            (fs, count) = re.subn(r"^/dev/", "", fs)
            fs = fs.replace('/', '_') # for vagrant
            if count == 0:
                continue
            metric_name = "filesystem." + fs + ".used"
            metrics_size = fetch_metrics(dat[hostname]['id'], "filesystem."+ fs +".size", epoch_time, epoch_time - 60 * 10)
            if len(metrics_size) == 0:
                logger.info("skip the fs: %s" % (metric_name))
                continue

            metrics = fetch_metrics(dat[hostname]['id'], metric_name, epoch_time, epoch_time - duration)

            size = 0
            for m in metrics_size:
                size = max(size, m['value'])

            latest = 0
            for m in metrics[::-1]:
                if m['value'] > 0:
                    latest = m['value']
                    break

            model = import_df(metrics, size)
            x =  model.beta.x
            i =  model.beta.intercept
            logger.debug("metric:%s, x: %f, intercept: %f, size: %s, current: %s" % (metric_name, x, i, size, latest))
            if x > 0:
                target = size * THRESHOLD
                e = (target-i)/x
                record['fs'].append({'name': fs, 'latest': latest, 'size': size, 'x': x, 'i': i, 'fullin': e})
                record['nearest'] = min(record['nearest'], e)
                logger.debug("fs: %s, size: %s/%s, estimated %s" % (
                    fs,
                    human_readable_size(latest),
                    human_readable_size(size),
                    human_readable_time(e)))
            else:
                record['fs'].append({'name': fs, 'latest': latest, 'size': size, 'x': x, 'i': i})
                logger.debug("fs: %s, used size is reducing." % (fs))
        res.append(record)
    return res

def output_results(res):
    res = sorted(res, key=lambda x: x['nearest'])
    for host in res:
        for fs in sorted(host['fs'], key=lambda x: x['fullin'] if x.has_key('fullin') else sys.maxint):
            if fs.has_key('fullin'):
                mension = " <!channel>" if fs['fullin'] < ALERT_THRESHOLD else ""
                text = "{0}:{1}, size: {2}/{3}, full in {4}  {5}".format(
                    host['hostname'], fs['name'],
                    human_readable_size(fs['latest']),
                    human_readable_size(fs['size']),
                    human_readable_time(fs['fullin']),
                    mension)
                post2slack(text)
            else:
                text = "{0}:{1}, size: {2}/{3}, never full".format(
                    host['hostname'], fs['name'],
                    human_readable_size(fs['latest']),
                    human_readable_size(fs['size']))
                post2slack(text)

def post2slack(text):
    post2slack_raw(SLACK_TOKEN, SLACK_URL, text, "#alert", "life_checker", ':police_car:')

def post2slack_raw(token, url, text, channel, user, emoji):
    payload = {
        'token': token,
        'channel': channel,
        'username': user,
        'text': text,
        'icon_emoji': emoji
    }
    result = requests.post(url, data=payload).json()
    if not result['ok']:
        return "Failed: %s" % result['error']
    else:
        return "Success"

if __name__ == "__main__":
    targets = fetch_alert_targets()
    logger.debug(targets)
    if targets:
        dat = prepare_targets(targets)
        res = process_targets(dat)
        output_results(res)