Building Custom Analytics Dashboards with Cloudflare Data and Ruby Gems

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gem 'cloudflare'

# Configure client
cf = Cloudflare.connect(
  email: ENV['CLOUDFLARE_EMAIL'],
  key: ENV['CLOUDFLARE_API_KEY']
)

# Fetch zone analytics
def fetch_zone_analytics(start_time, end_time, metrics, dimensions = [])
  query = {
    query: "
      query {
        viewer {
          zones(filter: {zoneTag: \"#{ENV['CLOUDFLARE_ZONE_ID']}\"}) {
            httpRequests1mGroups(
              limit: 10000,
              filter: {
                datetime_geq: \"#{start_time}\",
                datetime_leq: \"#{end_time}\"
              },
              orderBy: [datetime_ASC],
              #{dimensions.any? ? "dimensions: #{dimensions}," : ""}
            ) {
              dimensions {
                #{dimensions.join("\n")}
              }
              sum {
                #{metrics.join("\n")}
              }
              dimensions {
                datetime
              }
            }
          }
        }
      }
    "
  }
  
  cf.graphql.post(query)
end

# Common metrics and dimensions
METRICS = [
  'visits',
  'pageViews',
  'requests',
  'bytes',
  'cachedBytes',
  'cachedRequests',
  'threats',
  'countryMap { bytes, requests, clientCountryName }'
]

DIMENSIONS = [
  'clientCountryName',
  'clientRequestPath',
  'clientDeviceType',
  'clientBrowserName',
  'originResponseStatus'
]

# lib/data_collector.rb
class DataCollector
  def self.collect_hourly_metrics
    end_time = Time.now.utc
    start_time = end_time - 3600
    
    data = fetch_zone_analytics(
      start_time.iso8601,
      end_time.iso8601,
      METRICS,
      ['clientCountryName', 'clientRequestPath']
    )
    
    # Store in database
    store_in_database(data, 'hourly_metrics')
    
    # Calculate aggregates
    calculate_aggregates(data)
  end
  
  def self.store_in_database(data, table)
    DB[table].insert(
      collected_at: Time.now,
      data: Sequel.pg_json(data),
      period_start: start_time,
      period_end: end_time
    )
  end
  
  def self.calculate_aggregates(data)
    # Calculate traffic by country
    by_country = data.group_by { |d| d['dimensions']['clientCountryName'] }
    
    # Calculate top pages
    by_page = data.group_by { |d| d['dimensions']['clientRequestPath'] }
    
    # Store aggregates
    DB[:aggregates].insert(
      calculated_at: Time.now,
      top_countries: Sequel.pg_json(top_10(by_country)),
      top_pages: Sequel.pg_json(top_10(by_page)),
      total_visits: data.sum { |d| d['sum']['visits'] }
    )
  end
end

# Run every hour
DataCollector.collect_hourly_metrics

gem 'chartkick'

# Simple usage
<%= line_chart Visit.group_by_day(:created_at).count %>
<%= pie_chart Visit.group(:country).count %>
<%= column_chart PageView.group(:browser).count %>

# With Cloudflare data
def traffic_over_time_chart
  data = DB[:hourly_metrics].select(
    Sequel.lit("DATE_TRUNC('hour', period_start) as hour"),
    Sequel.lit("SUM((data->>'visits')::int) as visits")
  ).group(:hour).order(:hour).last(48)
  
  line_chart data.map { |r| [r[:hour], r[:visits]] }
end

gem 'gruff'

# Create charts as images
def create_traffic_chart_image
  g = Gruff::Line.new
  g.title = 'Traffic Last 7 Days'
  
  # Add data
  g.data('Visits', visits_last_7_days)
  g.data('Pageviews', pageviews_last_7_days)
  
  # Customize
  g.labels = date_labels_for_last_7_days
  g.theme = {
    colors: ['#ff9900', '#3366cc'],
    marker_color: '#aaa',
    font_color: 'black',
    background_colors: 'white'
  }
  
  # Write to file
  g.write('public/images/traffic_chart.png')
end

gem 'daru'
gem 'daru-view'  # For visualization

# Load Cloudflare data into dataframe
df = Daru::DataFrame.from_csv('cloudflare_data.csv')

# Analyze
daily_traffic = df.group_by([:date]).aggregate(visits: :sum, pageviews: :sum)

# Create visualization
Daru::View::Plot.new(
  daily_traffic[:visits],
  type: :line,
  title: 'Daily Traffic'
).show

gem 'rails-charts'

# Even without Rails
class DashboardController
  def index
    @charts = {
      traffic: RailsCharts::LineChart.new(
        traffic_data,
        title: 'Traffic Trends',
        height: 300
      ),
      sources: RailsCharts::PieChart.new(
        source_data,
        title: 'Traffic Sources'
      )
    }
  end
end

# app.rb
require 'sinatra'
require 'json'
require 'cloudflare'

get '/dashboard' do
  erb :dashboard
end

get '/stream' do
  content_type 'text/event-stream'
  
  stream do |out|
    loop do
      # Fetch latest data
      data = fetch_realtime_metrics
      
      # Send as SSE
      out   "data: #{data.to_json}\n\n"
      
      sleep 30  # Update every 30 seconds
    end
  end
end

# JavaScript in dashboard
const eventSource = new EventSource('/stream');
eventSource.onmessage = (event) => {
  const data = JSON.parse(event.data);
  updateCharts(data);
};

# Generate static dashboard every minute
namespace :dashboard do
  desc "Generate static dashboard"
  task :generate do
    # Fetch data
    metrics = fetch_all_metrics
    
    # Generate HTML with embedded data
    template = File.read('templates/dashboard.html.erb')
    html = ERB.new(template).result(binding)
    
    # Write to file
    File.write('public/dashboard/index.html', html)
    
    # Also generate JSON for AJAX updates
    File.write('public/dashboard/data.json', metrics.to_json)
  end
end

# Schedule with cron
# */5 * * * * cd /path && rake dashboard:generate

gem 'faye-websocket'

require 'faye/websocket'

App = lambda do |env|
  if Faye::WebSocket.websocket?(env)
    ws = Faye::WebSocket.new(env)
    
    ws.on :open do |event|
      # Send initial data
      ws.send(initial_dashboard_data.to_json)
      
      # Start update timer
      timer = EM.add_periodic_timer(30) do
        ws.send(update_dashboard_data.to_json)
      end
      
      ws.on :close do |event|
        EM.cancel_timer(timer)
        ws = nil
      end
    end
    
    ws.rack_response
  else
    # Serve static dashboard
    [200, {'Content-Type' => 'text/html'}, [File.read('public/dashboard.html')]]
  end
end

# lib/reporting/daily_report.rb
class DailyReport
  def self.generate
    # Fetch data for yesterday
    start_time = Date.yesterday.beginning_of_day
    end_time = Date.yesterday.end_of_day
    
    data = {
      summary: daily_summary(start_time, end_time),
      top_pages: top_pages(start_time, end_time, limit: 10),
      traffic_sources: traffic_sources(start_time, end_time),
      performance: performance_metrics(start_time, end_time),
      anomalies: detect_anomalies(start_time, end_time)
    }
    
    # Generate report in multiple formats
    generate_html_report(data)
    generate_pdf_report(data)
    generate_email_report(data)
    generate_slack_report(data)
    
    # Archive
    archive_report(data, Date.yesterday)
  end
  
  def self.generate_html_report(data)
    template = File.read('templates/report.html.erb')
    html = ERB.new(template).result_with_hash(data)
    
    File.write("reports/daily/#{Date.yesterday}.html", html)
    
    # Upload to S3 for sharing
    upload_to_s3("reports/daily/#{Date.yesterday}.html")
  end
  
  def self.generate_email_report(data)
    html = render_template('templates/email_report.html.erb', data)
    text = render_template('templates/email_report.txt.erb', data)
    
    Mail.deliver do
      to ENV['REPORT_RECIPIENTS'].split(',')
      subject "Daily Report for #{Date.yesterday}"
      html_part do
        content_type 'text/html; charset=UTF-8'
        body html
      end
      text_part do
        body text
      end
    end
  end
  
  def self.generate_slack_report(data)
    attachments = [
      {
        title: "📊 Daily Report - #{Date.yesterday}",
        fields: [
          {
            title: "Total Visits",
            value: data[:summary][:visits].to_s,
            short: true
          },
          {
            title: "Top Page",
            value: data[:top_pages].first[:path],
            short: true
          }
        ],
        color: "good"
      }
    ]
    
    Slack.notify(
      channel: '#reports',
      attachments: attachments
    )
  end
end

# Schedule with whenever
every :day, at: '6am' do
  runner "DailyReport.generate"
end

# In your dashboard template

  
  
  Update




# Backend API endpoint
get '/api/metrics' do
  start_date = params[:start_date] || 7.days.ago.to_s
  end_date = params[:end_date] || Date.today.to_s
  
  metrics = fetch_metrics_for_range(start_date, end_date)
  
  content_type :json
  metrics.to_json
end

# Click on a country to see regional data
<%= pie_chart traffic_by_country, 
  library: {
    onClick: 'function(point) { 
      window.location.href = "/dashboard/country/" + point.name;
    }'
  }
%>

# Country detail page
get '/dashboard/country/:country' do
  @country = params[:country]
  @metrics = fetch_country_metrics(@country)
  
  erb :country_dashboard
end

# Compare periods
def compare_periods(current_start, current_end, previous_start, previous_end)
  current = fetch_metrics(current_start, current_end)
  previous = fetch_metrics(previous_start, previous_end)
  
  {
    current: current,
    previous: previous,
    change: calculate_percentage_change(current, previous)
  }
end

# Display comparison
Visits: <%= current[:visits] %> 
  
    (<%= change[:visits] %>%)
  

# Cache dashboard data
def cached_dashboard_data
  Rails.cache.fetch('dashboard_data', expires_in: 5.minutes) do
    fetch_dashboard_data
  end
end

# Cache individual charts
def cached_chart(name, &block)
  Rails.cache.fetch("chart_#{name}_#{Date.today}", &block)
end

# Load initial data, then update incrementally

# Export dashboard as static HTML
task :export_dashboard do
  # Fetch all data
  data = fetch_complete_dashboard_data
  
  # Generate standalone HTML with embedded data
  html = generate_standalone_html(data)
  
  # Compress
  compressed = Zlib::Deflate.deflate(html)
  
  # Save
  File.write('dashboard_export.html.gz', compressed)
end

# Optimize database queries
def optimized_metrics_query
  DB[:metrics].select(
    :timestamp,
    Sequel.lit("SUM(visits) as visits"),
    Sequel.lit("SUM(pageviews) as pageviews")
  ).where(timestamp: start_time..end_time)
   .group(Sequel.lit("DATE_TRUNC('hour', timestamp)"))
   .order(:timestamp)
   .naked
   .all
end

# Use materialized views for complex aggregations
DB.run( SQL)
  CREATE MATERIALIZED VIEW daily_aggregates AS
  SELECT 
    DATE(timestamp) as date,
    SUM(visits) as visits,
    SUM(pageviews) as pageviews,
    COUNT(DISTINCT ip) as unique_visitors
  FROM metrics
  GROUP BY DATE(timestamp)
SQL