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https://github.com/pacnpal/thrilltrack-explorer.git
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Add Django Celery tasks and utilities to periodically collect system metrics (error rates, response times, queue sizes) and record them into metric_time_series. Include monitoring app scaffolding, metrics collector, Celery beat schedule, middleware for live metrics, and a Supabase edge function for cross-source metrics.
188 lines
6.0 KiB
TypeScript
188 lines
6.0 KiB
TypeScript
import { createClient } from 'https://esm.sh/@supabase/supabase-js@2.57.4';
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const corsHeaders = {
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'Access-Control-Allow-Origin': '*',
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'Access-Control-Allow-Headers': 'authorization, x-client-info, apikey, content-type',
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};
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interface MetricRecord {
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metric_name: string;
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metric_value: number;
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metric_category: string;
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timestamp: string;
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}
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Deno.serve(async (req) => {
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if (req.method === 'OPTIONS') {
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return new Response(null, { headers: corsHeaders });
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}
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try {
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const supabaseUrl = Deno.env.get('SUPABASE_URL')!;
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const supabaseKey = Deno.env.get('SUPABASE_SERVICE_ROLE_KEY')!;
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const supabase = createClient(supabaseUrl, supabaseKey);
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console.log('Starting metrics collection...');
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const metrics: MetricRecord[] = [];
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const timestamp = new Date().toISOString();
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// 1. Collect API error rate from recent logs
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const { data: recentErrors, error: errorQueryError } = await supabase
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.from('system_alerts')
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.select('id', { count: 'exact', head: true })
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.gte('created_at', new Date(Date.now() - 60000).toISOString())
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.in('severity', ['high', 'critical']);
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if (!errorQueryError) {
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const errorCount = recentErrors || 0;
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metrics.push({
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metric_name: 'api_error_count',
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metric_value: errorCount as number,
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metric_category: 'performance',
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timestamp,
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});
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}
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// 2. Collect rate limit violations
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const { data: rateLimitViolations, error: rateLimitError } = await supabase
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.from('rate_limit_logs')
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.select('id', { count: 'exact', head: true })
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.gte('timestamp', new Date(Date.now() - 60000).toISOString())
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.eq('action_taken', 'blocked');
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if (!rateLimitError) {
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const violationCount = rateLimitViolations || 0;
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metrics.push({
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metric_name: 'rate_limit_violations',
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metric_value: violationCount as number,
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metric_category: 'security',
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timestamp,
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});
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}
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// 3. Collect pending submissions count
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const { data: pendingSubmissions, error: submissionsError } = await supabase
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.from('submissions')
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.select('id', { count: 'exact', head: true })
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.eq('moderation_status', 'pending');
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if (!submissionsError) {
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const pendingCount = pendingSubmissions || 0;
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metrics.push({
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metric_name: 'pending_submissions',
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metric_value: pendingCount as number,
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metric_category: 'workflow',
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timestamp,
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});
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}
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// 4. Collect active incidents count
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const { data: activeIncidents, error: incidentsError } = await supabase
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.from('incidents')
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.select('id', { count: 'exact', head: true })
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.in('status', ['open', 'investigating']);
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if (!incidentsError) {
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const incidentCount = activeIncidents || 0;
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metrics.push({
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metric_name: 'active_incidents',
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metric_value: incidentCount as number,
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metric_category: 'monitoring',
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timestamp,
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});
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}
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// 5. Collect unresolved alerts count
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const { data: unresolvedAlerts, error: alertsError } = await supabase
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.from('system_alerts')
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.select('id', { count: 'exact', head: true })
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.eq('resolved', false);
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if (!alertsError) {
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const alertCount = unresolvedAlerts || 0;
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metrics.push({
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metric_name: 'unresolved_alerts',
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metric_value: alertCount as number,
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metric_category: 'monitoring',
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timestamp,
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});
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}
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// 6. Calculate submission approval rate (last hour)
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const { data: recentSubmissions, error: recentSubmissionsError } = await supabase
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.from('submissions')
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.select('moderation_status', { count: 'exact' })
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.gte('created_at', new Date(Date.now() - 3600000).toISOString());
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if (!recentSubmissionsError && recentSubmissions) {
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const total = recentSubmissions.length;
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const approved = recentSubmissions.filter(s => s.moderation_status === 'approved').length;
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const approvalRate = total > 0 ? (approved / total) * 100 : 100;
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metrics.push({
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metric_name: 'submission_approval_rate',
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metric_value: approvalRate,
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metric_category: 'workflow',
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timestamp,
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});
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}
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// 7. Calculate average moderation time (last hour)
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const { data: moderatedSubmissions, error: moderatedError } = await supabase
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.from('submissions')
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.select('created_at, moderated_at')
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.not('moderated_at', 'is', null)
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.gte('moderated_at', new Date(Date.now() - 3600000).toISOString());
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if (!moderatedError && moderatedSubmissions && moderatedSubmissions.length > 0) {
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const totalTime = moderatedSubmissions.reduce((sum, sub) => {
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const created = new Date(sub.created_at).getTime();
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const moderated = new Date(sub.moderated_at).getTime();
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return sum + (moderated - created);
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}, 0);
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const avgTimeMinutes = (totalTime / moderatedSubmissions.length) / 60000;
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metrics.push({
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metric_name: 'avg_moderation_time',
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metric_value: avgTimeMinutes,
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metric_category: 'workflow',
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timestamp,
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});
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}
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// Insert all collected metrics
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if (metrics.length > 0) {
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const { error: insertError } = await supabase
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.from('metric_time_series')
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.insert(metrics);
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if (insertError) {
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console.error('Error inserting metrics:', insertError);
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throw insertError;
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}
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console.log(`Successfully recorded ${metrics.length} metrics`);
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}
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return new Response(
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JSON.stringify({
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success: true,
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metrics_collected: metrics.length,
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metrics: metrics.map(m => ({ name: m.metric_name, value: m.metric_value })),
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}),
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{ headers: { ...corsHeaders, 'Content-Type': 'application/json' } }
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);
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} catch (error) {
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console.error('Error in collect-metrics function:', error);
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return new Response(
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JSON.stringify({ error: error.message }),
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{
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status: 500,
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headers: { ...corsHeaders, 'Content-Type': 'application/json' },
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}
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);
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}
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});
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