Is Helicone Down? How to Check Helicone Status in Real-Time

Is Helicone Down? How to Check Helicone Status in Real-Time

Quick Answer: To check if Helicone is down, visit apistatuscheck.com/api/helicone for real-time monitoring, or check the official status.helicone.ai page. Common signs include proxy connection failures, logging delays, dashboard errors, caching issues, and webhook delivery failures.

When your LLM observability suddenly stops working, you lose critical visibility into your AI application's performance, costs, and user interactions. Helicone provides essential monitoring, analytics, and caching for LLM applications using OpenAI, Anthropic, Cohere, and other providers. Any downtime means you're flying blind—unable to track usage, debug issues, or optimize costs. Whether you're seeing proxy timeouts, missing logs, or dashboard loading errors, knowing how to quickly verify Helicone's status can help you determine if the issue is with Helicone or your integration.

How to Check Helicone Status in Real-Time

1. API Status Check (Fastest Method)

The quickest way to verify Helicone's operational status is through apistatuscheck.com/api/helicone. This real-time monitoring service:

  • Tests actual proxy endpoints every 60 seconds
  • Monitors API response times and latency trends
  • Tracks historical uptime over 30/60/90 days
  • Provides instant alerts when issues are detected
  • Checks logging pipeline health and delays

Unlike status pages that rely on manual updates, API Status Check performs active health checks against Helicone's production infrastructure, giving you the most accurate real-time picture of service availability.

2. Official Helicone Status Page

Helicone maintains status.helicone.ai as their official communication channel for service incidents. The page displays:

  • Current operational status for all services
  • Active incidents and investigations
  • Scheduled maintenance windows
  • Historical incident reports
  • Component-specific status (Proxy, Dashboard, Logging, Caching, Webhooks)

Pro tip: Subscribe to status updates via email or RSS on the status page to receive immediate notifications when incidents occur.

3. Test Your Proxy Integration

The most direct way to check if Helicone's proxy is working is to make a test API call through it:

curl https://oai.helicone.ai/v1/chat/completions \
  -H "Authorization: Bearer YOUR_OPENAI_API_KEY" \
  -H "Helicone-Auth: Bearer YOUR_HELICONE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4",
    "messages": [{"role": "user", "content": "Test"}],
    "max_tokens": 5
  }'

If you receive timeout errors, connection failures, or 502/503 responses, Helicone's proxy infrastructure may be experiencing issues.

4. Check Your Dashboard

If the Helicone Dashboard at helicone.ai is loading slowly or showing errors, this often indicates broader infrastructure issues. Pay attention to:

  • Login failures or timeouts
  • Request log loading errors
  • Analytics charts not rendering
  • Delayed data refresh (logs appearing hours late)
  • Cache statistics not updating

5. Monitor Your Logging Pipeline

Since Helicone's primary value is observability, check if logs are appearing:

  1. Make a test LLM request through Helicone proxy
  2. Wait 30-60 seconds (normal logging delay)
  3. Check if the request appears in your Helicone dashboard

If requests consistently don't appear after several minutes, the logging pipeline may be degraded.

6. Verify Webhook Delivery

If you've configured webhooks for request notifications:

  • Check your webhook endpoint logs
  • Look for delivery delays (should be near real-time)
  • Verify webhook signatures are valid
  • Check the Helicone dashboard for webhook delivery status

Webhook failures or delays often indicate partial service degradation affecting the event processing pipeline.

Common Helicone Issues and How to Identify Them

Proxy Connection Failures

Symptoms:

  • Timeout errors when connecting to oai.helicone.ai, anthropic.helicone.ai, or other proxy endpoints
  • Connection refused errors
  • SSL/TLS handshake failures
  • 502 Bad Gateway or 504 Gateway Timeout errors
  • Requests that normally complete in 2-5 seconds timing out after 30+ seconds

What it means: The proxy is the core of Helicone's architecture, sitting between your application and the LLM provider. When it's down, all requests fail, and you lose both observability AND access to the underlying LLM service.

Immediate workaround:

// Fallback to direct LLM provider if Helicone is down
const HELICONE_PROXY = "https://oai.helicone.ai/v1";
const OPENAI_DIRECT = "https://api.openai.com/v1";

async function makeRequest(useProxy = true) {
  const baseURL = useProxy ? HELICONE_PROXY : OPENAI_DIRECT;
  
  try {
    const response = await fetch(`${baseURL}/chat/completions`, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${process.env.OPENAI_API_KEY}`,
        ...(useProxy && {
          'Helicone-Auth': `Bearer ${process.env.HELICONE_API_KEY}`
        }),
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({...}),
      timeout: 10000 // 10 second timeout
    });
    
    return await response.json();
  } catch (error) {
    if (useProxy && error.name === 'TimeoutError') {
      console.warn('Helicone proxy timeout, falling back to direct');
      return makeRequest(false); // Retry without proxy
    }
    throw error;
  }
}

Logging Delays

Symptoms:

  • Requests made through proxy succeed, but don't appear in dashboard
  • Logs appearing 10+ minutes late (normal is under 60 seconds)
  • Partial logs (some requests logged, others missing)
  • Analytics dashboards showing stale data
  • Cost tracking not updating

What it means: The proxy may be working, but the background logging pipeline that processes and stores request metadata is degraded. This is often a partial outage where LLM requests still work, but you lose observability temporarily.

Impact: While your application continues functioning, you lose real-time cost visibility and debugging capabilities during the outage period.

Dashboard Loading Issues

Signs the dashboard is impacted:

  • Infinite loading spinners on request logs page
  • "Failed to load requests" errors
  • Filters and search not working
  • Charts showing incomplete data
  • Dashboard timing out completely

Common causes during outages:

  • Database query performance degradation
  • API rate limiting on dashboard endpoints
  • CDN or frontend asset delivery issues
  • Authentication service problems

Dashboard issues don't necessarily mean the proxy is down—your LLM requests may still be logged successfully even if you can't view them temporarily.

Caching Errors

Helicone's caching feature can return cached LLM responses to save costs and latency. When caching is degraded:

Symptoms:

  • Cache hits suddenly dropping to 0% when they should be higher
  • Helicone-Cache header responses missing or returning errors
  • Cached responses taking as long as uncached requests
  • Cache statistics not updating in dashboard

Code to detect cache issues:

const response = await fetch('https://oai.helicone.ai/v1/chat/completions', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${OPENAI_API_KEY}`,
    'Helicone-Auth': `Bearer ${HELICONE_API_KEY}`,
    'Helicone-Cache-Enabled': 'true'
  },
  body: JSON.stringify({...})
});

const cacheStatus = response.headers.get('Helicone-Cache');
console.log(`Cache status: ${cacheStatus}`); // Should be 'HIT' or 'MISS'

if (!cacheStatus) {
  console.warn('Helicone caching may be down');
}

API Key Authentication Problems

Symptoms:

  • 401 Unauthorized errors with valid API keys
  • "Invalid Helicone API Key" errors
  • Intermittent authentication failures (works sometimes, fails others)
  • Keys that worked yesterday suddenly failing

What it means: Helicone's authentication service may be experiencing issues. This can affect both proxy requests and dashboard access.

Verification:

# Test API key validity
curl https://api.helicone.ai/v1/request/query \
  -H "Authorization: Bearer YOUR_HELICONE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "limit": 1
  }'

If you get 401 with a key that worked recently, and you haven't rotated it, authentication services may be impacted.

Rate Limiting Issues

Symptoms:

  • 429 Too Many Requests errors when within your plan limits
  • Rate limit headers showing incorrect values
  • Sudden rate limit drops (e.g., from 1000/min to 10/min)

Example:

HTTP/1.1 429 Too Many Requests
Helicone-RateLimit-Limit: 1000
Helicone-RateLimit-Remaining: 0
Helicone-RateLimit-Reset: 1234567890

If you're seeing rate limits that don't match your plan, Helicone's rate limiting service may be misconfigured during an incident.

The Real Impact When Helicone Goes Down

Lost Cost Visibility

Every minute of Helicone downtime means:

  • No cost tracking for LLM requests made during outage
  • Missing usage analytics for budgeting and forecasting
  • Incomplete cost attribution by user, feature, or team
  • Delayed billing alerts for overage protection

For a company spending $10,000/month on LLM APIs, losing even a few hours of cost tracking can mean significant budget blind spots and difficulty reconciling invoices.

Debugging Becomes Impossible

When Helicone's logging is down, you lose the ability to:

  • Debug user complaints ("Why did the AI give me that response?")
  • Identify prompt injection or misuse patterns
  • Analyze response quality issues
  • Track error rates and failure modes
  • Investigate latency spikes and performance degradation

Real scenario: A customer reports an AI hallucination issue. Without Helicone logs showing the exact prompt, model, temperature, and response, debugging requires reproducing the issue—which may be impossible if it was context-dependent.

Compliance and Audit Gaps

For organizations with compliance requirements:

  • Missing audit trails for LLM usage
  • Incomplete data retention records
  • Gaps in PII detection logs (if using Helicone's moderation features)
  • Lost evidence for security incident investigations

Healthcare, financial services, and legal tech companies relying on Helicone for HIPAA, SOC 2, or regulatory compliance may face audit issues if request logs have gaps.

Broken Automation and Alerts

Many teams build automation on Helicone webhooks:

  • Cost alert systems fail to trigger
  • Quality monitoring pipelines stop receiving data
  • Auto-scaling logic based on LLM usage breaks
  • Custom analytics dashboards show incomplete data

Example broken automation:

// Webhook receiver that triggers cost alerts
app.post('/helicone-webhook', async (req, res) => {
  const { cost, user_id } = req.body;
  
  // This won't trigger if webhooks are down
  if (cost > USER_DAILY_LIMIT) {
    await alertUser(user_id, 'Daily LLM budget exceeded');
    await disableUserAccess(user_id);
  }
});

During a webhook outage, users could exceed budgets without alerts, leading to unexpected costs.

Caching Failures Increase Costs

Helicone's caching can reduce LLM costs by 50-90% for applications with repetitive queries:

  • Cache hits drop to 0% during outages
  • Every request hits the LLM provider, multiplying costs
  • Latency increases (cached responses are near-instant)
  • API rate limits consumed faster

Cost impact example: An application making 1M requests/month with an 80% cache hit rate suddenly making 1M uncached requests could see costs jump from $200 to $1,000+ in a single day.

Lost Experimentation Data

Teams running A/B tests or prompt experiments through Helicone lose valuable data:

  • Incomplete experiment results if outage occurs mid-test
  • Biased data if logging is intermittent (some variants logged, others not)
  • Wasted experiment time that must be re-run
  • Delayed product decisions waiting for complete data

Incident Response Playbook for Helicone Outages

1. Implement Automatic Failover to Direct LLM Access

Priority: CRITICAL - Ensures your application continues working even if Helicone is completely down.

import { OpenAI } from 'openai';

class ResilientLLMClient {
  private heliconeClient: OpenAI;
  private directClient: OpenAI;
  private heliconeHealthy: boolean = true;
  private lastHealthCheck: number = 0;
  
  constructor() {
    // Helicone proxy client
    this.heliconeClient = new OpenAI({
      apiKey: process.env.OPENAI_API_KEY,
      baseURL: 'https://oai.helicone.ai/v1',
      defaultHeaders: {
        'Helicone-Auth': `Bearer ${process.env.HELICONE_API_KEY}`,
      },
      timeout: 10000, // 10 second timeout
    });
    
    // Direct OpenAI client (fallback)
    this.directClient = new OpenAI({
      apiKey: process.env.OPENAI_API_KEY,
    });
  }
  
  async chat(messages: any[], options: any = {}) {
    // Health check every 60 seconds
    if (Date.now() - this.lastHealthCheck > 60000) {
      await this.checkHeliconeHealth();
    }
    
    const client = this.heliconeHealthy ? this.heliconeClient : this.directClient;
    
    try {
      const response = await client.chat.completions.create({
        model: options.model || 'gpt-4',
        messages,
        ...options,
      });
      
      // If using fallback, it succeeded - mark as healthy
      if (!this.heliconeHealthy) {
        this.heliconeHealthy = true;
        console.log('✓ Helicone proxy restored, switching back');
      }
      
      return response;
    } catch (error: any) {
      // If Helicone fails, switch to direct
      if (this.heliconeHealthy && this.isHeliconeError(error)) {
        console.warn('✗ Helicone proxy failed, switching to direct OpenAI');
        this.heliconeHealthy = false;
        return this.directClient.chat.completions.create({
          model: options.model || 'gpt-4',
          messages,
          ...options,
        });
      }
      throw error;
    }
  }
  
  private isHeliconeError(error: any): boolean {
    return (
      error.code === 'ECONNREFUSED' ||
      error.code === 'ETIMEDOUT' ||
      error.message?.includes('502') ||
      error.message?.includes('504')
    );
  }
  
  private async checkHeliconeHealth(): Promise<void> {
    this.lastHealthCheck = Date.now();
    try {
      await this.heliconeClient.chat.completions.create({
        model: 'gpt-3.5-turbo',
        messages: [{ role: 'user', content: 'test' }],
        max_tokens: 1,
      });
      this.heliconeHealthy = true;
    } catch {
      this.heliconeHealthy = false;
    }
  }
}

// Usage
const llm = new ResilientLLMClient();
const response = await llm.chat([
  { role: 'user', content: 'Hello!' }
]);

2. Log Locally During Outages

Capture request metadata locally so you don't lose observability data:

import fs from 'fs';
import path from 'path';

async function logRequestLocally(request: any, response: any) {
  const logEntry = {
    timestamp: new Date().toISOString(),
    model: request.model,
    prompt: request.messages,
    response: response.choices[0].message,
    tokens: {
      prompt: response.usage.prompt_tokens,
      completion: response.usage.completion_tokens,
      total: response.usage.total_tokens,
    },
    cost: calculateCost(request.model, response.usage),
  };
  
  const logPath = path.join(
    './logs',
    `helicone-fallback-${new Date().toISOString().split('T')[0]}.jsonl`
  );
  
  fs.appendFileSync(logPath, JSON.stringify(logEntry) + '\n');
}

function calculateCost(model: string, usage: any): number {
  const pricing: Record<string, { prompt: number; completion: number }> = {
    'gpt-4': { prompt: 0.03, completion: 0.06 },
    'gpt-3.5-turbo': { prompt: 0.0015, completion: 0.002 },
    'claude-3-opus': { prompt: 0.015, completion: 0.075 },
  };
  
  const prices = pricing[model] || pricing['gpt-3.5-turbo'];
  return (
    (usage.prompt_tokens / 1000) * prices.prompt +
    (usage.completion_tokens / 1000) * prices.completion
  );
}

Recovery: Once Helicone is restored, batch-upload your local logs using their API:

# Upload logs to Helicone after outage
curl https://api.helicone.ai/v1/log/batch \
  -H "Authorization: Bearer YOUR_HELICONE_API_KEY" \
  -H "Content-Type: application/json" \
  -d @helicone-fallback-2026-02-04.jsonl

3. Set Up Comprehensive Monitoring

Don't rely solely on Helicone's status page. Monitor it yourself:

import fetch from 'node-fetch';

async function monitorHeliconeHealth() {
  const checks = [
    {
      name: 'OpenAI Proxy',
      url: 'https://oai.helicone.ai/v1/models',
      headers: {
        'Authorization': `Bearer ${process.env.OPENAI_API_KEY}`,
        'Helicone-Auth': `Bearer ${process.env.HELICONE_API_KEY}`,
      },
    },
    {
      name: 'Anthropic Proxy',
      url: 'https://anthropic.helicone.ai/v1/messages',
      method: 'POST',
      headers: {
        'x-api-key': process.env.ANTHROPIC_API_KEY,
        'Helicone-Auth': `Bearer ${process.env.HELICONE_API_KEY}`,
        'anthropic-version': '2023-06-01',
        'Content-Type': 'application/json',
      },
      body: JSON.stringify({
        model: 'claude-3-haiku-20240307',
        max_tokens: 1,
        messages: [{ role: 'user', content: 'test' }],
      }),
    },
    {
      name: 'Dashboard API',
      url: 'https://api.helicone.ai/v1/request/query',
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${process.env.HELICONE_API_KEY}`,
        'Content-Type': 'application/json',
      },
      body: JSON.stringify({ limit: 1 }),
    },
  ];
  
  for (const check of checks) {
    const start = Date.now();
    try {
      const response = await fetch(check.url, {
        method: check.method || 'GET',
        headers: check.headers,
        body: check.body,
        timeout: 10000,
      });
      
      const latency = Date.now() - start;
      const healthy = response.ok || response.status === 200;
      
      console.log(`${check.name}: ${healthy ? '✓' : '✗'} (${latency}ms)`);
      
      if (!healthy) {
        await sendAlert({
          service: 'Helicone',
          check: check.name,
          status: 'DOWN',
          statusCode: response.status,
          latency,
        });
      }
    } catch (error) {
      console.error(`${check.name}: ✗ (error: ${error.message})`);
      await sendAlert({
        service: 'Helicone',
        check: check.name,
        status: 'DOWN',
        error: error.message,
      });
    }
  }
}

// Run every 60 seconds
setInterval(monitorHeliconeHealth, 60000);

4. Configure Alternative Observability During Outages

Have a backup observability strategy:

// Log to DataDog, New Relic, or custom analytics
import { Logger } from './logger';

async function trackLLMRequest(request: any, response: any) {
  // Primary: Helicone (via proxy)
  // Backup: Custom logging
  try {
    await Logger.track('llm_request', {
      model: request.model,
      tokens: response.usage.total_tokens,
      cost: calculateCost(request.model, response.usage),
      latency: response.latency,
      user_id: request.user_id,
      tags: request.tags,
    });
  } catch (error) {
    console.error('Failed to log to backup analytics:', error);
  }
}

5. Communicate with Stakeholders

Internal communication template:

🔴 Helicone Outage Detected

Status: LLM observability unavailable
Impact: Application continues working, but we've lost cost tracking and request logging
Mitigation: Switched to direct LLM provider access + local logging
ETA: Monitoring Helicone status page for updates

Actions:
- ✅ Failover activated automatically
- ✅ Local logging enabled
- ✅ Monitoring increased frequency
- ⏳ Will backfill logs once service restored

No customer impact expected.

For customers (if you provide a managed LLM service):

Service Notice: Reduced Observability

We're experiencing issues with our LLM monitoring provider (Helicone).

Impact: None on your AI features - everything continues working normally. 
However, usage analytics may show delays of 1-2 hours.

We're monitoring the situation and will restore full analytics once resolved.

6. Post-Incident Recovery

Once Helicone is restored:

  1. Backfill missing logs from your local cache
  2. Verify data completeness - check for gaps in request history
  3. Reconcile costs - compare local calculations with Helicone's totals
  4. Review alerts - ensure all monitoring fired correctly
  5. Update runbooks - document what worked and what didn't
  6. Consider redundancy - evaluate multi-provider observability

Related Guides

Helicone integrates with multiple LLM providers. If you're troubleshooting issues, also check:

Important: If both Helicone AND the underlying LLM provider are down, you'll see proxy errors. Always check both services to isolate the issue.

Frequently Asked Questions

How often does Helicone experience outages?

Helicone maintains strong uptime (typically 99.9%+), but as a relatively newer service compared to major cloud providers, occasional incidents can occur. Most outages are partial (affecting logging or dashboard but not the proxy itself) and resolve within 1-2 hours. Complete proxy outages affecting all customers are rare, occurring 2-4 times per year.

What's the difference between the proxy being down vs logging being delayed?

The proxy (e.g., oai.helicone.ai) is a real-time service that forwards your LLM requests and returns responses. If it's down, your LLM requests fail completely. Logging is an asynchronous background process that records request metadata. Logging can be delayed or missing while the proxy continues working—meaning your app functions normally but you temporarily lose observability.

Can I use Helicone without the proxy?

Yes! Helicone offers SDK-based logging that doesn't require proxying requests:

import { HeliconeAsyncLogger } from "@helicone/helicone";

const logger = new HeliconeAsyncLogger({
  apiKey: process.env.HELICONE_API_KEY,
});

// Use OpenAI directly
const response = await openai.chat.completions.create({...});

// Log separately
await logger.log(requestData, response);

This provides more resilience (direct LLM access isn't dependent on Helicone), but you lose caching and real-time features.

Will I lose historical data if Helicone goes down?

No. Your historical request logs, analytics, and cost data are stored in Helicone's database and remain accessible even during outages affecting the proxy or logging pipeline. However, requests made during a logging outage may not be captured unless you implement local logging as a backup.

How do I prevent losing cost data during outages?

Implement local cost calculation and logging (see playbook above). Even simple logging to a file or database with timestamp, model, token counts, and calculated costs will let you backfill data or at minimum have accurate cost accounting for your own records, even if those requests never appear in Helicone.

Does Helicone offer SLA guarantees?

Helicone's enterprise plans typically include SLA commitments (usually 99.9% uptime for the proxy). Free and starter plans may not have formal SLAs. Check your specific plan details or contact Helicone sales for enterprise SLA options. Note that SLAs rarely cover consequential damages—they usually offer service credits for downtime.

Should I use Helicone in production?

Helicone is production-ready and used by many companies. However, as with any third-party service in your critical path, implement proper resilience patterns:

  • Automatic failover to direct LLM access
  • Timeout configurations (10-30 seconds max)
  • Health checks and monitoring
  • Local logging backup

With these safeguards, Helicone adds tremendous value (cost savings via caching, observability, analytics) while minimizing risk.

What regions does Helicone operate in?

Helicone's proxy infrastructure is globally distributed with endpoints in multiple regions (US, EU). However, your data residency and which endpoint your requests route through depends on your configuration. For latency-sensitive applications, verify that your chosen proxy endpoint (oai.helicone.ai, anthropic.helicone.ai, etc.) has low latency from your infrastructure region.

How do I monitor Helicone alongside my LLM providers?

Use API Status Check to monitor your entire LLM stack in one place:

Get instant alerts when any service in your stack degrades, helping you quickly determine if issues are with Helicone, the LLM provider, or your integration.

Can Helicone's caching cause stale responses during an outage?

Helicone's cache uses semantic similarity to match requests, and cached responses include age metadata. During a caching service outage, the cache simply won't be used—all requests pass through to the LLM provider. You won't get stale data; you'll just lose the cost and latency benefits of caching until the service is restored.

Stay Ahead of Helicone Outages

Don't let observability outages leave you flying blind. Subscribe to real-time Helicone alerts and get notified instantly when issues are detected—before your logs start disappearing.

API Status Check monitors Helicone 24/7 with:

  • 60-second health checks of proxy endpoints and logging pipeline
  • Instant alerts via email, Slack, Discord, or webhook
  • Historical uptime tracking and incident reports
  • Multi-service monitoring for your entire LLM stack (OpenAI, Anthropic, Cohere, etc.)

Start monitoring Helicone now →

Last updated: February 4, 2026. Helicone status information is provided in real-time based on active monitoring. For official incident reports, always refer to status.helicone.ai.

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