# Alerts
### Overview
Alerts evaluate your selected metrics at regular intervals and notify you when conditions are met. Each alert can have two severity levels:
* **Warning** — Early indicator that a metric is trending toward a problem
* **Critical** — Immediate attention required; metric has exceeded acceptable limits
Alerts are scoped to specific Projects, API Keys, and Models, giving you granular control over what you monitor.
Select metric, name and scope
Set threshold and subscribe to alert
***
### Available Metrics
#### Performance
| Metric | Description | Unit |
| ----------------------- | ----------------------------------------------------------------------------------------- | ----- |
| **Response Time** | Median (p50) end-to-end latency from request receipt to response completion | ms |
| **Time to First Token** | Median (p50) time from request submission until the first response token begins streaming | ms |
| **Throughput** | Median request throughput for streaming responses (`stream = true`) | req/s |
#### Reliability
| Metric | Description | Unit |
| --------------- | ------------------------------------------------------------ | ------ |
| **Error Count** | Total number of failed requests within the evaluation window | errors |
| **Error Rate** | Percentage of requests that failed | % |
#### Usage & Cost
| Metric | Description | Unit |
| --------------------- | ---------------------------------------------------------------- | -------- |
| **Token Consumption** | Total tokens consumed (input + output) | tokens |
| **Daily Spend** | Cumulative spending for the current day (resets at midnight UTC) | $ |
| **Monthly Spend** | Cumulative spending for the current month (resets on the 1st) | $ |
| **Total Requests** | Total number of API requests | requests |
***
### Scoping Alerts
Each alert can be scoped to monitor specific subsets of your traffic:
#### Projects
Select which projects to include in the alert evaluation. You can choose:
* **All Projects** — Monitor aggregate metrics across your entire organization
* **Specific Projects** — Monitor one or more selected projects
#### API Keys
Select which API keys to include:
* **All Keys** — Monitor all API keys within the selected projects
* **Specific Keys** — Monitor one or more selected API keys
#### Models
Select which models to include:
* **All Models** — Monitor requests to any model
* **Specific Models** — Monitor requests to selected models only (e.g., only GPT-4.1 and Claude 4.5 Sonnet)
> **Example**: You could create an alert that monitors Response Time only for your "Production" project, only for requests using a particular API key, and only for GPT-4.1 requests.
***
### Alert Types
#### Static Value
Triggers when the metric crosses a fixed threshold.
**Use cases:**
* Response Time > 2000ms
* Error Rate > 5%
* Daily Spend > $500
**Configuration:**
| Field | Description |
| ------------------ | ----------------------------------------------- |
| Condition | `Above` or `Below` |
| Warning Threshold | Value that triggers a warning (optional) |
| Critical Threshold | Value that triggers a critical alert (required) |
#### Percentage Change
Triggers when the metric changes by a specified percentage compared to a historical baseline.
**Use cases:**
* Response Time increased 50% vs same time yesterday
* Request volume dropped 30% vs same time last week
* Error Count spiked 100% vs previous hour
**Configuration:**
| Field | Description |
| ---------------------- | ------------------------------------------------ |
| Comparison Period | Historical baseline to compare against |
| Condition | `Above` or `Below` |
| Warning Threshold (%) | Percentage change that triggers a warning |
| Critical Threshold (%) | Percentage change that triggers a critical alert |
***
### Evaluation Interval
The evaluation interval determines how often the alert checks your metrics. Choose based on how quickly you need to detect issues:
| Interval | Best For | Trade-off |
| ---------- | -------------------------------- | ---------------------------------------------------- |
| **5 min** | Error Rate, Error Count | Fastest detection, may be noisy for volatile metrics |
| **15 min** | Response Time, TTFT, Throughput | Balances speed and noise reduction |
| **30 min** | Response Time, Token Consumption | Smooths transient spikes |
| **1 hour** | Spend metrics, Usage patterns | Good for slow-changing metrics |
| **Daily** | Daily Spend, Monthly Spend | End-of-day summaries |
#### Recommendations by Metric
| Metric | Recommended Interval |
| ------------------------ | -------------------- |
| Error Rate / Error Count | 5 min |
| Response Time / TTFT | 15–30 min |
| Throughput | 15 min |
| Token Consumption | 30–60 min |
| Daily/Monthly Spend | 1 hour or Daily |
***
### Comparison Periods
When using **Percentage Change** alerts, you compare the current value against a historical baseline. The comparison period determines which historical window to use.
| Comparison Period | What It Compares | Best For |
| ------------------------- | ---------------------------------- | -------------------------------------------------- |
| **Previous Period** | The immediately preceding interval | Detecting sudden spikes |
| **Same time 1 hour ago** | Same interval, 1 hour earlier | Intra-day patterns |
| **Same time 1 day ago** | Same interval, 24 hours earlier | Daily patterns (e.g., business hours vs off-hours) |
| **Same time 1 week ago** | Same interval, 7 days earlier | Weekly patterns (e.g., weekday vs weekend) |
| **Same time 1 month ago** | Same interval, 30 days earlier | Monthly patterns, seasonal trends |
#### How Comparison Works
The system compares two time windows of equal length:
```
Current Window: [T - interval, T]
Previous Window: [T - interval - offset, T - offset]
```
**Example:** Alert runs at 3:00 PM with a 15-minute interval, comparing to "Same time 1 day ago"
```
Current Window: 2:45 PM – 3:00 PM today
Previous Window: 2:45 PM – 3:00 PM yesterday
```
#### Percentage Change Formula
```
% Change = ((Current Value - Previous Value) / Previous Value) × 100
```
**Example:**
* Current Response Time: 450ms
* Previous Response Time: 300ms
* % Change: ((450 - 300) / 300) × 100 = **50%**
If your alert threshold is "Above 40%", this would trigger.
***
### Thresholds
Each alert supports two threshold levels:
#### Warning Threshold
An early indicator that the metric is trending toward a problem. Useful for:
* Getting advance notice before issues become critical
* Allowing time to investigate before escalation
* Tracking trends that may need attention
#### Critical Threshold
The primary alert trigger indicating immediate attention is needed. This is the main threshold that should reflect your SLA or operational limits.
#### Condition Direction
| Condition | Meaning | Typical Use |
| --------- | --------------------------------------- | -------------------------------- |
| **Above** | Alert when metric exceeds threshold | Response Time, Error Rate, Spend |
| **Below** | Alert when metric falls below threshold | Throughput, Request Volume |
> **Tip:** Set your Warning threshold at \~50-70% of your Critical threshold to give yourself response time.
***
### Notification Behavior
#### Notification Channels
* **Email** — Send alerts to specified email addresses
* **Organization Owners** — Automatically notify all org owners
* **Project Members** — Automatically notify all members of affected projects
#### Alert States
Alerts transition between three states:
```
threshold breached
┌───────────────────────────┐
│ ▼
┌──┴──┐ ┌─────────┐
│ OK │ │ FIRING │
└──┬──┘ └────┬────┘
▲ │
└───────────────────────────┘
below threshold (reset)
```
***
### Examples
#### Example 1: High Response Time Alert
**Goal:** Get notified when API response times are slow
| Setting | Value |
| ------------------- | ---------------------------------------- |
| Metric | Response Time |
| Scope | Production project, All keys, All models |
| Alert Type | Static Value |
| Condition | Above |
| Warning Threshold | 1500 ms |
| Critical Threshold | 3000 ms |
| Evaluation Interval | 15 min |
**Behavior:** Every 15 minutes, calculates the median response time. If it exceeds 1500ms, a warning is sent. If it exceeds 3000ms, a critical alert is sent.
***
#### Example 2: Error Rate Spike Detection
**Goal:** Detect sudden increases in error rate compared to normal
| Setting | Value |
| ------------------- | ---------------------------------- |
| Metric | Error Rate |
| Scope | All projects, All keys, All models |
| Alert Type | Percentage Change |
| Comparison Period | Same time 1 day ago |
| Condition | Above |
| Warning Threshold | 50% |
| Critical Threshold | 100% |
| Evaluation Interval | 5 min |
**Behavior:** Every 5 minutes, compares the current error rate to the same 5-minute window yesterday. If today's error rate is 50% higher, a warning is sent. If it's 100% higher (doubled), a critical alert is sent.
***
#### Example 3: Daily Spend Limit
**Goal:** Get notified before exceeding daily budget
| Setting | Value |
| ------------------- | ---------------------------------------- |
| Metric | Daily Spend |
| Scope | Production project, All keys, All models |
| Alert Type | Static Value |
| Condition | Above |
| Warning Threshold | $400 |
| Critical Threshold | $500 |
| Evaluation Interval | 1 hour |
**Behavior:** Every hour, checks the cumulative daily spend. Sends a warning at $400 and a critical alert at $500.
***
#### Example 4: Traffic Drop Detection
**Goal:** Detect if request volume suddenly drops (may indicate an outage)
| Setting | Value |
| ------------------- | ---------------------------------------- |
| Metric | Total Requests |
| Scope | Production project, All keys, All models |
| Alert Type | Percentage Change |
| Comparison Period | Same time 1 hour ago |
| Condition | Below |
| Warning Threshold | 30% |
| Critical Threshold | 50% |
| Evaluation Interval | 5 min |
**Behavior:** Every 5 minutes, compares request count to the same period 1 hour ago. If traffic drops by 30%, a warning is sent. If it drops by 50%, a critical alert is sent.
***
### Best Practices
1. **Start with Critical thresholds only** — Add Warning thresholds once you understand your baseline metrics.
2. **Use appropriate intervals** — Don't use 5-minute intervals for metrics that naturally fluctuate; you'll get too many false positives.
3. **Leverage Percentage Change for anomalies** — Static thresholds work well for known limits, but percentage change is better for detecting unusual patterns.
4. **Scope alerts appropriately** — Create separate alerts for Production vs Staging environments rather than one alert for everything.
5. **Set up resolved notifications** — Knowing when an issue is resolved is as important as knowing when it started.
6. **Document your thresholds** — Keep a record of why you chose specific threshold values so future team members understand the rationale.
***
### FAQ
**Q: What happens if there's no data in the evaluation window?**
A: The alert maintains its current state. If there were zero requests in the window, metrics like Error Rate cannot be calculated, so the alert remains unchanged.
**Q: Can I have multiple alerts for the same metric?**
A: Yes. You might have one alert for Production and another for Staging, or different thresholds for different models.
**Q: When do cumulative metrics (Daily Spend, Monthly Spend) reset?**
A: Daily Spend resets at midnight UTC. Monthly Spend resets on the 1st of each month at midnight UTC.
**Q: What timezone are alerts evaluated in?**
A: All alert evaluations use UTC. "Same time 1 day ago" means the same UTC time yesterday.
**Q: Can I pause an alert without deleting it?**
A: Yes. You can pause an alert from the Alerts list page. Paused alerts retain their configuration but do not evaluate or send notifications.
---
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