--- title: "Alerting / Webhooks" description: "import Image from '@theme/IdealImage'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';" type: skill canonical_url: https://claudary.paisolsolutions.com/skills/alerting source: "Claudary" difficulty: intermediate author: "Claude Code Knowledge Pack" date: 2026-07-10T11:07:26.149Z license: CC-BY-4.0 attribution: "Alerting / Webhooks โ€” Claudary (https://claudary.paisolsolutions.com/skills/alerting)" --- # Alerting / Webhooks import Image from '@theme/IdealImage'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; ## Overview import Image from '@theme/IdealImage'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; # Alerting / Webhooks Get alerts for: | Category | Alert Type | |----------|------------| | **LLM Performance** | Hanging API calls, Slow API calls, Failed API calls, Model outage alerting | | **Budget & Spend** | Budget tracking per key/user, Soft budget alerts, Weekly & Monthly spend reports per Team/Tag | | **System Health** | Failed database read/writes | | **Daily Reports** | Top 5 slowest LLM deployments, Top 5 LLM deployments with most failed requests, Weekly & Monthly spend per Team/Tag | Works across: - [Slack](#quick-start) - [Discord](#advanced---using-discord-webhooks) - [Microsoft Teams](#advanced---using-ms-teams-webhooks) ## Quick Start Set up a slack alert channel to receive alerts from proxy. ### Step 1: Add a Slack Webhook URL to env Get a slack webhook url from https://api.slack.com/messaging/webhooks You can also use Discord Webhooks, see [here](#using-discord-webhooks) Set `SLACK_WEBHOOK_URL` in your proxy env to enable Slack alerts. ```bash export SLACK_WEBHOOK_URL="https://hooks.slack.com/services/<>/<>/<>" ``` ### Step 2: Setup Proxy ```yaml general_settings: alerting: ["slack"] alerting_threshold: 300 # sends alerts if requests hang for 5min+ and responses take 5min+ spend_report_frequency: "1d" # [Optional] set as 1d, 2d, 30d .... Specify how often you want a Spend Report to be sent # [OPTIONAL ALERTING ARGS] alerting_args: daily_report_frequency: 43200 # 12 hours in seconds report_check_interval: 3600 # 1 hour in seconds budget_alert_ttl: 86400 # 24 hours in seconds outage_alert_ttl: 60 # 1 minute in seconds region_outage_alert_ttl: 60 # 1 minute in seconds minor_outage_alert_threshold: 5 major_outage_alert_threshold: 10 max_outage_alert_list_size: 1000 log_to_console: false ``` Start proxy ```bash $ litellm --config /path/to/config.yaml ``` ### Step 3: Test it! ```bash curl -X GET 'http://0.0.0.0:4000/health/services?service=slack' \\ -H 'Authorization: Bearer sk-1234' ``` ## Advanced ### Redacting Messages from Alerts By default alerts show the `messages/input` passed to the LLM. If you want to redact this from slack alerting set the following setting on your config ```shell general_settings: alerting: ["slack"] alert_types: ["spend_reports"] litellm_settings: redact_messages_in_exceptions: True ``` ### Soft Budget Alerts for Virtual Keys Use this to send an alert when a key/team is close to it's budget running out Step 1. Create a virtual key with a soft budget Set the `soft_budget` to 0.001 ```shell curl -X 'POST' \\ 'http://localhost:4000/key/generate' \\ -H 'accept: application/json' \\ -H 'x-goog-api-key: sk-1234' \\ -H 'Content-Type: application/json' \\ -d '{ "key_alias": "prod-app1", "team_id": "113c1a22-e347-4506-bfb2-b320230ea414", "soft_budget": 0.001 }' ``` Step 2. Send a request to the proxy with the virtual key ```shell curl http://0.0.0.0:4000/chat/completions \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer sk-Nb5eCf427iewOlbxXIH4Ow" \\ -d '{ "model": "openai/gpt-4", "messages": [ { "role": "user", "content": "this is a test request, write a short poem" } ] }' ``` Step 3. Check slack for Expected Alert ### Add Metadata to alerts Add alerting metadata to proxy calls for debugging. ```python import openai client = openai.OpenAI( api_key="anything", base_url="http://0.0.0.0:4000" ) # request sent to model set on litellm proxy, `litellm --model` response = client.chat.completions.create( model="gpt-4o", messages = [], extra_body={ "metadata": { "alerting_metadata": { "hello": "world" } } } ) ``` **Expected Response** ### Select specific alert types Set `alert_types` if you want to Opt into only specific alert types. When alert_types is not set, all Default Alert Types are enabled. ๐Ÿ‘‰ [**See all alert types here**](#all-possible-alert-types) ```shell general_settings: alerting: ["slack"] alert_types: [ "llm_exceptions", "llm_too_slow", "llm_requests_hanging", "budget_alerts", "spend_reports", "db_exceptions", "daily_reports", "cooldown_deployment", "new_model_added", ] ``` ### Map slack channels to alert type Use this if you want to set specific channels per alert type **This allows you to do the following** ``` llm_exceptions -> go to slack channel #llm-exceptions spend_reports -> go to slack channel #llm-spend-reports ``` Set `alert_to_webhook_url` on your config.yaml ```yaml model_list: - model_name: gpt-4 litellm_params: model: openai/fake api_key: fake-key api_base: https://exampleopenaiendpoint-production.up.railway.app/ general_settings: master_key: sk-1234 alerting: ["slack"] alerting_threshold: 0.0001 # (Seconds) set an artificially low threshold for testing alerting alert_to_webhook_url: { "llm_exceptions": "example-slack-webhook-url", "llm_too_slow": "example-slack-webhook-url", "llm_requests_hanging": "example-slack-webhook-url", "budget_alerts": "example-slack-webhook-url", "db_exceptions": "example-slack-webhook-url", "daily_reports": "example-slack-webhook-url", "spend_reports": "example-slack-webhook-url", "cooldown_deployment": "example-slack-webhook-url", "new_model_added": "example-slack-webhook-url", "outage_alerts": "example-slack-webhook-url", } litellm_settings: success_callback: ["langfuse"] ``` Provide multiple slack channels for a given alert type ```yaml model_list: - model_name: gpt-4 litellm_params: model: openai/fake api_key: fake-key api_base: https://exampleopenaiendpoint-production.up.railway.app/ general_settings: master_key: sk-1234 alerting: ["slack"] alerting_threshold: 0.0001 # (Seconds) set an artificially low threshold for testing alerting alert_to_webhook_url: { "llm_exceptions": ["os.environ/SLACK_WEBHOOK_URL", "os.environ/SLACK_WEBHOOK_URL_2"], "llm_too_slow": ["https://webhook.site/7843a980-a494-4967-80fb-d502dbc16886", "https://webhook.site/28cfb179-f4fb-4408-8129-729ff55cf213"], "llm_requests_hanging": ["os.environ/SLACK_WEBHOOK_URL_5", "os.environ/SLACK_WEBHOOK_URL_6"], "budget_alerts": ["os.environ/SLACK_WEBHOOK_URL_7", "os.environ/SLACK_WEBHOOK_URL_8"], "db_exceptions": ["os.environ/SLACK_WEBHOOK_URL_9", "os.environ/SLACK_WEBHOOK_URL_10"], "daily_reports": ["os.environ/SLACK_WEBHOOK_URL_11", "os.environ/SLACK_WEBHOOK_URL_12"], "spend_reports": ["os.environ/SLACK_WEBHOOK_URL_13", "os.environ/SLACK_WEBHOOK_URL_14"], "cooldown_deployment": ["os.environ/SLACK_WEBHOOK_URL_15", "os.environ/SLACK_WEBHOOK_URL_16"], "new_model_added": ["os.environ/SLACK_WEBHOOK_URL_17", "os.environ/SLACK_WEBHOOK_URL_18"], "outage_alerts": ["os.environ/SLACK_WEBHOOK_URL_19", "os.environ/SLACK_WEBHOOK_URL_20"], } litellm_settings: success_callback: ["langfuse"] ``` Test it - send a valid llm request - expect to see a `llm_too_slow` alert in it's own slack channel ```shell curl -i http://localhost:4000/v1/chat/completions \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer sk-1234" \\ -d '{ "model": "gpt-4", "messages": [ {"role": "user", "content": "Hello, Claude gm!"} ] }' ``` ### MS Teams Webhooks MS Teams provides a slack compatible webhook url that you can use for alerting ##### Quick Start 1. [Get a webhook url](https://learn.microsoft.com/en-us/microsoftteams/platform/webhooks-and-connectors/how-to/add-incoming-webhook?tabs=newteams%2Cdotnet#create-an-incoming-webhook) for your Microsoft Teams channel 2. Add it to your .env ```bash SLACK_WEBHOOK_URL="https://berriai.webhook.office.com/webhookb2/...6901/IncomingWebhook/b55fa0c2a48647be8e6effedcd540266/e04b1092-4a3e-44a2-ab6b-29a0a4854d1d" ``` 3. Add it to your litellm config ```yaml model_list: model_name: "azure-model" litellm_params: model: "azure/gpt-35-turbo" api_key: "my-bad-key" # ๐Ÿ‘ˆ bad key general_settings: alerting: ["slack"] alerting_threshold: 300 # sends alerts if requests hang for 5min+ and responses take 5min+ ``` 4. Run health check! Call the proxy `/health/services` endpoint to test if your alerting connection is correctly setup. ```bash curl --location 'http://0.0.0.0:4000/health/services?service=slack' \\ --header 'Authorization: Bearer sk-1234' ``` **Expected Response** ### Discord Webhooks Discord provides a slack compatible webhook url that you can use for alerting ##### Quick Start 1. Get a webhook url for your discord channel 2. Append `/slack` to your discord webhook - it should look like ``` "https://discord.com/api/webhooks/1240030362193760286/cTLWt5ATn1gKmcy_982rl5xmYHsrM1IWJdmCL1AyOmU9JdQXazrp8L1_PYgUtgxj8x4f/slack" ``` 3. Add it to your litellm config ```yaml model_list: model_name: "azure-model" litellm_params: model: "azure/gpt-35-turbo" api_key: "my-bad-key" # ๐Ÿ‘ˆ bad key general_settings: alerting: ["slack"] alerting_threshold: 300 # sends alerts if requests hang for 5min+ and responses take 5min+ environment_variables: SLACK_WEBHOOK_URL: "https://discord.com/api/webhooks/1240030362193760286/cTLWt5ATn1gKmcy_982rl5xmYHsrM1IWJdmCL1AyOmU9JdQXazrp8L1_PYgUtgxj8x4f/slack" ``` ## [BETA] Webhooks for Budget Alerts **Note**: This is a beta feature, so the spec might change. Set a webhook to get notified for budget alerts. 1. Setup config.yaml Add url to your environment, for testing you can use a link from [here](https://webhook.site/) ```bash export WEBHOOK_URL="https://webhook.site/6ab090e8-c55f-4a23-b075-3209f5c57906" ``` Add 'webhook' to config.yaml ```yaml general_settings: alerting: ["webhook"] # ๐Ÿ‘ˆ KEY CHANGE ``` 2. Start proxy ```bash litellm --config /path/to/config.yaml # RUNNING on http://0.0.0.0:4000 ``` 3. Test it! ```bash curl -X GET --location 'http://0.0.0.0:4000/health/services?service=webhook' \\ --header 'Authorization: Bearer sk-1234' ``` **Expected Response** ```bash { "spend": 1, # the spend for the 'event_group' "max_budget": 0, # the 'max_budget' set for the 'event_group' "token": "example-api-key-123", "user_id": "default_user_id", "team_id": null, "user_email": null, "key_alias": null, "projected_exceeded_data": null, "projected_spend": null, "event": "budget_crossed", # Literal["budget_crossed", "threshold_crossed", "projected_limit_exceeded"] "event_group": "user", "event_message": "User Budget: Budget Crossed" } ``` ### API Spec for Webhook Event - `spend` *float*: The current spend amount for the 'event_group'. - `max_budget` *float or null*: The maximum allowed budget for the 'event_group'. null if not set. - `token` *str*: A hashed value of the key, used for authentication or identification purposes. - `customer_id` *str or null*: The ID of the customer associated with the event (optional). - `internal_user_id` *str or null*: The ID of the internal user associated with the event (optional). - `team_id` *str or null*: The ID of the team associated with the event (optional). - `user_email` *str or null*: The email of the internal user associated with the event (optional). - `key_alias` *str or null*: An alias for the key associated with the event (optional). - `projected_exceeded_date` *str or null*: The date when the budget is projected to be exceeded, returned when 'soft_budget' is set for key (optional). - `projected_spend` *float or null*: The projected spend amount, returned when 'soft_budget' is set for key (optional). - `event` *Literal["budget_crossed", "threshold_crossed", "projected_limit_exceeded"]*: The type of event that triggered the webhook. Possible values are: * "spend_tracked": Emitted whenever spend is tracked for a customer id. * "budget_crossed": Indicates that the spend has exceeded the max budget. * "threshold_crossed": Indicates that spend has crossed a threshold (currently sent when 85% and 95% of budget is reached). * "projected_limit_exceeded": For "key" only - Indicates that the projected spend is expected to exceed the soft budget threshold. - `event_group` *Literal["customer", "internal_user", "key", "team", "proxy"]*: The group associated with the event. Possible values are: * "customer": The event is related to a specific customer * "internal_user": The event is related to a specific internal user. * "key": The event is related to a specific key. * "team": The event is related to a team. * "proxy": The event is related to a proxy. - `event_message` *str*: A human-readable description of the event. ### Digest Mode (Reducing Alert Noise) By default, LiteLLM sends a separate Slack message for **every** alert event. For high-frequency alert types like `llm_requests_hanging` or `llm_too_slow`, this can produce hundreds of duplicate messages per day. **Digest mode** aggregates duplicate alerts within a configurable time window and emits a single summary message with the total count and time range. #### Configuration Use `alert_type_config` in `general_settings` to enable digest mode per alert type: ```yaml general_settings: alerting: ["slack"] alert_type_config: llm_requests_hanging: digest: true digest_interval: 86400 # 24 hours (default) llm_too_slow: digest: true digest_interval: 3600 # 1 hour llm_exceptions: digest: true # uses default interval (86400 seconds / 24 hours) ``` | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `digest` | bool | `false` | Enable digest mode for this alert type | | `digest_interval` | int | `86400` (24h) | Time window in seconds. Alerts are aggregated within this interval. | #### How It Works 1. When an alert fires for a digest-enabled type, it is **grouped** by `(alert_type, request_model, api_base)` instead of being sent immediately 2. A counter tracks how many times the alert fires within the interval 3. When the interval expires, a **single summary message** is sent: ``` Alert type: `llm_requests_hanging` (Digest) Level: `Medium` Start: `2026-02-19 03:27:39` End: `2026-02-20 03:27:39` Count: `847` Message: `Requests are hanging - 600s+ request time` Request Model: `gemini-2.5-flash` API Base: `None` ``` #### Limitations - **Per-instance**: Digest state is held in memory per proxy instance. If you run multiple instan --- Source: [Claudary](https://claudary.paisolsolutions.com/skills/alerting) ยท https://claudary.paisolsolutions.com