Axiom

Axiom is a cloud-native observability platform for storing, querying, and analyzing log and event data at scale. Use the REST API to ingest data, run queries using APL (Axiom Processing Language), and manage datasets programmatically.

Official docs: https://axiom.co/docs/restapi/introduction

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When to Use

Use this skill when you need to:

• Send logs, metrics, or event data to Axiom
• Query and analyze data using APL (Axiom Processing Language)
• Manage datasets, monitors, and annotations
• Build observability pipelines and dashboards

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Prerequisites

1. Create an Axiom account at https://app.axiom.co/register
2. Create an API token with appropriate permissions (Settings > API Tokens)
3. Create a dataset to store your data

Token Types

Axiom supports two token types:

Type	Prefix	Use Case
API Token	xaat-	Most operations (datasets, ingest, queries, monitors)
Personal Access Token (PAT)	xapt-	Full account access (required for /v2/user endpoint)

Set environment variables:

# Required: API Token for most operations
export AXIOM_TOKEN="xaat-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"

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How to Use

Base URLs

• Ingest (US East): https://us-east-1.aws.edge.axiom.co
• Ingest (EU Central): https://eu-central-1.aws.edge.axiom.co
• API: https://api.axiom.co

1. List Datasets

curl -s "https://api.axiom.co/v2/datasets" -H "Authorization: Bearer $(printenv AXIOM_TOKEN)"

2. Get Dataset Info

curl -s "https://api.axiom.co/v2/datasets/my-logs" -H "Authorization: Bearer $(printenv AXIOM_TOKEN)"

3. Create Dataset

Write to /tmp/axiom_request.json:

{
  "name": "my-logs",
  "description": "Application logs"
}

Then run:

curl -s -X POST "https://api.axiom.co/v2/datasets" -H "Authorization: Bearer $(printenv AXIOM_TOKEN)" -H "Content-Type: application/json" -d @/tmp/axiom_request.json

4. Ingest Data (JSON)

Write to /tmp/axiom_request.json:

[
  {"message": "User logged in", "user_id": "123", "level": "info"}
]

Then run:

curl -s -X POST "https://us-east-1.aws.edge.axiom.co/v1/ingest/my-logs" -H "Authorization: Bearer $(printenv AXIOM_TOKEN)" -H "Content-Type: application/json" -d @/tmp/axiom_request.json

5. Ingest Data (NDJSON)

Write to /tmp/axiom_ndjson.ndjson:

{"message": "Event 1", "level": "info"}
{"message": "Event 2", "level": "warn"}

Then run:

curl -s -X POST "https://us-east-1.aws.edge.axiom.co/v1/ingest/my-logs" -H "Authorization: Bearer $(printenv AXIOM_TOKEN)" -H "Content-Type: application/x-ndjson" -d @/tmp/axiom_ndjson.ndjson

6. Query Data with APL

Write to /tmp/axiom_request.json:

{
  "apl": "[\"my-logs\"] | where level == \"error\" | limit 10",
  "startTime": "2024-01-01T00:00:00Z",
  "endTime": "2025-12-31T23:59:59Z"
}

Then run:

curl -s -X POST "https://api.axiom.co/v1/datasets/_apl?format=tabular" -H "Authorization: Bearer $(printenv AXIOM_TOKEN)" -H "Content-Type: application/json" -d @/tmp/axiom_request.json

7. Query with Aggregation

Write to /tmp/axiom_request.json:

{
  "apl": "[\"my-logs\"] | summarize count() by level",
  "startTime": "2024-01-01T00:00:00Z",
  "endTime": "2025-12-31T23:59:59Z"
}

Then run:

curl -s -X POST "https://api.axiom.co/v1/datasets/_apl?format=tabular" -H "Authorization: Bearer $(printenv AXIOM_TOKEN)" -H "Content-Type: application/json" -d @/tmp/axiom_request.json

8. Create Annotation

Write to /tmp/axiom_request.json:

{
  "datasets": ["my-logs"],
  "type": "deployment",
  "title": "v1.2.0 deployed",
  "time": "2024-12-24T10:00:00Z"
}

Then run:

curl -s -X POST "https://api.axiom.co/v2/annotations" -H "Authorization: Bearer $(printenv AXIOM_TOKEN)" -H "Content-Type: application/json" -d @/tmp/axiom_request.json

9. List Monitors

curl -s "https://api.axiom.co/v2/monitors" -H "Authorization: Bearer $(printenv AXIOM_TOKEN)"

10. Delete Dataset

curl -s -X DELETE "https://api.axiom.co/v2/datasets/my-logs" -H "Authorization: Bearer $(printenv AXIOM_TOKEN)"

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APL Query Examples

APL (Axiom Processing Language) is similar to Kusto Query Language (KQL). Use ["dataset-name"] syntax for dataset names with special characters.

Query	Description
["dataset"] | limit 10	Get first 10 events
["dataset"] | where level == "error"	Filter by field value
["dataset"] | where message contains "timeout"	Search in text
["dataset"] | summarize count() by level	Count by group
["dataset"] | summarize avg(duration_ms) by bin(_time, 1h)	Hourly average
["dataset"] | sort by _time desc | limit 100	Latest 100 events
["dataset"] | where _time > ago(1h)	Events in last hour

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Guidelines

1. Use Edge URLs for Ingest: Always use the edge endpoint (us-east-1.aws.edge.axiom.co or eu-central-1.aws.edge.axiom.co) for data ingestion, not api.axiom.co
2. Batch Events: Send multiple events in a single request for better performance
3. Include Timestamps: Events without timestamps will use server receive time
4. Rate Limits: Check X-RateLimit-Remaining header to avoid hitting limits
5. APL Time Range: Always specify startTime and endTime for queries to improve performance
6. Data Formats: JSON array is recommended; NDJSON and CSV are also supported