Connect Axiom with Convex

Connect Axiom with Convex to get comprehensive observability into your backend functions and app events. Stream function executions, console logs, and metadata from your Convex deployment to Axiom for powerful querying, data visualization, and monitoring.

Convex and log streams

Convex is the backend platform that keeps your app in sync. It’s the open source, reactive database where queries are TypeScript code running right in the database. Just like React components react to state changes, Convex queries react to database changes.

Convex provides a database, a place to write your server functions, and client libraries. It makes it easy to build and scale dynamic live-updating apps.

Log streams enable streaming of events such as function executions and console.logs from your Convex deployment to supported destinations like Axiom, Datadog, or custom webhooks.

Benefits of connecting Axiom with Convex

Convex’s built-in features allow you to see the most recent logs produced by your deployment. Additionally, log streaming to Axiom provides comprehensive observability for your backend operations.

• Historical log storage beyond the recent logs view.
• Powerful querying with Axiom Processing Language (APL).
• Advanced data visualization and custom dashboards.
• Integration with monitoring tools like PagerDuty, Slack, and more.
• Real-time alerting based on function performance and errors.

Analyze function performance

Convex log streams send structured data to Axiom that includes the following key fields:

After sending Convex log streams to Axiom, explore your Convex data and analyze your function performance using Axiom’s powerful query capabilities.

['convex']
| where ['data.topic'] == "function_execution"
| summarize 
    avg_time_ms = avg(['data.execution_time_ms']),
    max_time_ms = max(['data.execution_time_ms']),
    total_calls = count()
  by ['data.function.path']
| order by avg_time_ms desc

['convex']
| where ['data.topic'] == "function_execution" and ['data.status'] == "failure"
| summarize count() by ['data.function.path'], ['data.function.type']
| order by count_ desc

['convex']
| where ['data.topic'] == "function_execution"
| summarize 
    total_calls = count(),
    avg_duration_ms = avg(['data.execution_time_ms'])
  by ['data.function.type']

['convex']
| where ['data.topic'] == "function_execution"
| summarize 
    avg_docs_read = avg(['data.usage.database_read_documents']),
    avg_bytes_read = avg(['data.usage.database_read_bytes'])
  by ['data.function.path']
| order by avg_bytes_read desc

['convex']
| where ['data.topic'] == "function_execution" 
  and ['data.function.type'] == "query"
  and isnotempty(['data.function.cached'])
| summarize 
    cache_hits = countif(['data.function.cached'] == true),
    total_queries = count()
| extend cache_hit_rate = (cache_hits * 100) / total_queries

['convex']
| where ['data.topic'] == "scheduled_job_lag"
| summarize 
    max_lag_seconds = max(['data.lag_seconds']),
    avg_lag_seconds = avg(['data.lag_seconds'])
  by ['convex.project_slug'], ['convex.deployment_name']

Set up monitoring and alerting

Create monitors to get notified about issues in your Convex deployment.

['convex']
| where ['data.topic'] == "function_execution"
| summarize 
    total_calls = count(),
    failures = countif(['data.status'] == "failure")
  by ['data.function.path']
| extend error_rate = (failures * 100) / total_calls
| where error_rate > 5  // Alert if error rate exceeds 5%

['convex']
| where ['data.topic'] == "function_execution" and ['data.execution_time_ms'] > 5000
| summarize count() by ['data.function.path']

Prebuilt dashboard

When you configure a Convex dataset in Axiom, a dashboard is automatically created in the Integrations section of the Dashboards tab. This prebuilt dashboard provides immediate insights into your Convex function performance and errors.

The dashboard includes:

• Function execution metrics: Success rates, error counts, and performance trends.
• Database operation insights: Query patterns, mutation frequencies, and subscription activity.
• Error analysis: Error types, frequency, and affected functions.
• Performance monitoring: Response times, throughput, and resource utilization.

You can customize this dashboard or create additional dashboards tailored to your specific monitoring needs and business requirements. For more information, see Create dashboards and Configure dashboards.

Next steps

• Explore your Convex data in Axiom and learn APL to query your Convex logs.
• Create custom dashboards for your team.
• Set up monitors to get alerted about issues.