Data Sources

Parseable supports ingesting telemetry from a wide variety of data sources. Whether you're sending telemetry directly from your applications or using popular telemetry agents, Parseable provides flexible integration options to fit your logging infrastructure.

Overview

There are two primary ways to send telemetry to Parseable:

1. Direct Application Integration - Send telemetry directly from your application code using HTTP APIs
2. Telemetry Agents - Use industry-standard telemetry collection agents to aggregate and forward telemetry

Applications

Send telemetry directly from your applications using Parseable's HTTP API. This approach gives you fine-grained control over what gets logged and when. Parseable provides examples and guidance for popular programming languages:

• Python - Send telemetry using Python's requests library
• JavaScript - Integrate telemetry in Node.js and browser applications
• Go - Use Go's native HTTP client for telemetry ingestion
• Java - Send telemetry from Java applications
• Rust - Integrate Parseable in Rust applications
• C# - Send telemetry from .NET applications

Each language guide includes examples for:

• Creating telemetry streams
• Sending telemetry events with custom metadata and tags
• Querying telemetry using SQL

Log Agents

Use established log collection agents to aggregate telemetry from multiple sources and forward them to Parseable. This approach is ideal for:

• Collecting telemetry from multiple applications and services
• Aggregating system telemetry and container telemetry
• Processing and transforming telemetry before ingestion
• Implementing centralized telemetry architectures

Parseable integrates seamlessly with popular log agents:

• Fluent Bit - Lightweight and high-performance log processor
• Fluentd - Unified logging layer with extensive plugin ecosystem
• Vector - High-performance observability data pipeline
• OpenTelemetry Collector - Vendor-agnostic telemetry data collection
• Logstash - Server-side data processing pipeline
• Syslog - Traditional system logging protocol
• Apache Log4j - Java-based logging utility

Choosing the Right Approach

Use Direct Application Integration When:

• You need fine-grained control over telemetry content and structure
• You want to minimize infrastructure dependencies
• You're building a new application or microservice
• You need to add custom metadata or tags at the application level

Use Telemetry Agents When:

• You need to collect telemetry from multiple sources
• You want to aggregate container or system telemetry
• You need to transform or enrich telemetry before ingestion
• You're implementing a centralized telemetry strategy
• You want to buffer telemetry during network issues

Next Steps

Choose your integration method and follow the corresponding guide:

• Browse the Applications section for language-specific examples
• Explore the Log Agents section for agent-specific configurations

For API reference and advanced configuration options, see the API Documentation.