Table of Content

• Overview
• Option 1: Sending Data via the Wavefront Proxy
• Option 2: Sending Data via Direct ingestion
• Share a WavefrontSender
• Where to Go Next

Overview

You can send metrics, histograms, or trace data from your application to the Wavefront service using a Wavefront proxy or direct ingestions.

• Use a Wavefront proxy, which then forwards the data to the Wavefront service. This is the recommended choice for a large-scale deployment that needs resilience to internet outages, control over data queuing and filtering, and more.
• Use direct ingestion to send the data directly to the Wavefront service. This is the simplest way to get up and running quickly.

The WavefrontSender interface has two implementations:

• Option 1: Create a WavefrontProxyClient to send data to a Wavefront proxy.
• Option 2: Create a WavefrontDirectIngestionClient to send data directly to a Wavefront service.

Option 1: Sending Data via the Wavefront Proxy

Prerequisite Before your application can use a WavefrontProxyClient, you must set up and start a Wavefront proxy.

When sending data via the Wavefront proxy, you need to create a WavefrontProxyClient. Include the following information.

• The name of the host that will run the Wavefront proxy.
• One or more proxy listening ports to send data to. The ports you specify depend on the kinds of data you want to send (metrics, histograms, and/or trace data). You must specify at least one listener port.
• Optional settings for tuning communication with the proxy.

Note: See Advanced Proxy Configuration and Installation for details.

from wavefront_sdk import WavefrontProxyClient

# Create a sender with:
   # the proxy hostname or address
   # the recommended listener port (30000) for sending trace data 
   # the recommended listener port (2878) for sending histograms
   # the default listener port (2878) for sending metrics  
   # a nondefault interval (2 seconds) for flushing data from the sender to the proxy. Default: 5 seconds
wavefront_sender = WavefrontProxyClient(
   host="<PROXY_HOST>",
   tracing_port=30000,
   distribution_port=2878,
   metrics_port=2878,
   internal_flush=2
)

Note: When you set up a Wavefront proxy on the specified proxy host, you specify the port it will listen to for each type of data to be sent. The WavefrontProxyClient must send data to the same ports that the Wavefront proxy listens to. Consequently, the port-related builder methods must specify the same port numbers as the corresponding proxy configuration properties. See the following table:

WavefrontProxyClient() parameter	Corresponding property in wavefront.conf
metrics_port	pushListenerPorts=
distribution_port	histogramDistListenerPorts=
tracing_port	traceListenerPorts=

Option 2: Sending Data via Direct Ingestion

When sending data via direct ingestion, you need to create a WavefrontDirectIngestionClient, and build it with the Wavefront URL and API token to send data directly to Wavefront.

Prerequisite

• Verify that you have the Direct Data Ingestion permission. For details, see Examine Groups, Roles, and Permissions.
• The URL of your Wavefront instance. This is the URL you connect to when you log in to Wavefront, typically something like https://<domain>.wavefront.com.
• Obtain the API token.

Initialize the WavefrontDirectIngestionClient

You initialize a WavefrontDirectClient by building it with the access information you obtained in the Prerequisite section.

from wavefront_sdk import WavefrontDirectClient

# Create a sender with:
   # the Wavefront URL 
   # a Wavefront API token that was created with direct ingestion permission
wavefront_sender = WavefrontDirectClient(
    server="<SERVER_ADDR>",
    token="<TOKEN>"
)

Share a Wavefront Sender

If you are using multiple Wavefront Python SDKs within the same process, you can create a single Wavefront sender, and share it among the SDKs.

Note: If you use SDKs in different processes, you must create one Sender instance per process.

Where to Go Next

To continue, select one of the Wavefront Python SDK links in the table below.

SDK Type	SDK Description	Python SDKs
OpenTracing SDK	Implements the OpenTracing specification. Lets you define, collect, and report custom trace data from any part of your application code. Automatically derives RED metrics from the reported spans.	Python OpenTracing SDK
Metrics SDK	Implements a standard metrics library. Lets you define, collect, and report custom business metrics and histograms from any part of your application code.	Pyformance SDK
Sender SDK	Lets you send raw values to Wavefront for storage as metrics, histograms, or traces, e.g., to import CSV data into Wavefront.	Python Sender SDK