Version: Self Hosted Turbo

Python on Instance

Supported Frameworks

Django | Flask | Odoo 15 | Odoo 16

Standard Library Modules

Django

Prerequisite

To enable tracing for an application that is developed by the Django framework, sf-elastic-apm and sf-apm-lib must be available in your environment. These libraries can be installed by the following methods:

Add the below-mentioned entries in the requirements.txt file.

sf-elastic-apm==6.7.2
sf-apm-lib==0.1.1

Install the libraries using CLI.

pip install sf-elastic-apm==6.7.2 
pip install sf-apm-lib==0.1.1

Configuration

Case 1: sfAgent installed in your instance

In this case, the trace agent picks up the profileKey, projectName, and appName from the config.yaml file.

Add the below entries in the settings.py file.

Add the following import statement.

from sf_apm_lib.snappyflow import Snappyflow

Add the following entry in the INSTALLED_APPS block.
```
'elasticapm.contrib.django'
```

Add the following entry in the MIDDLEWARE block.

'elasticapm.contrib.django.middleware.TracingMiddleware'

Add the following source code to integrate a Django application with SnappyFlow.

try: 
   # Initialize Snappyflow. By default intialization will take profileKey, projectName and appName from sfagent config.yaml
   sf = Snappyflow()  
   SFTRACE_CONFIG = sf.get_trace_config()

   ELASTIC_APM={ 
      # Specify your service name for tracing 
      'SERVICE_NAME': "custom-service" , 
      'SERVER_URL': SFTRACE_CONFIG.get('SFTRACE_SERVER_URL'), 
      'GLOBAL_LABELS': SFTRACE_CONFIG.get('SFTRACE_GLOBAL_LABELS'), 
      'VERIFY_SERVER_CERT': SFTRACE_CONFIG.get('SFTRACE_VERIFY_SERVER_CERT'), 
      'SPAN_FRAMES_MIN_DURATION':    SFTRACE_CONFIG.get('SFTRACE_SPAN_FRAMES_MIN_DURATION'), 
      'STACK_TRACE_LIMIT': SFTRACE_CONFIG.get('SFTRACE_STACK_TRACE_LIMIT'), 
      'CAPTURE_SPAN_STACK_TRACES': SFTRACE_CONFIG.get('SFTRACE_CAPTURE_SPAN_STACK_TRACES'), 
      'DJANGO_TRANSACTION_NAME_FROM_ROUTE': True, 
      'CENTRAL_CONFIG': False, 
      'METRICS_INTERVAL': '0s'
   } 
except Exception as error: 
   print("Error while fetching snappyflow tracing configurations", error) 

note

If your app is in debug mode (eg: settings.Debug = true), then the agent won’t send any tracing data to the SnappyFlow server. You can override it by adding 'Debug':True configuration in the ELASTIC_APM block.

Case 2: sfAgent not installed in your instance

In this case, follow the below steps to enable tracing.

Make sure that the project and the application are created in the SnappyFlow Server. Click here to know how to create a project and an application in SnappyFlow.

Export SF_PROJECT_NAME, SF_APP_NAME, SF_PROFILE_KEY as the environment variables.

# Update the below default values with proper values
  export SF_PROJECT_NAME=<SF_PROJECT_NAME>
  export SF_APP_NAME=<SF_APP_NAME>
  export SF_PROFILE_KEY=<SF_PROFILE_KEY> 

Add the following entries in the settings.py file.

Add the following import statement.

from sf_apm_lib.snappyflow import Snappyflow 
import os

Add the following entry in the INSTALLED_APPS block.
```
'elasticapm.contrib.django'
```

Add the following entry in the MIDDLEWARE block.

'elasticapm.contrib.django.middleware.TracingMiddleware'

Add the following source code to integrate a Django application with SnappyFlow.

    try: 
       sf = Snappyflow()  
       # Add below part to manually configure the initialization 
       SF_PROJECT_NAME = os.getenv('SF_PROJECT_NAME') 
       SF_APP_NAME = os.getenv('SF_APP_NAME') 
       SF_PROFILE_KEY = os.getenv('SF_PROFILE_KEY') 
       sf.init(SF_PROFILE_KEY, SF_PROJECT_NAME, SF_APP_NAME) 
       # End of manual configuration   
       SFTRACE_CONFIG = sf.get_trace_config()
       
       ELASTIC_APM={ 
          # Specify your service name for tracing
          'SERVICE_NAME': "custom-service" , 
          'SERVER_URL': SFTRACE_CONFIG.get('SFTRACE_SERVER_URL'), 
          'GLOBAL_LABELS': SFTRACE_CONFIG.get('SFTRACE_GLOBAL_LABELS'), 
          'VERIFY_SERVER_CERT': SFTRACE_CONFIG.get('SFTRACE_VERIFY_SERVER_CERT'), 
          'SPAN_FRAMES_MIN_DURATION': SFTRACE_CONFIG.get('SFTRACE_SPAN_FRAMES_MIN_DURATION'), 
          'STACK_TRACE_LIMIT': SFTRACE_CONFIG.get('SFTRACE_STACK_TRACE_LIMIT'), 
          'CAPTURE_SPAN_STACK_TRACES': SFTRACE_CONFIG.get('SFTRACE_CAPTURE_SPAN_STACK_TRACES'), 
          'DJANGO_TRANSACTION_NAME_FROM_ROUTE': True, 
          'CENTRAL_CONFIG': False, 
          'METRICS_INTERVAL': '0s'
       } 
    except Exception as error: 
       print("Error while fetching snappyflow tracing configurations", error) 

note

Verification

Follow the below steps to verify whether SnappyFlow has started to collect the trace data.

Go to the Application tab in SnappyFlow and navigate to your Project > Application > Dashboard.
Navigate to the Tracing section and click the View Transactions button.
You can view the traces in the Aggregate and the Real Time tabs.

Troubleshoot

If the trace data is unavailable in the SnappyFlow server, check the trace configuration in the settings.py.
Add the key-value pair in the ELASTIC_APM block of the settings.py file to enable the debug logs.

   'DEBUG':'true'

Complete Instrumentation

Click here to view the complete instrumentation.

Flask

Prerequisite

To enable tracing for the application that is developed by the Flask framework, sf-elastic-apm and sf-apm-lib must be available in your environment. These libraries can be installed by the following methods:

Add the below-mentioned entries in the requirements.txt file.

sf-elastic-apm[flask]==6.7.2
sf-apm-lib==0.1.1

Install the libraries using CLI.

pip install sf-elastic-apm[flask]==6.7.2 
pip install sf-apm-lib==0.1.1

Configuration

Case 1: sfAgent installed in your instance

In this case, the trace agent picks up the profileKey, projectName, and appName from the config.yaml file.

Add the below entries in the app.py file.

Add the following import statements.

from elasticapm.contrib.flask import ElasticAPM
from sf_apm_lib.snappyflow import Snappyflow

Add the following source code to integrate a Flask application with SnappyFlow.

   # Initialize Snappyflow. By default intialization will take profileKey, projectName and appName from sfagent config.yaml
   sf = Snappyflow() 
   SFTRACE_CONFIG = sf.get_trace_config()
   app.config['ELASTIC_APM'] = { 
      # Specify your service name for tracing 
      'SERVICE_NAME': 'flask-service', 
      'SERVER_URL': SFTRACE_CONFIG.get('SFTRACE_SERVER_URL'), 
      'GLOBAL_LABELS': SFTRACE_CONFIG.get('SFTRACE_GLOBAL_LABELS'), 
      'VERIFY_SERVER_CERT': SFTRACE_CONFIG.get('SFTRACE_VERIFY_SERVER_CERT'), 
      'SPAN_FRAMES_MIN_DURATION': SFTRACE_CONFIG.get('SFTRACE_SPAN_FRAMES_MIN_DURATION'), 
      'STACK_TRACE_LIMIT': SFTRACE_CONFIG.get('SFTRACE_STACK_TRACE_LIMIT'), 
      'CAPTURE_SPAN_STACK_TRACES': SFTRACE_CONFIG.get('SFTRACE_CAPTURE_SPAN_STACK_TRACES'), 
      'METRICS_INTERVAL': '0s'
   } 
   apm = ElasticAPM(app)

note

If your app is in debug mode (eg: app.Debug = true), then the agent won’t send any tracing data to the SnappyFlow server. You can override it by adding 'Debug':True configuration in the ELASTIC_APM block.

Case 2: sfAgent not installed in your instance

In this case, follow the below steps to enable tracing.

Make sure that the project and the application are created in the SnappyFlow Server. Click here to know how to create a project and an application in SnappyFlow.

Export SF_PROJECT_NAME, SF_APP_NAME, and SF_PROFILE_KEY as the environment variables.

#Update the below default values with proper values
SF_PROJECT_NAME=<project name>
SF_APP_NAME=<app-name>
SF_PROFILE_KEY=<profile-key>

Add the following entries in the app.py file.

Add the following import statements.

from elasticapm.contrib.flask import ElasticAPM 
from sf_apm_lib.snappyflow import Snappyflow 
import os

Add the following source code to integrate a Flask application to the SnappyFlow.

sf = Snappyflow() 
# Add below part to manually configure the initialization 
SF_PROJECT_NAME = os.getenv('SF_PROJECT_NAME') 
SF_APP_NAME = os.getenv('SF_APP_NAME') 
SF_PROFILE_KEY = os.getenv('SF_PROFILE_KEY') 
sf.init(SF_PROFILE_KEY, SF_PROJECT_NAME, SF_APP_NAME) 
# End of manual configuration   
SFTRACE_CONFIG = sf.get_trace_config()
app.config['ELASTIC_APM'] = { 
   # Specify your service name for tracing 
   'SERVICE_NAME': 'flask-service', 
   'SERVER_URL': SFTRACE_CONFIG.get('SFTRACE_SERVER_URL'), 
   'GLOBAL_LABELS': SFTRACE_CONFIG.get('SFTRACE_GLOBAL_LABELS'), 
   'VERIFY_SERVER_CERT':   SFTRACE_CONFIG.get('SFTRACE_VERIFY_SERVER_CERT'), 
 'SPAN_FRAMES_MIN_DURATION': SFTRACE_CONFIG.get('SFTRACE_SPAN_FRAMES_MIN_DURATION'), 
 'STACK_TRACE_LIMIT': SFTRACE_CONFIG.get('SFTRACE_STACK_TRACE_LIMIT'), 
 'CAPTURE_SPAN_STACK_TRACES': SFTRACE_CONFIG.get('SFTRACE_CAPTURE_SPAN_STACK_TRACES'), 
 'METRICS_INTERVAL': '0s'
  } 
 apm = ElasticAPM(app) 

note

Verification

Follow the below steps to verify whether SnappyFlow has started to collect the trace data.

Go to the Application tab in SnappyFlow and navigate to your Project > Application > Dashboard..
Navigate to the Tracing section and click the View Transactions button.
You can view the traces in the Aggregate and the Real Time tabs.

Troubleshoot

If the trace data is unavailable in SnappyFlow server, check the trace configuration in the app.py file.
Add the key-value pair in the app.config block of the app.py file to enable the debug logs.
```
'DEBUG':'true'
```

Sample Application Code

Click here to view the sample application for which the configuration mentioned in the above sections enables the tracing feature.

Odoo 15

Prerequisite

To enable tracing for an application developed using Odoo version 15, sf-elastic-apm and sf-apm-lib must be available in your environment.

Install the libraries using CLI.

pip install sf-elastic-apm==6.7.2 
pip install sf-apm-lib==0.1.4

Configuration

To setup the elastic apm client, add the following code in the http.py file of Odoo application.

import elasticapm 
from sf_apm_lib.snappyflow import Snappyflow, begin_transaction, end_transaction

Add the below code in the http.py file to manually configure the initialization. By default, initialization will pick profileKey, projectName and appName from sfagent config.yaml file.

Class: Root and Method: init

sf = Snappyflow()
SF_PROJECT_NAME = '<Snappyflow Project Name>' 
SF_APP_NAME = '<Snappyflow App Name>' 
SF_PROFILE_KEY = '<Snappyflow Profile Key>' 
sf.init(SF_PROFILE_KEY, SF_PROJECT_NAME, SF_APP_NAME) 
# End of manual configuration

trace_config = sf.get_trace_config() # Returns trace config 
self.client = elasticapm.Client(
   service_name="<Service name> ",# Specify service name for tracing 
   server_url=trace_config['SFTRACE_SERVER_URL'], 
   verify_cert=trace_config['SFTRACE_VERIFY_SERVER_CERT'], 
   global_labels=trace_config['SFTRACE_GLOBAL_LABELS'] 
) 
elasticapm.instrument()

Once the request is declared, add the below codes in the http.py file to capture the transaction.

Class: Root and Method: dispatch

begin_transaction(elasticapm, self.client, request) #add after self.get request

end_transaction(elasticapm, self.client, request, response) #add before return response

Click here complete configuration.

Verification

Go to the Application tab in SnappyFlow and navigate to your Project > Application > Dashboard.
Navigate to the Tracing section and click the View Transactions button.
You can view the traces in the Aggregate and the Real Time tabs.

Odoo 16

Prerequisite

To enable tracing for an application developed using Odoo version 16, sf-elastic-apm and sf-apm-lib must be available in your environment.

Install the libraries using CLI.

pip install sf-elastic-apm==6.7.2 
pip install sf-apm-lib==0.1.4

Configuration

To setup the elastic apm client, add the following code at the Root class of http.py file in Odoo application.
```
import elasticapm 
from sf_apm_lib.snappyflow import Snappyflow, begin_transaction, end_transaction
```

Add the below code in the http.py file to manually configure the initialization. By default, initialization will pick profileKey, projectName and appName from sfagent config.yaml file.

Class: Application and Method: call

sf = Snappyflow()
SF_PROJECT_NAME = '<Snappyflow Project Name>' 
SF_APP_NAME = '<Snappyflow App Name>' 
SF_PROFILE_KEY = '<Snappyflow Profile Key>' 
sf.init(SF_PROFILE_KEY, SF_PROJECT_NAME, SF_APP_NAME) 
# End of manual configuration

trace_config = sf.get_trace_config() # Returns trace config 
client = elasticapm.Client(
   service_name="<Service name> ",# Specify service name for tracing 
   server_url=trace_config['SFTRACE_SERVER_URL'], 
   verify_cert=trace_config['SFTRACE_VERIFY_SERVER_CERT'], 
   global_labels=trace_config['SFTRACE_GLOBAL_LABELS'] 
) 
elasticapm.instrument()

Once the request is declared, add the below codes in the http.py file to capture the transaction.

Class: Application and Method: call

begin_transaction(elasticapm, client, request) #add after request

end_transaction(elasticapm, client, request, response) #add before return response

Click here for complete configuration.

Verification

Go to the Application tab in SnappyFlow and navigate to your Project > Application > Dashboard.
Navigate to the Tracing section and click the View Transactions button.
You can view the traces in the Aggregate and the Real Time tabs.

Script

Prerequisite

To enable tracing for an application developed by Script, sf-elastic-apm and sf-apm-lib must be available in your environment. These libraries can be installed by the following method:

Install the libraries using CLI.

 pip install sf-elastic-apm==6.7.2 
 pip install sf-apm-lib==0.1.1

Configuration

To setup the elastic apm client, add the following code at the start of the Script file.

import elasticapm 
from sf_apm_lib.snappyflow import Snappyflow 

sf = Snappyflow() # Initialize Snappyflow. By default intialization will pick profileKey, projectName and appName from sfagent config.yaml.

# Add below part to manually configure the initialization 
SF_PROJECT_NAME = '<Snappyflow Project Name>' 
SF_APP_NAME = '<Snappyflow App Name>' 
SF_PROFILE_KEY = '<Snappyflow Profile Key>' 
sf.init(SF_PROFILE_KEY, SF_PROJECT_NAME, SF_APP_NAME) 
# End of manual configuration

trace_config = sf.get_trace_config() # Returns trace config 
client = elasticapm.Client(
   service_name="<Service name> ",# Specify service name for tracing 
   server_url=trace_config['SFTRACE_SERVER_URL'], 
   verify_cert=trace_config['SFTRACE_VERIFY_SERVER_CERT'], 
   global_labels=trace_config['SFTRACE_GLOBAL_LABELS'] 
) 
elasticapm.instrument()  # Only call this once, as early as possible. 

Once instrumentation is complete you can create custom transactions and spans.

Example: This example shows how to custom transactions and spans.

def main(): 
    sess = requests.Session() 
    for url in [ 'https://www.elastic.co', 'https://benchmarks.elastic.co' ]: 
        resp = sess.get(url) 
        time.sleep(1) 
client.begin_transaction(transaction_type="script") 
main() 
# Record an exception 
try: 
    1/0 
except ZeroDivisionError: 
    ident = client.capture_exception() 
    print ("Exception caught; reference is %s" % ident) 
client.end_transaction(name=__name__, result="success") 

Refer to the link to know more about instrumenting the tracing feature for an application developed by script: https://www.elastic.co/guide/en/apm/agent/python/master/instrumenting-custom-code.html

Verification

Follow the below steps to verify and view the trace data.

Go to the Application tab in SnappyFlow and navigate to your Project > Application > Dashboard.
Navigate to the Tracing section and click the View Transactions button.
You can view the traces in the Aggregate and the Real Time tabs.

Reference Code

Refer to the link to get the complete configuration code: https://github.com/snappyflow/tracing-reference-apps/blob/master/refapp-django/python_script_trace.py

Celery

note

The Celery configuration explained below is based on the redis broker.

Prerequisite

To enable tracing for an application that is developed by Celery, sf-elastic-apm, redis and sf-apm-lib must be available in your environment.

Install the following requirements.

pip install sf-elastic-apm==6.7.2 
pip install redis 
pip install sf-apm-lib==0.1.1 

Configuration

Add following code at start of the file where celery app is initialized to setup elastic apm client.

from sf_apm_lib.snappyflow import Snappyflow 
from elasticapm import Client, instrument 
from elasticapm.contrib.celery import register_exception_tracking, register_instrumentation 

instrument() 
try: 
 sf = Snappyflow() # Initialize Snappyflow. By default intialization will take profileKey, projectName and appName from sfagent config.yaml

 # Add below part to manually configure the initialization 
 SF_PROJECT_NAME = '<SF_PROJECT_NAME>' # Replace with appropriate Snappyflow project name 
 SF_APP_NAME = '<SF_APP_NAME>' # Replace with appropriate Snappyflow app name 
 SF_PROFILE_KEY = '<SF_PROFILE_KEY>' # Replace Snappyflow Profile key
 sf.init(SF_PROFILE_KEY, SF_PROJECT_NAME, SF_APP_NAME) 
 # End of manual configuration 
 
 SFTRACE_CONFIG = sf.get_trace_config() 
 apm_client = Client(
     service_name= '<Service_Name>', # Specify service name for tracing
     server_url= SFTRACE_CONFIG.get('SFTRACE_SERVER_URL'), 
     global_labels= SFTRACE_CONFIG.get('SFTRACE_GLOBAL_LABELS'), 
     verify_server_cert= SFTRACE_CONFIG.get('SFTRACE_VERIFY_SERVER_CERT')
 )
 
 register_exception_tracking(apm_client) 
 register_instrumentation(apm_client) 
 except Exception as error: 
 print("Error while fetching snappyflow tracing configurations", error)

Verification

Once the instrumentation is done and the celery worker is running, you can see a trace for each celery task in the Snappyflow server. Follow the below steps to verify and view the trace data.

Go to the Application tab in SnappyFlow and navigate to your Project > Application > Dashboard.
Navigate to the Tracing section and click the View Transactions button.
You can view the traces in the Aggregate and the Real Time tabs.

Reference Code

For the complete script refer to: https://github.com/snappyflow/tracing-reference-apps/blob/master/ref-celery/tasks.py

Python on Instance

Django​

Prerequisite​

Configuration​

Case 1: sfAgent installed in your instance​

Case 2: sfAgent not installed in your instance​

Verification​

Troubleshoot​

Complete Instrumentation​

Flask​

Prerequisite​

Configuration​

Case 1: sfAgent installed in your instance​

Case 2: sfAgent not installed in your instance​

Verification​

Troubleshoot​

Sample Application Code​

Odoo 15​

Prerequisite​

Configuration​

Verification​

Odoo 16​

Prerequisite​

Configuration​

Verification​

Script​

Prerequisite​

Configuration​

Verification​

Celery​

Prerequisite​

Configuration​

Verification​

Django

Prerequisite

Configuration

Case 1: sfAgent installed in your instance

Case 2: sfAgent not installed in your instance

Verification

Troubleshoot

Complete Instrumentation

Flask

Prerequisite

Configuration

Case 1: sfAgent installed in your instance

Case 2: sfAgent not installed in your instance

Verification

Troubleshoot

Sample Application Code

Odoo 15

Prerequisite

Configuration

Verification

Odoo 16

Prerequisite

Configuration

Verification

Script

Prerequisite

Configuration

Verification

Celery

Prerequisite

Configuration

Verification