Skip to main content

StackImpact Python Agent

Project description

Overview

StackImpact is a performance profiler for production applications. It gives developers continuous and historical view of application performance with line-of-code precision, which includes CPU, memory allocation and blocking call hot spots as well as execution bottlenecks, errors and runtime metrics. Learn more at stackimpact.com.

dashboard

dashboard

Features

  • Automatic hot spot profiling for CPU, memory allocations, blocking calls

  • Automatic bottleneck tracing for HTTP handlers and other libraries

  • Exception monitoring

  • Health monitoring including CPU, memory, garbage collection and other runtime metrics

  • Anomaly alerts on most important metrics

  • Multiple account users for team collaboration

Learn more on the features page (with screenshots).

Documentation

See full documentation for reference.

Requirements

  • Linux, OS X or Windows. Python version 2.7, 3.4 or higher.

  • Memorly allocation profiler and some GC metrics are only available for Python 3.

  • CPU and Time profilers only supports Linux and OS X.

  • Time (blocking call) profiler supports threads and gevent.

Getting started

Create StackImpact account

Sign up for a free account at stackimpact.com.

Installing the agent

Install the Go agent by running

pip install stackimpact

And import the package in your application

import stackimpact

Configuring the agent

Start the agent in the main thread by specifying the agent key and application name. The agent key can be found in your account’s Configuration section.

agent = stackimpact.start(
    agent_key = 'agent key here',
    app_name = 'MyPythonApp',

Other initialization options:

  • app_version (Optional) Sets application version, which can be used to associate profiling information with the source code release.

  • app_environment (Optional) Used to differentiate applications in different environments.

  • host_name (Optional) By default, host name will be the OS hostname.

  • debug (Optional) Enables debug logging.

Analyzing performance data in the Dashboard

Once your application is restarted, you can start observing regular and anomaly-triggered CPU, memory, I/O, and other hot spot profiles, execution bottlenecks as well as process metrics in the Dashboard.

Troubleshooting

To enable debug logging, add debug = True to startup options. If the debug log doesn’t give you any hints on how to fix a problem, please report it to our support team in your account’s Support section.

Overhead

The agent overhead is measured to be less than 1% for applications under high load.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

stackimpact-1.0.0.tar.gz (14.0 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page