Python agent release notesRSS

Notes

This release of the Python agent adds support for Cross Application Tracing.

The agent can be installed using easy_install/pip/distribute via the Python Package Index or can be downloaded directory from our download site.

For a list of known issues with the Python agent see our online help article on the status of the Python agent.

New features:

• Support for New Relic's Cross Application Tracing feature is now available for the Python agent. This feature enables correlation of transaction traces between different services in your stack. It works on external calls made between applications monitored by any New Relic agents (Java, .NET, Ruby and Python), which support this feature. At this time the Python agent supports this feature on outgoing calls when using the 'httplib' module or any other module which uses 'httplib', such as the 'urllib', 'urllib2', 'urllib3' and 'requests' modules. Any inbound calls from other agents which support the feature will also be handled.
• Added instrumentation for the weberror package. This provides visibility into potentially blocking operations such as sending of email for exceptions which are being reported.
• Added instrumentation for the umemcache package.
• Added instrumentation for the DBAPI2 compliant interface for the IBM DB2 ibm_db_dbi database client package.

Bug fixes/Improvements:

• When running a WSGI application under the Tornado WSGI container, data reporting would stop if an unhandled exception managed to propagate back up to the Tornado WSGI container. This was due to a bug in Tornado in respect of its compliance with the WSGI specification. A workaround is provided to avoid the problems this caused to the Python agent. Tornado versions prior to 3.2 will still carry that bug however and we make no attempt to address the bug in Tornado.
• The Tornado instrumentation was causing template rendering to fail where a relative path was used to refer to the template and no template path had been specified for the RequestHandler instance or globally.
• The Tornado instrumentation was causing exceptions when using the @tornado.gen decorators under Tornado 2.X.
• When using Django, web transactions will now be named after individual view handlers when using class based views, rather than being named after the class itself.
• When using Pyramid, web transactions will now be named after individual view handlers when using view classes, rather than being named after the class itself.
• Celery instrumentation had stopped working correctly for Celery versions 2.5.3 through 2.5.5.
• No data was being reported where a monitored process was being shutdown within a couple of seconds of being started even if the agent was able to register. This could result in custom metrics in particular not being reported.
• SSL certificate validation was failing on older Debian systems due to the OpenSSL libraries not being able to process a couple of the certificates bundled with the Python agent. Those certificates were not required and have been removed.
• Calculation of a time string was failing on Windows due to using a strftime() formatter which only existed on UNIX systems.

Notes

This release of the Python agent removes the experimental label from our Tornado Web and Pyramid support, with support now being enabled by default.

The agent can be installed using easy_install/pip/distribute via the Python Package Index or can be downloaded directory from our download site.

For a list of known issues with the Python agent, see Status of the Python agent.

New features:

• The previously experimental support for the native Tornado Web API has been greatly expanded and is now enabled by default. This is in addition to the tornado.wsgi.WSGIContainer support we previously provided and includes the native Tornado Web API for constructing async applications. Running a limited subset of the native Tornado Web API within a separate WSGI server using the tornado.wsgi.WSGIApplication adapter is also now supported.
• The previously experimental support for the Pyramid web framework has been improved and is now enabled by default.
• When using a DBAPI2 compliant database client, calls to stored procedures via the callproc() method of the database cursor are now tracked. Previously, only calls made to stored procedures by explicitly using a CALL SQL statement were being tracked. All calls to stored procedures currently appear under the category of 'SQL - Other'. A future agent update is planned which will split out calls to stored procedures separately and report them on the databases tab.
• Added instrumentation for automatically wrapping the WSGI application when using the CherryPy WSGI server bundled with the CherryPy framework.
• Added instrumentation for automatically wrapping the WSGI application when using the WSGI server from the Python standard library wsgiref module. Be aware that due to non conformance with the WSGI specification, it is not recommended that the WSGI server from the wsgiref module be used unless using Python 2.7.4 or higher. Issues with older versions of the WSGI server in the wsgiref module will cause incorrect reporting of data. More details are provided in our status of the Python agent.

Bug fixes/Improvements:

• External web calls made using the 'requests' module from a session were not being correctly monitored, resulting in such requests being picked up as being performed by the lower level 'httplib' module and the time taken not being inclusive of the whole request.
• The collection of explain plans by the agent in a background thread when performing a data harvest, was not explicitly performing a rollback. This could result in database proxies such as pgbouncer believing the database connection was now dirty and force closing the connection and ejecting it from the current database connection pool.
• The wrapper used by the agent around wsgi.input passed in the WSGI request environment was preventing non standard WSGI applications directly reaching down to the original socket connection so as to implement extensions such as websockets.
• The object wrapper used in our instrumentation for function traces has been improved so that it will pass type checks performed using builtin Python calls such as isinstance(), isfunction() and isclass(). This addresses issues where the object wrappers could interfere with the correct operation of web frameworks which derived the calling convention to be used when invoking a handler function from the type of the handler. Note that using type() on the wrapper object will still yield its true type, so functions such as isinstance() should always be used where possible.
• The agent could fail on startup when running on a system with a non English locale using a custom date/time format.

Notes

This release of the Python agent introduces a major new feature called X-Ray Sessions. This feature allows you to gain deeper insights into a key transaction's performance by showing transaction traces alongside long-running profiler results.

For a list of known issues with the Python agent see our online help article on the status of the Python agent.

New features:

• X-Ray Sessions provide more targeted transaction trace samples and thread profiling for web transactions. For full details see our X-Ray sessions documentation.
• For new agent installations, the agent will now default to using a SSL connection when connecting to our data collector to report any data. If updating from an older agent version, you will however need to manually update your agent configuration file and change the 'ssl' setting to 'true' to always use SSL connections.
• When connecting direct to our data collector over a SSL connection, SSL certificate validation will now be performed to mitigate the possibility of man in the middle attacks.
• Breakdown metrics for transactions are now recorded as unscoped metrics as well as the existing metrics scoped to a web transaction. As custom dashboards can only chart unscoped metrics, what this means is that it is now possible to create custom dashboards that display data on specific breakdown metrics, such as time spent in traced functions. For example, you may wish to chart time spent in creating database connections, or specific middleware and view handler functions.
• When displaying error details, the full path of the exception is now displayed and not just the class name. This makes it easier to correctly identify the full name, with that name then being able to be directly copied into the 'error_collector.ignore_errors' setting of the agent configuration file if it is desired that that exception be ignored.
• Added the 'newrelic.agent.record_custom_metrics()' function to the public API for the agent to allow the recording of many custom metrics in one function call to the agent.

XXXFeatures Changed:

• We have temporarily disabled the generation of CPU burn information for transaction traces. This was displaying inaccurate values after a UI change, but also had an underlying issue whereby it was reporting CPU burn by the whole process and not just the thread handling the request. We are withdrawing the feature until we can improve the accuracy of the reported value.
• We have disabled the ability to get thread profiling information when a WSGI server makes use of coroutine libraries such as gevent or eventlet. This is because the nature of how coroutines are implemented, means we were are not able to generate accurate usable data.

Bug fixes/Improvements:

• When queueing Celery tasks from a web application, those web transactions were in some cases being wrongly categorised as background tasks. The name of the transaction was also being labelled with a string with the object representation, resulting in metric grouping issues.
• The older version of the 'requests' package we were bundling and were using for any HTTP calls was not closing socket descriptors immediately when a requests session object was disposed of. This could result in a small number of open socket descriptors being held open until the Python garbage collector kicked in and closed them.
• Login credentials supplied as part of a URL, could in some circumstances appear with the URL parameter associated with a web external node in a transaction trace sample.
• Django 1.5 moved which module the 'Http404' exception was declared in. As a result we were no longer correctly ignoring it when catching exceptions to process as errors.
• A check designed to warn against the use of uWSGI versions prior to 1.2.6, which contain a bug which results in the agent recording incorrect response times, was failing on very old uWSGI versions.
• Updated our gevent instrumentation to accommodate a prototype change in gevent 1.0rc1.
• Updated our bottle instrumentation to handle the non numeric version string used in bottle development versions.
• After five minutes of being unable to connect to our data collector to report data, the agent will now internally reset itself, discarding accumulated metric data and require the agent to reregister itself with our core application before collecting data once again. This is to ensure that we do not unnecessarily keep accruing data and causing an increase in memory usage while we cannot contact our data collector.
• Avoid the potential for a web request to deadlock in a situation where a web framework transaction management system made a copy of the object we use to record details about web transactions or background tasks.

Notes

This release of the Python agent fixes an issue when floating point values were used in headers used to calculate queueing time.

For a list of known issues with the Python agent see our online help article on the status of the Python agent.

Bug fixes/Improvements:

• When a float value was provided in the X-Request-Start or X-Queue-Start headers as the time stamp, it was not being parsed correctly and the fractional part was being discarded. This was resulting in loss off accuracy.

Notes

This release of the Python agent contains improvements in the way that queueing time is calculated.

For a list of known issues with the Python agent see our online help article on the status of the Python agent.

Bug fixes/Improvements:

• Resolved some issues with tracking of front-end queue time, particularly when the agent is running on an app hosted on Heroku. The agent will now more reliably parse the headers described in https://newrelic.com/docs/features/tracking-front-end-time and will automatically detect whether the times provided are in seconds, milliseconds or microseconds.

Notes

This release of the Python agent contains a fix for when reporting to multiple applications, as well as other minor bug fixes and enhancements.

For a list of known issues with the Python agent see our online help article on the status of the Python agent.

New features:

• On the Linux platform, the agent environment now reports the total amount of system memory available.
• Added support for psycopg2cffi database module.
• Custom parameters can be associated with function trace nodes for display against transaction traces in the UI.
• The URL associated with a call to an external service will now be shown in the custom parameters section for the node in a transaction trace. Previously would have been shown as a label when hovering other the node.

Bug fixes/Improvements:

• The agent was not reporting any data where multiple applications were being listed in in the app_name configuration setting.
• Calling register_application() in the context of a module import could cause a temporary deadlock when a timeout period was specified. The potential for deadlock will now be detected and the function will return without waiting.
• When the agent was configured to capture query string parameters, a key with an empty value was being discarded and not reported.
• When using gevent mode of gunicorn, the SystemExit exception was being logged on process shutdown due to gevent sending the SystemExit exception to all greenlets and not just the main thread when sys.exit() was called.
• Instrumentation wrapping the Django reverse() function was not accepting named parameters.
• If custom parameters were used with a transaction, the HTTP response STATUS was duplicated in details related to an error raised from that transaction.
• Changes to Django instrumentation to avoid metric grouping issues resulting from raw URLs leaking through as transaction name.

Notes:

This release of the Python agent addresses an issue with under reporting of memory use on Linux, as well as other minor bug fixes and enhancements.

For a list of known issues with the Python agent see our online help article on the status of the Python agent.

New features:

• Added support for automatically wrapping the WSGI application entry point when using the Paste HTTP server.
• Custom metrics can now be reported via the public agent API by supplying an appropriate application object as an additional argument to 'newrelic.agent.record_custom_metric()'.
• Added support for the 'psycopg2ct' database client module for PostgreSQL.
• When needing to communicate via a firewall, the proxy settings can now be set via environment variables in addition to being able to be set in the agent configuration file.
• The number of CPU cores is now being reported in the agent environment and displayed in the UI.
• A warning will now be logged in the agent log file if an older version of uWSGI is being used which has bugs with its conformance to the WSGI specification. Such older uWSGI versions would see incorrect data being reported due to the bug in uWSGI.
• A warning will now be logged in the agent log file if uWSGI is being used and the 'enable-threads' option is not being supplied to uWSGI to enable threading within the Python interpreter, a feature which is a mandatory requirement for the Python agent to be able to work.
• A range of additional logging and debugging options have been added to allow our support team to better help you when you are having issues with setting up the agent.

Bug fixes/Improvements:

• Addressed problem where memory usage was being under reported on Linux systems. The degree to which memory usage was under reported was dependent on the memory page size the system was using. If affected you can expect to see memory usage being reported jump up as it reports the correct value.
• If the local Python installation is already using a 'sitecustomize.py' file, the agent's own 'sitecustomize.py' file will ensure that the existing copy is imported and code in it executed so that existing definitions are still applied.
• Installation of the agent could fail under buildout due to a missing Python future import for the Python with statement under Python 2.5.
• Made parsing of URLs more tolerant to malformed URLs in web external calls. The agent was encountering an error when the port number of a URL was not an integer, resulting in the data for that transaction being discarded.
• Use of raw greenlets from within a transaction was failing causing an exception and the users web request to typically fail with a HTTP 500 error response.
• Configuration of the agent will no longer fail on startup if there is no 'newrelic' section in the configuration file.

Notes:

This release of the Python agent enables the ability to set apdex values and alerts for key transactions (discussed here)

For a list of known issues with the Python agent see our online help article on the status of the Python agent.

New features:

• Added support in the agent required to enable apdex values to be specified for key transactions.
• Added support for tracking SQL database queries when using the 'oursql' database client module for MySQL.

Bug fixes/Improvements:

• The sqlite3 instrumentation was preventing the use of a sqlite3 database connection object as a context manager together with the 'with' statement.
• Suppressed the logging produced by the urllib3 module included within the bundled requests module, when making socket connections.

Notes:

This release of the Python agent focuses on providing a low-overhead thread profiler which can monitor and record executing threads for a specified time, without affecting the customer experience.

For a list of known issues with the Python agent see our online help article on the status of the Python agent.

New features:

• Low-overhead thread profiler. A profiling session can be initiated for a period from 2 to 10 minutes. The profiler will periodically sample what all the executing threads are doing, aggregating the results together to get a statistical snapshot of where in your application most time is being spent.

Bug fixes/Improvements:

• Importing of the greenlet module was resulting in the capacity analysis report metrics being disabled, even though it was meant to only be disabled when specifically using a coroutine based WSGI server such as gevent and eventlet mode of gunicorn.
• Improvements to the instrumentation wrapper applied to the Django view handler function so that code which tries to compare the view handler to an expected value should work. Note that this is dependent upon using an equality test rather than an identity test.
• Reverted prior change which stripped the instrumentation wrapper from the Django view handler when it was passed to any Django view middleware. Improvements to the instrumentation wrapper should remove the need to do this. Having the view handler passed in with the wrapper applied is required to ensure that calls to the view handler are tracked properly where the view handler is called from within the view middleware.
• Although not strictly required due to improvements to the instrumentation wrapper applied to a Django view handler, strip the wrapper when a view handler is passed into django.core.urlresolvers.reverse() function to ensure it can correctly determine the URL mapping to the view handler.
• Disable automatic RUM header/footer insertion when using Django 1.5 and the new streaming HTTP response object is returned. This is being disabled so that the response is not buffered, thereby interfering with the streaming process. If streaming a HTML response and RUM reporting is still required, the RUM header and footer will need to be added manually.
• Instrumentation of the feedparser module was causing an exception when a file like object rather than a string was passed to the feedparser.parse() function.
• Tastypie instrumentation was failing to be applied if using Python 2.5.