중요
The end-of-life date for this agent version is July 29, 2019. To update to the latest agent version, see Update the agent. For more information, see End-of-life policy.
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.
중요
The end-of-life date for this agent version is July 29, 2019. To update to the latest agent version, see Update the agent. For more information, see End-of-life policy.
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.
중요
The end-of-life date for this agent version is July 29, 2019. To update to the latest agent version, see Update the agent. For more information, see End-of-life policy.
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.
중요
The end-of-life date for this agent version is July 29, 2019. To update to the latest agent version, see Update the agent. For more information, see End-of-life policy.
Notes:
This release of the Python agent is a minor feature and bug fix release.
For a list of known issues with the Python agent see our online help article on the status of the Python agent.
New features:
- When reporting web application performance data against multiple applications in the New Relic UI at the same time, any end user metric data will now also be reported against all applications. Previously end user metric data would only be reported against the first application.
- The environment variable 'NEW_RELIC_SSL' can now be set to enable use of a SSL connection when reporting data to our data collector. Enabling values are 'true', 'on' or '1'. This can be used on platforms such as Heroku where configuration is performed using environment variables instead of an agent configuration file.
- Added instrumentation for tracking database queries when using the 'pymysql' module for the MySQL database.
Bug fixes/Improvements:
- Fix to algorithm calculating name of function for case where function was wrapped with a decorator implemented using a class. Previously was using the name of the decorator class rather than the name of the wrapped function.
- Fix for ZeroDivision error when calculating per request CPU burn, where due to clock granularity for system the request was quick enough to effectively have zero duration.
- Fix for AttributeError when trying to process None as a slow transaction trace when in a harvest period there were browser traces but no application server traces.
중요
The end-of-life date for this agent version is July 29, 2019. To update to the latest agent version, see Update the agent. For more information, see End-of-life policy.
Notes:
This release of the Python agent contains capacity analysis reporting, an improved sampling algorithm to ensure a wider sampling of slow transactions and added support for TastyPie, dropbox and facepy modules.
For a list of known issues with the Python agent see our online help article on the status of the Python agent.
New features:
- Enable capacity analysis reporting where web application is single threaded or multithreaded (but not coroutine based system such as gevent and eventlet). This report helps you determine if you have enough instances deployed to keep up with request load and so tune your configuration for optimal performance.
- Criteria by which slow transaction samples are captured has been changed so as to include slow transactions for a broader range of transactions. Previously the transaction with the slowest overall response time would always be captured and reported. Whether a specific transaction will be preserved as a sample of a slow transaction will now also depend on whether a recent slow transaction had already been captured for it and give preference to recording slow transactions for a different transaction, rather than the same transaction all the time, if it is always the slowest.
- Where TastyPie is being used with Django, instead of all web transactions being handled by TastyPie being labeled against the TastyPie wrapper, the web transactions will now be aggregated against the specific methods of the resource or API object handling the request.
- Added instrumentation for the 'dropbox' Python module to track time spent calling out to the DropBox web service. A call to this web service would have been tracked previously by virtue of the 'dropbox' module internally using the 'httplib' module. This added instrumentation however makes the data collected more accurate as will properly track time spent sending the request and receiving the response. It will also attribute the call to the 'dropbox' module in transaction traces and performance breakdown data.
- Added instrumentation for the 'facepy' Python module to track time spent calling out to the Facebook web service. A call to this web service would have been tracked previously by virtue of the 'facepy' module internally using the 'requests' module. This added instrumentation however allows the call to be attributed to the 'facepy' module in transaction traces and performance breakdown data.
- Added support for gevent < 0.13.7 by way of patching an existing bug in gevent. The specific problem in gevent was patched in version 0.13.7 of that package. This change will allow older versions of gevent to also be used if there is a requirement.
Bug fixes/Improvements:
- Instrumentation for Genshi templates was failing when the OR operator was used inside of a template.
- If an exception occurred in the first call to read data from wsgi.input to get the request content, it would cause a subsequent exception when recording of response time was being finalised. This wasn't causing any impact on user requests, but would result in any metrics for that request being discarded and an error being logged in the agent log.
중요
The end-of-life date for this agent version is July 29, 2019. To update to the latest agent version, see Update the agent. For more information, see End-of-life policy.
Notes:
This release of the Python agent introduces a number of new features including improvements to RUM browser traces. Performance of the agent has also been improved though reducing some of the overheads when dealing with tracking SQL database queries.
For a list of known issues with the Python agent see our online help article on the status of the Python agent.
New features:
- The agent now collects additional application tier transaction trace samples for slow transactions and will correlate them with any corresponding RUM browser trace.
- Slow transaction traces will now show a figure corresponding to the amount of CPU burn that occurred during the period the transaction was running. This can be used to get an indication of whether code being executed was CPU intensive or principally waiting on I/O.
- Slow transaction traces for web requests will now provide an indication of how many concurrent requests were executing at the same time in the process the request was being handled. This can be used to determine how busy the process was at that time, but would also be used in conjunction with the recorded CPU burn to determine whether CPU burn was all from the one transaction or could also be due to parallel executing web requests in a multithreaded application. Note that this measure is dependent on an optional C extension component of the agent being able to be installed at the time of installation of the agent.
- Slow transaction traces for web requests will now display information about the amount of request content read and the amount of response content generated. This will include details about what methods of 'wsgi.input' were used to read content and how long it in total took to read the request content. Similar details are also provided about how response content was generated and how long it took from start to finish.
- Slow transaction traces for web requests will now display the value of any frontend queueing time within the server stack which pertained to that specific request. Note that this is dependent on the server stack having being configured to introduce the required header to allow queueing time to be measured. The Python agent recognises the 'X-Queue-Start' header.
- Automatic support is now provided for tracking frontend queueing time within the server stack when an application is deployed to Heroku.
- An API call and means via the WSGI environ dictionary is now provided for indicating that a transaction should not be a candidate for slow transaction traces. This is to allow one to ignore transactions which are known to always be slow. The API call is 'newrelic.agent.suppress_transaction_trace()'.
- Calls to Django APIs for sending emails will now be tracked in the performance breakdown for transactions, as well as being displayed in slow transaction traces.
- Support for Celery 3.0.
Bug fixes/Improvements:
- Overheads within the agent which could affect performance of the application have been reduced. The improvements specifically revolve around the processing of SQL database queries. This is principally to address larger than expected overheads seen by a very small subset of users which had large or more complicated SQL queries. The changes could though still result in a small general reduction in overhead and CPU usage directly attributable to the monitoring down by the agent when SQL database queries are being tracked.
- Where it is possible to build C extension components at the time the agent is installed, optional C speedups for JSON will now be installed. This reduces the overhead of JSON encoding when data is being sent by the agent to the New Relic data collector on each one minute harvest cycle. If the C extension cannot be compiled, the agent will fall back to using pure Python code as it has done in prior versions of the agent.
- Django instrumentation has been improved and issues addressed with the way that instrumentation wrappers were applied to view handlers. For example, when a view handler is passed to a view middleware, any instrumentation wrapper is now removed. This is because the wrapper could cause issues for some code which tried to do a direct comparison between the view handler passed and an expected value. It is believed this change will fix issues when using Mezzanine.
- A sporadic issue with the data collector rejecting uploaded data due to what it believes was malformed JSON should be addressed. This was due to some metric values being aggregated as integers rather than as float values. This resulted in overflow of 64 bit values in the data collector due to Python supporting arbitrary length integers and thus being able to send values larger than 64 bits.
- The agent will now no longer fail on import when -OO option is used with the Python interpreter to enable highest level of optimisation. This was an issue as -OO strips documentation strings from code and the agent was not handling the case that the documentation string would then be a None object.
중요
The end-of-life date for this agent version is July 29, 2019. To update to the latest agent version, see Update the agent. For more information, see End-of-life policy.
Notes:
This release of the Python agent has focused on improving the way the agent communicates with the New Relic core application. This includes improved logging and error handling, but also adds support for SSL and connecting via a proxy when the monitored host is located behind a firewall.
For a list of known issues with the Python agent see our online help article on the status of the Python agent.
Changed features:
- The request method for a call to an external web service, when able to be collected by instrumentation, is now shown against a web external node in a slow transaction trace where as previously it showed the path segment of the URL. The URL, minus embedded user/password and query string is instead now shown as a label when hovering over the web external node in the slow transaction trace details.
- Improved logging and error handling when communicating with the New Relic core application. Many messages previously logged as errors will now be logged as warnings and an error only logged when a recurring problem is detected. This should reduce emails triggered from errors logged via the Python logging module to only those that may actually require action.
- Significant error messages or warnings will be output to standard output when running the agent test via the 'newrelic-admin validate-config' command. This ensures that it will be easier to detect when the test has failed due to network connectivity or license key issues.
New features:
- Connecting to the New Relic core application using a secure SSL connection is now supported. This is enabled by setting the 'ssl' setting in the agent configuration file to 'true'.
- Connecting to the New Relic core application via a proxy is now supported. This is enabled by setting the 'proxy_host' and 'proxy_port' settings in the agent configuration file. If a secure SSL connection is desired, the 'ssl' setting can be set to 'true' at the same time. If the proxy requires a user name and password, the 'proxy_user' and 'proxy_pass' settings can be additionally set.
- When sending collected data to the New Relic core application it will be compressed when over a certain size to cut down on the amount of data being sent.
- The Python agent now includes its own self instrumentation and profiling capabilities to allow New Relic to monitor the performance of the agent itself and help debug any performance issues reported by a user which may occur in rare circumstances with certain web applications.
Bug fixes:
- Where a user name and password were being included as part of a URL for a call to an external web service, eg., 'user:pass@localhost/', that the Python agent was instrumenting, the details were not always being scrubbed properly from details being reported to the New Relic core application.
중요
The end-of-life date for this agent version is July 29, 2019. To update to the latest agent version, see Update the agent. For more information, see End-of-life policy.
Bug fixes:
- Fix assertion violations when greenlets were used explicitly in the context of a normal thread based request handler.
- Installation of package using Python 2.5 was giving warnings when trying to byte code compile installed .py files due to missing import for 'with_statement' from __future__ module in some modules.
- The newrelic-admin script is now installed correctly when installing the package as an egg under buildout.
- The newrelic.agent.stop_recording() function was causing errors when using any WSGI hosting mechanism other than Apache/mod_wsgi and wasn't working as intended even under mod_wsgi.
- Disable CPU sampling when os.times() is not available, such as when using Jython.
- Derivation of name when instrumenting the __init__() method of a class could fail if the class had a __len__() method which accessed methods/attributes which were only setup during the constructor.
- Move importing of multiprocessing module to global scope to avoid logging module bug in Python versions up to 2.6.
중요
The end-of-life date for this agent version is July 29, 2019. To update to the latest agent version, see Update the agent. For more information, see End-of-life policy.
Bug fixes:
- Added full support for being able to use agent package with buildout. Previously the 'newrelic-admin' script was not installed correctly when buildout was being used to manage package installation.
- Added support for versions 2.2 and 2.5 of the distributed task queuing system Celery.
- Added support for older 'redis' client versions which did not separate commands into 'StrictRedis' and 'Redis' client objects.
- The database table name was not always extracted properly from SQL queries where sub selects were being used, especially when additional bracketing was being used for readability. Usually this was occuring where hand crafted SQL was being generated rather than being automatically generated through an ORM or DAL.
- Type handler registration in psycopg2 client module would fail due to agent instrumentation wrapper around connection and cursor objects.
- Javascript header added into response of type 'text/html' when Django being used and end user monitoring enabled, would be placed into wrong location of '' element if 'X-UA-Compatible' meta tag existed. This would cause issues for IE browser clients which meta tag related to.
New features:
- Server side configuation is now available for the Python agent. This will be of most use for Heroku installations where there is by default no agent configuration file for defining local override settings.
- Distiguish time spent invoking the WSGI application for a request and the subsequent processing of any iterable returned by the WSGI application. These will show as nodes 'WSGI/Application' and 'WSGI/Response' in performance breakdowns and slow transaction traces. This mainly helps where iterable is a generator which performs work for each yielded item as provides proper context. Time spent in writing back a large reponse to a slow HTTP client will also be more visible.
- Distinguish separately the time spent in the top level WSGI application callable where the agent WSGI middleware wrapper is being applied. This will be the node which gets listed immediately under 'WSGI/Application' in a slow transaction trace.
- For Django, record separately time spent in processing certain types of form POSTs. This helps to show where being spent processing a large data upload.
- Show content length and content type details for a request in slow transaction and error details.
- Show content length for a response in slow transaction and error details.
Features changed:
- Longer timeout when doing an agent test using the 'validate-config' command of the 'newrelic-admin' script. The short timeout was previously causing some users with slow DNS or networks to see the test as failing.
중요
The end-of-life date for this agent version is July 29, 2019. To update to the latest agent version, see Update the agent. For more information, see End-of-life policy.
Fixes:
- Addressed a performance issue which would cause high CPU load, when parsing SQL queries which had a large number of values for a SQL 'IN' clause.
- Agent version was not reported in form A.B.C.D in all cases. This was causing UI to warn that Python agent was out of date even when running version newer than the minimum recommended version.
- When 'feedparser' module is used, now correctly track external web service requests where URI used 'feed' or feed:http' for scheme.
- Illegal non ASCII characters in a URL could cause the agent to generate Unicode conversion warnings or outright fail a request with an exception where the character sequence could not be decoded to Unicode using the Python system default encoding.
- The table name for a SQL query was not being correctly derived when the SQL contained a select sub query or table name aliases were being used.
- Number of nodes captured for a slow transaction trace was not being capped properly resulted in too much data being sent through to core application. This could result in details of slow transaction being rejected by core application, or result in a timeout in UI when attempting to display the slow transaction trace.
- SQL calls made using 'psycopg2' were failing where optional parameters argument was not supplied to database cursor 'execute()' method and the SQL contained a '%' character such as in a 'LIKE' clause.
- Was not ignoring exception of type 'bottle.HTTPError' raised within application using Bottle. This is not a true exception but is used to programmatically indicate a non 200 HTTP response so shouldn't have been recorded as an error.
- The 'django-piston' instrumentation was failing when an error occurred in users handler and it tried to generate an error response. This was because 'django-piston' was assuming that a handler would always be a normal function. It would therefore fail for a decorator/wrapper implemented using a class object as is used by the agent instrumentation.
New features:
- Added support for capturing explain plans for slow SQL when using MySQL and PostgreSQL.
- Added preliminary public API for manually instrumenting additional functions in user code and interacting with the current transaction to override how and what details about the transaction are recorded.
- Added the 'transaction_tracer.function_trace' setting in the agent configuration file for providing a simplified way of specifying additional Python functions for which time metrics should be collected. Time spent in these functions will then appear in web transaction performance break down and slow transaction traces.
- Added new or improved support for tracking external web service requests made using the 'urllib', 'urllib2', 'urllib3', 'httplib', 'httplib2' and 'requests' modules. Note that only time taken for the initial connect for the HTTP connection may be recorded. Uninstrumented time which appears immediately after an external web service request in a slow transaction trace made using one of these modules, will therefore possibly be the time then taken to send request data, wait for a response and consume that response data.
- Added support for tracking external requests to a Solr service using the 'pysolr' and 'solrpy' modules. Time spent making the request will show on the overview charts as Solr time. Metrics for individual types of requests will also be listed in web transaction performance breakdown and slow transaction traces.
- Added Django application called 'newrelic.extras.framework_django' which explicitly adds in 'newrelic_tags' tag library containing template tags for manually adding in RUM header and footer. Reliance on the old method whereby template tag library was added automatically is now deprecated and will be removed in a future version.
- Added support for Bottle 0.10.X in Bottle specific instrumentation.
- Added support for Redis using the 'redis' module. Support consists of tracking time spent connecting to and issuing commands against the Redis service.
- Added support for MongoDB using the 'pymongo' module. Support consists of tracking time spent connecting to and issuing commands against the MongoDB service.
Features changed:
- The 'capture_params' setting was defaulting to 'true' rather than 'false' resulting in the request query string parameters being reported against errors and slow transaction traces. If upgrading you will need to change the agent configuration file you are already using to change it to 'false' if capturing parameters is not desired.
- Rollup metrics against web transactions for external web service requests will now only be recorded against the host and will not be broken out based on resource requested on the remote service.