This release of the Python agent includes a major update to how we capture and represent metrics for both SQL databases and NoSQL datastores. Metrics for both types of products will now be displayed in a unified "Databases" tab in the APM UI, and these metrics will also be associated with the specific product being used. In addition, we have enabled support for having key transactions on other transactions, such as background tasks.
The agent can be installed using easy_install/pip/distribute via the Python Package Index or can be downloaded directly from our download site.
For a list of known issues with the Python agent, see Status of the Python agent.
Unified view for SQL database and NoSQL datastore products.
The response time charts in the application overview page will now include NoSQL datastores such as Memcached, Redis and MongoDB and also the product name of existing SQL databases such as MySQL, Postgres, Oracle etc.
We also introduced a new unified view within the APM UI for visualizing time spent in queries made against SQL databases and NoSQL datastore products.
For existing SQL databases, in addition to the existing breakdown of SQL statements and operations, the queries are now also associated with the database product being used.
For NoSQL datastores such as Memcached, Redis and MongoDB, we have now added information about operations performed against those products, similar to what is being done for SQL databases.
Because this introduces a notable change to how SQL database metrics are collected, it is important that you upgrade the Python agent version on all hosts. If you are unable to transition to the latest agent version on all hosts at the same time, you can still access old and new metric data for SQL databases, but the information will be split across two separate views.
Key transactions for other transactions.
In addition to being able to create key transactions for web transactions, it is now possible to create key transactions for other transactions, such as background tasks executed by Celery.
Key transactions enable the setting of a per transaction Apdex and alerts, as well as the ability to run X-Ray sessions, including transaction specific thread profiling.
No SQL datastore instrumentation.
To complement our new unified view for SQL database and NoSQL datastore products in the APM UI, we have upgraded our existing instrumentation for Redis and MongoDB. Previously, these only provided a function breakdown in transaction summaries and sample transaction traces, but now they will report into the unified view for database and datastore products under their respective product categories.
Existing instrumentation for Memcached clients have similarly been updated, as well as new support for the
pymemcachemodule being added.