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Supported Technologies

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Supported Technologies

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Python

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The following Python versions are supported:

  • 2.7
  • 3.4
  • 3.5
  • 3.6
  • 3.7

Python 2.7 will reach End of Life on January 1, 2020. The Elastic APM agent will stop supporting Python 2.7 in the first major version after that date.

Django

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We support these Django versions:

  • 1.11
  • 2.0
  • 2.1
  • 2.2

For upcoming Django versions, we generally aim to ensure compatibility starting with the first Release Candidate.

Flask

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We support these Flask versions:

  • 0.10
  • 0.11
  • 0.12
  • 1.0

Automatic Instrumentation

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The Python APM agent comes with automatic instrumentation of various 3rd party modules and standard library modules.

Databases

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Elasticsearch

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Instrumented methods:

  • elasticsearch.connection.http_urllib3.Urllib3HttpConnection.perform_request
  • elasticsearch.connection.http_requests.RequestsHttpConnection.perform_request

Additionally, the instrumentation wraps the following methods of the Elasticsearch client class:

  • elasticsearch.client.Elasticsearch.delete_by_query
  • elasticsearch.client.Elasticsearch.search
  • elasticsearch.client.Elasticsearch.count
  • elasticsearch.client.Elasticsearch.update

Collected trace data:

  • the query string (if available)
  • the query element from the request body (if available)

SQLite

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Instrumented methods:

  • sqlite3.connect
  • sqlite3.dbapi2.connect
  • pysqlite2.dbapi2.connect

The instrumented connect method returns a wrapped connection/cursor which instruments the actual Cursor.execute calls.

Collected trace data:

  • parametrized SQL query

MySQL

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Library: MySQLdb

Instrumented methods:

  • MySQLdb.connect

The instrumented connect method returns a wrapped connection/cursor which instruments the actual Cursor.execute calls.

Collected trace data:

  • parametrized SQL query

PostgreSQL

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Library: psycopg2, psycopg2-binary (>=2.5,<2.8)

Instrumented methods:

  • psycopg2.connect

The instrumented connect method returns a wrapped connection/cursor which instruments the actual Cursor.execute calls.

Collected trace data:

  • parametrized SQL query

PyODBC

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Library: pyodbc, (>=4.0)

Instrumented methods:

  • pyodbc.connect

The instrumented connect method returns a wrapped connection/cursor which instruments the actual Cursor.execute calls.

Collected trace data:

  • parametrized SQL query

MS-SQL

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Library: pymssql, (>=2.1.0)

Instrumented methods:

  • pymssql.connect

The instrumented connect method returns a wrapped connection/cursor which instruments the actual Cursor.execute calls.

Collected trace data:

  • parametrized SQL query

MongoDB

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Library: pymongo, >=2.9,<3.8

Instrumented methods:

  • pymongo.collection.Collection.aggregate
  • pymongo.collection.Collection.bulk_write
  • pymongo.collection.Collection.count
  • pymongo.collection.Collection.create_index
  • pymongo.collection.Collection.create_indexes
  • pymongo.collection.Collection.delete_many
  • pymongo.collection.Collection.delete_one
  • pymongo.collection.Collection.distinct
  • pymongo.collection.Collection.drop
  • pymongo.collection.Collection.drop_index
  • pymongo.collection.Collection.drop_indexes
  • pymongo.collection.Collection.ensure_index
  • pymongo.collection.Collection.find_and_modify
  • pymongo.collection.Collection.find_one
  • pymongo.collection.Collection.find_one_and_delete
  • pymongo.collection.Collection.find_one_and_replace
  • pymongo.collection.Collection.find_one_and_update
  • pymongo.collection.Collection.group
  • pymongo.collection.Collection.inline_map_reduce
  • pymongo.collection.Collection.insert
  • pymongo.collection.Collection.insert_many
  • pymongo.collection.Collection.insert_one
  • pymongo.collection.Collection.map_reduce
  • pymongo.collection.Collection.reindex
  • pymongo.collection.Collection.remove
  • pymongo.collection.Collection.rename
  • pymongo.collection.Collection.replace_one
  • pymongo.collection.Collection.save
  • pymongo.collection.Collection.update
  • pymongo.collection.Collection.update_many
  • pymongo.collection.Collection.update_one

Collected trace data:

  • database name
  • method name

Redis

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Library: redis (>=2.8,<3.2.0)

Instrumented methods:

  • redis.client.Redis.execute_command
  • redis.client.Pipeline.execute

Collected trace data:

  • Redis command name

Cassandra

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Library: cassandra-driver (>=3.4,<4.0)

Instrumented methods:

  • cassandra.cluster.Session.execute
  • cassandra.cluster.Cluster.connect

Collected trace data:

  • CQL query

External HTTP requests

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urllib3

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Library: urllib3

Instrumented methods:

  • urllib3.connectionpool.HTTPConnectionPool.urlopen

Additionally, we instrumented vendored instances of urllib3 in the following libraries:

  • requests
  • botocore

Both libraries have "unvendored" urllib3 in more recent versions, we recommend to use the newest versions.

Collected trace data:

  • HTTP method
  • requested URL

requests

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Instrumented methods:

  • requests.sessions.Session.send

Collected trace data:

  • HTTP method
  • requested URL

Services

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AWS Boto3 / Botocore

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Library: boto3 (>=1.0)

Instrumented methods:

  • botocore.client.BaseClient._make_api_call

Collected trace data:

  • AWS region (e.g. eu-central-1)
  • AWS service name (e.g. s3)
  • operation name (e.g. ListBuckets)

Template Engines

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Django Template Language

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Library: Django (see Django for supported versions)

Instrumented methods:

  • django.template.Template.render

Collected trace data:

  • template name

Jinja2

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Library: jinja2

Instrumented methods:

  • jinja2.Template.render

Collected trace data:

  • template name
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