v0.26.0

New Features

Queue consumer support with Kombu

Baseplate now has first class support for consuming messages from queue brokers like RabbitMQ using Kombu. The full trace and diagnostic framework works here.

from kombu import Connection, Exchange
from baseplate import queue_consumer

def process_links(context, msg_body, msg):
    print('processing %s' % msg_body)

queue_consumer.consume(
    baseplate=make_baseplate(cfg, app_config),
    exchange=Exchange('reddit_exchange', 'direct'),
    connection=Connection(
      hostname='amqp://guest:guest@reddit.local:5672',
      virtual_host='/',
    ),
    queue_name='process_links_q',
    routing_keys=[
        'link_created',
        'link_deleted',
        'link_updated',
    ],
    handler=process_links,
)

See the documentation for more details.

Changes

• The memcached instrumentation now adds details about each call to span tags. This includes key names, key counts, and other settings.
• When preparing CQL statements with the Cassandra integration, Baseplate will now cache the prepared statement for you. This means you can call prepare() every time safely.
• The secret fetcher daemon can now be run in a single-shot mode where it exits immediately after fetching secrets. This can be used for situations like cron jobs in Kubernetes.
• When installing as a wheel, the baseplate CLI scripts no longer have a Python version suffix. baseplate-serve2 -> baseplate-serve.
• The Zipkin tracing observer can now ship spans to a sidecar span publisher daemon rather than sending from within the application itself.
• There are now new methods to check experiment names are valid and to get lists of all active experiments.
• Experiments now send exposure events.

Bug Fixes

• Fix a case where connection failures in the thrift connection pool implementation would cause the pool to lose connection slots and eventually be depleted.
• Fix an issue where for r2 experiments with low bucketing and 3 total treatments, bucketing is uneven.