between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers Cryptographic message signing. Features • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time

between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers Cryptographic message signing. Features • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time

between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers Cryptographic message signing. Features • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time

between clients and workers. To initiate a task, a client adds a message to the queue, which the broker then delivers to a worker. A Celery system can consist of multiple workers and brokers, giving way broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers Cryptographic message signing. Features • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time

between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers Cryptographic message signing. Features • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time

between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers Cryptographic message signing. Features • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time

between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers Cryptographic message signing. Features • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time

between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers Cryptographic message signing. Features • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time

between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers Cryptographic message signing. Features • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time

between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving broker='amqp://guest@localhost//') @app.task def hello(): return 'hello world' • Highly Available Workers and clients will automatically retry in the event of connection loss or failure, and some brokers Cryptographic message signing. Features • Monitoring A stream of monitoring events is emitted by workers and is used by built-in and external tools to tell you what your cluster is doing – in real-time