x/crypto/salsa20 2019/07/16 23:34:59 workers: 4, corpus: 5 (1s ago), crashers: 0, restarts: 1/0, execs: 0 (0/sec), cover: 0, uptime: 3s 2019/07/16 23:35:02 workers: 4, corpus: 6 (1s ago), crashers: 0, uptime: 6s 2019/07/16 23:35:05 workers: 4, corpus: 6 (4s ago), crashers: 0, restarts: 1/6797, execs: 95167 (10568/sec), cover: 26, uptime: 9s 2019/07/16 23:35:08 workers: 4, corpus: 6 (7s ago), crashers: uptime: 12s 2019/07/16 23:35:11 workers: 4, corpus: 7 (2s ago), crashers: 0, restarts: 1/7269, execs: 203535 (13564/sec), cover: 26, uptime: 15s 2019/07/16 23:35:14 workers: 4, corpus: 7 (5s ago), crashers:

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

machines. Supports broker clustering and HA when used in combination with RabbitMQ. You can set up new workers without central configuration (e.g. use your grandma’s laptop to help if the queue is temporarily globally for all. Routing Using AMQP’s flexible routing model you can route tasks to different workers, or select different message topologies, by configuration or even at runtime. Remote- control Worker define your own. (AMQP/Redis only) Moni- toring You can capture everything happening with the workers in real-time by subscribing to events. A real-time web monitor is in development. Serial- ization

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