#Run unix commands in ruby runner how to
#Run unix commands in ruby runner code

We add this command to the startup script of our servers, and our consumer group will be up and running! Conclusion

#Run unix commands in ruby runner how to

How to start Monit? monit reload & sleep 1 Generated file output: payments_consumer.monitrc # consumer worker 0 check process consumer_payments_0 with pidfile /data/app/pids/consumer_payments_0.pid start program = '/bin/sh -c '/usr/bin/wrapper app start production payments 0'' stop program = '/bin/env /usr/bin/wrapper app stop production payments 0' group consumer # consumer worker 1 # similar # consumer worker 2 # similar workers: number_of_consumer_processes_to_run consumer_group_name: consumer_group_name Generate_monitrc.erb # consumer worker check process _consumer with pidfile /data//shared/pids/_consumer.pid start program = '/bin/sh -c '/usr/bin/ start '' as uid and gid with timeout 90 seconds stop program = '/bin/env /usr/bin/consumer_wrapper stop ' as uid and gid with timeout 90 seconds if totalmem is greater than MB for 3 cycles then restart group consumer Īrguments passed to the file above. This file serves as a template to create monitrc files as per arguments passed to it. We will programmatically generate monitrc files. How to Configure Monit for Consumer Process Management ?

We have to create consumer group specific monitrc files in each compute instance. The behavior of Monit is controlled by command-line options and a run control file, ~/.monitrc. It can start a process if it does not run, restart a process if it does not respond, and stop a process if it uses too many resources. It is a utility for managing and monitoring processes, files, directories and filesystems on a Unix system. For example, here, we are giving it the name payments. Options parser will parse the name of the consumer from the command and load it’s configuration from the yml file we specified above.

#Run unix commands in ruby runner code

We will create a new service/group of instances designated to consume events (data) from Kafka topics.Ĭonsumer group configs (meta data) to keep in a yml file: payments: group_id: 'payments-events-sync-group' topics: number_of_consumers: 3 bitcoin_streamer: group_id: 'bitcoin-btc-sync-group' topics: number_of_consumers: 7Ĭonsumer.rb CONSUMERS = YAML.load_file(File.join(Rails.root, 'config', 'consumer_config.yml')) def run consumer_config = # use the consumer config to run end OptionParser.new do |opts| opts.on('-name Consumer', 'A consumer group to start and attach consumer processes') end.parse! Services::Runner.new(options).runĮxample command to run this code from the command line: RAILS_ENV=production rails runner consumer.rb -name payments Now, the question is: How do we run multiple consumers on an instance/container and gracefully monitor them for errors and log our processes? How to Run Multiple Consumers Groups in Production (Live Environment) To overcome this delay, we need to run multiple consumer processes in parallel. When throughput is high, a single process will cause delay in reading. This will run one instance of our consumer, which will process messages from all the partitions in a topic. consumer.each_message do |message| process_message(message.value, meta) end consumer = nsumer(group_id: 'stream-group-1') consumer.subscribe('stream') # This will loop indefinitely, yielding each message in turn. Kafka Consumer Hello World require 'kafka' kafka = Kafka.new() # Consumers with the same group id will form a Consumer Group together. To follow this guide, you will need to be familiar with the basic Kafka terminology, like Kafka Topics and Partitions. This guide will help you build a robust, resilient and fault-tolerant Kafka consumer and also deploy it to serve millions of requests on production servers. But after that, you need to go a step further.

I was able to set up a running Kafka consumer group locally on a dev machine using those tutorials and documentation. There are a plethora of tutorials on what Apache Kafka is and how to set up and run a Kafka project.