slave-api

Chikka API integration but on a queue-based workflow. It runs on python, flask, nginx, gunicorn, rabbitmq, celery & mongodb for database(redis if ram wasn't that expensive =( ). Test server runs on Vagrant and workers(gunicorn, celery workers) are daemonized via supervisor.

Platform Structure:

. sms/ +--    wsgi.py  (gunicorn container)
+--    api.py  (entrypoint once nginx relayed the request, routes wether to go to)
+--    celeryconfig.py  (configurations as well as routings for workers)
+--    mongo.py  (mongo connection handler)
+--    slaves/
|    +--  message.py (resource handler for chikka's message inbound transaction)
|    +--  notification.py (resource handler for chikka's delivery notification)
|    +--  reply.py (worker for handling message replies for inbound messages)
|    +--  broadcast.py (todo for message broadcasts)
|    +--  keywords/
|    |    +--  project1
|    |    +--  project2
|    |    +--  projectN

1. create ubuntu instance
2. open port 80 from amazon security group
3. get the hostname that we are connecting to: ec2-13-112-67-6.ap-northeast-1.compute.amazonaws.com
4. install rabbitmq: https://www.rabbitmq.com/ec2.html
5. install mongodb
6. install python-pip
7. install from pip:
   • virtualenv
8. create directory 'apps'
9. checkout https://github.com/ricasiano/slave-api.git
10. go to 'sms' directory
11. enable virtualenv: virtualenv venv
12. run: 'source venv/bin/activate'
13. create the environment variables CHIKKA_CLIENT_ID="YOUR CHIKKA ID HERE" CHIKKA_SECRET_KEY="YOUR CHIKKA SECRET KEY HERE" CHIKKA_SHORTCODE="YOUR SHORTCODE HERE"
14. logout/login again to that session
15. create init.py on configs directory

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test: on 'sms' directory workers: celery -A routing.post.notification worker -Q notification --loglevel=info -n notification1.worker.%h celery -A routing.post.message worker -Q message --loglevel=info -n message1.worker.%h celery -A routing.post.message worker -Q message --loglevel=info -n message2.worker.%h celery -A routing.post.inbound.keywords.bord.process worker -Q bord --loglevel=info -n bord1.worker.%h

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16. Install gunicorn from pip
17. /etc/supervisor/conf.d

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[program:sms] command=/home/ubuntu/apps/slave-api/sms/venv/bin/gunicorn --bind unix:app.sock api:app --pythonpath /home/ubuntu/apps/slave-api/sms priority=999 ; the relative start priority (default 999) autostart=true ; start at supervisord start (default: true) autorestart=true ; retstart at unexpected quit (default: true) startsecs=10 ; number of secs prog must stay running (def. 10) startretries=3 ; max # of serial start failures (default 3) exitcodes=0,2 ; 'expected' exit codes for process (default 0,2) stopsignal=QUIT ; signal used to kill process (default TERM) stopwaitsecs=10 ; max num secs to wait before SIGKILL (default 10) user=ubuntu ; setuid to this UNIX account to run the program log_stdout=true ; if true, log program stdout (default true) log_stderr=true ; if true, log program stderr (def false) logfile=/var/log/flask-sms.log ; child log path, use NONE for none; default AUTO logfile_maxbytes=1MB ; max # logfile bytes b4 rotation (default 50MB) logfile_backups=10 ; # of logfile backups (default 10) directory=/home/ubuntu/apps/slave-api

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18. install nginx
19. go to /etc/nginx/conf.d/default.conf

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server { listen 0.0.0.0:80; server_name *.amazonaws.com; location / { include proxy_params; proxy_pass http://unix:/home/ubuntu/apps/slave-api/app.sock; } }

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