autoscaling

To implement a slack bot, i need to deal with 'Real Time Messaging API' of slack. It is a WebSocket-based API that allows you to receive events from Slack in real time and send messages as user. more info: https://api.slack.com/rtm To create a bot for only one team , i need to open one websocket connection and listen it for events. To make available the slack bot for another team. I need to open a new websocket connection. So, 1 team => 1 websocket connection 2 teams => 2 websocket connections N teams => N websocket connections what should i do to scale my websocket connections for endless

I want to autoscale the infrastructure when load gets high. I am running my infrastructure on AWS . I have a requirement where I need to pull the application code from Github when autoscaling happens. As the code changes frequently, we can't take an AMI and launch an instance from that AMI . So I want to pull the latest code from repositories . AWS just launched a service called AWS CodeDeploy . How can I use this service to automate the process of pulling the code when the instances start? P.S. I have written an init script to automatically attach an EIP , whitelist that IP on different

I have multiple instances running behind Load balancer with Auto Scaling in AWS. Now, if I have to push some code changes to these instances and any new instances that might launch because of auto scaling policy, what's the best way to do this? The only way I am aware of is, to create a new AMI with latest code, modify the auto scaling policy to use this new AMI and then terminate the existing instances. But this might involve a longer downtime and I am not sure whether the whole process can be automated. Any pointers in this direction will be highly appreciated. The way I do my code changes

We're looking at using EC2 autoscaling to deal with spikes in load. In our case we want to scale up instances based on an SQS queue size and then down scale with the queue size gets back under control. Each SQS message defines a potentially long running job (sometimes up to 20 minutes each for message) that must complete before the instance can be terminated. Our software handles the shutdown process gracefully, so issuing sudo service ourapp stop will wait for the app to complete before returning. My question; when autoscaling starts scaling down it issues a terminate (which apparently is

When you setup an Auto Scaling groups in AWS EC2 Min and Max bounds seem to make sense: The minimum number of instances to scale down to based on policies The maximum number of instances to scale up to based on policies However, I've never been able to wrap my head around what the heck Desired is intended to affect. I've always just set Desired equal to Min , because generally, I want to pay Amazon the minimum tithe possible, and unless you need an instance to handle load it should be at the Min number of instances. I know if you use ElasticBeanstalk and set a Min to 1 and Max to 2 it sets a