I am newbie in AWS and totally confused about the deploy. here i have
React for front-end , Nodejs for API, Mongodb for database and redis for session store.
Can i use 1 EC2 for every service ? or
Divide every service as different EC2
Can i use Elastic Beanstalk Environment?
Which is better option for scaling and update without downtime in future ?
Can I use 1 EC2 for every service?
Its depend on your case but the best approach is to utilize the underlying EC2 instance is to run multiple services on single EC2 for nodejs and front-end app, as nodejs container-based application take maximum advantage in this case. in this case, ECS blue-green deployment with the dynamic port of the container can help to scale with zero downtime.
Divide every service as different EC2
In nodejs based application this approach does not help you a lot where for Redis and mongo it make sense if you are planning for clustering and replica also these applications need persistent storage so will keep storage on each instance, so my suggestion is to keep redis and mongo DB in daemon mode and application in replica mode, as these are application that will do blue-green deployment not the redis or Db.
AWS provides two types of task to deal with such cases
REPLICA—
The replica scheduling strategy places and maintains the desired
number of tasks across your cluster. By default, the service scheduler
spreads tasks across Availability Zones. You can use task placement
strategies and constraints to customize task placement decisions. For
more information, see Replica.
DAEMON—
The daemon scheduling strategy deploys exactly one task on each active
container instance that meets all of the task placement constraints
that you specify in your cluster. When using this strategy, there is
no need to specify a desired number of tasks, a task placement
strategy, or use Service Auto Scaling policies. For more information
ecs_services
Related
I have a service that needs to run on our own EC2 instances, since it requires some support from the kernel. My previous experience is all with containers in AWS. The application itself is distributed as a single JAR file and I'm looking for advice for how I should automate deployments. The architecture is:
An ALB in front of the ASG.
EC2 instance running a single Java application.
Any open sockets are open for an hour tops and to not cause any trouble, we have to drain the connections to the EC2 instances before performing an update, so a hard requirement is for the ALB to stop opening new connections for an hour before updating the software. The application is mission critical and ECS has had some issues last year, so I want to minimize the AWS services I depend on. While I could do what I want on my own ECS cluster with custom AMIs, I don't want to do it, since I will run a single instance of the app per host and don't need the extra layer.
My question: What is the simplest method to achieve this using CodePipeline? My understanding is that I need to use a CodeDeploy deployment step to push something to bare EC2 instances. How does draining with an ALB work in this case? We're using CloudFormation for the deployment.
You need to use codedeploy. You can find tutorial on AWS codedeploy documentation.
Codedeploy deployment lifecycle hooks for EC2.
https://docs.aws.amazon.com/codedeploy/latest/userguide/reference-appspec-file-structure-hooks.html#appspec-hooks-server
I'm new to these both technologies but have trouble understanding what exactly do these two do different, a use case example will be very helpful.
AWS ECS is the container orchestration service that allows deployment, scale of the containers. Let's say you have 10 apps to be deployed on EC2 machines. ECS will provide you an easy way to deploy and manage them, scale the app when needed etc.
Now, these 10 apps might want to talk to each other. One way is to use the ip address and make an RPC call to the other application. However, this process doesn't scale. What if the machine is restarted or the app or the app is moved to another EC2 machine etc.
So, you require a middleware that manages the mapping of app to the EC2 machine so that the application doesn't need to bother about how to call the other application.
AWS AppMesh provides exactly that middleware. It provides an application level networking so that your service can communicate with other services.
ECS - Platform to run containers as task/service in a clustered manner.
when multiple containers are running in an ecs cluster they may want to talk with each other OR other aws services. These containers should know where other containers/services are by means of ip/endpoint..etc. That's where service discovery comes into picture.
Appmesh - Appmesh is a service discovery tool plus a lot more feature. One of them is to ensuring reliable communication between containers.
Appmesh uses envoy as sidecar in ecs to implement service discovery(plus many more) functionality.
Most of the time Appmesh is used in conjunction with Aws CloudMap.
I have successfully deployed a MEAN app on AWS ECS, but there are a couple things I don't have set-up properly.
1) If I spin up a new task, the Mongo data does not persist between the containers
2) Should my Mongo container and my frontend container be in the same task definition? This seems wrong because I feel like they should be able to scale independently of each other. But if they should be in separate task definitions, do I link them the same way?
Current Architecture:
1 Task Defintion
contains frontend container and mongo container which are linked
I did not define any mounts or volumes (which I assume is why data isn't persisting, but I am struggling to figure out how to properly set this up)
1 Cluster
1 service
contains load balancer and auto-scaling group (when this auto-scaling group creates a new task, I run into the issue of not having data persistence)
I guess what you assume is correct. Since you are not defining any mounts the data is not persistent. I recommend using Amazon EFS to Persist Data from Amazon ECS Containers.You can find step by step guide below to achieve the same.
Using Amazon EFS to Persist Data from Amazon ECS Containers
I have multiple microservices that I have to run independently. I am thinking of deploying them in docker containers in one ec2 instances. But then there is the question of scaling. I knowledge is ecs gives me the ability to scale. I haven't used ecs though. So my question is can I scale all my containers by creating one ec2 networks ? Or is there anything I haven't thought or know about ? Also, what is the performance issues with this deployment ?
Thanks
Amit
For the microservices deployment, one ec2 instance will never suffice for production workload considering HA, scaling, performance etc.
You should think of cluster. A compute cluster is a multi-tenant computing environment consisting of servers (called “nodes”) whose resources have been pooled together and are used to execute processes. To enable this behavior, the nodes in a cluster must be managed by some sort of cluster management framework.
So you have to choose between multiple options from Kubernets, Mesos & Marathon and AWS ECS.
The EC2 Container Service is: A cluster management framework that uses optimistic, shared state scheduling to execute processes on EC2 instances using Docker containers.
The above option provides all the functionality you looking for. So you need to analyze more of them and select the most suitable option as per your need.
I recently tried to deploy docker containers using task definition by AWS. Along the way, I came across the following questions.
How to add an instance to a cluster? When creating a new cluster using Amazon ECS console, how to add a new ec2 instance to the new cluster. In other words, when launching a new ec2 instance, what config is needed in order to allocate it to a user created cluster under Amazon ECS.
How many ECS instances are needed in a cluster, and what are the factors?
If I have two instances (ins1, ins2) in a cluster, and my webapp, db containers are running in ins1. After I updated the running service (through http://docs.aws.amazon.com/AmazonECS/latest/developerguide/update-service.html), I can see the newly created service is running in "ins2", before draining the old service in "ins1". My question is that after my webapp container allocated to another instance, the access IP address becomes another instance IP. How to prevent or what the solution to make the same IP address access to webapp? Not only IP, what about the data after changing to a new instance?
These are really three fairly different questions, so it might best to split them into different questions here accordingly - I'll try to provide an answer regardless:
Amazon ECS Container Instances are added indirectly, it's the job of the Amazon ECS Container Agent on each instance to register itself with the cluster created and named by you, see concepts and lifecycle for details. For this to work, you need follow the steps outlined in Launching an Amazon ECS Container Instance, be it manually or via automation. Be aware of step 10.:
By default, your container instance launches into your default
cluster. If you want to launch into your own cluster instead of the
default, choose the Advanced Details list and paste the following
script into the User data field, replacing your_cluster_name with the
name of your cluster.
#!/bin/bash
echo ECS_CLUSTER=your_cluster_name >> /etc/ecs/ecs.config
You only need a single instance for ECS to work as such, because the cluster itself is managed by AWS on your behalf. This wouldn't be sufficient for high availability scenarios though:
Because the container hosts are just regular Amazon EC2 instances, you would need to follow AWS best practices and spread them over two or three Availability Zones (AZ) so that a (rare) outage of an AZ doesn't impact your cluster, because ECS can migrate your containers to a different host instance (provided your cluster has sufficient spare capacity).
Many advanced clustering technologies that facilitate containers have their own service orchestration layers and usually require an uneven number >= 3 (service) instances for a high availability setup. You can read more about this in section Optimal Cluster Size within Administration for example (see also Running CoreOS with AWS EC2 Container Service).
This refers back to the high availability and service orchestration topics mentioned in 2. already, more precisely your are facing the problem of service discovery, which becomes more prevalent even when using container technologies in general and micro-services in particular:
To get familiar with this, I recommend Jeff Lindsay's Understanding Modern Service Discovery with Docker for an excellent overview specifically focused on your use case.
Jeff also maintains a containerized version of the increasingly popular Consul, which makes it simple for services to register themselves and to discover other services via a DNS or HTTP interface (see Running Consul in Docker and gliderlabs/docker-consul).