I want to create Java application with use of Amazon Web Services and I also want to have ability to run it as local application. So it will be in two versions: Amazon cloud and as local application. I don't know AWS yet and I'am worry about if there is some specific api or database access so I couldn't run as local app. I simply do not want to write two separate versions of that app, or just write as less as possible.
Is it possible?
In EC2, you can launch virtual servers (or instances) with root or administrator access. That means your EC2 instances are capable of running mostly everything you can run locally.
There are no specific APIs to learn to run Java code on EC2. Just compile and package your code, upload it to your server (using scp/rsync/anything else you might be more used to), then run it with java -jar myapp.jar, after installing Java on the instance. You can also upload the source code directly into your instance and compile it there if you want. It really behaves like a "normal" server.
About database access, again, it works exactly as you would expect: just install your database server on the instance, say, MySQL, and connect to it normally (using JDBC for example). Also, note that there's a service called Relational Database Service (RDS), which simplifies the deployment and management of a database system: you don't have to install your database software, maintain it, upgrade, backup, etc, everything is done for you. You simply specify the name and password of the "master" user, and it gives you back a connection string. (and there's also a "micro" RDS instance which is included in the free tier so that you can start exploring for free!)
Finally, if you don't want to launch and maintain a virtual server by yourself, you could use Elastic Beanstalk, which automates lots of things for you: using the web interface, you simply upload your ".war" file, and Elastic Beanstalk launches and instance for you, installs Java, Tomcat, deploys your application, and monitor it for you -- you get emails in your inbox if anything goes wrong. There are tons of other features included in Elastic Beanstalk, and it is all completely free (you just pay for the servers it launches -- also, if you instruct it to launch at most a single t1.micro instance, which is included on the free tier, again, you pay nothing!)
Related
I know that you can create an image of your server as-is and setup auto-scaling on that, but what if I then make changes to my original server? Do I have to then make another snapshot of that and setup auto-scaling again?
There are two approaches for configuring a server:
Creating an Amazon Machine Image (AMI) with all software fully configured, or
Having the instance configure itself via a startup script triggered via User Data
A fully-configured AMI is fast to startup, whereas a configuration script can take several minutes to configure the instance before the instance is ready to accept traffic.
In general, it is not considered good practice to "make changes to my original server" because there is no concept of an "original server". All instances are considered equal. Instead, the configuration should be created and tested on development servers separate to any production servers and then released by deploying new servers or by having an 'update' script intelligently run on existing servers. Some of these capabilities are provided by AWS CodeDeploy.
Can we run an application that is configured to run on multi-node AWS EC2 K8s cluster using kops (project link) into local Kubernetes cluster (setup using kubeadm)?
My thinking is that if the application runs in k8s cluster based on AWS EC2 instances, it should also run in local k8s cluster as well. I am trying it locally for testing purposes.
Heres what I have tried so far but it is not working.
First I set up my local 2-node cluster using kubeadm
Then I modified the installation script of the project (link given above) by removing all the references to EC2 (as I am using local machines) and kops (particularly in their create_cluster.py script) state.
I have modified their application yaml files (app requirements) to meet my localsetup (2-node)
Unfortunately, although most of the application pods are created and in running state, some other application pods are unable to create and therefore, I am not being able to run the whole application on my local cluster.
I appreciate your help.
It is the beauty of Docker and Kubernetes. It helps to keep your development environment to match production. For simple applications, written without custom resources, you can deploy the same workload to any cluster running on any cloud provider.
However, the ability to deploy the same workload to different clusters depends on some factors, like,
How you manage authorization and authentication in your cluster? for example, IAM, IRSA..
Are you using any cloud native custom resources - ex, AWS ALBs used as LoadBalancer Services
Are you using any cloud native storage - ex, your pods rely on EFS/EBS volumes
Is your application cloud agonistic - ex using native technologies like Neptune
Can you mock cloud technologies in your local - ex. Using local stack to mock Kinesis, Dynamo
How you resolve DNS routes - ex, Say you are using RDS n AWS. You can access it using a route53 entry. In local you might be running a mysql instance and you need a DNS mechanism to discover that instance.
I did a google search and looked at the documentation of kOps. I could not find any info about how to deploy to local, and it only supports public cloud providers.
IMO, you need to figure out a way to set up your local EKS cluster, and if there are any usage of cloud native technologies, you need to figure out an alternative way about doing the same in your local.
The true answer, as Rajan Panneer Selvam said in his response, is that it depends, but I'd like to expand somewhat on his answer by saying that your application should run on any K8S cluster given that it provides the services that the application consumes. What you're doing is considered good practice to ensure that your application is portable, which is always a factor in non-trivial applications where simply upgrading a downstream service could be considered a change of environment/platform requiring portability (platform-independence).
To help you achieve this, you should be developing a 12-Factor Application (12-FA) or one of its more up-to-date derivatives (12-FA is getting a little dated now and many variations have been suggested, but mostly they're all good).
For example, if your application uses a database then it should use DB independent SQL or no-sql so that you can switch it out. In production, you may run on Oracle, but in your local environment you may use MySQL: your application should not care. The credentials and connection string should be passed to the application via the usual K8S techniques of secrets and config-maps to help you achieve this. And all logging should be sent to stdout (and stderr) so that you can use a log-shipping agent to send the logs somewhere more useful than a local filesystem.
If you run your app locally then you have to provide a surrogate for every 'platform' service that is provided in production, and this may mean switching out major components of what you consider to be your application but this is ok, it is meant to happen. You provide a platform that provides services to your application-layer. Switching from EC2 to local may mean reconfiguring the ingress controller to work without the ELB, or it may mean configuring kubernetes secrets to use local-storage for dev creds rather than AWS KMS. It may mean reconfiguring your persistent volume classes to use local storage rather than EBS. All of this is expected and right.
What you should not have to do is start editing microservices to work in the new environment. If you find yourself doing that then the application has made a factoring and layering error. Platform services should be provided to a set of microservices that use them, the microservices should not be aware of the implementation details of these services.
Of course, it is possible that you have some non-portable code in your system, for example, you may be using some Oracle-specific PL/SQL that can't be run elsewhere. This code should be extracted to config files and equivalents provided for each database you wish to run on. This isn't always possible, in which case you should abstract as much as possible into isolated services and you'll have to reimplement only those services on each new platform, which could still be time-consuming, but ultimately worth the effort for most non-trival systems.
1. Summarize the problem
Google Cloud Run advertises that it is "stateless containers". Is there a way to run anything at all, have it save state somewhere?
I want to run Postgres in a container, but only have it up on demand, spin up the PG container when there is a request made.
The same question goes for a container that will hold a REST API (web server), to connect to the PG container.
So when the web app (hosted on Firebase), makes a request to the REST API (container), it would spin up, and then the PG instance that gets queried from the REST api would spin up (or can simply put both DB , REST API in one container).
For a dev instance, I don't want something up 24x7x365 doing mostly nothing, just something that will spin up during development hours, but have a number of these, am the only OPS guy, want to automate it for developers, including myself and minimize billing.
Any best approach here would be appreciated.
2. Provide background including what you've already tried
I have created Docker containers and deployed to Cloud Run
3. Show some code
yum install buildah podman -y
4. Describe expected and actual results including any error messages
I am looking for a solution to minimize billing for a dev environment that will include hosting and a database/REST API (database has to be Postgres).
I'm looking for a stateful cloud run that will maintain the state of a database.
Cloud Run is not suitable for hosting a database. Server instances allocated for incoming requests to Cloud Run can come and go, and not all requests will go to the same instance, which means that not all clients will see the same data. That's the problem with "stateless containers".
If you want to use Cloud Run to provide database access, it would best be as a proxy to some other cloud-hosted database service. You might use to it host a REST API endpoint that accesses some other database service (for example: Cloud Firestore, Cloud SQL). But it doesn't make sense to host the database itself in your docker image, since those server instances can come and go unpredictably, destroying any database state stored in each instance.
Is it possible to create a database server (MySQL or PostgreSQL) inside an EC2 instance (running Windows 2016) and access it the way we access an RDS or do I need to have a separate RDS for that purpose?
My plan was to have an EC2 instance and use it as a server for accessing some Windows applications to my (small) company as well as an always-available database to store our reports.
Please let me know if I am on the wrong path.
Yes, you can install MySQL or PostgreSQL on an EC2 instance, just like you would for a server that was within your company.
You of course won't have all of the extra redundancy/backup features that RDS provides for you - unless you start adding all of that yourself i.e. automated backups, slave/master configurations, read replicas etc. (and if you do start adding all of those extra features in I would reconsider your decision not to use RDS).
I do this for some smaller, less mission critical solutions I support, and generally have not had many issues; I still prefer RDS when possible, but its not always an option for me.
You can install and configure DB on windows and access from your app. the endpoint will be windows machine IP and running service port. you have to allow the application from the security group.
I have an application that have several environments (all running in Amazon Elastic Beanstalk), namely, Production, Worker and Debug. Each environment have corresponding git branch that is different from master in some ways (like, configuration is changed and some code is deleted).
I use eb deploy to deploy the new version of application from its branch. It zips current git branch using git zip and sends the information to Amazon. Then it deploys to running instances.
The problem, however, is that deploying takes some time (about 5 minutes). Thus, between deploying, say, worker and production it have different code. Which is bad, because my changes might have change the queue protocol or something like that.
What I want is to be able to upload the information and to do its processing on all the environments, but not actually replace the code, just prepare it. And after I did it for all the environments issue command like "finish deploy" so that the code base is replaced on all the environments simultaneously.
Is there a way to do it?
You need to perform a "blue-green" deploy and not do this in-place. Because your deployment model requires synchronization of more than one piece, a change to the protocol those pieces use means those pieces MUST be deployed at the same time. Treat it as a single service if there's a frequently-breaking protocol that strongly binds the design.
"Deployed" means that the outermost layer of the system is exposed and usable by other systems. In this case, it sounds like you have a web server tier exposing an API to some other system, and a worker tier that reads messages produced by the web tier.
When making a breaking queue protocol change, you should deploy BOTH change-sets (web server layer and queue layer) to entirely NEW beanstalk environments, have them configured to use each other, then do a DNS swap on the exposed endpoint, from the old webserver EB environment to the new one. After swapping DNS on the webserver tier and verifying the environment works as expected, you can destroy the old webserver and queue tiers.
On non-protocol-breaking updates, you can simply update one environment or the other.
It sounds complex because it is. If you are breaking the protocol frequently, then your system is not decoupled enough to expect to version the worker and webserver tiers, which is why you have to do this complex process to version them together.
Hope this helps!