I have created an application using mySQL, Express.js, React, Node.js
My question is, which servers would allow me to deploy this application for free? I'm assuming TOMCAT wouldn't allow me to create it because I have a node.js / express.js as back-end.
Outside of Heroku, here are a few free and easy deployment options:
Serverless:
AWS Lambda: https://amzn.to/2JgBFlL
Azure Web Services: https://azure.microsoft.com/en-us/free/cloud-services/search/?&OCID=AID719825_SEM_UHdSDoOS&lnkd=Google_Azure_Brand&gclid=EAIaIQobChMIh7rFgt2k3gIVGMNkCh0wOwnqEAAYASAAEgKkP_D_BwE
Of course in the future if you have a super lightweight 'app' you're trying to deploy, Github pages is a good option.
Serverless is a really good option though because deployment becomes as simple as pointing the serverless service to a repo and committing to the repo. The rest of the deployment process is handled by in these cases, either AWS or Azure. And for AWS and Azure, you can easily link in a lightweight, free SQL DB.
The learning curve is no less daunting than learning to deploy on Heroku, but it is much much simpler once it's set up. Plus - you get the added benefit of scalability for free because AWS and Azure takes care of it for you!
Related
I am new with AWS stuff so here is my application requirement.
Node Js with express js
Mysql Database
PHP web application + API application
So how do I need to deploy it on AWS for a basic start so that after testing the platform I can deploy my production on it. So can you guys help me for:
How many instances are needed
What if I need to go with CentOS + cPanel hosting for mysql and PHP application
you can go for plain 1 VM in AWS for start and if you tell about how much concurrent user are expected on your apps so we can help you to determine the resources.
My project is currently hosted by an independent cloud provider.
I am using 2 Virtual Machines, with Linux:
one hosts a Go application
one hosts a MySql database
I would now like to move to the Google Cloud Platform.
Do you think does it make sense to move to Google Cointainer Engine (GKE), rather than to the Google Compute Engine (which would have the same virtual machine model (IaaS) I am using with the current provider)?
I have never used Kubernetes and Docker. How easy would it be to make the migration? Am I going to complicate my life uselessly?
How difficult is the configuration for my simple model?
I have never used Kubernetes and Docker.
Moving to a platform that you have no experience with doesn't sound like a great idea. Instead, why not start by doing some tutorials about Docker and then Kubernetes?
After that, you might try Minikube (https://kubernetes.io/docs/getting-started-guides/minikube/) locally to start writing some manifests for the components (which sound like maybe a DaemonSet or single Pod with PersistentVolume for MySQL and a Deployment for the Go application).
Once you have the pieces working locally, then it would probably make more sense to think about migrating. You would have a much better understanding of what you are getting into and if it is something you would want to undertake.
What's the difference between OpenShift and Kubernetes and when should you use each? I understand that OpenShift is running Kubernetes under the hood but am looking to determine when running OpenShift would be better than Kubernetes and when OpenShift may be overkill.
In addition to the additional API entities, as mentioned by #SteveS, Openshift also has advanced security concepts.
This can be very helpful when running in an Enterprise context with specific requirements regarding security.
As much as this can be a strength for real-world applications in production, it can be a source of much frustration in the beginning.
One notable example is the fact that, by default, containers run as root in Kubernetes, but run under an arbitrary user with a high ID (e.g. 1000090000) in Openshift. This means that many containers from DockerHub do not work as expected. For some popular applications, The Red Hat Container Catalog supplies images with this feature/limitation in mind. However, this catalog contains only a subset of popular containers.
To get an idea of the system, I strongly suggest starting out with Kubernetes. Minikube is an excellent way to quickly setup a local, one-node Kubernetes cluster to play with. When you are familiar with the basic concepts, you will better understand the implications of the Openshift features and design decisions.
OpenShift includes a distribution of Kubernetes, so if you don't need any of those added features of OpenShift you can choice to ignore them such as: Web Console, Builds, advanced deployment models and much, much more.
Here's a summary of items available on the OpenShift website.
Kubernetes comes with Ingress Rules but Openshift comes with Routes
Kubernetes has IngressController but Openshift has Router as HAProxy
To swtich namespace in cli for openshift is very easy but in
kubernetes you need to create contex and switch between context
Openshift UI has more interactive and informative then Kubernetes
To bake docker image inside Openshift has BuildConfig but kubernetes
don't has any thing you need to build image and push to registry
Openshift has Pipeline where u don't need any jenkins to deploy any
app but Kubernetes don't has.
The easiest way to differentiate between them is to understand that while vanilla K8S is community project, OpenShift is more focused towards making it a enterprise ready product. Resources like Imagestreams, BC, Builds, DC, Routes etc along with leveraging functionalities like S2I, Router etc make it easier for Developers and admin alike to use OCP for development, deployment and lifecycle management. You can refer to the URL https://cloud.redhat.com/learn/topics/kubernetes/ for getting more information on key differences between them.
OCP makes your life much easier by giving easy actions using CLI command OC and fine grained webconsole.
You can try OCP and get first hand experience of the features using https://developers.redhat.com/developer-sandbox
where you can quick get access to sandboxed environment in a shared cluster.
I have a publicly accessed database on RDS that works like a charm from Netbeans. I would like to deploy my Java application on AWS. What is the simplest way to do this? I will only use the application for some very basic tasks, getting used to cloud computing working on a small scale. Is EC2 my best bet and is it possible to upload apps as easily as with the Google App Engine plugin. Can I use the same jdbc driver as I use locally, and can I use JPA against the database? I would rather not use Eclipse for now as I am in a bit of a hurry and need to get this working as soon as possible.
This is a lot of questions for one question, but I'll see if I can help you out.
1. Simplest Way to deploy to AWS
If this application is as simple as you say it is, the most cost effective solution while you're getting used to AWS will be to deploy to a micro instance and take advantage of the free tier. From Amazon:
AWS Free Tier includes 750 hours of Linux and Windows Micro Instances each month for one year. To stay within the Free Tier, use only EC2 Micro instances.
The simplest way to deploy directly from Netbeans is to use the integrated Elastic Beanstalk support. This saves you from having to configure things yourself.
Another option is to launch a Ubuntu AMI and install Tomcat. Create a WAR file from your application and place it where Tomcat can find it. I suggest using the first method.
2. Is EC2 my best bet?
This is a little open ended. For a nice learning experience as you get accustomed to AWS, the free tier for EC2 is a nice platform to learn with. If your application needs to eventually scale, using EBS is a pretty simple way to manage an application. My answer is an opinion because "best bet" depends solely on the requirements of your application, but I say yes.
3. Is it possible to upload apps as easily as with the Google App Engine plugin?
For simple applications I think so. I think it's even easier if you switch to Eclipse and use the toolkit for AWS. Whether Google App Engine or AWS is easier for you will once again depend on personal preference, the application, and your requirements.
4. Can I use the same JDBC driver as I use locally?
If you're using MySQL Connector/J then yes. Read this to understand how it works with RDS.
5. Can I use JPA against the database?
Yes. You'll change the endpoint from localhost to the endpoint of your RDS instance.
6. I would rather not use Eclipse for now...
Another personal preference, but the AWS toolkit for Eclipse is very easy to use and can speed the process up a bit.
What are the advantages we get by using Elastic Beanstalk over maually creating EC2 instance and setting up tomcat server and deploy etc for a typical java web applicaion. Are load balancing, Monitoring and autoscaling the only advantages?
Suppose for my web application which uses database I installed the database in the EC2 instance itself. When Autoscalling takes place will the database gets created in the newly created instance or it will be accessing the database I created in the master instance... If it creates just a replica when autoscaling happens how will be data sync happens between the instances?
All the things you mentioned like load balancing, monitoring and auto-scaling are definitely advantages.
However, you have to kind of think about it this way: In a true Platform as a Service (PAAS), the goal is to separate the application from the platform. As a developer, you only worry about your application. The platform is "rented" to you. The platform "instances" are automatically updated, administered, scaled, balanced, etc. for you. You just upload your WAR file and it just works (at least theoretically).
EC2 by itself is not PAAS. It is more like IAAS (Infrastructure as a Service). You still have to take care of the server instances, install software on them, keep them updated, etc.
Elastic Beanstalk is a PAAS system. So are App Engine and Azure among many others.
In a true PAAS system, the DBMS is a separate component from the web application server(s). The reason is obvious: The DBMS cannot be possibly installed on the instances that are being used for the application server because, as instances are created and destroyed based on your traffic, the DBMS would be lost! Having the DBMS and application server on the same machine/instance is not generally a good idea anyway.
In a PAAS system, the DBMS is a separate service. For Amazon, it would be Amazon RDS. Just like with Elastic Beanstalk, where you don't have to worry about the application server and you just upload your WAR file, with RDS, you don't have to worry about the DBMS and you just deploy your database(s).
Elastic Beanstalk and RDS work very well together, especially when deployed in the same availability zone, where the latency would be very low.
Finally, using Elastic Beanstalk doesn't cost anything more than the deployed resources (EC2 instances and the load balancer). However, RDS is not cheap and would definitely be more expensive than using a single EC2 instance for both the application server and the DBMS.
Elastic Beanstalk does more than just load balancing, monitoring, and autoscaling.
1) Manages application versions by storing and managing different versions of your application, allowing you to easily switch back and forth between different versions of your applications.
2) Has the concept of "environments" for each application, allowing you to deploy different versions of your application in each environment. This is handy for example if you want to set up separate QA and DEV environments, and you want to easily deploy a build first in DEV then deploy the same version of the application in QA when your QA team is ready for the next build.
3) Externalizes the important container configuration properties (Tomcat memory settings, for example) to the Elastic Beanstalk console and API. Because of this you can easily save the settings and copy them between environments.
4) View application log files through the console and automatically roll and archive log files to S3. (Admittedly this feature is currently a little weak.)
I had an app deployed both in EC2 dedicated(Nginx & Gunicorn) and Beanstalk Environment(CentOS & Apache2).
My observations:
BeanStalk is Paas. Manually creating an EC2 instance(IAAS), is like doing everything from scratch, but you have solid control.
BeanStalk comes with by default CentOS and Apache(Httpd). You could choose OS in dedicated instance.
These things that mattered to me,
There were lots of 504 errors showing up in Beanstalk environment.
It was difficult to debug when BeanStalk server crashed, as logs would also not show up and could not ssh into machine. This is very important.
Installing/configuring tools like Celery, Redis (need to run another port) etc.,. in dedicated instance is lot more easier.
In my case, I had to scale up (Beanstalk)server in order to run installation of some packages(like pandoc). These things are more simpler in Ubuntu.
Scaling is a lot more easier in BeanStalk. Cloning servers is straightforward in BeanStalk.
I had taken micro in both the cases (dedicated & Beanstalk). I felt dedicated micro instance was better.
Automated deployment in Beanstalk. I had to write scripts to automate the same, which is fine, since it is only once.