Just trying to understand what's the difference between bitnami apps and google 'click-to-deploy' options on Google Cloud Engine?
For example: There is a 'Cassandra' click-to-deploy and there is a Bitnami version of 'Cassandra'
Can anyone tell me how do they compare and what are the differences?
- is one restrictive compared to the other?
- does bitnami version lock you in somehow?
- is there any performance difference (other than obvious performance difference that the hardware change would bring)
Thanks.
Bitnami makes application stacks that run on several cloud platforms including Google Cloud Platform, AWS, Azure and a few others. The Bitnami images you see on Google Cloud Launcher are created by employees of Bitnami and are mostly standard across cloud.
Click to Deploy images are usually created by Google Cloud Platform employees working in conjunction with application vendors.
There are differences in versions here and there related to maintenance, but there isn't any difference in the way they are intended to be used. Some Click to Deploy images will incur higher use charges due to licensing (ie. the Click to Deploy image contains the "Pro" version of a vendor's software), but these are called out during the selection process.
Neither version is intended to lock you into a particular platform, Google or Bitnami, it's just that there is duplication among the applications provided.
Related
I am planning to migrated from DigitalOcean(DO) to Google Cloud(GCP).
I have taken trial on GCP and hosted Django website on it, but it is running too slow (it take 12-15 seconds to open page). Same website running on DO is very fast(it take hardly 1 second to open page).
Website is hosted on Ubuntu 20 LTS (on DO & GCP) & Apache2 server
On GCP there is no user right now, for testing I am only one user and it is running too slow. I have 2CPU and 8GB memory on VM.
I am not able to find out the issue why it is running slow on GCP and running fast on DO?
Can someone please help to find out solution?
When comparing Google Cloud Platform performance with the local one you should keep in mind that deploying on GCP needs more time to import all the necessary libraries and set up the Django framework.
In general it doesn't make much sense to compare the performance on your local machine with the performance on GCE, as local machines are likely running a different OS than GCE
In addition to that there are various ways to optimize your application’s performance, as the following typical ones:
Scaling configuration, by setting up “min_idle_instances” to be kept running and ready to serve traffic.
Using Warm Up Requests to reduce request and response latency during when your app's code is being loaded to a newly created instance.
I came across PageSpeed Insights, which analyzes the content of a web page, then generates suggestions to make that page faster and could be handy
I am going to create environments. For now i have gcp machine and i run jupyter in there. Everytime, i need start it, and with 3 people it is hard to work in same environment. I know, there is docker, jupyter hub, but did not find and suitable roadmap to create dev/prod environment.
My aim to create dev and production environment. Everything should be on GCP.
Any suggested path ?
Thanks
You can take a look at the best practices for enterprise organizations. In order to properly split resources it's often advised to use different projects. However, depending on the GCP product, you could also use versions, such as with App Engine (see this StackOverflow thread).
I'm working on web app and i want to migrate this web app to virtual machine scale set in windows azure cloud,i'm new to cloud computing ,till i didn't got any proper tutorial about virtual machine scale set,please someone help with this
A few things to consider..
You could build a custom VM which contains the complete app, or you could use VM extensions to deploy the app on a platform image each time a new VM in the scale set is deployed. See: https://msftstack.wordpress.com/2016/04/20/deploying-applications-in-azure-vm-scale-sets/ for some thoughts on this. Ultimately it might depend on how much you need to install over a base image, and how fast you want scaling to be.
Do you need autoscale based on resource usage or do you plan to manually increase/decrease the number of VMs in the set? See https://azure.microsoft.com/en-us/documentation/articles/virtual-machine-scale-sets-windows-autoscale/
A good way to get started with scale sets is to deploy an existing template directly from Azure Quick start templates. Look at https://github.com/Azure/azure-quickstart-templates and search for vmss. These templates will give you an idea of some of the options you have.
To learn the basics about VM Scale Sets, start with the documentation page: https://azure.microsoft.com/documentation/services/virtual-machine-scale-sets/ and the GA announcement: https://azure.microsoft.com/en-us/blog/azure-virtual-machine-scale-sets-ga/
Also look at higher level services like the Azure Web App service if you haven't already, the advantage of a higher level service is that some of the basic web app operations get taken care of for you: https://azure.microsoft.com/en-us/services/app-service/web/
So I have created a local java web application and many JasperReports. It is now time to move to production and I think I am going to use the Google App Engine. Before I started though I wanted to make sure all my JasperReports would work?
The previous questions regarding this were from 3-5 years ago, so I was just wondering if the Google App Engine now supports this?
Or should I use Amazon Elastic Beanstalk? (If this even supports JasperReports also)
No, it doesn't work on App Engine. Jasper Reports uses classes from AWT/Swing, that are restricted on App Engine
Btw, as you're comparing App Engine to Beanstalk (that's different things anyway), then maybe Google Compute Engine or Container Engine could help you? There're no any restrictions, just plain VMs, you may run anything here. And Google Cloud will provide load balancing, automatic scaling and restart after failure.
PS Also, I don't think that "just app" can be moved to App Engine. App Engine is very specific platform, and app should be designed specifically for App Engine from the beginning.
Let's say that I setup my own cloud using the open source cloud foundry implementation provided on cloudfoundry.org. Will each app that I deploy be run as a separate user? Or is there any of VMWare's virtualization technology in use here? E.g. would each app run in a separate virtual machine or anything like that? How can I configure the memory, cpu, and disk resource limits for each app?
I asked this on the mailing list. Here's the response I got:
If your DEA is configured to run in secure mode, then each app runs as its own user and process isolation is used to protect them. We are moving toward a model of using linux cgroups http://en.wikipedia.org/wiki/Cgroups when on linux, using the warden cgroup wrappers that are already in our source tree.
VM based isolation for a single app is pretty heavy weight, but we have long term plans to provide this for apps that need/desire it. (As opposed to the warden/cgroup work which is a near term project)
Since this is related to the open source for cloud foundry, you can try asking your question on https://groups.google.com/a/cloudfoundry.org/group/vcap-dev
You should get a quick response there!