I am planning to use Azure VMSS for deploying a set of spring boot apps. I am planning to create a custom linux VM image with all the required softwares/utilities as well as the required directory structure and configure this image in VMSS. We use jenkins as CI/CD tool and Git as source code repo. What is the best way to build and deploy these spring boot apps on VMSS?
I think one way is to write a custom script extension which downloads code from Git repo and then starts these spring boot apps. I believe this script will then get executed every time a new VM is provisioned.
But what about cases where already multiple VMs are running on top of minimum scale instance count. I believe a manual restart will not trigger the CSE script to run on these already running VMs right?
Could anyone advise the best way to handle this?
Also once a VM is deallocated due to auto scale down, what is the best/cost optimal way to back up the log files from VM to storage (blob or file share)?
You could enable Automatically tear down virtual machines after every use in the organization settings/project setting >> agent pool >> VMSS agent pool >> settings. Then, a new VM instance is used for every job. After running a job, the VM will go offline and be reimaged before it picks up another job. The Custom Script Extension will be executed on every virtual machine in the scaleset immediately after it is created or reimaged. Here is the reference document: Create the scale set agent pool.
To back up the log files from VM, you could refer to Troubleshoot and support about related file path on the target virtual machine.
Related
I'm preparing to get in to the world of cloud computing.
My first question is:
Is it possible to programmatically create a new, or duplicate an existing VM from my server?
Project Background
I provide a file processing service, and as it's been growing I need to offer a better service.
Project Requirement
Machine specs:
HDD: Min 16gb
CPU: Min 1 core
RAM: Min 2
GB GPU: Min CUDA 10.1 compatible
What I'm thinking is the following steps:
User uploads a file
A dedicated VM is created for that specific file inside Google Cloud Compute
The file is sent to the VM
File is processed using a Anaconda environment
Results are downloaded to local server
Dedicated VM is removed
Results are served to user
How is this accomplished?
PS: I'm looking for resources and advice. Not code.
Your question is a perfect formulation of the concept of Google Cloud Run. At the highest level concept, you create a Docker image (think of it like a VM) and then register that Docker image with GCP Cloud Run. When a trigger occurs, GCP will spin up an instance of that Docker container and pass in information about the cause of that trigger (a file created in GCS or a REST request or others ...). What you do in your container is up to you. You have full power of the Linux environment (under Docker) to do as you like. When your request ends, the container is spun down. You are only billed for the compute resources you use. If your container (VM) isn't being used, you pay nothing until the next trigger.
An alternative to Cloud Run is Cloud Functions. This is a higher level abstraction where instead of providing a Docker container, you provide the body of a function (JavaScript, Java, Python or others) and the request is passed to that function when a trigger occurs. Which you use is mostly personal choice (you didn't elaborate on "File is processed").
References:
Cloud Run
Cloud Functions
Cloud build uses worker pool of VM and that is not able to access my on-prem Compute Engine resources So, is there any way to run cloud build on my own VM or any solution for these?
While waiting for the custom worker-pool feature you mentioned in your previous question to become available to public, you can use the custom builder remote-builder.
You'll need to first build the builder image that you'll be able to use then in your Cloud Builds steps. When using the remote-builder image, the following will happen:
A temporary SSH key will be created in your Container Builder
workspace
A instance will be launched with your configured flags
The workpace will be copied to the remote instance
Your command will be run inside that instance's workspace
The workspace will be copied back to your Container Builder
workspace
The build steps using this builder image will therefore run on a VM instance in your project's network and will be able to access other resources, provided your network configuration allows it.
Edit: The cos image used in the example cloudbuild.yaml file seems to include it so you'd be able to run it directly. In case you'd like to customize your instances with specific software, you have several options:
you can create an instance template (based on a custom image that includes the software or with a startup script that will install it at boot time) and specify that instance template in INSTANCE_ARGS in your cloudbuild.yaml.
you can use a standard image and just pass the startup script installing the software as INSTANCE_ARGS.
you can install it within a shell script executed in your build step.
Why can't you just fix the access issue? You can configure cloud build to create build workers within your VPC within your cloud infrastructure:
See the following video which explain how this works:
https://youtu.be/IUKCbq1WNWc?t=820
Hope this helps.
We have a load balanced setup in AWS with two instances. We do pretty frequent code updates, utilizing SVN. I need to know how easy it is to update the code changes across all the instances in our cluster. Can we simply do 'snapshots' and create new volumes each time for the instances?...or?...
I would not do updates via EBS snapshots. Think of EBS volumes as a hard disk - you would not change your harddisk if you have an update for your software.
As you have your code in a version control system, code updates should be quite simple like logging in to your (multiple) servers and doing a git pull or svn update. This should fetch the latest code files from your servers. Depending on the type of application you would have to do some other tasks afterwards, running build scripts, emptying cache etc.
The problem is that this kind of setup does not scale well. If you have n servers, you will have to login and do this command n times. Therefore it makes sense to look into some remote management tools that you can use in one step. With a lot of these tools, you also get a complete configuration management stack: you define a set of recipes or tasks (like installed packages, configuration files, fetch the latest code, necessary build steps) for each of your servers, and when you boot up a new server it fetches the lastest version of its configuration and installs itself.
Popular configuration management tools include Puppet or Salt. Both tools have remote execution included which should make your task to publish your code base easier, you would only have to fire one command on your master server and it automatically executes this task on all its minions / slave servers.
I am currently using AWS ElasticBeanStalk and I was curious as to how (as in internally) it knows that when you fire up an instance (or it automatically does with scaling), to unpack the zip I uploaded as a version? Is there some enviroment setting that looks up my zip in my S3 bucket and then unpacks automatically for every instance running in that environment?
If so, could this be used to automate a task such as run an SQL query on boot-up (instance deployment) too? Are these automated tasks changeable or viewable at all?
Thanks
I don't know how beanstalk knows which version to download and unpack, but running a task on start-up is trivial. Check out cloud-init, a tool written by Ubuntu that's now packaged in Amazon Linux. It allows you to pass arbitrary shell scripts into the UserData section of the instance configuration, and those shell scripts will run on startup.
It's a great way to bootstrap instances on startup, which avoids the soul-sucking misery of managing AMIs.
A quick (possibly non-applicable) warning: If you're running a SQL query on a database that lives on the beanstalk AMI, you're pretty much guaranteed to lose your database at some point. Those machines are designed to be entirely transient. Do not put databases on them. See this answer for more details.
Since your goal seems to be to run custom configuration tasks, the answer is yes, there is a way to do that. You can define custom actions in an .ebextensions file packaged with your app. For example, you can configure a command to run every time a new machine is deployed:
http://docs.aws.amazon.com/elasticbeanstalk/latest/dg/customize-containers-ec2.html#linux-commands
Heya,
Quick question.
I've got multiple instances on EC2 with a load balancer between them. I use an SVN app that used to push to my live env. at will.
With the multiple EC2's, how would I push a codebase to all of them at once?
Any thoughts/links would be appreciated.
There are a few different ways to do this.
If You Are Using Elastic Load Balancers
Write a script that:
Removes a machine from the pool
Updates the SVN repository
Re-adds the machine to the pool
Repeats for any additional machines
You could also get fancy and remove one machine, update it, remove all other machines and update them, if you're concerned about consistency.
If You Are Using a Custom Load Balancing Application
Look into Capistrano. You don't need to use it with Ruby/Rake -- you can write custom cap files that can do parallel deploys.
How about vlad or fabric for code deployment.
We use Scalr. It is available as a service (Scalr.net) or you can run it yourself (it is Open Source - though the source in the googlecode repository is sometimes a little behind the version the service uses).
Basically, Scalr has a global scripting feature whereby you can specify a script (e.g. bash, PHP, anything with #!bang) and trigger it to be run on all instances of a given 'role' (e.g. web instance). In our case we have a script that just does svn checkout or svn update as appropriate. Scalr supports periodic scheduling of scripts, so in the dev environment I run it every 5 mins to keep dev in synch with SVN, but obviously I manually trigger it for production.
(I have the script taking a param to specify the SVN branch to use)