From what I gather, the only way to use a MySQL database with Azure websites is to use Cleardb but can I install MySQL on VMs provided in Azure Cloud Services. And if so how?
This question might get closed and moved to ServerFault (where it really belongs). That said: ClearDB provides MySQL-as-a-Service in Azure. It has nothing to do with what you can install in your own Virtual Machines. You can absolutely do a VM-based MySQL install (or any other database engine that you can install on Linux or Windows). In fact, the Azure portal even has a tutorial for a MySQL installation on OpenSUSE.
If you're referring to installing in web/worker roles: This simply isn't a good fit for database engines, due to:
the need to completely script/automate the install with zero interaction (which might take a long time). This includes all necessary software being downloaded/installed to the vm images every time a new instance is spun up.
the likely inability for a database cluster to cope with arbitrary scale-out (the typical use case for web/worker roles). Database clusters may or may not work well when a scale-out occurs (adding an additional vm). Same thing when scaling in (removing a vm).
less-optimal attached-storage configuration
inability to use Linux VMs
So, assuming you're still ok with Virtual Machines (vs stateless Cloud Service vm's): You'll need to carefully plan your deployment, with decisions such as:
Distro (Ubuntu, CentOS, etc). Azure-supported Linux distro list here
Selecting proper VM size (the DS series provide SSD attached disk support; the G series scale to 448GB RAM)
Azure Storage attached disks being non-Premium or Premium (premium disks are SSD-backed, durable disks scaling to 1TB/5000 IOPS per disk, up to 32 disks per VM depending on VM size)
Virtual network configuration (for multi-node cluster)
Accessibility of database cluster (whether your app is in the vnet or accesses it through a public endpoint; and if the latter, setting up ACL's)
Backup / HA / DR planning
Someone else mentioned using a pre-built VM image from VM Depot. Just realize that, if you go that route, you're relying on someone else to configure the database engine install for you. This may or may not be optimal for what you're trying to achieve. And the images may or may not be up-to-date with the latest versions, patches, etc.
Of course, what I wrote applies to any database engine you install in your own virtual machines, where a service provider (such as ClearDB) tends to take care of most of these things for you.
If you are talking about standard VMs then you can use a pre-built images on VMDepot for that.
If you are talking about web or worker roles (PaaS) I wouldn't recommend it, but if you really want to you could. You would need to fully script the install of the solution on the host. The only downside (and it's a big one) you would have would be the that the host will be moved to a new host at some point which would mean your MySQL data files would be lost - if you backed up frequently and were happy to lose some data then this option may work for you.
I think, that the main question is "what You want to achieve?". As I see, You want to use PaaS solution with Web Apps or Cloud Service and You need a MySQL database. If Yes, You have two options (both technically as David Makogon said). First one is to deploy Your own (one) server with MySQL and connect to it from the outside (internet side). Second solution is to create one MySQL server or cluster and connect Your application internally in Azure virtual network. WIth Cloud Service it is simple but with Web App it is not. You must create VPN gateway in Azure VM and connect Your Web App to this gateway. In this way You will have internal connection wfrom Your application to Your own MySQL cluster.
Related
I'm struggling with finding out how to properly test stuff on my local PC and then transfer that over to production.
So here is my situation:
I got a project in NodeJS/typescript, and I'm using Prisma in it for managing my database. On my server I just run a MySQL database, and for testing on my PC I always just used SQLite.
But now that I want to use Prisma Migrate (because it's highly recommended to do so in production) I can't because I use different databases on my PC vs on my Server. Now here comes my question, what is the correct way to test with a database during development?
Should I just connect to my server and make a test database there? Use VS Code's SSH coding function to code directly on the server and connect to the database? Install MySQL on my PC? Like, what's the correct way to do it?
Always use the same brand and same version database in development and testing that you will eventually deploy to. There are compatibility differences between brands, i.e. an SQL query that works on SQLite does not necessarily work the same on MySQL, and vice-versa. Even data types and schema definitions aren't all the same between different SQL products.
If you use different SQL databases in development and production, you will waste a bunch of time and increase your gray hair debugging problems in production, as you insist, "it works on my machine."
This is avoidable!
When I develop on my local computer, I usually have an instance of MySQL Server running in a Docker container on my laptop.
I assume any test data on my laptop is temporary. I can easily recreate schema and data at any time, using scripts that are checked into my source control repo, so I don't worry about losing any data. In fact, I feel no hesitation to drop it and recreate it several times a week.
So if I need to upgrade the local database version to match an upgrade on production, I just delete the Docker container and its data, pull the new Docker image version, initialize a new data dir, and reload my test data again.
Every step is scripted, even the Docker pull.
The caveat to my practice is that you can't necessarily duplicate the software if you use cloud databases, for example Amazon Aurora. There's no way to run an Aurora-compatible instance on your laptop (and don't believe the salespeople that Aurora is fully compatible with MySQL; it's not). So you could run a small Aurora instance in a development VPC and connect to that from your app development environment. At least if your internet connection is reliable enough.
By the way, a similar rule applies to all the other technology you use in development. The version of Node.js, Prisma, other NPM dependencies, http and cache servers, etc. Even the operating system might be the source of compatibility issues, but you may have to develop in a Virtual Machine to match the OS to production exactly.
At one past job, I did help the developer team create what we called the "golden image" which was a pre-configured VM with all our software dependencies installed, and we used this golden image for both the developer sandbox VM, and also an AMI from which we launched the production Amazon EC2 instances. So all the developers were guaranteed to have a test environment that matched production exactly. After that, if they had code problems, they could fix it in development and have a much higher confidence it would work after deploying to production.
I have done extensive research, i feel that i have good candidates but i still lack enough knowledge to decide which one i should implement, ideally i would like to hear from someone that actually implemented a solution to a similar problem.
The Problem
Our project consists of a community of distributed nodes (25 nodes). The nods run on Linux computers, and are installed in the typical residential setting (behind a NAT), with wide dispersion geographically and ISP wise.
Our software on the node collects a variety of its own unique data which is logged to MySQL DB on the local host (node) which is not WAN accessible directly. We also have a Web interface for each node that uses the local node DB to allow the local node user to visualize certain data and parameters; this is only accessible on the LAN.
We typically set-up and maintain an open port for SSH from our labs to each node. All remote DB on nodes have the exact same schema but completely different data. We need an automated way to collect all data from all the nodes and get them to our WAN accessible lab servers (Windows 7 servers, but can be Linux if it provide a better solution). We have narrowed the option as follow:
Solutions:
Create a .bat script that sequentially connect to each node over SSH to import data.
Use the web interface that runs on each node to periodically query the local db then save that data to a central MySQL server. I know i can connect to two db in PHP. seems to be doable here.
Use the MySQL supported “slave-master” replication setup which will duplicate all remote databases on the server.
Use the MySQL supported federated engine setup which will link local tables to remote ones.
Questions:
Are all these viable solutions?
Any major cons i should be aware of for the viable ones?
is there better solutions available (paid or otherwise) ?
Simple question can a Java service layer running on Tomcat7 on a host machine connect to persistent data store (mySQL) running inside a virtual box with portforwarding? I want to know if the hibernate or Jdbc connection strings from host machine work if mySQL server is installed inside a VirtualBox.
Also if it does work can I expect behavioral deviations in terms of speed and connection pooling if everything is packaged into one single system and deployed in a real world web server in a single enviroment?
The short answer is yes, it is possible and will work. You will likely have to play with the firewall settings on your virtual box instance. You don't specify OS, so it's hard to tell you what exactly you'll need to tweak.
As far as deploying this in a real-world environment, if you mean production, you probably should NOT do that. This is a great setup to build on, but not something I would run in production.
To be clear, there won't be any issues behaviorally speaking, it will act as MySQL always acts, but it will absolutely be slower than running it on 'bare metal' -- how much slower will vary based on hardware, workload, etc. and it is generally not a great design for a production deployment..
We have a Java EE application (EAR file deployed on JBoss, MySQL, MongoDB) which we would like to deploy on an Amazon EC2 instance. I have several questions regarding deployment best practices.
What is the most commonly used Linux AMI which we can rely on for a robust deployment (There are so many Linux variants, and I am not sure which AMI is commonly used, is it Fedora, CentOS, Red Hat, SUSE ...)
How do we handle production upgrades (EAR file modifications or schema upgrades). Are there any tools which are available to handle this installation or rollback of these changes.
What kind of data backup capability is available for the database?
Should I rely on Amazon RDS for MySQL support?
How should I handle support for MongoDB?
This is the first time, I am hosting an web-app and would appreciate some inputs on how to manage the production instance.
I agree with Mark Robinson's answer: Use whichever Unix variant you're most comfortable with. It may pay to pick one with decent cloud support. For my site I use Ubuntu.
I have a common image which is the base of every version deploy I do. I have www.mysite.com pointing to an Elastic IP so I can decide which instance it goes to. The common image has all the software I need installed (Postgres/Postgis/Tomcat/etc) but the database and web server data folders and symlinked to Elastic Block Store (EBS) instances.
When it comes time to do a deploy I start a new instance up, freeze and snapshot the EBS volumes on production and make new volumes. I point my new instance at the new volumes and then install whatever I need to onto that. Once I've smoke tested everything successfully I can switch the Elastic IP to point to the new instance and everything keeps on going.
I'll note that I currently have the advantage where only I can modify the database; no users can. This will become a problem shortly.
If you use the XFS filesystem on top of the EBS volume then you can tell XFS to freeze the file system (so no updates happen) then call the EC2 api to snapshot the volume then unfreeze the file system. The result is that the snapshot is taken quickly and sent to S3. I have a nightly script which does this.
If RDS looks like it will suit your needs then use it. Amazon is building lots of solid tools quickly and this will ease your scalability issues if you have any.
I'm sorry, I have no idea.
Good question!
1) I would recommend going with whatever Linux variant you are most comfortable with. If you have someone who is really keen on CentOS, go with that. Once you have selected your AMI, take it and customize it by configuring how you want it. Then save that AMI as you base-layout. It will make rolling out new machines much easier and save your bacon if EC2 goes down.
2) Upgrades with EC2 can be tres cool. Instead of upgrading a live system, take your pre-configured AMI, update that and save that AMI as myAMI-1.1 (or whatever). That way, you can flip over to the new system almost instantly AND roll back to a previous version in case something breaks. You can also back-up DB instances to S3. It's cheap at about $0.10/GB/Month.
3) It depends where you are storing your DB. If you are storing it on your EC2 instance you are in trouble. The EC2 instances have no persistence storage. So if your machine crashes, you lose everything. I'm not familiar with Amazon DB system but you should also look into Elastic Block Store. It's basically an actual hard-drive you can write to. When you want to upgrade your schema, do a full DB dump to S3 and then do an upgrade of your actual schema. If something goes wrong, you can pull the previous version out of S3.
4) & 5) I have never used those so I can't help you.
What is the most commonly used Linux AMI which we can rely on for a robust deployment (There are so many Linux variants, and I am not sure which AMI is commonly used, is it Fedora, CentOS, Red Hat, SUSE ...)
How do we handle production upgrades (EAR file modifications or schema upgrades). Are there any tools which are available to handle this installation or rollback of these changes.
What kind of data backup capability is available for the database?
Should I rely on Amazon RDS for MySQL support?
How should I handle support for MongoDB?
Any Linux AMI will do the job, what you need is a JRE only. (assuming development work not required). If you need to monitor the JVM behavior then get JConsole installed.
Easiest and painless way is to SSH into the local home directory, transfer the updated class file/EAR file (depends the number of changes applied) and copy and replace into the Tomcat deployment directory, restart apache. (make sure you tested locally before upload to production).
Depends on which database you are using, if you are using MySQL then just do scheduled backup that writes to your home directory so that from time to time you could SSH in and download a copy for backup purpose.
I would not consider reply on Amazon RDS for MySQL support due to 2 reasons: MySQL is small enough and manageable, and also I would want to have total complete control of the database and why pay for more when you can do it yourself FOC?
The usage of MongoDB should be align with the purpose of your application and benefits you gain from that. I would recommend you use MongoDB for static data retrieval like state, country, area etc... where MySQL to be use for transaction data only.
If you can live with deploying your Java EE application on TomEE instead of JBoss, Boxfuse does what you want.
For you Java EE application you literally only have to execute (TomEE uses war files instead of ear files):
boxfuse run my-tomee-app-1.0.war -env=prod
This will
Create AMI containing TomEE and your application ready to boot
Create an Elastic IP or ELB
Create a security group with the correct ports defined
Create an auto-scaling group
Launch your instance(s)
Any subsequent update will be done as a zero downtime blue/green deployment.
More info: https://boxfuse.com/blog/javaee-aws
Is there an easy way to setup an environment on one machine (or a VM) with MySQL replication? I would like to put together a proof of concept of MySQL replication with one Master write instance and two slave instances for reads.
I can see doing it across 2 or 3 VMs running on my computer, but that would really bog down my system. I'd rather have everything running on the same VM. What's the best way to proof out scalability solutions like this in a local dev environment?
Thanks for your help,
Dave
I think to truly test MySQL Replication it is important to do so in realistic constraints.
If you put all the replicate nodes under one operating system then you no longer have the bandwidth constraint, the data transfer speed would be much higher that what you would get if those replicate DBs are on different sites.
Everything under one VM is a shortcut to configurations, for instance it does not make you go through the configuration of the networking.
I suggest you use multiple VMs, even if you have to put them under one physical machine, you can always configure the hypervisor to make the packets go through a router, in which case the I/O will be bound by whatever the network interface has as throughput.
I can see doing it across 2 or 3 VMs
running on my computer, but that would
really bog down my system.
You can try and make a few VMs with JeOS (Just Enough OS) versions of the operating system you want. I know Ubuntu has one and it can boot on 128 RAM, which makes it convenient to deploy lots of cloned VMs under one physical machine without monster RAM.
Next step would be doing the same thing on a cloud (Infrastructure as a Service, IaaS) provider, and try your setup on different geographical sites.
If what you're testing is machine-to-machine replication, then setting up multiple VMs on a virtual private network would be the correct environment to test it. If you use Ubuntu Server, you don't have to install more than you actually need -- just give the VMs enough space for a base install + MySQL + your data. Memory usage can be as little as 256MB per VM. All you have to do is suspend or shutdown the VMs when you're not running a full-up test.
I've had situations where I was running 4 or more VMs simultaneously on my workstation, either for development or testing purposes -- it's not that taxing unless you're trying to do video rendering in each VM.