Is it alright to use Google Compute Engine virtual machines for MySQL DB?
db-n1-standard-2 costs around $97 DB for single Clould SQL instance and replication makes it double.
So I was wondering if its okay to use n1-standard-2 which costs around $48 and the applications will be in Kubernetes cluster and the pods would connect to Compute Engine VM for DB connection. Would the pods be able to connect to Compute Engine VM?
Also is it true that Google doesn't charge GKE Cluster Management Fees when using Zonal Kubernetes cluster? When I check with calculator it shows they don't charge management fees.
This is entirely up to your needs. If you want to be on call for DB failover and replication management, it will definitely be cheaper to run it yourself. Zalando has a lot of Postgres-on-Kubernetes automation that is very good, but at the end of the day who do you want waking up at 2AM if something breaks. I will never run another production SQL database myself as long as I live, it's just always worth the money.
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I am building my own webapp which requires a huge database. I want to build and manage my own Mongo database on AWS rather than using Mongo Atlas. Which will be more cost saving? And whether I should go for Mongo Atlas? What will be its advantage over my own database?
There are pros and cons for both approaches:
Running MongoDB on AWS
Pros:
Complete control over how you run the database and how resources are allocated on the server. This could even be together with an application server on the same EC2 instance depending on your traffic and load. This might help with cost saving if your database is huge but isn't likely to see much traffic.
Cons:
You will be responsible for ensuring database availability and applying security patches as and when they are available. You may also have to setup firewalls and protect the EC2 instance and database in other ways that would be trivial to do on a hosted service like Atlas.
Data sharding and clustering can be a real pain to manage by yourself.
Running on Atlas
Pros:
Completely managed service where you don't have to be concerned about performance optimization or scalability. You pay for the services and Mongodb takes care of the rest.
You can focus on building a great application instead of spending your time on administering the database and the EC2 instance on which the database runs.
Cons:
You will be constrained by the options offered by Atlas. For most use cases this should be fine, but if you really want a specific change, it would be difficult to implement it if Mongodb doesn't already support it as a part of Atlas.
Think running your application on EC2 vs buying a server on-premise and running your application on that.
Being a managed service, costs might also be higher if your database does not see much traffic.
HOSTING yourself: You can get one or more AWS ec2 instances(which are VMs) where you can install and run Mongo DB yourself and manage it like you wanted to, making sure that you spin up more instances when the workload becomes large and there are instances up and running at all times to enable high availability.
Cost (high) - Management responsibilities (lots) - Full MongoDB functionality
MongoDB Atlas is a managed service, you don't need to worry about management tasks like scaling of your database and high availability when a single/more instances die... You pay a very low cost for it - this is run by MongoDb themselves on AWS, Azure, Google cloud;
Cost (low) - Management responsibilities (some) - Full MongoDB functionality
Now AWS has its own Mongo compatible database called DocumentDB - this is also a managed database, so you don't need to worry about scalability, high availability etc. This is only available on AWS so super simple and convinient.
Cost (low) - Management responsibilities (minimal) - Limited MongoDB functionality
i am working on my next project currently which works 100% on mongo,
my past projects worked on SQL + Mongo on which i used AWS RDS + AWS EC2 and could connect them both in AWS internal IP which result me with much faster connection.
Now in mongo there is alot of fancy cloud servers like MLab and MongoDB Atlas which is actually cheaper then AWS.
My concern is that moving back to external DB connection will be slower and more network consuming then the internal connection in RDS
Have anyone experienced in such issue? maybe the different isn't that big as i make it but i need it to be optimized
This depends on your setup. Many of the "fancy" services also host stuff on AWS, so latency is minimal. Some even offer "private environments" or such, so you can hide your databases from public view.
The only thing left to care about is the amount of network traffic. But this will be your problem regardless of your database host. You can test this relatively easily (e.g. get a trial from one of the providers and test for throughput, or raise your own MongoDB docker cluster to use as a test etc) just to get an idea of the performance range you'll be in.
Been working on a web app with a simple database model that only needs CRUD operations, figured MongoDB would be perfect for it. The most important constraints of the project is that it be able to scale from a small amount of users to a large amount. I’ve been looking at the cloud launcher and I’ve noticed that the most popular MongoDB solution advertises a cost of ~$350/mo. This is a surprisingly large amount that makes me consider using cloud sql for my database instead. Is there a better way to deploy MongoDB to GCP that’s more fitted to my use case? I’ve been reading about automatic scaling with kubernetes but I can’t find anything about price. Any and all advice is greatly appreciated
I haven't used mongodb with kubernetes but we do use the cloud launcher solution at work. We use 2 nodes(n1-standard-1) and an arbiter(micro) + 100GB storage on each node which comes up around $100 a month. You would need a replicaset in a production environment so this seems to be a reasonable base cost.
Kubernetes does not provide a lot of advantages over the classic GCE deployment for mongodb compared to a webserver. Setting up a replicaset on kubernetes is a bit more work compared to GCE setup. https://medium.com/google-cloud/mongodb-replica-sets-with-kubernetes-d96606bd9474 and http://blog.kubernetes.io/2017/01/running-mongodb-on-kubernetes-with-statefulsets.html should serve as decent references but wouldn't lower your costs. Scaling nodes would be slightly easier though but does not strictly translate to scaling mongodb.
I have lately been working on a similar solution.
GCP announced that they don't charge for Kubernetes cluster management but only for resources used by it (instances, network ...):
https://cloud.google.com/kubernetes-engine/pricing
In general, databases are high maintenance (data mounts, backups, migrations...), so I would not start running Mongo on Kubernetes right away. You could get there but it will be more complicated than deploying your web app on Kubernetes.
Better to use MongoDB as a service that supports GCP (e.g. MongoDB Atlas), I have done so myself and see a few other companies do that.
If you scale gradually you should be able to control your costs.
The web app itself should be easy to deploy and maintain on Kubernetes.
Is it possible to have an app running at aws EC2 and have it's database running at heroku's postgres?
In case it is, what are the downsides I should consider?
Since heroku is hosted at AWS, is there a way to know where is the location of the machine running my database?
Hosting my app in the same region of the database would help to keep the performance?
I would like to hear some opinions about this, I've been searching the topic without much success.
You can determine the public-facing location of your Heroku DB at any given time with a traceroute ... but there's no guarantee that it'll stay at that location, or that there isn't any internal re-routing going on. You'd probably want to speak directly with Heroku support about ways to make sure your Heroku DB instances are local to your AWS application instances, as that certainly would benefit performance. See if you can find out which availability zone, or at least which major region, they run the DB in, and whether you can "pin" your database instance to a given region/zone.
Amazon's RDS looks OK, but doesn't support PostgreSQL. Please keep nagging them to.
I'd probably just run the DB on AWS if performance wasn't particularly important. Use a raid10 of provisioned IOPS EBS volumes on an EBS-optimized instance and you'll get kind-of-ok performance (but at a really big price); alternately, you can use non-crash-safe ssd-based instance store servers and rely on replication and backups to keep your data safe.
I dont have any experience on Heroku PostgreSQL.
Generally of course you can run your own service on Amazon EC2 and use the managed database services of Heroku.
Downsides might be
nobody guarantees, that Herouku exclusively uses AWS and you probably can't determine the physical Heroku service location within the cloud so you will have to deal with network latencies
in addition to your external traffic fees you'll have to pay for the database traffic unless you talk to a server in the same availability zone in the same region
My suggestion ( without knowing any detail about the pros of Heroku )
Have a look at Amazon RDS if you don't want to run a database server on our own.
http://aws.amazon.com/de/rds/
I am operating around 70 server instances on AWS, both RDS and EC2 for more than a year now and I can't imagine any simpler way to keep your stuff running
Was wondering if anyone out there has any experience in deploying a Zend community app to the cloud (e.g. AWS or similar)?
I'm new to cloud hosting having always been fortunate enough in the past to work for folks who have dedicated servers, my main concern (non-zend specific) is how you manage resilience at the database level? FOr example I would in a traditional setup have 2 boxes running the DB (Mysql) in Master/Slave mode with the master replicating to the slave. Assuming any HD failure of the Master I could swap the DB connection over from the Master to the slave and rebuild master at a later point? is this done differently in the cloud?
Any help/pointers greatly appreciated?
It depends on the type of cloud service that you use. If you're using AWS to get your own virtual machine ( Amazon EC2 ) then it's basically the same as having a dedicated server and you can keep a master slave setup and work them much the same way.
However, if you plan on using Amazon's cloud database service ( Amazon Simple DB ) then you don't have to worry about masters and slaves since Amazon does this for you and makes sure that you always have access to your data. The only thing is that it's in beta.
One of the points of the cloud is to take your mind off the hardware. Amazon worries about that.
You might still want to have two virtual machines in case amazon is doing maintenance that might cause your vm to become unavailable, however, Amazon stresses that it would be highly available and never go down really, so long as you pay.