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I have free credit account on Google Cloud Platform. I want to access a GPU for training my deep learning project. I even submitted different quota requests, but every time it got rejected. Do I need to pay some money to GCP to access a GPU? How can I do that? Here is the reply that I got from Google every time,"We have received your quota request for deep-learning-261006.
Unfortunately, we are unable to grant you additional quota at this time. If
this is a new project please wait 48h until you resubmit the request or
until your Billing account has additional history.
Your Sales Rep is a good Escalation Path for these requests, and we highly
recommend you to reach out to them."
From the docs:
Program coverage
You can't have more than 8 cores (or virtual CPUs) running at the same time.
You can't add GPUs to your VM instances.
You can't request a quota increase. For an overview of Compute Engine quotas, see Resource quotas.
You can't create VM instances that are based on Windows Server images.
You'll be able to add GPUs to your VM instances by upgrading your account. This can be done by clicking on the activate button in the cloud console. Please note that your credit card on file is charged for resources you use in excess of what's covered by any remaining credit.
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I'm being charged for "E2 Instance Core running in Seoul". The billing report says the related service is "Compute Engine", but there is no VM instance running from Compute Engine. I can't track the cause of the bill.
Not sure if it's related, but I created 4 Cloud Run services with 0 minimum instances auto-scaling settings and runs probably 0~5 mins per day. But the usage of the "E2 Instance Core running in Seoul" is 84 hours for 7 days. So I don't think that's the cause.
Why am I being charged for "E2 Instance Core running in Seoul"?
As confirmed in the comments, when using a VPC Serverless Connector, this connector is charged as e2-micro instances as stated by pricing docs.
This is the reason why you see these charges even if you're not having a VM in GCE.
Also to confirm, you can use the following tip from the docs:
You can view your Serverless VPC Access costs in the Cloud Console by filtering your billing reports by the label key serverless-vpc-access.
There are two possiblities:
Resources were created in the wrong region due to a bug - contact billing support and explain everything. If they confirm that it's a bug you can file it on IssueTracker.
Your account has been compromised - in this case I can recommend reading some documentation:
Compromised credentials
Identify and secure compromised accounts
Check the login audit log and see for any unathorised / suspicious looking logins and audit logs for entries related to the resources located in Seoul. It may be in a different project (which would support "being hacked" version).
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Currently having more than twenty AWS accounts and under each account having 6-10 On-demand EC2 instances both Linux and windows of different sizes and types ,altogether around 100 instances . So looking for cost saving options with various options such as Compute Saving Plan, EC2 Saving Plan, Reserve Instance however unable compare of all different options and their estimates side by side.
Though compute and EC2 estimates are given as recommendation through Billing->Cost Explorer but you need to go through each account , then select different option e.c Compute or EC2 saving , then payment options ,then tenure 1 or 3 years and it display estimates .
I want to see all 100 instance and their prices on one page if possible as below
Under Compute saving plan for 1 and 3 year with full , partial or no upfront payment
under EC2 saving plan for 1 and 3 years with full , partial or no upfront payment
Under reserved instance for 1 and 3 year with full , partial or no upfront payment
is there any easier way to get this done ?
This is probably the best you can get in terms of what you are looking for:
https://calculator.s3.amazonaws.com/index.html
From What is AWS Compute Optimizer? - AWS Compute Optimizer:
AWS Compute Optimizer is a service that analyzes the configuration and utilization metrics of your AWS resources. It reports whether your resources are optimal, and generates optimization recommendations to reduce the cost and improve the performance of your workloads. Compute Optimizer also provides graphs showing recent utilization metric history data, as well as projected utilization for recommendations, which you can use to evaluate which recommendation provides the best price-performance trade-off. The analysis and visualization of your usage patterns can help you decide when to move or resize your running resources, and still meet your performance and capacity requirements.
Compute Optimizer provides a console experience, and a set of APIs that allows you to view the findings of the analysis and recommendations for your resources across multiple AWS Regions. You can also view findings and recommendations across multiple accounts, if you opt in the management account of an organization. The findings from the service are also reported in the consoles of the supported services, such as the Amazon EC2 console.
https://ec2instances.github.io/ tiny opensource tool that pulls pricing data from AWS json-API and presents it as a table.
Disclaimer: I've built this (for myself)
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I have one GCP project and multiple users/service accounts that use the google cloud APIs (e. g. Cloud text-to-speech, Cloud speech-to-text etc.). In the metrics overview for each API it is possible to see how often an API has been called by whom, but for the billing overview, it is not possible to identify which user/service account caused a specific amount of costs. So my question is: Is it possible to identify the different users/service accounts in the actual billing costs?
Normally, one would use labels to distinguish between different users, but unfortunately labels are not supported for those APIs (see list of currently supported services: https://cloud.google.com/resource-manager/docs/creating-managing-labels#label_support)
Additionally, each user/service account has a separate Cloud run instance connected to it, that runs a server listening for incoming requests and forwards them to the corresponding API. Would this approach somehow facilitates the mapping from user to costs in one GCP project?
Metrics and billing are 2 different things.
Google provides metrics to follow and understand the usage of your service in your project
The billing is at the project level, whatever the user/service account, YOU pay, it's not the concern of Google of how will you rebill the service to your users.
So, here the solution is to use the metrics to get the data and then to equally distribute the cost according to the APIs usages.
Similarly, Cloud Run label will help you to have details in the BigQuery billing export, but google will charge you for all your services.
Ultimately, if the services/customers are independent, you can imagine to create a project per customer, and thus to have 1 free tiers per project (when applicable) and, above all, 1 billing per project, and thus per customer!
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I want to host my website (PHP/MySQL) on a cloud platform. For sure, my website is new and I don't think that there will be too much traffic.
So, I tried to compare the lowest config costs of cloud services between GCP and AWS. The lowest config cost according Google Cloud Platform pricing calculator is as follows:
Google Compute Engine (f1-micro): $4.09
Google Cloud SQL (D0 Instance): $11.30
Datastore (1GB): $0.18
Total: $15.57
(For details, have a look on this link: https://goo.gl/wJZikT )
Meanwhile, the lowest config cost according AWS Pricing calculator is:
Amazon EC2 (t1.micro): $14.64
Amazon RDS (db.t1.micro with 1GB of storage): $18.42
Amazon S3: $0.11
Total: $33.17
(For details, have a look on this link http://goo.gl/Pe7dFt )
My question is: how can it be that there is a big difference in the cost of cloud services between google cloud platform and AWS? Is there any thing wrong in my estimation? If it is the case please share with me a link on the configuration of the minimal configuration on AWS...
Thanks.
2 main reasons for the difference:
Google micro VM uses a shared core and not a dedicated one. Cores seem to be the most expensive part of a VM if you look at prices for both AWS an GCE
Google provide their sustained usage discount on a monthly basis (30% effective discount per month), while amazon forces you to commit for a year with upfront payment to get any discount.
Both factors above allow you to have a lower cost for the Google VM.
I have tried VMs on GCE with shared cores and did not have any problems. If you use Google monitoring, you can actually track how much the core being shared is affecting you using the CPU steal metric. This article from stackdriver explain it really well.
Side note: stackdriver has been since acquired by Google and is what Google use for monitoring the VMs.
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I'm planning to move my Website which is using multiple wordpress to Amazon Services. However, my daily vistors are about 22,000 and sometimes goes to over 90k and the web crashes! However, the hosting company charge me nearly $100 including support without support it would cost $50. the average bandwidth is about 400GB.
Can I ask please how much will it cost me? and how I can start with Amazon Services?
Kind regards
Start out by looking at the different types of hosting that Amazon offers and which one will be the correct fit for your site. Amazon's EC2 (Elastic Cloud Computing) is the servers that you can get hosted in the cloud.
Depending on how much storage space and bandwidth, the costs differ. They have a helpful cost guide on their EC2 page. They offer different pricing for the different types of servers you need. They have on demand spot instances which can be brought up and down on the fly. If you need a server to be running constantly you can put a down payment and have a reserved instance to provide the server.
You can calculate your fees depending on your current usage from the tools AWS provides. http://calculator.s3.amazonaws.com/calc5.html
This is also a good article for getting started with using WordPress under AWS.
http://wp.tutsplus.com/tutorials/scaling-caching/deploy-your-wordpress-blog-to-the-cloud/
AWS also provides a Free Tier of services provided you stay under a certain amount of usage. That is detailed at http://aws.amazon.com/free/ . I also found this YouTube video on setting up EC2 instances very helpful. http://www.youtube.com/watch?v=JPFoDnjR8e8 . From what I understand, unless your WordPress install gets a crazy number of hits you will probably fall under the Free Tier.