vania-janet/multiturn-rag-retrieval-data huggingface dataset:
[Provisioning public instances](https://cloud.ibm.com/docs/virtual-servers?topic=virtual-servers-ordering-vs-public) Provision public instances with various options 
 [Provisioning transient instances](https://cloud.ibm.com/docs/virtual-servers?topic=virtual-servers-ordering-vs-transient) Provision transient instances with various options 
 [Provisioning reserved capacity and instances](https://cloud.ibm.com/docs/virtual-servers?topic=virtual-servers-provisioning-reserved-capacity-and-instances) Provision reserved capacity and instances with various options 
 [Provisioning dedicated hosts and instances](https://cloud.ibm.com/docs/virtual-servers?topic=virtual-servers-dedicated-hosts-and-dedicated-instances) Provision private instances or dedicated instances on dedicated hosts 







 Next steps 

After your virtual server is provisioned and available to use, you can configure your virtual servers by using the IBM Cloud console. For more information, see [Configuring virtual servers](https://cloud.ibm.com/docs/virtual-servers?topic=virtual-servers-configuring-virtual-servers).
Then, you can set up a serverless programming model such as Red Hat™ OpenShift™ Serverless™ to provide a simplified programming model with a REST interface to query your trained model to produce a prediction.





 Setting up your edge solution with Satellite 

While you can set up many possible solutions to the challenges of your edge environment, you can use Satellite to provide a consistent, scalable experience across environments. An example setup is as follows.



1. Set up machine learning and model training for your data.
2. Deploy Satellite with a serverless component to your edge environment.
3. Run model inferencing at the edge.





 Step 1: Set up machine learning and model training for your data 

As an AI model developer, you prepare your edge data with machine learning and AI tools in IBM Cloud. Before you begin, you must have access to Watson Studio and Machine Learning instances, such as in an IBM Cloud account or through IBM Cloud Pak for Data.



1. Upload the training data to [IBM Cloud Object Storage](https://cloud.ibm.com/docs/cloud-object-storage?topic=cloud-object-storage-getting-started-cloud-object-storage).
2. Use [Watson Studio](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/data-science.html) and [Machine Learning](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/ml-overview.html) to pull the training data from IBM Cloud Object Storage, analyze the data, and train a model with TensorFlow, Keras, SciKit-Learn, or another popular machine learning algorithm.



The trained model is saved back to IBM Cloud Object Storage, so that the data does not take up storage space in your edge environment.





 Step 2: Deploy Satellite with a serverless component to your edge environment 

As the edge environment system administrator, you enable a serverless tool to simplify model inferencing at the edge.



1. [Create a Satellite location](https://cloud.ibm.com/docs/satellite?topic=satellite-locations) on your edge computing infrastructure.
For more information, see [Reconfiguring an existing virtual server](https://cloud.ibm.com/docs/virtual-servers?topic=virtual-servers-reconfiguring-virtual-servers).





 How many hourly virtual servers can I start? 

The number of instances that you can run depends on the maturity level of your account. By default, an account older than 45 days has a limit of 20 instances that can run on public virtual servers, dedicated virtual servers, and bare metal servers, at any time. A newer account has a smaller limit. If you would like to increase your limit, contact support about what you are doing and how many concurrent instances you might need.





 How am I billed for bandwidth for my hourly virtual servers? 

Hourly virtual billing is broken down for inbound and outbound traffic. All inbound traffic to your virtual server is free of charge. Outbound traffic is metered and charged per GB, with totals assessed at the end of your billing period.





 What happens to my data when my portable storage is deleted? 

Virtual server instance SAN is similar to file storage. Virtual server instance disks are just files on an NFS share that Xen presents to the instance as a block device, that is, a hard disk drive. When you delete an instance SAN disk, you delete the file, after which undelete is not possible. Any pointers to the data on that volume are removed, and the data becomes inaccessible. If the physical storage is reprovisioned to another account, a new set of pointers is assigned. A new account can't access any data that was on the physical storage. The new set of pointers shows all 0's. When new data is written to the volume or LUN, any inaccessible data that still exists is overwritten.





 Can I use a Red Hat Cloud Access subscription to create a virtual server? 

Yes. When you import an image, you can specify that you provide the operating system license. For more information, see [Use Red Hat Cloud Access](https://cloud.ibm.com/docs/image-templates?topic=image-templates-using-your-own-os-license-or-subscription).
Windows server 2022
: IBM Cloud® server software now supports Windows® server 2022 as an OS option for bare metal servers. For more information, see the Bare metal servers tab in [Supported operating systems for IBM Cloud® server software](https://cloud.ibm.com/docs/bare-metal?topic=bare-metal-about-softwaresupported-operating-systems-for-ibm-cloud-servers).







 December 2021 



 02 December 2021 

Custom image template add-ons
: Custom image templates now support the following add-ons. For more information, see the supported add-ons section in [About bare metal custom image templates](https://cloud.ibm.com/docs/bare-metal?topic=bare-metal-getting-started-bm-custom-image-templatesbm-image-template-supported-addons).



* McAfee (free license add-on)
* MySQL (free license add-on)
* Microsoft SQL Server
* R1Soft client



: You can now migrate a bare metal server by using add-on software such as cPanel, MS SQL Server, Plesk, or R1Soft Backup Agent. For more information, see [Migrating bare metal servers with add-on software](https://cloud.ibm.com/docs/bare-metal?topic=bare-metal-bm-migrate-with-add-on-software).







 October 2021 



 05 October 2021 

Intel Xeon 8260 CPU
: You can now select the Intel Xeon 8260 CPU when you provision a bare metal server. For more information, see [Bare metal server options](https://cloud.ibm.com/docs/bare-metal?topic=bare-metal-about-bmbm-cascade-lake-support).







 February 2021 



 01 February 2020 

25 Gbps port space is now available
: You can now use 25 Gbps port speed on select Cascade Lake processor servers.
Architecture flow diagram of IBM Analytics Engine





 Key concepts 

With IBM Analytics Engine serverless instances, you can spin up Apache Spark clusters as needed and customize the Spark runtime and default Spark configuration options.

The following sections describe key concepts when provisioning serverless instances.



 IBM Analytics Engine service instance 

An IBM Cloud® service is cloud extension that provides ready-for-use functionality, such as database, messaging, and web software for running code, or application management or monitoring capabilities. Services usually do not require installation or maintenance and can be combined to create applications. An instance of a service is an entity that consists of resources that are reserved for a particular application or a service.

When you create an IBM Analytics Engine from the catalog, you will give the service instance a name of your choice, select the default Spark runtime you want to associate with the instance and provide the default Spark configuration to use with the instance. Additionally, you need have to specify the Instance home, which is the storage attached to the instance for instance related data only.

Note:



* When you create an IBM Analytics Engine service instance, no costs are incurred unless you have Spark applications running or the Spark history server is accessed.
* Costs are incurred if IBM Cloud Object Storage if accessed through public endpoints, and when you enable forwarding IBM Analytics Engine logs to IBM Log Analysis.
* There is a default limit on the number of service instances permitted per IBM Cloud® account and on the amount of CPU and memory that can be used in any given IBM Analytics Engine service instance. See [Limits and quotas for Analytics Engine instances](https://cloud.ibm.com/docs/AnalyticsEngine?topic=AnalyticsEngine-limits). If you need to adjust these limits, open an IBM Support ticket.
* There is no limit on the number of Spark applications that can be run in an IBM Analytics Engine service instance.







 Default Spark runtime 

You can select which Spark version to use when the instance is provisioned. Currently, you can choose between Spark 3.1 and Spark 3.3. If you don't select a Spark runtime version, Spark 3.1 is taken by default.

The runtime contains only open source Spark binaries and is configured to help you to quickly get started to create and run Spark applications in the instance.
crn:v1:staging:public:ibmanalyticsengine:us-south:a/XXXXX:XXXXX::
GUID: XXXXX
Location: us-south
Service Name: ibmanalyticsengine
Service Plan Name: standard-serverless-spark
Resource Group Name: Default
State: active
Type: service_instance
Sub Type:
Created at: 2021-01-06T07:49:12Z
Created by: XXXXX
Updated at: 2021-01-06T07:51:01Z
Last Operation:
status create succeeded
Message Started create instance operation
Show more

The response includes the GUID and the provisioning state of your instance.

Note that the returned state create succeeded indicates that the provision request was successfully accepted. However, in order to run applications, the instance needs to move to active state. Track the status of the instance readiness before performing any operation on the instance. See [Tracking instance readiness](https://cloud.ibm.com/docs/AnalyticsEngine?topic=AnalyticsEngine-provisioning-serverlessinstance-readiness).







 Accessing instance details by using the IBM Cloud REST API 

You need the ID of a IBM Analytics Engine serverless instance to get the details of the instance, which include the GUID and the provisioning state of the instance for example.

To get the details of an instance:



1. List all of the created serverless instances in the resource group your account:

GET <resource-controller-url>/v2/resource_instances

Example of a request:

curl -X GET https://resource-controller.cloud.ibm.com/v2/resource_instances? resource_plan_id=8afxxxx-xxxx-xxxx-xxxx-946d843xxxx -H "Authorization: Bearer <>"

Example response:

{
"rows_count": 1,
"next_url": null,
"resources": [{
[-r, --rotation]



 Example 

The example shows how to use the command and the results. If the service has no results to the query, an empty array ([]) will be returned.,

 update the instance policy and set the allowed network to public-and-private
$ ibmcloud kp instance policy-update allowed-network --enable --network-type public-and-private

Updating instance policy...
OK

 list the instance policies
$ ibmcloud kp instance policies

Retrieving policy details for instance: a192d603-0b8d-452f-aac3-f9e1f95e7411...
OK
Created By user id ...<redacted>...
Creation Date 2020-06-22T16:17:52Z
Last Updated 2020-06-22T16:17:52Z
Updated By user id ...<redacted>...
Policy Type allowedNetwork
Enabled true
Network Allowed public-and-private

 disable the instance allowed-network policy
$ ibmcloud kp instance policy-update allowed-network --disable

Updating instance policy...
OK

 list the instance policies - the policy exists and it's disabled
$ ibmcloud kp instance policies

Retrieving policy details for instance: a192d603-0b8d-452f-aac3-f9e1f95e7411...
OK
Created By user id ...<redacted>...
Creation Date 2020-06-22T16:17:52Z
Last Updated 2020-06-22T16:20:08Z
Updated By user id ...<redacted>...
Policy Type allowedNetwork
Enabled false
Network Allowed public-and-private

 list the instance policies and show the output as JSON
$ ibmcloud kp instance policies --output json

[
{
"createdBy": "user id ...<redacted>..."
Understanding your responsibilities when using IBM Analytics Engine serverless instances 

Learn about the management responsibilities and terms and conditions that you have when you use IBM Analytics Engine serverless instances. For a high-level view of the service types in IBM Cloud® and the breakdown of responsibilities between the customer and IBM for each type, see [Shared responsibilities for IBM Cloud offerings](https://cloud.ibm.com/docs/overview?topic=overview-shared-responsibilities).

Review the following sections for the specific responsibilities for you and for IBM when you use IBM Analytics Engine serverless instances. For the overall terms of use, see [IBM Cloud® Terms and Notices](https://cloud.ibm.com/docs/overview/terms-of-use?topic=overview-terms).



 Incident and operations management 

Incident and operations management includes tasks such as monitoring, event management, high availability, problem determination, recovery, and full state backup and recovery.



Table 1. Responsibilities for incident and operations
The rows are read from left to right. The first column describes the task that a the customer or IBM might be responsibility for. The second column describes IBM responsibilities for that task. The third column describes your responsibilities as the customer for that task.

 Task IBM responsibilities Your responsibilities 

 IBM Analytics Engine instance administration <br><br> * Provide infrastructure operating system (OS), version, and security updates.<br> * Clean up all instance resources.<br> * Track hardware issues on running cluster.<br><br><br> <br><br> * Create an instance using the provided API, CLI or console tools.<br> * Delete a service instance using the provided API, CLI or console tools.<br> * Customize a service instance using the provided API or CLI.<br> * View or change the instance configuration using the provided API, CLI or console tools.<br><br><br>
[Deploy one VSI](https://cloud.ibm.com/docs-content/v1/content/f84e2238288b7f0355715a4c355609ce7ac48fb0/solution-tutorials/images/solution62-vpc-scaling-dedicated/one_vsi.svg)

Deploy one VSI

As the load increases, you may need more instances to serve the traffic. You may configure a public load balancer for the frontend app and a private load balancer for the backend app to equally distribute incoming requests across instances. With a load balancer, you can configure specific health checks for the pool members associated with instances.

Zoom

![Deploy multiple VSIs](https://cloud.ibm.com/docs-content/v1/content/f84e2238288b7f0355715a4c355609ce7ac48fb0/solution-tutorials/images/solution62-vpc-scaling-dedicated/multiple_vsi.svg)

Deploy multiple VSIs

An instance template is required before you can create an instance group for auto scaling. The instance template defines the details of the virtual server instances that are created for your instance group. For example, specify the profile (vCPU and memory), image, attached volumes, and network interfaces for the image template. Additionally, user data is specified to automatically run [initialization scripts](https://github.com/IBM-Cloud/vpc-scaling-dedicated-host/blob/master/modules/create_vpc/main.tfL109) required for the frontend and backend applications respectively. All of the VSIs that are created for an instance group use the instance template that is defined in the instance group. The script provisions an instance template and an instance group (one for frontend and one for backend) with no auto scaling policies defined yet.
Additionally, server instances from the neighboring data centers within the same city can also be added (for instance, if the first three letters of the data center name are the same).

If the load balancer type is Public to Public, the server instances are added with their Public IP, as shown in the following image.

Server weights are relevant only when using the Weighted Round Robin load-balancing method. The default weight is 50 and the range is 0-100. The weights are disabled with other load-balancing methods.

Refer to [Limitations on number of application servers](https://cloud.ibm.com/docs/loadbalancer-service?topic=loadbalancer-service-faqs-for-ibm-cloud-load-balancerwhat-s-the-maximum-number-of-compute-instances-i-can-associate-with-my-load-balancer-) for more information on the maximum limit for the number of application servers.





 Step 4 - Placing your order 

Finally, to place your order:



1. Review the Order Information in the right column of the page.
2. Click the checkbox after reading the Master Service Agreement.
3. Click Create.

The system creates your load balancer and takes you to the Load Balancers summary page. Refresh your browser window to see the entry for your new load balancer and its state change from offline to online, which usually takes a few minutes. Offline load balancers are disabled, while online load balancers can be clicked to manage and monitor them, as shown in the following image.







 What's next 

[Managing and monitoring your service](https://cloud.ibm.com/docs/loadbalancer-service?topic=loadbalancer-service-monitoring-and-managing-your-service) to edit configuration and monitor service performance.
--------------------







 ibmcloud is bare-metal-server-profile 

View details of a bare metal server profile.

ibmcloud is bare-metal-server-profile PROFILE_NAME [--output JSON] [-q, --quiet]



 Command options 



* PROFILE_NAME: Name of the profile.
* --output: Specify output format, only JSON is supported. One of: JSON.
* -q, --quiet: Suppress verbose output.



--------------------







 ibmcloud is bare-metal-server-profiles 

List all bare metal server profiles in the region.

ibmcloud is bare-metal-server-profiles [--output JSON] [-q, --quiet]



 Command options 



* --output: Specify output format, only JSON is supported. One of: JSON.
* -q, --quiet: Suppress verbose output.



--------------------







 ibmcloud is bare-metal-server-restart 

Restart a bare metal server.

ibmcloud is bare-metal-server-restart SERVER [-f, --force] [-q, --quiet]



 Command options 



* SERVER: ID or name of the server.
* --force, -f: Force the operation without confirmation.
* -q, --quiet: Suppress verbose output.



--------------------







 ibmcloud is bare-metal-server-start 

Start a bare metal server.

ibmcloud is bare-metal-server-start SERVER [-q, --quiet]



 Command options 



* SERVER: ID or name of the server.
* -q, --quiet: Suppress verbose output.



--------------------







 ibmcloud is bare-metal-server-stop 

Stop a bare metal server.
Best practices 

Use the following set of recommended guidelines when provisioning and managing your serverless instances and when running Spark applications.



Table 1. Best practices when using serverless instances including detailed descriptions and reference links

 Best Practice Description Reference Link 

 Use separate IBM Analytics Engine service instances for your development and production environments. This is a general best practice. By creating separate IBM Analytics Engine instances for different environments, you can test any configuration and code changes before applying them on the production instance. NA 
 Upgrade to the latest Spark version As open source Spark versions are released, they are made available in IBM Analytics Engine after a time interval required for internal testing. Watch out for the announcement of a new Spark versions in the Release Notes section and upgrade the runtime of your instance to move your applications to latest Spark runtime. Older runtimes are be deprecated and eventually removed as newer versions are released. Make sure you test your applications on the new runtime before making changes on the production instances. <br><br> * [Release notes for IBM Analytics Engine serverless instances](https://cloud.ibm.com/docs/AnalyticsEngine?topic=AnalyticsEngine-iae-serverless-relnotes)<br><br><br> 
 Grant role-based access You should grant role-based access to all users on the IBM Analytics Engine instances based on their requirements. For example, only your automation team should have permissions to submit applications because it has access to secrets and your DevOps team should only be able to see the list of all applications and their states. <br><br> * [Granting permissions to users](https://cloud.ibm.com/docs/AnalyticsEngine?topic=AnalyticsEngine-grant-permissions-serverless)<br><br><br> 
 Choose the right IBM Cloud Object Storage configuration <br><br> * Disaster Recovery (DR) Resiliency: You should use the IBM Cloud Object Storage Cross Regional resiliency option that backs up your data across several different cities in a region. In contrast, the Regional resiliency option back ups data in a single data center.<br> * Encryption: IBM Cloud Object Storage comes with default built-in encryption.
* UI
* CLI
* API







 Creating Bare Metal Servers on VPC 

Use the following information to create a bare metal server on your IBM Cloud® Virtual Private Cloud (VPC) with the configuration of your choice.



 Creating a bare metal server by using the UI 

Use the following steps to create a bare metal server by using the IBM Cloud® console. You can also check out the following [video](https://mediacenter.ibm.com/media/t/1_j2pdfua6) to learn more about creating a bare metal server.



1. In the [IBM Cloud console ![External link icon](https://cloud.ibm.com/docs-content/v1/content/f02b9c9adcbb7328d95a45e105cec371d50f15eb/icons/launch-glyph.svg)](https://cloud.ibm.com/login), go to Menu icon ![Menu icon](https://cloud.ibm.com/docs-content/v1/content/icons/icon_hamburger.svg) > VPC Infrastructure > Compute > Bare metal servers.
2. Click Create and enter the information that is in Table 1.
3. For Advanced options, you can choose to complete extra server configurations. For more information, see Table 2.
4. Review the configuration Summary and click Create bare metal server.





Table 1. Bare metal server provisioning selections

 Field Value 

 Server type Select the architecture type of your bare metal server. The value can be either Intel (x86 architecture) or IBM LinuxONE (s390x architecture). 
 Location Locations are composed of regions (specific geographic areas) and zones (fault tolerant data centers within a region). Select the location where you want your bare metal server. 
 Name A name is required for your bare metal server. 
 Resource group Select a resource group for the server. 
 Tags You can assign labels to your server so that you can easily filter resources in your resource list. 
 Access management tags Access management tags help you apply flexible access policies on specific resources.
Subnet [List all subnets](https://cloud.ibm.com/apidocs/vpclist-subnets) 
 Security groups (optional) [List all security groups](https://cloud.ibm.com/apidocs/vpclist-security-groups) 
 Profile [List all bare metal server profiles](https://cloud.ibm.com/apidocs/vpclist-bare-metal-server-profiles) 
 Zone [List all regions](https://cloud.ibm.com/apidocs/vpclist-regions) <br>[List all zones in a region](https://cloud.ibm.com/apidocs/vpclist-region-zones) 







 Creating a bare metal server 

After you have all the information, use the [Create bare metal server](https://cloud.ibm.com/apidocs/vpccreate-bare-metal-server) API request to create a bare metal server.



* For x86 architecture, you can create a bare metal server with the following example configuration:



* ESXi image ID: "r134-31c8ca90-2623-48d7-8cf7-737be6fc4c3e"
* SSH Key ID: "a6b1a881-2ce8-41a3-80fc-36316a73f803"
* Name of the bare metal server: "my-bare-metal-server"
* A primary network interface with the following configurations:



* Allows VLAN with the ID of "4" to be attached
* Name: "my-primary-network-interface"
* Subnet ID: "7ec86020-1c6e-4889-b3f0-a15f2e50f87e"



* A secondary VLAN interface with ID "4". This VLAN interface is floatable.
* Profile name: "bx2d-metal-192x768"
* Zone: "us-south-1"



The API request is similar to: