Web Applications – What's the Lightest Web Framework for Deploying a Single Page App on Raspberry Pi?

I plan to install BalenaOS and run a small one-page web app from a Docker container. It only needs to provide static content because there is an API somewhere else. According to Balena documents, they provide images with Node.js, Python, Go, Java and Dotnet.

Which platform offers the lightest web frame fork?

How do I install the List View command-set extension in a site collection after deploying it with CSOM in an App Catalog?

I've created a Listview command extension with SPFX and added it to the App Catalog. Now I want to install this extension only for certain sites. I tried to add it as a custom action, but it does not work. Any help would be appreciated.

Bitcoin Core – What is a mechanism for deploying Merkle Path?

They may not like calculating to find a transaction when they need to do a sequence search because they are busy finding the hash value of a block to get a block reward

You confuse the mining with the node operation.

It's a complete node in the network that returns information about the relevant Merkle path to the SPV wallet.

The dismantling is done separately by special hardware just Be extremely efficient to find a new block. The mining hardware connects to a complete node so that you can retrieve the relevant information for creating new block templates. However, the two calculations are performed in parallel on separate hardware.

Even if a mining node provided the Merkle path information, this would not affect mining time.

A simple business plan for deploying managed shared hosting services to 100 clients

Hello, can anyone criticize this simple business plan?

I intend to purchase a fully managed InVation Hosting vps plan. It costs about $ 800 a year.

I want to use IM Creator as my primary CMS – the annual plan costs about $ 2,500.

I would like to charge my customers an annual or monthly flat fee. First and foremost I will use IM Creator (EXPRS Website Builder) to build the websites.

1. How feasible is this plan in terms of safety?

Deploying a React application on GitHub Pages gets a 404

I'm new to React (and still a beginner in programming and syntax) and have read tutorials (like https://github.com/gitname/react-gh-pages and Youtube) to deploy my app for deployment GitHub.
But I still get a "404 There is no GitHub Pages page here."
The GitHub pages are created from the gh-pages branch.

This is my project: https://github.com/yumichelle/studio-ghibli

Vendor hosted app – Error deploying the .sppkg file in SharePoint App Catalog

I've been following this tutorial and having trouble deploying the app catalog app in my Office 365 SP online tenant.

I've decided to start all over again, but this time I did not add the extra features the tutorial goes through. I kept it simple and tried to deploy the base app that is generated when running yo @ microsoft / sharepoint in PowerShell (surely this would just work as it is).

I run Swig package solution and upload the .sppkg file to my App Catalog. SP asks me if I trust the app. I say "yes" and click "deploy." I then get the following error in the "App Package Error Message" column.

Provision failed. Correlation ID: 0382f19e-3074-0000-a490-b4c1f2311f84

Any help would be appreciated!

Wet transfer link to the .sppkg file:
https://we.tl/t-VKvMd9XnH7

SQL Server – An intermediate error while deploying the Azure ARM template for the SQL backup

A temporary error occurs when trying to deploy a backup solution during deployment. The mistake I sometimes get is:

Provision failed. Correlation ID: bb100978-3c7b-46f4-bcca-8b9abb490a98. {
"Error": {
"code": "GuestAgentStatusUnavailableUserError",
"message": "The Azure Backup service uses the Azure VM Guest Agent for backup, but the Guest Agent is not available on the destination server. r nGuest Agent is a prerequisite for the Azure Workload Backup extension. Please install the guest agent. " .
"Goal": zero,
"Details": zero,
"innerError": zero
}
}

I wrote the dependency to depend on the IAAS extension:

{
"type": "Microsoft.RecoveryServices / vaults / backupFabrics / protectionContainers",
"apiVersion": "2016-06-01",
"Surname": "[concat(parameters('vaultName'), '/', parameters('fabricName'), '/',parameters('protectionContainers')[copyIndex()])]"
"Properties": {
"backupManagementType": "[parameters('backupManagementType')]"
"workloadType": "[parameters('workloadType')]"
"Container Type": "[parameters('protectionContainerTypes')[copyIndex()]]"
"sourceResourceId": "[parameters('sourceResourceIds')[copyIndex()]]"
"operationType": "[parameters('operationType')]"
"depends on": [
                    "[concat('Microsoft.SqlVirtualMachine/SqlVirtualMachines/',parameters('sqlVmNamePrefix'),'-', copyIndex())]"
]},
"Copy": {
"name": "protectionContainersCopy",
"Number": "[length(parameters('protectionContainers'))]"
}




{
"apiVersion": "2017-05-10",
"type": "Microsoft.Resources / deployments",
"Surname": "[concat(parameters('sqlVmNamePrefix'),'-', copyIndex(),'-SQLIaaSLoop')]"
"Copy": {
"name": "nestedSQLLoop",
"Number": "[parameters('sqlNumberOfInstances')]"
"mode": "Serial"
},
"depends on": [
                "nestedChefloop"
            ].
"Properties": {
"mode": "Incremental",
"Template": {
"$ schema": "https://schema.management.azure.com/schemas/2015-01-01/deploymentTemplate.json#",
"contentVersion": "1.0.0.0",
"Resources": [
                        {
                            "name": "[concat(parameters('sqlVmNamePrefix'),'-', copyIndex())]"
"type": "Microsoft.SqlVirtualMachine / SqlVirtualMachines",
"apiVersion": "01.03.2017 preview",
"Location": "[parameters('location')]"
"Properties": {
"virtualMachineResourceId": "[resourceId('Microsoft.Compute/virtualMachines', concat(parameters('sqlVmNamePrefix'),'-', copyIndex()))]"
"SqlServerLicenseType": "AHUB",
AutoPatchingSettings: {
"Activate": true,
"Weekday": "[parameters('sqlAutopatchingDayOfWeek')]"
"MaintenanceWindowStartingHour":[parameters('sqlAutopatchingStartHour')]"
"MaintenanceWindowDuration":[parameters('sqlAutopatchingWindowDuration')]"
},
"KeyVaultCredentialSettings": {
"Activate": false,
"CredentialName": ""
},
"ServerConfigurationManagementSettings": {
"SQLConnectivityUpdateSettings": {
"Connectivity Type": "[parameters('sqlConnectivityType')]"
"Port": "[parameters('sqlPortNumber')]"
"SQLAuthUpdateUserName": "[parameters('sqlAuthenticationLogin')]"
SQLAuthUpdatePassword: "[parameters('sqlAuthenticationPassword')]"
},
SQLWorkloadTypeUpdateSettings: {
"SQLWorkloadType": "[parameters('sqlStorageWorkloadType')]"
},
SQLStorageUpdateSettings: {
"DiskCount": "[parameters('sqlStorageDisksCount')]"
"DiskConfigurationType": "[parameters('sqlStorageDisksConfigurationType')]"
StartingDeviceID: "[parameters('sqlStorageStartingDeviceId')]"
},
"AdditionalFeaturesServerConfigurations": {
"IsRServicesEnabled": "[parameters('rServicesEnabled')]"
}

The error occurs about 1/4 of the time, I do not think that I can make it dependent on anything later than it already is. Is this GuestAgent installed at some point? From what I read, it happens when the image is dropped, so the dependency should be okay, but it still fails again and again.

amazon ec2 – Always timed out when deploying the API "React App + Rails" on ec2

Rails: 5.2.3
Ruby: 2.6.3p62
Node: v4.6.0

Hello, So I'm trying to implement new Rails API + apps.
Most of the time I've followed the tutorial here (except for the part with the Bitbucket pipelines).

Everything was fine until I added a post-deployment script to run the rake task to create the front end.

.extensions / post_deploy.config

files:
"/Opt/elasticbeanstalk/hooks/appdeploy/post/91_post_deploy_process.sh":
Mode: "000744"
Owner: root
Group: root
Content: |
#! / usr / bin / env bash
set -xe

EB_SCRIPT_DIR = $ (/ opt / elasticbeanstalk / bin / get-config container -k script_directory)
EB_SUPPORT_DIR = $ (/ opt / elasticbeanstalk / bin / get-config container -k support_dir)
EB_DEPLOY_DIR = $ (/ opt / elasticbeanstalk / bin / get-config container -k app_deploy_dir)

, $ EB_SUPPORT_DIR / envvars
, $ EB_SCRIPT_DIR / use-app-ruby.sh

echo "[POST DEPLOY] RAKE START PRODUCTION "
cd $ EB_DEPLOY_DIR
su -c "Bundle Exec Rake Start: Production"

especially the last line.

that's what my rake Task looks like this:

        Task: do production
exec # NPM_CONFIG_PRODUCTION = true npm run clientbuild & # 39;
The End

where mine package.json Script is:

"Scripts": {
"build": "cd frontend && npm install && npm run build && cd ..",
"deploy": "cp -a frontend / build /. public /",
"clientbuild": "npm run build & npm run deploy & echo" client
built & # 39; "
}

and frontend / package.json Script is:

"Scripts": {
"start": "PORT = start 3000 reaction scripts",
"build": "Build React scripts",
"test": "React-Scripts-Test --env = jsdom",
"Eject": "React Scripts Eject"
},

After a long debugging I realized that the problem exists npm install Command on ec2 instance. I run manually su -c "Bundle Exec Rake Start: Production" on ssh, to find out). It just takes too long and is never finished.

What can I do to make this deployment a success? What do I have to do to fix bugs and find out more? I am really lost here.

c – Saving * TF2 * Keras models, deploying and running C_API

I am trying to deploy TF2.Keras models as part of a large existing application with the TF-ready C_API on user computers (Win / Linux / Mac) (I do not want to recompile TF2 for C ++). Initially targeted only at the CPU, although ultimately a GPU is desired.

The code must be able to quickly execute one of several different neural networks in any order as needed. (Live code is multithreaded, so I'm assuming you have to go through a critical section or view a single launcher thread.)

I'm struggling to learn TF2 and figure out how to deliver TF2 models as the useful and well-known TF1 approach to freezing models seems to be gone.

It looks like SaveModel is the current proposal, even though it's stored in a full directory of files, which is not an option for just about any metric.
I need to be able to load the models from memory or at most a single external file.

How can I transform the training model into the inference model? Rebuild it and transfer weights as constants, not as variables? Any TF2 help for that?

Can the model be sufficiently overhauled so that SaveModel creates only one .pb file?

How can I force the tensors of the inputs and outputs to always have predefined names? The code must be independent of the models so that a different network can be selected for a certain function without knowing the internal structure. And the models can be exchanged at any time.

It seems you should use @tf.function and AutoGraph to simplify the usage (from C_API)?

If so, can the @tf. function use Model.predict ()? Or how can I generate this function generically from the levels of the model?

What operations are required to power the network in the C_API? I will have TF_Tensors in the CPU memory to power the model and get the output. Conceptually, it's like a function call.

Which compiler options are used for the ready-made C_API libraries? What kind of machine functions are required or do the libraries select internally suitable code paths? (For example, for AVX and non-AVX devices.)

For the GPU library … there is a CUDA10 dependency, but CUDA10 has already been superseded. The end user may use other software that requires different versions of CUDA. Can these be next to each other? Is there any meaningful way to deploy TF with GPU support? Compiling TF2 for different machine / CUDA versions and providing different versions for each of the various variations of the application is not practical, although theoretically possible.

If you're using the C_API GPU version, is the API doing something to use an existing GPU? How about more than one? That is, does the library take over putting models on the GPU or does the application have to notice the GPUs and decide how to use them?