1600675200
Ingress for Anthos is a Google cloud-hosted multi-cluster ingress controller for Anthos GKE clusters. Ingress for Anthos supports deploying shared load balancing resources across clusters and across regions enabling users to use a same load balancer with an anycast IP for applications running in a multi-cluster and multi-region topology.
In simpler terms this allows users to place multiple GKE clusters located in different regions under one LoadBalancer. It’s a controller for the external HTTP(S) load balancer to provide ingress for traffic coming from the internet across one or more clusters by programming the external HTTP(S) load balancer using network endpoint groups (NEGs). NEGs are useful for Container native load balancing where each Container can be represented as endpoint to the load balancer.
#google-cloud-platform #kubernetes #google-kubernetes-engine #anthos
1647064260
Run C# scripts from the .NET CLI, define NuGet packages inline and edit/debug them in VS Code - all of that with full language services support from OmniSharp.
Name | Version | Framework(s) |
---|---|---|
dotnet-script (global tool) | net6.0 , net5.0 , netcoreapp3.1 | |
Dotnet.Script (CLI as Nuget) | net6.0 , net5.0 , netcoreapp3.1 | |
Dotnet.Script.Core | netcoreapp3.1 , netstandard2.0 | |
Dotnet.Script.DependencyModel | netstandard2.0 | |
Dotnet.Script.DependencyModel.Nuget | netstandard2.0 |
The only thing we need to install is .NET Core 3.1 or .NET 5.0 SDK.
.NET Core 2.1 introduced the concept of global tools meaning that you can install dotnet-script
using nothing but the .NET CLI.
dotnet tool install -g dotnet-script
You can invoke the tool using the following command: dotnet-script
Tool 'dotnet-script' (version '0.22.0') was successfully installed.
The advantage of this approach is that you can use the same command for installation across all platforms. .NET Core SDK also supports viewing a list of installed tools and their uninstallation.
dotnet tool list -g
Package Id Version Commands
---------------------------------------------
dotnet-script 0.22.0 dotnet-script
dotnet tool uninstall dotnet-script -g
Tool 'dotnet-script' (version '0.22.0') was successfully uninstalled.
choco install dotnet.script
We also provide a PowerShell script for installation.
(new-object Net.WebClient).DownloadString("https://raw.githubusercontent.com/filipw/dotnet-script/master/install/install.ps1") | iex
curl -s https://raw.githubusercontent.com/filipw/dotnet-script/master/install/install.sh | bash
If permission is denied we can try with sudo
curl -s https://raw.githubusercontent.com/filipw/dotnet-script/master/install/install.sh | sudo bash
A Dockerfile for running dotnet-script in a Linux container is available. Build:
cd build
docker build -t dotnet-script -f Dockerfile ..
And run:
docker run -it dotnet-script --version
You can manually download all the releases in zip
format from the GitHub releases page.
Our typical helloworld.csx
might look like this:
Console.WriteLine("Hello world!");
That is all it takes and we can execute the script. Args are accessible via the global Args array.
dotnet script helloworld.csx
Simply create a folder somewhere on your system and issue the following command.
dotnet script init
This will create main.csx
along with the launch configuration needed to debug the script in VS Code.
.
├── .vscode
│ └── launch.json
├── main.csx
└── omnisharp.json
We can also initialize a folder using a custom filename.
dotnet script init custom.csx
Instead of main.csx
which is the default, we now have a file named custom.csx
.
.
├── .vscode
│ └── launch.json
├── custom.csx
└── omnisharp.json
Note: Executing
dotnet script init
inside a folder that already contains one or more script files will not create themain.csx
file.
Scripts can be executed directly from the shell as if they were executables.
foo.csx arg1 arg2 arg3
OSX/Linux
Just like all scripts, on OSX/Linux you need to have a
#!
and mark the file as executable via chmod +x foo.csx. If you use dotnet script init to create your csx it will automatically have the#!
directive and be marked as executable.
The OSX/Linux shebang directive should be #!/usr/bin/env dotnet-script
#!/usr/bin/env dotnet-script
Console.WriteLine("Hello world");
You can execute your script using dotnet script or dotnet-script, which allows you to pass arguments to control your script execution more.
foo.csx arg1 arg2 arg3
dotnet script foo.csx -- arg1 arg2 arg3
dotnet-script foo.csx -- arg1 arg2 arg3
All arguments after --
are passed to the script in the following way:
dotnet script foo.csx -- arg1 arg2 arg3
Then you can access the arguments in the script context using the global Args
collection:
foreach (var arg in Args)
{
Console.WriteLine(arg);
}
All arguments before --
are processed by dotnet script
. For example, the following command-line
dotnet script -d foo.csx -- -d
will pass the -d
before --
to dotnet script
and enable the debug mode whereas the -d
after --
is passed to script for its own interpretation of the argument.
dotnet script
has built-in support for referencing NuGet packages directly from within the script.
#r "nuget: AutoMapper, 6.1.0"
Note: Omnisharp needs to be restarted after adding a new package reference
We can define package sources using a NuGet.Config
file in the script root folder. In addition to being used during execution of the script, it will also be used by OmniSharp
that provides language services for packages resolved from these package sources.
As an alternative to maintaining a local NuGet.Config
file we can define these package sources globally either at the user level or at the computer level as described in Configuring NuGet Behaviour
It is also possible to specify packages sources when executing the script.
dotnet script foo.csx -s https://SomePackageSource
Multiple packages sources can be specified like this:
dotnet script foo.csx -s https://SomePackageSource -s https://AnotherPackageSource
Dotnet-Script can create a standalone executable or DLL for your script.
Switch | Long switch | description |
---|---|---|
-o | --output | Directory where the published executable should be placed. Defaults to a 'publish' folder in the current directory. |
-n | --name | The name for the generated DLL (executable not supported at this time). Defaults to the name of the script. |
--dll | Publish to a .dll instead of an executable. | |
-c | --configuration | Configuration to use for publishing the script [Release/Debug]. Default is "Debug" |
-d | --debug | Enables debug output. |
-r | --runtime | The runtime used when publishing the self contained executable. Defaults to your current runtime. |
The executable you can run directly independent of dotnet install, while the DLL can be run using the dotnet CLI like this:
dotnet script exec {path_to_dll} -- arg1 arg2
We provide two types of caching, the dependency cache
and the execution cache
which is explained in detail below. In order for any of these caches to be enabled, it is required that all NuGet package references are specified using an exact version number. The reason for this constraint is that we need to make sure that we don't execute a script with a stale dependency graph.
In order to resolve the dependencies for a script, a dotnet restore
is executed under the hood to produce a project.assets.json
file from which we can figure out all the dependencies we need to add to the compilation. This is an out-of-process operation and represents a significant overhead to the script execution. So this cache works by looking at all the dependencies specified in the script(s) either in the form of NuGet package references or assembly file references. If these dependencies matches the dependencies from the last script execution, we skip the restore and read the dependencies from the already generated project.assets.json
file. If any of the dependencies has changed, we must restore again to obtain the new dependency graph.
In order to execute a script it needs to be compiled first and since that is a CPU and time consuming operation, we make sure that we only compile when the source code has changed. This works by creating a SHA256 hash from all the script files involved in the execution. This hash is written to a temporary location along with the DLL that represents the result of the script compilation. When a script is executed the hash is computed and compared with the hash from the previous compilation. If they match there is no need to recompile and we run from the already compiled DLL. If the hashes don't match, the cache is invalidated and we recompile.
You can override this automatic caching by passing --no-cache flag, which will bypass both caches and cause dependency resolution and script compilation to happen every time we execute the script.
The temporary location used for caches is a sub-directory named dotnet-script
under (in order of priority):
DOTNET_SCRIPT_CACHE_LOCATION
, if defined and value is not empty.$XDG_CACHE_HOME
if defined otherwise $HOME/.cache
~/Library/Caches
Path.GetTempPath
for the platform.The days of debugging scripts using Console.WriteLine
are over. One major feature of dotnet script
is the ability to debug scripts directly in VS Code. Just set a breakpoint anywhere in your script file(s) and hit F5(start debugging)
Script packages are a way of organizing reusable scripts into NuGet packages that can be consumed by other scripts. This means that we now can leverage scripting infrastructure without the need for any kind of bootstrapping.
A script package is just a regular NuGet package that contains script files inside the content
or contentFiles
folder.
The following example shows how the scripts are laid out inside the NuGet package according to the standard convention .
└── contentFiles
└── csx
└── netstandard2.0
└── main.csx
This example contains just the main.csx
file in the root folder, but packages may have multiple script files either in the root folder or in subfolders below the root folder.
When loading a script package we will look for an entry point script to be loaded. This entry point script is identified by one of the following.
main.csx
in the root folderIf the entry point script cannot be determined, we will simply load all the scripts files in the package.
The advantage with using an entry point script is that we can control loading other scripts from the package.
To consume a script package all we need to do specify the NuGet package in the #load
directive.
The following example loads the simple-targets package that contains script files to be included in our script.
#load "nuget:simple-targets-csx, 6.0.0"
using static SimpleTargets;
var targets = new TargetDictionary();
targets.Add("default", () => Console.WriteLine("Hello, world!"));
Run(Args, targets);
Note: Debugging also works for script packages so that we can easily step into the scripts that are brought in using the
#load
directive.
Scripts don't actually have to exist locally on the machine. We can also execute scripts that are made available on an http(s)
endpoint.
This means that we can create a Gist on Github and execute it just by providing the URL to the Gist.
This Gist contains a script that prints out "Hello World"
We can execute the script like this
dotnet script https://gist.githubusercontent.com/seesharper/5d6859509ea8364a1fdf66bbf5b7923d/raw/0a32bac2c3ea807f9379a38e251d93e39c8131cb/HelloWorld.csx
That is a pretty long URL, so why don't make it a TinyURL like this:
dotnet script https://tinyurl.com/y8cda9zt
A pretty common scenario is that we have logic that is relative to the script path. We don't want to require the user to be in a certain directory for these paths to resolve correctly so here is how to provide the script path and the script folder regardless of the current working directory.
public static string GetScriptPath([CallerFilePath] string path = null) => path;
public static string GetScriptFolder([CallerFilePath] string path = null) => Path.GetDirectoryName(path);
Tip: Put these methods as top level methods in a separate script file and
#load
that file wherever access to the script path and/or folder is needed.
This release contains a C# REPL (Read-Evaluate-Print-Loop). The REPL mode ("interactive mode") is started by executing dotnet-script
without any arguments.
The interactive mode allows you to supply individual C# code blocks and have them executed as soon as you press Enter. The REPL is configured with the same default set of assembly references and using statements as regular CSX script execution.
Once dotnet-script
starts you will see a prompt for input. You can start typing C# code there.
~$ dotnet script
> var x = 1;
> x+x
2
If you submit an unterminated expression into the REPL (no ;
at the end), it will be evaluated and the result will be serialized using a formatter and printed in the output. This is a bit more interesting than just calling ToString()
on the object, because it attempts to capture the actual structure of the object. For example:
~$ dotnet script
> var x = new List<string>();
> x.Add("foo");
> x
List<string>(1) { "foo" }
> x.Add("bar");
> x
List<string>(2) { "foo", "bar" }
>
REPL also supports inline Nuget packages - meaning the Nuget packages can be installed into the REPL from within the REPL. This is done via our #r
and #load
from Nuget support and uses identical syntax.
~$ dotnet script
> #r "nuget: Automapper, 6.1.1"
> using AutoMapper;
> typeof(MapperConfiguration)
[AutoMapper.MapperConfiguration]
> #load "nuget: simple-targets-csx, 6.0.0";
> using static SimpleTargets;
> typeof(TargetDictionary)
[Submission#0+SimpleTargets+TargetDictionary]
Using Roslyn syntax parsing, we also support multiline REPL mode. This means that if you have an uncompleted code block and press Enter, we will automatically enter the multiline mode. The mode is indicated by the *
character. This is particularly useful for declaring classes and other more complex constructs.
~$ dotnet script
> class Foo {
* public string Bar {get; set;}
* }
> var foo = new Foo();
Aside from the regular C# script code, you can invoke the following commands (directives) from within the REPL:
Command | Description |
---|---|
#load | Load a script into the REPL (same as #load usage in CSX) |
#r | Load an assembly into the REPL (same as #r usage in CSX) |
#reset | Reset the REPL back to initial state (without restarting it) |
#cls | Clear the console screen without resetting the REPL state |
#exit | Exits the REPL |
You can execute a CSX script and, at the end of it, drop yourself into the context of the REPL. This way, the REPL becomes "seeded" with your code - all the classes, methods or variables are available in the REPL context. This is achieved by running a script with an -i
flag.
For example, given the following CSX script:
var msg = "Hello World";
Console.WriteLine(msg);
When you run this with the -i
flag, Hello World
is printed, REPL starts and msg
variable is available in the REPL context.
~$ dotnet script foo.csx -i
Hello World
>
You can also seed the REPL from inside the REPL - at any point - by invoking a #load
directive pointed at a specific file. For example:
~$ dotnet script
> #load "foo.csx"
Hello World
>
The following example shows how we can pipe data in and out of a script.
The UpperCase.csx
script simply converts the standard input to upper case and writes it back out to standard output.
using (var streamReader = new StreamReader(Console.OpenStandardInput()))
{
Write(streamReader.ReadToEnd().ToUpper());
}
We can now simply pipe the output from one command into our script like this.
echo "This is some text" | dotnet script UpperCase.csx
THIS IS SOME TEXT
The first thing we need to do add the following to the launch.config
file that allows VS Code to debug a running process.
{
"name": ".NET Core Attach",
"type": "coreclr",
"request": "attach",
"processId": "${command:pickProcess}"
}
To debug this script we need a way to attach the debugger in VS Code and the simplest thing we can do here is to wait for the debugger to attach by adding this method somewhere.
public static void WaitForDebugger()
{
Console.WriteLine("Attach Debugger (VS Code)");
while(!Debugger.IsAttached)
{
}
}
To debug the script when executing it from the command line we can do something like
WaitForDebugger();
using (var streamReader = new StreamReader(Console.OpenStandardInput()))
{
Write(streamReader.ReadToEnd().ToUpper()); // <- SET BREAKPOINT HERE
}
Now when we run the script from the command line we will get
$ echo "This is some text" | dotnet script UpperCase.csx
Attach Debugger (VS Code)
This now gives us a chance to attach the debugger before stepping into the script and from VS Code, select the .NET Core Attach
debugger and pick the process that represents the executing script.
Once that is done we should see our breakpoint being hit.
By default, scripts will be compiled using the debug
configuration. This is to ensure that we can debug a script in VS Code as well as attaching a debugger for long running scripts.
There are however situations where we might need to execute a script that is compiled with the release
configuration. For instance, running benchmarks using BenchmarkDotNet is not possible unless the script is compiled with the release
configuration.
We can specify this when executing the script.
dotnet script foo.csx -c release
Starting from version 0.50.0, dotnet-script
supports .Net Core 3.0 and all the C# 8 features. The way we deal with nullable references types in dotnet-script
is that we turn every warning related to nullable reference types into compiler errors. This means every warning between CS8600
and CS8655
are treated as an error when compiling the script.
Nullable references types are turned off by default and the way we enable it is using the #nullable enable
compiler directive. This means that existing scripts will continue to work, but we can now opt-in on this new feature.
#!/usr/bin/env dotnet-script
#nullable enable
string name = null;
Trying to execute the script will result in the following error
main.csx(5,15): error CS8625: Cannot convert null literal to non-nullable reference type.
We will also see this when working with scripts in VS Code under the problems panel.
Download Details:
Author: filipw
Source Code: https://github.com/filipw/dotnet-script
License: MIT License
1619096139
Having a multi-services app would help you to excel in your on-demand services business. An on-demand app solution empowers entrepreneurs to offer multiple on-demand services in a single app. In short, this is an efficient app to run a business successfully. If you are an entrepreneur who plans to start a business with the multi-services app, go forward with the multi-service app development.
What are the multiple services offered in the on-demand multi-services app?
Services are categorized as follows.
Ride services – Taxi ride, Moto ride, Car rental, and Moto rental.
Delivery services – Food delivery, Courier delivery, Logistics delivery, Grocery delivery, Medicine delivery, Flower delivery, Fuel delivery, and Plant delivery.
Other services – Plumber, Electrician, Car wash, Fitness, Handyman, Car repair, and beauty services.
Apart from these, you can consider integrating several other services while developing your app.
3 Significant reasons to invest in the on-demand multi-services app
The first and foremost reason why customers use this app is the on-demand multi-service on one platform. Usually, people do not like to install so many apps for availing various services. Instead, they can have a single app for that. This is the reason why the demand for such apps is high.
Next, the incurred cost is less in this app when compared to the single service app. With the seamless navigation feature, customers can easily avail of any services with just a few taps.
Thirdly, they feel more convenient in availing themselves various services in one platform.
Future scope of the multi-service industry
There are 7.6 million users for the multi-service apps in 2019. Recently, the demand for such apps is high considerably due to the covid-19 pandemic. It is expected to flourish more in the future. By 2023, this industry will hit 161.74 billion. This is so inspiring and so many entrepreneurs plan to propel into this industry in 2021.
Consider the following aspects for multi-service app development
Integrate the Multilingual and Multiple currencies features
Never let language be a barrier to your business. Therefore, incorporate the multilingual feature so that customers can use the app in their languages.
The global launch will help you to have a more extensive user base for your app. Just like language, do not let the currency restrict you from launching your app across many countries.
User-friendly design
The UI/UX of the app has to be simple and appealing. This plays a vital role in gaining more customers. If the design is not user-friendly and unimpressive, they won’t prefer your app for the next time. Instead, they prefer using your competitors’ app for availing multiple services. To gain new customers and to retain the existing customers, focus on the app design.
App platform
To cover all the audiences, consider launching the app on both the Android and iOS platforms. Decide on which platform you will launch the app based on your target audience.
White-label solution
It is a known fact that making an app from scratch needs more time and requires a considerable amount of money. On the counter side, creating the app using the white-label solution is budget-friendly and time-conserving. Because, it is a readily available solution. Upon making modifications, you can launch the app instantly. Being the customizable solution, any new features can be incorporated based on the requirements.
The decision of starting a business with the on-demand multi-services app is good as the market will flourish further in the upcoming days. Take away the points from this blog to withstand in the highly competitive market. Reach out to Uberlikeapp for multi-services app development. We provide a customizable app solution that is scalable based on your needs.
#on demand multi services app #multi services app development #multi service booking app #on-demand service app clone #on-demand multi-services app solution
1594162500
A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.
Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.
By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.
However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.
Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.
Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.
Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.
Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.
The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.
For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.
#cloud computing services #all #hybrid cloud #cloud #multi-cloud strategy #cloud spend #multi-cloud spending #multi cloud adoption #why multi cloud #multi cloud trends #multi cloud companies #multi cloud research #multi cloud market
1600675200
Ingress for Anthos is a Google cloud-hosted multi-cluster ingress controller for Anthos GKE clusters. Ingress for Anthos supports deploying shared load balancing resources across clusters and across regions enabling users to use a same load balancer with an anycast IP for applications running in a multi-cluster and multi-region topology.
In simpler terms this allows users to place multiple GKE clusters located in different regions under one LoadBalancer. It’s a controller for the external HTTP(S) load balancer to provide ingress for traffic coming from the internet across one or more clusters by programming the external HTTP(S) load balancer using network endpoint groups (NEGs). NEGs are useful for Container native load balancing where each Container can be represented as endpoint to the load balancer.
#google-cloud-platform #kubernetes #google-kubernetes-engine #anthos
1593444960
One of the obvious advantages of load balancing architecture is to increase the availability and reliability of applications, so if a certain number of clients request some number of resources to backends, Load balancer stays between them and route the traffic to the backend that fills most the routing criteria (less busy, most healthy, located in a given region … etc).
There are a lot of routing criteria, but we will focus on this article on fixed round-robin criteria — meaning each backend receives a fixed amount of traffic — which I think rarely documented :).
To simplify we will create two backends “applications” based on flask Python files. We will use NGINX as a load balancer to distribute 60% of traffic to application1 and 40% of traffic to application2.
Let’s start the coding, hereafter the complete architecture of our project:
app1/app1.py
from flask import request, Flask
import json
app1 = Flask(__name__)
@app1.route('/')
def hello_world():
return 'Salam alikom, this is App1 :) '
if __name__ == '__main__':
app1.run(debug=True, host='0.0.0.0')
app2/app2.py
from flask import request, Flask
import json
app1 = Flask(__name__)
@app1.route('/')
def hello_world():
return 'Salam alikom, this is App2 :) '
if __name__ == '__main__':
app1.run(debug=True, host='0.0.0.0')
Then we have to dockerize both applications by adding the requirements.txt file. It will contain only the flask library since we are using the python3 image.
#load-balancing #python-flask #docker-load-balancing #nginx #flask-load-balancing