Ella  Windler

Ella Windler

1665831360

Kaps: An Experimental OCI Container Runtime Written in Rust

Kaps

kaps is an experimental OCI container runtime written in Rust. The project aims to provide a performant, intuitive and OCI-compliant CLI allowing users to run & manage containers.

Project is experimental and should not be used in any production systems.

Install

To easily install kaps on your computer, simply run :

$ cargo install --path . && sudo mv $HOME/.cargo/bin/kaps /usr/local/bin

Quickstart

Here a little quickstart to run an alpine container, depending on your architecture, for amd64 :

At the moment, Kaps need to be run with root privileges. Consider adding sudo before each command or directly execute the following commands as root.

# --name is used to give an identifier to our image. See reference for more information.
$ kaps pull docker.io/amd64/alpine --name alpine
# Mount the image as an OCI bundle into /tmp/alpine
$ kaps mount alpine /tmp/alpine
# Run your container with the bundle
$ kaps run --bundle /tmp/alpine

For more documentation about commands, please see : Command line reference

.gitignore

# Generated by Cargo
# will have compiled files and executables
target

# Remove Cargo.lock from gitignore if creating an executable, leave it for libraries
# More information here https://doc.rust-lang.org/cargo/guide/cargo-toml-vs-cargo-lock.html
Cargo.lock
!crates/**/Cargo.lock
# These are backup files generated by rustfmt
**/*.rs.bk

.idea
*.tar.gz
.vscode

Cargo.toml

[package]
name = "kaps"
version = "0.1.0"
edition = "2021"
authors = ["Polytech Montpellier - DevOps"]

[dependencies]
oci-image = { path = "oci-image" }
clap = { version = "3.0.5", features = ["derive"] }
container = { path = "container" }
lazy_static = "1.4.0"
oci-spec = "0.5.3"
unshare = { git = "https://github.com/virt-do/unshare", branch = "main" }
tokio = {version = "1.0", features = ["full"]}
async-trait = "0.1.52"
log = "0.4.14"
env_logger = "0.9.0"

[workspace]
members = [
        "container",
        "oci-image"
]

Makefile

TMP_BUNDLE ?= /tmp/run0-bundle
BINARY := $(shell cat Cargo.toml | grep "name = " | sed 's/name = //g' | cut -d '"' -f2)

.PHONY: bundle build run0 run

# Helper to build run0
run0: src/*
	cargo build

# Helper to create a bundle.
# Simply call `make bundle` before running `make run`
bundle:
	./hack/mkbundle.sh $(TMP_BUNDLE)

# Helper to run run0.
# Requires that `make bundle` was executed before.
run: run0
	sudo ./target/debug/$(BINARY) run -b $(TMP_BUNDLE)

Download Details:

Author: virt-do
Source Code: https://github.com/virt-do/kaps

License: Apache-2.0 license

#rust 

What is GEEK

Buddha Community

Kaps: An Experimental OCI Container Runtime Written in Rust

Serde Rust: Serialization Framework for Rust

Serde

*Serde is a framework for serializing and deserializing Rust data structures efficiently and generically.*

You may be looking for:

Serde in action

Click to show Cargo.toml. Run this code in the playground.

[dependencies]

# The core APIs, including the Serialize and Deserialize traits. Always
# required when using Serde. The "derive" feature is only required when
# using #[derive(Serialize, Deserialize)] to make Serde work with structs
# and enums defined in your crate.
serde = { version = "1.0", features = ["derive"] }

# Each data format lives in its own crate; the sample code below uses JSON
# but you may be using a different one.
serde_json = "1.0"

 

use serde::{Serialize, Deserialize};

#[derive(Serialize, Deserialize, Debug)]
struct Point {
    x: i32,
    y: i32,
}

fn main() {
    let point = Point { x: 1, y: 2 };

    // Convert the Point to a JSON string.
    let serialized = serde_json::to_string(&point).unwrap();

    // Prints serialized = {"x":1,"y":2}
    println!("serialized = {}", serialized);

    // Convert the JSON string back to a Point.
    let deserialized: Point = serde_json::from_str(&serialized).unwrap();

    // Prints deserialized = Point { x: 1, y: 2 }
    println!("deserialized = {:?}", deserialized);
}

Getting help

Serde is one of the most widely used Rust libraries so any place that Rustaceans congregate will be able to help you out. For chat, consider trying the #rust-questions or #rust-beginners channels of the unofficial community Discord (invite: https://discord.gg/rust-lang-community), the #rust-usage or #beginners channels of the official Rust Project Discord (invite: https://discord.gg/rust-lang), or the #general stream in Zulip. For asynchronous, consider the [rust] tag on StackOverflow, the /r/rust subreddit which has a pinned weekly easy questions post, or the Rust Discourse forum. It's acceptable to file a support issue in this repo but they tend not to get as many eyes as any of the above and may get closed without a response after some time.

Download Details:
Author: serde-rs
Source Code: https://github.com/serde-rs/serde
License: View license

#rust  #rustlang 

Ella  Windler

Ella Windler

1665831360

Kaps: An Experimental OCI Container Runtime Written in Rust

Kaps

kaps is an experimental OCI container runtime written in Rust. The project aims to provide a performant, intuitive and OCI-compliant CLI allowing users to run & manage containers.

Project is experimental and should not be used in any production systems.

Install

To easily install kaps on your computer, simply run :

$ cargo install --path . && sudo mv $HOME/.cargo/bin/kaps /usr/local/bin

Quickstart

Here a little quickstart to run an alpine container, depending on your architecture, for amd64 :

At the moment, Kaps need to be run with root privileges. Consider adding sudo before each command or directly execute the following commands as root.

# --name is used to give an identifier to our image. See reference for more information.
$ kaps pull docker.io/amd64/alpine --name alpine
# Mount the image as an OCI bundle into /tmp/alpine
$ kaps mount alpine /tmp/alpine
# Run your container with the bundle
$ kaps run --bundle /tmp/alpine

For more documentation about commands, please see : Command line reference

.gitignore

# Generated by Cargo
# will have compiled files and executables
target

# Remove Cargo.lock from gitignore if creating an executable, leave it for libraries
# More information here https://doc.rust-lang.org/cargo/guide/cargo-toml-vs-cargo-lock.html
Cargo.lock
!crates/**/Cargo.lock
# These are backup files generated by rustfmt
**/*.rs.bk

.idea
*.tar.gz
.vscode

Cargo.toml

[package]
name = "kaps"
version = "0.1.0"
edition = "2021"
authors = ["Polytech Montpellier - DevOps"]

[dependencies]
oci-image = { path = "oci-image" }
clap = { version = "3.0.5", features = ["derive"] }
container = { path = "container" }
lazy_static = "1.4.0"
oci-spec = "0.5.3"
unshare = { git = "https://github.com/virt-do/unshare", branch = "main" }
tokio = {version = "1.0", features = ["full"]}
async-trait = "0.1.52"
log = "0.4.14"
env_logger = "0.9.0"

[workspace]
members = [
        "container",
        "oci-image"
]

Makefile

TMP_BUNDLE ?= /tmp/run0-bundle
BINARY := $(shell cat Cargo.toml | grep "name = " | sed 's/name = //g' | cut -d '"' -f2)

.PHONY: bundle build run0 run

# Helper to build run0
run0: src/*
	cargo build

# Helper to create a bundle.
# Simply call `make bundle` before running `make run`
bundle:
	./hack/mkbundle.sh $(TMP_BUNDLE)

# Helper to run run0.
# Requires that `make bundle` was executed before.
run: run0
	sudo ./target/debug/$(BINARY) run -b $(TMP_BUNDLE)

Download Details:

Author: virt-do
Source Code: https://github.com/virt-do/kaps

License: Apache-2.0 license

#rust 

Christa  Stehr

Christa Stehr

1602964260

50+ Useful Kubernetes Tools for 2020 - Part 2

Introduction

Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.

According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.

(State of Kubernetes and Container Security, 2020)

And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.

(State of Kubernetes and Container Security, 2020)

#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml

Awesome  Rust

Awesome Rust

1654894080

Serde JSON: JSON Support for Serde Framework

Serde JSON

Serde is a framework for serializing and deserializing Rust data structures efficiently and generically.

[dependencies]
serde_json = "1.0"

You may be looking for:

JSON is a ubiquitous open-standard format that uses human-readable text to transmit data objects consisting of key-value pairs.

{
    "name": "John Doe",
    "age": 43,
    "address": {
        "street": "10 Downing Street",
        "city": "London"
    },
    "phones": [
        "+44 1234567",
        "+44 2345678"
    ]
}

There are three common ways that you might find yourself needing to work with JSON data in Rust.

  • As text data. An unprocessed string of JSON data that you receive on an HTTP endpoint, read from a file, or prepare to send to a remote server.
  • As an untyped or loosely typed representation. Maybe you want to check that some JSON data is valid before passing it on, but without knowing the structure of what it contains. Or you want to do very basic manipulations like insert a key in a particular spot.
  • As a strongly typed Rust data structure. When you expect all or most of your data to conform to a particular structure and want to get real work done without JSON's loosey-goosey nature tripping you up.

Serde JSON provides efficient, flexible, safe ways of converting data between each of these representations.

Operating on untyped JSON values

Any valid JSON data can be manipulated in the following recursive enum representation. This data structure is serde_json::Value.

enum Value {
    Null,
    Bool(bool),
    Number(Number),
    String(String),
    Array(Vec<Value>),
    Object(Map<String, Value>),
}

A string of JSON data can be parsed into a serde_json::Value by the serde_json::from_str function. There is also from_slice for parsing from a byte slice &[u8] and from_reader for parsing from any io::Read like a File or a TCP stream.

use serde_json::{Result, Value};

fn untyped_example() -> Result<()> {
    // Some JSON input data as a &str. Maybe this comes from the user.
    let data = r#"
        {
            "name": "John Doe",
            "age": 43,
            "phones": [
                "+44 1234567",
                "+44 2345678"
            ]
        }"#;

    // Parse the string of data into serde_json::Value.
    let v: Value = serde_json::from_str(data)?;

    // Access parts of the data by indexing with square brackets.
    println!("Please call {} at the number {}", v["name"], v["phones"][0]);

    Ok(())
}

The result of square bracket indexing like v["name"] is a borrow of the data at that index, so the type is &Value. A JSON map can be indexed with string keys, while a JSON array can be indexed with integer keys. If the type of the data is not right for the type with which it is being indexed, or if a map does not contain the key being indexed, or if the index into a vector is out of bounds, the returned element is Value::Null.

When a Value is printed, it is printed as a JSON string. So in the code above, the output looks like Please call "John Doe" at the number "+44 1234567". The quotation marks appear because v["name"] is a &Value containing a JSON string and its JSON representation is "John Doe". Printing as a plain string without quotation marks involves converting from a JSON string to a Rust string with as_str() or avoiding the use of Value as described in the following section.

The Value representation is sufficient for very basic tasks but can be tedious to work with for anything more significant. Error handling is verbose to implement correctly, for example imagine trying to detect the presence of unrecognized fields in the input data. The compiler is powerless to help you when you make a mistake, for example imagine typoing v["name"] as v["nmae"] in one of the dozens of places it is used in your code.

Parsing JSON as strongly typed data structures

Serde provides a powerful way of mapping JSON data into Rust data structures largely automatically.

use serde::{Deserialize, Serialize};
use serde_json::Result;

#[derive(Serialize, Deserialize)]
struct Person {
    name: String,
    age: u8,
    phones: Vec<String>,
}

fn typed_example() -> Result<()> {
    // Some JSON input data as a &str. Maybe this comes from the user.
    let data = r#"
        {
            "name": "John Doe",
            "age": 43,
            "phones": [
                "+44 1234567",
                "+44 2345678"
            ]
        }"#;

    // Parse the string of data into a Person object. This is exactly the
    // same function as the one that produced serde_json::Value above, but
    // now we are asking it for a Person as output.
    let p: Person = serde_json::from_str(data)?;

    // Do things just like with any other Rust data structure.
    println!("Please call {} at the number {}", p.name, p.phones[0]);

    Ok(())
}

This is the same serde_json::from_str function as before, but this time we assign the return value to a variable of type Person so Serde will automatically interpret the input data as a Person and produce informative error messages if the layout does not conform to what a Person is expected to look like.

Any type that implements Serde's Deserialize trait can be deserialized this way. This includes built-in Rust standard library types like Vec<T> and HashMap<K, V>, as well as any structs or enums annotated with #[derive(Deserialize)].

Once we have p of type Person, our IDE and the Rust compiler can help us use it correctly like they do for any other Rust code. The IDE can autocomplete field names to prevent typos, which was impossible in the serde_json::Value representation. And the Rust compiler can check that when we write p.phones[0], then p.phones is guaranteed to be a Vec<String> so indexing into it makes sense and produces a String.

The necessary setup for using Serde's derive macros is explained on the Using derive page of the Serde site.

Constructing JSON values

Serde JSON provides a json! macro to build serde_json::Value objects with very natural JSON syntax.

use serde_json::json;

fn main() {
    // The type of `john` is `serde_json::Value`
    let john = json!({
        "name": "John Doe",
        "age": 43,
        "phones": [
            "+44 1234567",
            "+44 2345678"
        ]
    });

    println!("first phone number: {}", john["phones"][0]);

    // Convert to a string of JSON and print it out
    println!("{}", john.to_string());
}

The Value::to_string() function converts a serde_json::Value into a String of JSON text.

One neat thing about the json! macro is that variables and expressions can be interpolated directly into the JSON value as you are building it. Serde will check at compile time that the value you are interpolating is able to be represented as JSON.

let full_name = "John Doe";
let age_last_year = 42;

// The type of `john` is `serde_json::Value`
let john = json!({
    "name": full_name,
    "age": age_last_year + 1,
    "phones": [
        format!("+44 {}", random_phone())
    ]
});

This is amazingly convenient, but we have the problem we had before with Value: the IDE and Rust compiler cannot help us if we get it wrong. Serde JSON provides a better way of serializing strongly-typed data structures into JSON text.

Creating JSON by serializing data structures

A data structure can be converted to a JSON string by serde_json::to_string. There is also serde_json::to_vec which serializes to a Vec<u8> and serde_json::to_writer which serializes to any io::Write such as a File or a TCP stream.

use serde::{Deserialize, Serialize};
use serde_json::Result;

#[derive(Serialize, Deserialize)]
struct Address {
    street: String,
    city: String,
}

fn print_an_address() -> Result<()> {
    // Some data structure.
    let address = Address {
        street: "10 Downing Street".to_owned(),
        city: "London".to_owned(),
    };

    // Serialize it to a JSON string.
    let j = serde_json::to_string(&address)?;

    // Print, write to a file, or send to an HTTP server.
    println!("{}", j);

    Ok(())
}

Any type that implements Serde's Serialize trait can be serialized this way. This includes built-in Rust standard library types like Vec<T> and HashMap<K, V>, as well as any structs or enums annotated with #[derive(Serialize)].

Performance

It is fast. You should expect in the ballpark of 500 to 1000 megabytes per second deserialization and 600 to 900 megabytes per second serialization, depending on the characteristics of your data. This is competitive with the fastest C and C++ JSON libraries or even 30% faster for many use cases. Benchmarks live in the serde-rs/json-benchmark repo.

Getting help

Serde is one of the most widely used Rust libraries, so any place that Rustaceans congregate will be able to help you out. For chat, consider trying the #rust-questions or #rust-beginners channels of the unofficial community Discord (invite: https://discord.gg/rust-lang-community), the #rust-usage or #beginners channels of the official Rust Project Discord (invite: https://discord.gg/rust-lang), or the #general stream in Zulip. For asynchronous, consider the [rust] tag on StackOverflow, the /r/rust subreddit which has a pinned weekly easy questions post, or the Rust Discourse forum. It's acceptable to file a support issue in this repo, but they tend not to get as many eyes as any of the above and may get closed without a response after some time.

No-std support

As long as there is a memory allocator, it is possible to use serde_json without the rest of the Rust standard library. This is supported on Rust 1.36+. Disable the default "std" feature and enable the "alloc" feature:

[dependencies]
serde_json = { version = "1.0", default-features = false, features = ["alloc"] }

For JSON support in Serde without a memory allocator, please see the serde-json-core crate.

Link: https://crates.io/crates/serde_json

#rust  #rustlang  #encode   #json 

Rust Lang Course For Beginner In 2021: Guessing Game

 What we learn in this chapter:
- Rust number types and their default
- First exposure to #Rust modules and the std::io module to read input from the terminal
- Rust Variable Shadowing
- Rust Loop keyword
- Rust if/else
- First exposure to #Rust match keyword

=== Content:
00:00 - Intro & Setup
02:11 - The Plan
03:04 - Variable Secret
04:03 - Number Types
05:45 - Mutability recap
06:22 - Ask the user
07:45 - First intro to module std::io
08:29 - Rust naming conventions
09:22 - Read user input io:stdin().read_line(&mut guess)
12:46 - Break & Understand
14:20 - Parse string to number
17:10 - Variable Shadowing
18:46 - If / Else - You Win, You Loose
19:28 - Loop
20:38 - Match
23:19 - Random with rand
26:35 - Run it all
27:09 - Conclusion and next episode

#rust