Tag Archives: war

TheFatRat – Massive Exploitation Tool

Post Syndicated from Darknet original http://feedproxy.google.com/~r/darknethackers/~3/A3ozOmH4BDE/

TheFatRat is an easy-to-use Exploitation Tool that can help you to generate backdoors and post exploitation attacks like browser attack DLL files. This tool compiles malware with popular payloads and then the compiled malware can be executed on Windows, Linux, Mac OS X and Android. The malware that is created with this tool also has […]

The…

Read the full post at darknet.org.uk

Banning VPNs and Proxies is Dangerous, IT Experts Warn

Post Syndicated from Andy original https://torrentfreak.com/banning-vpns-and-proxies-is-dangerous-it-experts-warn-170623/

In April, draft legislation was developed to crack down on systems and software that allow Russian Internet users to bypass website blockades approved by telecoms watchdog Roskomnadzor.

Earlier this month the draft bill was submitted to the State Duma, the lower house of the Russian parliament. If passed, the law will make it illegal for services to circumvent web blockades by “routing traffic of Russian Internet users through foreign servers, anonymous proxy servers, virtual private networks and other means.”

As the plans currently stand, anonymization services that fail to restrict access to sites listed by telecoms watchdog Rozcomnadzor face being blocked themselves. Sites offering circumvention software for download also face potential blacklisting.

This week the State Duma discussed the proposals with experts from the local Internet industry. In addition to the head of Rozcomnadzor, representatives from service providers, search engines and even anonymization services were in attendance. Novaya Gazeta has published comments (Russian) from some of the key people at the meeting and it’s fair to say there’s not a lot of support.

VimpelCom, the sixth largest mobile network operator in the world with more than 240 million subscribers, sent along Director for Relations with Government, Sergey Malyanov. He wondered where all this blocking will end up.

“First we banned certain information. Then this information was blocked with the responsibility placed on both owners of resources and services. Now there are blocks on top of blocks – so we already have a triple effort,” he said.

“It is now possible that there will be a fourth iteration: the block on the block to block those that were not blocked. And with that, we have significantly complicated the law and the activities of all the people affected by it.”

Malyanov said that these kinds of actions have the potential to close down the entire Internet by ruining what was once an open network running standard protocols. But amid all of this, will it even be effective?

“The question is not even about the losses that will be incurred by network operators, the owners of the resources and the search engines. The question is whether this bill addresses the goal its creators have set for themselves. In my opinion, it will not.”

Group-IB, one of the world’s leading cyber-security and threat intelligence providers, was represented CEO Ilya Sachkov. He told parliament that “ordinary respectable people” who use the Internet should always use a VPN for security. Nevertheless, he also believes that such services should be forced to filter sites deemed illegal by the state.

But in a warning about blocks in general, he warned that people who want to circumvent them will always be one step ahead.

“We have to understand that by the time the law is adopted the perpetrators will already find it very easy to circumvent,” he said.

Mobile operator giant MTS, which turns over billions of dollars and employs 50,000+ people, had their Vice-President of Corporate and Legal Affairs in attendance. Ruslan Ibragimov said that in dealing with a problem, the government should be cautious of not causing more problems, including disruption of a growing VPN market.

“We have an understanding that evil must be fought, but it’s not necessary to create a new evil, even more so – for those who are involved in this struggle,” he said.

“Broad wording of this law may pose a threat to our network, which could be affected by the new restrictive measures, as well as the VPN market, which we are currently developing, and whose potential market is estimated at 50 billion rubles a year.”

In its goal to maintain control of the Internet, it’s clear that Russia is determined to press ahead with legislative change. Unfortunately, it’s far from clear that there’s a technical solution to the problem, but if one is pursued regardless, there could be serious fallout.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

Kotlin and Groovy JVM Languages with AWS Lambda

Post Syndicated from Juan Villa original https://aws.amazon.com/blogs/compute/kotlin-and-groovy-jvm-languages-with-aws-lambda/


Juan Villa – Partner Solutions Architect

 

When most people hear “Java” they think of Java the programming language. Java is a lot more than a programming language, it also implies a larger ecosystem including the Java Virtual Machine (JVM). Java, the programming language, is just one of the many languages that can be compiled to run on the JVM. Some of the most popular JVM languages, other than Java, are Clojure, Groovy, Scala, Kotlin, JRuby, and Jython (see this link for a list of more JVM languages).

Did you know that you can compile and subsequently run all these languages on AWS Lambda?

AWS Lambda supports the Java 8 runtime, but this does not mean you are limited to the Java language. The Java 8 runtime is capable of running JVM languages such as Kotlin and Groovy once they have been compiled and packaged as a “fat” JAR (a JAR file containing all necessary dependencies and classes bundled in).

In this blog post we’ll work through building AWS Lambda functions in both Kotlin and Groovy programming languages. To compile and package our projects we will use Gradle build tool.

To follow along, please clone the Git repository available at GitHub here. Also, I recommend using an Integrated Development Environment (IDE) such as JetBrain’s IntelliJ IDEA, this is the IDE I used while working on these projects.

Kotlin

Kotlin is a statically-typed JVM language designed and developed by JetBrains (one of our Amazon Partner Network Technology partners) and the open source community. Compared to Java the programming language, Kotlin has additional powerful language features such as: Data Classes, Default Arguments, Extensions, Elvis Operator, and Destructuring Declarations. This is a just a short list of Kotlin’s powerful language features. For a more thorough list of features, and how to use them, refer to the full documentation of the Kotlin language.

Let’s jump right into the code and see what an AWS Lambda function looks like in Kotlin.

package com.aws.blog.jvmlangs.kotlin

import java.io.*
import com.fasterxml.jackson.module.kotlin.*

data class HandlerInput(val who: String)
data class HandlerOutput(val message: String)

class Main {
    val mapper = jacksonObjectMapper()

    fun handler(input: InputStream, output: OutputStream): Unit {
        val inputObj = mapper.readValue<HandlerInput>(input)
        mapper.writeValue(output, HandlerOutput("Hello ${inputObj.who}"))
    }
}

The above example is a very simple Hello World application that accepts as an input a JSON object containing a key called “who” and returns a JSON object containing a key called “message” with a value of “Hello {who}”.

AWS Lambda does not support serializing JSON objects into Kotlin data classes, but don’t worry! AWS Lambda supports passing an input object as a Stream, and also supports an output Stream for returning a result (see this link for more information). Combined with the Input/Output Stream form of the handler function, we are using the Jackson library with a Kotlin extension function to support serialization and deserialization of Kotlin data class types.

To get started with this example, let’s first compile and package the Kotlin project.

git clone https://github.com/awslabs/lambda-kotlin-groovy-example
cd lambda-kotlin-groovy-example/kotlin
./gradlew shadowJar

Once packaged, a JAR file containing all necessary dependencies will be available at “build/libs/ jvmlangs-kotlin-1.0-SNAPSHOT-all.jar”. Now let’s deploy this package to AWS Lambda.

To deploy the lambda function, we will be using the AWS Command Line Interface (CLI). You can find information on how to set up the AWS CLI here. This tool allows you to set up and manage AWS services via the command line.

aws lambda create-function --region us-east-1 --function-name kotlin-hello \
--zip-file fileb://build/libs/jvmlangs-kotlin-1.0-SNAPSHOT-all.jar \
--role arn:aws:iam::<account_id>:role/lambda_basic_execution \
--handler com.aws.blog.jvmlangs.kotlin.Main::handler --runtime java8 \
--timeout 15 --memory-size 128

Once deployed, we can test the function by invoking the lambda function from the CLI.

aws lambda invoke --function-name kotlin-hello --payload '{"who": "AWS Fan"}' output.txt
cat output.txt

If successful, you’ll see an output of “{"message":"Hello AWS Fan"}”.

Groovy

Groovy is an optionally typed JVM language with both dynamic and static typing capabilities. Groovy is currently being supported by the Apache Software Foundation. Like Kotlin, Groovy also packs a lot of powerful features such as: Closures, Dynamic Typing, Collection Literals, String Interpolation, and Elvis Operator. This is just a short list, see the full documentation for a list of features and how to use them.

Once again, let’s jump right into the code.

package com.aws.blog.jvmlangs.groovy

class HandlerInput {
    String who
}
class HandlerOutput {
    String message
}

class Main {
    def handler(HandlerInput input) {
        return new HandlerOutput(message: "Hello ${input.who}")
    }
}

Just like the Kotlin example, we have defined a function that takes a simple JSON object containing a “who” key value and build a response containing a “message” key. Note that in this case we are not using the Input/Output Stream form of the handler function, but rather we are letting AWS Lambda serialize the input JSON object into the type HandlerInput. To accomplish this, AWS Lambda uses the Jackson library and handles the serialization for us.

Let’s go ahead and compile and package this Groovy example.

git clone https://github.com/awslabs/lambda-kotlin-groovy-example
cd lambda-kotlin-groovy-example/groovy
./gradlew shadowJar

Once packaged, a JAR file containing all necessary dependencies will be available at “build/libs/ jvmlangs-groovy-1.0-SNAPSHOT-all.jar”. Now let’s deploy this package to AWS Lambda.

aws lambda create-function --region us-east-1 --function-name groovy-hello \
--zip-file fileb://build/libs/jvmlangs-groovy-1.0-SNAPSHOT-all.jar \
--role arn:aws:iam::<account_id>:role/lambda_basic_execution \
--handler com.aws.blog.jvmlangs.groovy.Main::handler --runtime java8 \
--timeout 15 --memory-size 128

Once deployed, we can test the function by invoking the lambda function from the CLI.

aws lambda invoke --function-name groovy-hello --payload '{"who": "AWS Fan"}' output.txt
cat output.txt

If successful, you’ll see an output of “{"message":"Hello AWS Fan"}”.

Gradle Build Tool

Finally, let’s touch up on how we built the JAR package from the Kotlin and Groovy sources above. To build the JARs we used the Gradle build tool. Gradle builds a project by reading instructions from a file called “build.gradle”. This is a file written in Gradle’s Groovy Domain Specific Langauge (DSL). You can find more information on the gradle build file by looking at their documentation. Let’s take a look at the Gradle build files we used for this post.

For the Kotlin example, this is the build file we used.

buildscript {
    repositories {
        mavenCentral()
        jcenter()
    }
    dependencies {
        classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
        classpath "com.github.jengelman.gradle.plugins:shadow:1.2.3"
    }
}

group 'com.aws.blog.jvmlangs.kotlin'
version '1.0-SNAPSHOT'

apply plugin: 'kotlin'
apply plugin: 'com.github.johnrengelman.shadow'

repositories {
    mavenCentral()
}

dependencies {
    compile "org.jetbrains.kotlin:kotlin-stdlib:$kotlin_version"
    compile "com.fasterxml.jackson.module:jackson-module-kotlin:2.8.2"
}

For the Groovy example this is the build file we used.

buildscript {
    repositories {
        jcenter()
    }
    dependencies {
        classpath 'com.github.jengelman.gradle.plugins:shadow:1.2.3'
    }
}

group 'com.aws.blog.jvmlangs.groovy'
version '1.0-SNAPSHOT'

apply plugin: 'groovy'
apply plugin: 'com.github.johnrengelman.shadow'

repositories {
    mavenCentral()
}

dependencies {
    compile 'org.codehaus.groovy:groovy-all:2.3.11'
    testCompile group: 'junit', name: 'junit', version: '4.11'
}

As you can see, the build files for both Kotlin and Groovy files are very similar. For the Kotlin project we define a dependency on the Jackson Kotlin module. Also, for each respective language we include the language supporting libraries (kotlin-stdlib and groovy-all respectively).

In addition, you will notice that we are using a plugin called “shadow”. We use this plugin to package all the project dependencies into one JAR by using the Gradle task “shadowJar”. You can find more information on Shadow in their documentation.

Final Words

Don’t stop here though! Take a look at other JVM languages and get them running on AWS Lambda with the Java 8 runtime. Maybe start with Clojure? or Scala?

Also take a look AWS Lambda Java libraries provided by AWS. They provide interfaces and models to make handling events from event sources easier to handle.

A Raspbian desktop update with some new programming tools

Post Syndicated from Simon Long original https://www.raspberrypi.org/blog/a-raspbian-desktop-update-with-some-new-programming-tools/

Today we’ve released another update to the Raspbian desktop. In addition to the usual small tweaks and bug fixes, the big new changes are the inclusion of an offline version of Scratch 2.0, and of Thonny (a user-friendly IDE for Python which is excellent for beginners). We’ll look at all the changes in this post, but let’s start with the biggest…

Scratch 2.0 for Raspbian

Scratch is one of the most popular pieces of software on Raspberry Pi. This is largely due to the way it makes programming accessible – while it is simple to learn, it covers many of the concepts that are used in more advanced languages. Scratch really does provide a great introduction to programming for all ages.

Raspbian ships with the original version of Scratch, which is now at version 1.4. A few years ago, though, the Scratch team at the MIT Media Lab introduced the new and improved Scratch version 2.0, and ever since we’ve had numerous requests to offer it on the Pi.

There was, however, a problem with this. The original version of Scratch was written in a language called Squeak, which could run on the Pi in a Squeak interpreter. Scratch 2.0, however, was written in Flash, and was designed to run from a remote site in a web browser. While this made Scratch 2.0 a cross-platform application, which you could run without installing any Scratch software, it also meant that you had to be able to run Flash on your computer, and that you needed to be connected to the internet to program in Scratch.

We worked with Adobe to include the Pepper Flash plugin in Raspbian, which enables Flash sites to run in the Chromium browser. This addressed the first of these problems, so the Scratch 2.0 website has been available on Pi for a while. However, it still needed an internet connection to run, which wasn’t ideal in many circumstances. We’ve been working with the Scratch team to get an offline version of Scratch 2.0 running on Pi.

Screenshot of Scratch on Raspbian

The Scratch team had created a website to enable developers to create hardware and software extensions for Scratch 2.0; this provided a version of the Flash code for the Scratch editor which could be modified to run locally rather than over the internet. We combined this with a program called Electron, which effectively wraps up a local web page into a standalone application. We ended up with the Scratch 2.0 application that you can find in the Programming section of the main menu.

Physical computing with Scratch 2.0

We didn’t stop there though. We know that people want to use Scratch for physical computing, and it has always been a bit awkward to access GPIO pins from Scratch. In our Scratch 2.0 application, therefore, there is a custom extension which allows the user to control the Pi’s GPIO pins without difficulty. Simply click on ‘More Blocks’, choose ‘Add an Extension’, and select ‘Pi GPIO’. This loads two new blocks, one to read and one to write the state of a GPIO pin.

Screenshot of new Raspbian iteration of Scratch 2, featuring GPIO pin control blocks.

The Scratch team kindly allowed us to include all the sprites, backdrops, and sounds from the online version of Scratch 2.0. You can also use the Raspberry Pi Camera Module to create new sprites and backgrounds.

This first release works well, although it can be slow for some operations; this is largely unavoidable for Flash code running under Electron. Bear in mind that you will need to have the Pepper Flash plugin installed (which it is by default on standard Raspbian images). As Pepper Flash is only compatible with the processor in the Pi 2.0 and Pi 3, it is unfortunately not possible to run Scratch 2.0 on the Pi Zero or the original models of the Pi.

We hope that this makes Scratch 2.0 a more practical proposition for many users than it has been to date. Do let us know if you hit any problems, though!

Thonny: a more user-friendly IDE for Python

One of the paths from Scratch to ‘real’ programming is through Python. We know that the transition can be awkward, and this isn’t helped by the tools available for learning Python. It’s fair to say that IDLE, the Python IDE, isn’t the most popular piece of software ever written…

Earlier this year, we reviewed every Python IDE that we could find that would run on a Raspberry Pi, in an attempt to see if there was something better out there than IDLE. We wanted to find something that was easier for beginners to use but still useful for experienced Python programmers. We found one program, Thonny, which stood head and shoulders above all the rest. It’s a really user-friendly IDE, which still offers useful professional features like single-stepping of code and inspection of variables.

Screenshot of Thonny IDE in Raspbian

Thonny was created at the University of Tartu in Estonia; we’ve been working with Aivar Annamaa, the lead developer, on getting it into Raspbian. The original version of Thonny works well on the Pi, but because the GUI is written using Python’s default GUI toolkit, Tkinter, the appearance clashes with the rest of the Raspbian desktop, most of which is written using the GTK toolkit. We made some changes to bring things like fonts and graphics into line with the appearance of our other apps, and Aivar very kindly took that work and converted it into a theme package that could be applied to Thonny.

Due to the limitations of working within Tkinter, the result isn’t exactly like a native GTK application, but it’s pretty close. It’s probably good enough for anyone who isn’t a picky UI obsessive like me, anyway! Have a look at the Thonny webpage to see some more details of all the cool features it offers. We hope that having a more usable environment will help to ease the transition from graphical languages like Scratch into ‘proper’ languages like Python.

New icons

Other than these two new packages, this release is mostly bug fixes and small version bumps. One thing you might notice, though, is that we’ve made some tweaks to our custom icon set. We wondered if the icons might look better with slightly thinner outlines. We tried it, and they did: we hope you prefer them too.

Downloading the new image

You can either download a new image from the Downloads page, or you can use apt to update:

sudo apt-get update
sudo apt-get dist-upgrade

To install Scratch 2.0:

sudo apt-get install scratch2

To install Thonny:

sudo apt-get install python3-thonny

One more thing…

Before Christmas, we released an experimental version of the desktop running on Debian for x86-based computers. We were slightly taken aback by how popular it turned out to be! This made us realise that this was something we were going to need to support going forward. We’ve decided we’re going to try to make all new desktop releases for both Pi and x86 from now on.

The version of this we released last year was a live image that could run from a USB stick. Many people asked if we could make it permanently installable, so this version includes an installer. This uses the standard Debian install process, so it ought to work on most machines. I should stress, though, that we haven’t been able to test on every type of hardware, so there may be issues on some computers. Please be sure to back up your hard drive before installing it. Unlike the live image, this will erase and reformat your hard drive, and you will lose anything that is already on it!

You can still boot the image as a live image if you don’t want to install it, and it will create a persistence partition on the USB stick so you can save data. Just select ‘Run with persistence’ from the boot menu. To install, choose either ‘Install’ or ‘Graphical install’ from the same menu. The Debian installer will then walk you through the install process.

You can download the latest x86 image (which includes both Scratch 2.0 and Thonny) from here or here for a torrent file.

One final thing

This version of the desktop is based on Debian Jessie. Some of you will be aware that a new stable version of Debian (called Stretch) was released last week. Rest assured – we have been working on porting everything across to Stretch for some time now, and we will have a Stretch release ready some time over the summer.

The post A Raspbian desktop update with some new programming tools appeared first on Raspberry Pi.

Sci-Hub Ordered to Pay $15 Million in Piracy Damages

Post Syndicated from Ernesto original https://torrentfreak.com/sci-hub-ordered-to-pay-15-million-in-piracy-damages-170623/

Two years ago, academic publisher Elsevier filed a complaint against Sci-Hub and several related “pirate” sites.

It accused the websites of making academic papers widely available to the public, without permission.

While Sci-Hub is nothing like the average pirate site, it is just as illegal according to Elsevier’s legal team, who obtained a preliminary injunction from a New York District Court last fall.

The injunction ordered Sci-Hub’s founder Alexandra Elbakyan to quit offering access to any Elsevier content. However, this didn’t happen.

Instead of taking Sci-Hub down, the lawsuit achieved the opposite. Sci-Hub grew bigger and bigger up to a point where its users were downloading hundreds of thousands of papers per day.

Although Elbakyan sent a letter to the court earlier, she opted not engage in the US lawsuit any further. The same is true for her fellow defendants, associated with Libgen. As a result, Elsevier asked the court for a default judgment and a permanent injunction which were issued this week.

Following a hearing on Wednesday, the Court awarded Elsevier $15,000,000 in damages, the maximum statutory amount for the 100 copyrighted works that were listed in the complaint. In addition, the injunction, through which Sci-Hub and LibGen lost several domain names, was made permanent.

Sci-Hub founder Alexandra Elbakyan says that even if she wanted to pay the millions of dollars in revenue, she doesn’t have the money to do so.

“The money project received and spent in about six years of its operation do not add up to 15 million,” Elbakyan tells torrentFreak.

“More interesting, Elsevier says: the Sci-Hub activity ’causes irreparable injury to Elsevier, its customers and the public’ and US court agreed. That feels like a perfect crime. If you want to cause an irreparable injury to American public, what do you have to do? Now we know the answer: establish a website where they can read research articles for free,” she adds.

Previously, Elbakyan already confirmed to us that, lawsuit or not, the site is not going anywhere.

“The Sci-Hub will continue as usual. In case of problems with the domain names, users can rely on TOR scihub22266oqcxt.onion,” Elbakyan added.

Sci-Hub is regularly referred to as the “Pirate Bay for science,” and based on the site’s resilience and its response to legal threats, it can certainly live up to this claim.

The Association of American Publishers (AAP) is happy with the outcome of the case.

“As the final judgment shows, the Court has not mistaken illegal activity for a public good,” AAP President and CEO Maria A. Pallante says.

“On the contrary, it has recognized the defendants’ operation for the flagrant and sweeping infringement that it really is and affirmed the critical role of copyright law in furthering scientific research and the public interest.”

Matt McKay, a spokesperson for the International Association of Scientific, Technical and Medical Publishers (STM) in Oxford went even further, telling Nature that the site doesn’t offer any value to the scientific comunity.

“Sci-Hub does not add any value to the scholarly community. It neither fosters scientific advancement nor does it value researchers’ achievements. It is simply a place for someone to go to download stolen content and then leave.”

Hundreds of thousands of academics, who regularly use the site to download papers, might contest this though.

With no real prospect of recouping the damages and an ever-resilient Elbakyan, Elsevier’s legal battle could just be a win on paper. Sci-Hub and Libgen are not going anywhere, it seems, and the lawsuit has made them more popular than ever before.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

digiKam 5.6.0 is released

Post Syndicated from ris original https://lwn.net/Articles/726278/rss

The digiKam Team has released
version 5.6.0 of the digiKam Software Collection for photo management. “With this version the HTML gallery and the video slideshow tools are back, database shrinking (e.g. purging stale thumbnails) is also supported on MySQL, grouping items feature has been improved, the support for custom sidecars type-mime have been added, the geolocation bookmarks introduce fixes to be fully functional with bundles, the support for custom sidecars, and of course a lots of bug has been fixed.

From Idea to Launch: Getting Your First Customers

Post Syndicated from Gleb Budman original https://www.backblaze.com/blog/how-to-get-your-first-customers/

line outside of Apple

After deciding to build an unlimited backup service and developing our own storage platform, the next step was to get customers and feedback. Not all customers are created equal. Let’s talk about the types, and when and how to attract them.

How to Get Your First Customers

First Step – Don’t Launch Publicly
Launch when you’re ready for the judgments of people who don’t know you at all. Until then, don’t launch. Sign up users and customers either that you know, those you can trust to cut you some slack (while providing you feedback), or at minimum those for whom you can set expectations. For months the Backblaze website was a single page with no ability to get the product and minimal info on what it would be. This is not to counter the Lean Startup ‘iterate quickly with customer feedback’ advice. Rather, this is an acknowledgement that there are different types of feedback required based on your development stage.

Sign Up Your Friends
We knew all of our first customers; they were friends, family, and previous co-workers. Many knew what we were up to and were excited to help us. No magic marketing or tech savviness was required to reach them – we just asked that they try the service. We asked them to provide us feedback on their experience and collected it through email and conversations. While the feedback wasn’t unbiased, it was nonetheless wide-ranging, real, and often insightful. These people were willing to spend time carefully thinking about their feedback and delving deeper into the conversations.

Broaden to Beta
Unless you’re famous or your service costs $1 million per customer, you’ll probably need to expand quickly beyond your friends to build a business – and to get broader feedback. Our next step was to broaden the customer base to beta users.

Opening up the service in beta provides three benefits:

  1. Air cover for the early warts. There are going to be issues, bugs, unnecessarily complicated user flows, and poorly worded text. Beta tells people, “We don’t consider the product ‘done’ and you should expect some of these issues. Please be patient with us.”
  2. A request for feedback. Some people always provide feedback, but beta communicates that you want it.
  3. An awareness opportunity. Opening up in beta provides an early (but not only) opportunity to have an announcement and build awareness.

Pitching Beta to Press
Not all press cares about, or is even willing to cover, beta products. Much of the mainstream press wants to write about services that are fully live, have scale, and are important in the marketplace. However, there are a number of sites that like to cover the leading edge – and that means covering betas. Techcrunch, Ars Technica, and SimpleHelp covered our initial private beta launch. I’ll go into the details of how to work with the press to cover your announcements in a post next month.

Private vs. Public Beta
Both private and public beta provide all three of the benefits above. The difference between the two is that private betas are much more controlled, whereas public ones bring in more users. But this isn’t an either/or – I recommend doing both.

Private Beta
For our original beta in 2008, we decided that we were comfortable with about 1,000 users subscribing to our service. That would provide us with a healthy amount of feedback and get some early adoption, while not overwhelming us or our server capacity, and equally important not causing cash flow issues from having to buy more equipment. So we decided to limit the sign-up to only the first 1,000 people who signed up; then we would shut off sign-ups for a while.

But how do you even get 1,000 people to sign up for your service? In our case, get some major publications to write about our beta. (Note: In a future post I’ll explain exactly how to find and reach out to writers. Sign up to receive all of the entrepreneurial posts in this series.)

Public Beta
For our original service (computer backup), we did not have a public beta; but when we launched Backblaze B2, we had a private and then a public beta. The private beta allowed us to work out early kinks, while the public beta brought us a more varied set of use cases. In public beta, there is no cap on the number of users that may try the service.

While this is a first-class problem to have, if your service is flooded and stops working, it’s still a problem. Think through what you will do if that happens. In our early days, when our system could get overwhelmed by volume, we had a static web page hosted with a different registrar that wouldn’t let customers sign up but would tell them when our service would be open again. When we reached a critical volume level we would redirect to it in order to at least provide status for when we could accept more customers.

Collect Feedback
Since one of the goals of betas is to get feedback, we made sure that we had our email addresses clearly presented on the site so users could send us thoughts. We were most interested in broad qualitative feedback on users’ experience, so all emails went to an internal mailing list that would be read by everyone at Backblaze.

For our B2 public and private betas, we also added an optional short survey to the sign-up process. In order to be considered for the private beta you had to fill the survey out, though we found that 80% of users continued to fill out the survey even when it was not required. This survey had both closed-end questions (“how much data do you have”) and open-ended ones (“what do you want to use cloud storage for?”).

BTW, despite us getting a lot of feedback now via our support team, Twitter, and marketing surveys, we are always open to more – you can email me directly at gleb.budman {at} backblaze.com.

Don’t Throw Away Users
Initially our backup service was available only on Windows, but we had an email sign-up list for people who wanted it for their Mac. This provided us with a sense of market demand and a ready list of folks who could be beta users and early adopters when we had a Mac version. Have a service targeted at doctors but lawyers are expressing interest? Capture that.

Product Launch

When
The first question is “when” to launch. Presuming your service is in ‘public beta’, what is the advantage of moving out of beta and into a “version 1.0”, “gold”, or “public availability”? That depends on your service and customer base. Some services fly through public beta. Gmail, on the other hand, was (in)famous for being in beta for 5 years, despite having over 100 million users.

The term beta says to users, “give us some leeway, but feel free to use the service”. That’s fine for many consumer apps and will have near zero impact on them. However, services aimed at businesses and government will often not be adopted with a beta label as the enterprise customers want to know the company feels the service is ‘ready’. While Backblaze started out as a purely consumer service, because it was a data backup service, it was important for customers to trust that the service was ready.

No product is bug-free. But from a product readiness perspective, the nomenclature should also be a reflection of the quality of the product. You can launch a product with one feature that works well out of beta. But a product with fifty features on which half the users will bump into problems should likely stay in beta. The customer feedback, surveys, and your own internal testing should guide you in determining this quality during the beta. Be careful about “we’ve only seen that one time” or “I haven’t been able to reproduce that on my machine”; those issues are likely to scale with customers when you launch.

How
Launching out of beta can be as simple as removing the beta label from the website/product. However, this can be a great time to reach out to press, write a blog post, and send an email announcement to your customers.

Consider thanking your beta testers somehow; can they get some feature turned out for free, an extension of their trial, or premium support? If nothing else, remember to thank them for their feedback. Users that signed up during your beta are likely the ones who will propel your service. They had the need and interest to both be early adopters and deal with bugs. They are likely the key to getting 1,000 true fans.

The Beginning
The title of this post was “Getting your first customers”, because getting to launch may feel like the peak of your journey when you’re pre-launch, but it really is just the beginning. It’s a step along the journey of building your business. If your launch is wildly successful, enjoy it, work to build on the momentum, but don’t lose track of building your business. If your launch is a dud, go out for a coffee with your team, say “well that sucks”, and then get back to building your business. You can learn a tremendous amount from your early customers, and they can become your biggest fans, but the success of your business will depend on what you continue to do the months and years after your launch.

The post From Idea to Launch: Getting Your First Customers appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

Kim Dotcom Opposes US’s “Fugitive” Claims at Supreme Court

Post Syndicated from Ernesto original https://torrentfreak.com/kim-dotcom-opposes-uss-fugitive-claims-supreme-court-170622/

megaupload-logoWhen Megaupload and Kim Dotcom were raided five years ago, the authorities seized millions of dollars in cash and other property.

The US government claimed the assets were obtained through copyright crimes so went after the bank accounts, cars, and other seized possessions of the Megaupload defendants.

Kim Dotcom and his colleagues were branded as “fugitives” and the Government won its case. Dotcom’s legal team quickly appealed this verdict, but lost once more at the Fourth Circuit appeals court.

A few weeks ago Dotcom and his former colleagues petitioned the Supreme Court to take on the case.

They don’t see themselves as “fugitives” and want the assets returned. The US Government opposed the request, but according to a new reply filed by Megaupload’s legal team, the US Government ignores critical questions.

The Government has a “vested financial stake” in maintaining the current situation, they write, which allows the authorities to use their “fugitive” claims as an offensive weapon.

“Far from being directed towards persons who have fled or avoided our country while claiming assets in it, fugitive disentitlement is being used offensively to strip foreigners of their assets abroad,” the reply brief (pdf) reads.

According to Dotcom’s lawyers there are several conflicting opinions from lower courts, which should be clarified by the Supreme Court. That Dotcom and his colleagues have decided to fight their extradition in New Zealand, doesn’t warrant the seizure of their assets.

“Absent review, forfeiture of tens of millions of dollars will be a fait accompli without the merits being reached,” they write, adding that this is all the more concerning because the US Government’s criminal case may not be as strong as claimed.

“This is especially disconcerting because the Government’s criminal case is so dubious. When the Government characterizes Petitioners as ‘designing and profiting from a system that facilitated wide-scale copyright infringement,’ it continues to paint a portrait of secondary copyright infringement, which is not a crime.”

The defense team cites several issues that warrant review and urges the Supreme Court to hear the case. If not, the Government will effectively be able to use assets seizures as a pressure tool to urge foreign defendants to come to the US.

“If this stands, the Government can weaponize fugitive disentitlement in order to claim assets abroad,” the reply brief reads.

“It is time for the Court to speak to the Questions Presented. Over the past two decades it has never had a better vehicle to do so, nor is any such vehicle elsewhere in sight,” Dotcom’s lawyers add.

Whether the Supreme Court accepts or denies the case will likely be decided in the weeks to come.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

Security updates for Thursday

Post Syndicated from jake original https://lwn.net/Articles/726234/rss

Security updates have been issued by Arch Linux (lxterminal, lxterminal-gtk3, openvpn, and pcmanfm), CentOS (thunderbird), Debian (jython, spip, tomcat7, and tomcat8), openSUSE (openvpn), Oracle (thunderbird), Slackware (openvpn), SUSE (openvpn), and Ubuntu (kernel, linux-lts-trusty, nss, and valgrind).

CoderDojo Coolest Projects 2017

Post Syndicated from Ben Nuttall original https://www.raspberrypi.org/blog/coderdojo-coolest-projects-2017/

When I heard we were merging with CoderDojo, I was delighted. CoderDojo is a wonderful organisation with a spectacular community, and it’s going to be great to join forces with the team and work towards our common goal: making a difference to the lives of young people by making technology accessible to them.

You may remember that last year Philip and I went along to Coolest Projects, CoderDojo’s annual event at which their global community showcase their best makes. It was awesome! This year a whole bunch of us from the Raspberry Pi Foundation attended Coolest Projects with our new Irish colleagues, and as expected, the projects on show were as cool as can be.

Coolest Projects 2017 attendee

Crowd at Coolest Projects 2017

This year’s coolest projects!

Young maker Benjamin demoed his brilliant RGB LED table tennis ball display for us, and showed off his brilliant project tutorial website codemakerbuddy.com, which he built with Python and Flask. [Click on any of the images to enlarge them.]

Coolest Projects 2017 LED ping-pong ball display
Coolest Projects 2017 Benjamin and Oly

Next up, Aimee showed us a recipes app she’d made with the MIT App Inventor. It was a really impressive and well thought-out project.

Coolest Projects 2017 Aimee's cook book
Coolest Projects 2017 Aimee's setup

This very successful OpenCV face detection program with hardware installed in a teddy bear was great as well:

Coolest Projects 2017 face detection bear
Coolest Projects 2017 face detection interface
Coolest Projects 2017 face detection database

Helen’s and Oly’s favourite project involved…live bees!

Coolest Projects 2017 live bees

BEEEEEEEEEEES!

Its creator, 12-year-old Amy, said she wanted to do something to help the Earth. Her project uses various sensors to record data on the bee population in the hive. An adjacent monitor displays the data in a web interface:

Coolest Projects 2017 Aimee's bees

Coolest robots

I enjoyed seeing lots of GPIO Zero projects out in the wild, including this robotic lawnmower made by Kevin and Zach:

Raspberry Pi Lawnmower

Kevin and Zach’s Raspberry Pi lawnmower project with Python and GPIO Zero, showed at CoderDojo Coolest Projects 2017

Philip’s favourite make was a Pi-powered robot you can control with your mind! According to the maker, Laura, it worked really well with Philip because he has no hair.

Philip Colligan on Twitter

This is extraordinary. Laura from @CoderDojo Romania has programmed a mind controlled robot using @Raspberry_Pi @coolestprojects

And here are some pictures of even more cool robots we saw:

Coolest Projects 2017 coolest robot no.1
Coolest Projects 2017 coolest robot no.2
Coolest Projects 2017 coolest robot no.3

Games, toys, activities

Oly and I were massively impressed with the work of Mogamad, Daniel, and Basheerah, who programmed a (borrowed) Amazon Echo to make a voice-controlled text-adventure game using Java and the Alexa API. They’ve inspired me to try something similar using the AIY projects kit and adventurelib!

Coolest Projects 2017 Mogamad, Daniel, Basheerah, Oly
Coolest Projects 2017 Alexa text-based game

Christopher Hill did a brilliant job with his Home Alone LEGO house. He used sensors to trigger lights and sounds to make it look like someone’s at home, like in the film. I should have taken a video – seeing it in action was great!

Coolest Projects 2017 Lego home alone house
Coolest Projects 2017 Lego home alone innards
Coolest Projects 2017 Lego home alone innards closeup

Meanwhile, the Northern Ireland Raspberry Jam group ran a DOTS board activity, which turned their area into a conductive paint hazard zone.

Coolest Projects 2017 NI Jam DOTS activity 1
Coolest Projects 2017 NI Jam DOTS activity 2
Coolest Projects 2017 NI Jam DOTS activity 3
Coolest Projects 2017 NI Jam DOTS activity 4
Coolest Projects 2017 NI Jam DOTS activity 5
Coolest Projects 2017 NI Jam DOTS activity 6

Creativity and ingenuity

We really enjoyed seeing so many young people collaborating, experimenting, and taking full advantage of the opportunity to make real projects. And we loved how huge the range of technologies in use was: people employed all manner of hardware and software to bring their ideas to life.

Philip Colligan on Twitter

Wow! Look at that room full of awesome young people. @coolestprojects #coolestprojects @CoderDojo

Congratulations to the Coolest Projects 2017 prize winners, and to all participants. Here are some of the teams that won in the different categories:

Coolest Projects 2017 winning team 1
Coolest Projects 2017 winning team 2
Coolest Projects 2017 winning team 3

Take a look at the gallery of all winners over on Flickr.

The wow factor

Raspberry Pi co-founder and Foundation trustee Pete Lomas came along to the event as well. Here’s what he had to say:

It’s hard to describe the scale of the event, and photos just don’t do it justice. The first thing that hit me was the sheer excitement of the CoderDojo ninjas [the children attending Dojos]. Everyone was setting up for their time with the project judges, and their pure delight at being able to show off their creations was evident in both halls. Time and time again I saw the ninjas apply their creativity to help save the planet or make someone’s life better, and it’s truly exciting that we are going to help that continue and expand.

Even after 8 hours, enthusiasm wasn’t flagging – the awards ceremony was just brilliant, with ninjas high-fiving the winners on the way to the stage. This speaks volumes about the ethos and vision of the CoderDojo founders, where everyone is a winner just by being part of a community of worldwide friends. It was a brilliant introduction, and if this weekend was anything to go by, our merger certainly is a marriage made in Heaven.

Join this awesome community!

If all this inspires you as much as it did us, consider looking for a CoderDojo near you – and sign up as a volunteer! There’s plenty of time for young people to build up skills and start working on a project for next year’s event. Check out coolestprojects.com for more information.

The post CoderDojo Coolest Projects 2017 appeared first on Raspberry Pi.

NSA Insider Security Post-Snowden

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/06/nsa_insider_sec.html

According to a recently declassified report obtained under FOIA, the NSA’s attempts to protect itself against insider attacks aren’t going very well:

The N.S.A. failed to consistently lock racks of servers storing highly classified data and to secure data center machine rooms, according to the report, an investigation by the Defense Department’s inspector general completed in 2016.

[…]

The agency also failed to meaningfully reduce the number of officials and contractors who were empowered to download and transfer data classified as top secret, as well as the number of “privileged” users, who have greater power to access the N.S.A.’s most sensitive computer systems. And it did not fully implement software to monitor what those users were doing.

In all, the report concluded, while the post-Snowden initiative — called “Secure the Net” by the N.S.A. — had some successes, it “did not fully meet the intent of decreasing the risk of insider threats to N.S.A. operations and the ability of insiders to exfiltrate data.”

Marcy Wheeler comments:

The IG report examined seven of the most important out of 40 “Secure the Net” initiatives rolled out since Snowden began leaking classified information. Two of the initiatives aspired to reduce the number of people who had the kind of access Snowden did: those who have privileged access to maintain, configure, and operate the NSA’s computer systems (what the report calls PRIVACs), and those who are authorized to use removable media to transfer data to or from an NSA system (what the report calls DTAs).

But when DOD’s inspectors went to assess whether NSA had succeeded in doing this, they found something disturbing. In both cases, the NSA did not have solid documentation about how many such users existed at the time of the Snowden leak. With respect to PRIVACs, in June 2013 (the start of the Snowden leak), “NSA officials stated that they used a manually kept spreadsheet, which they no longer had, to identify the initial number of privileged users.” The report offered no explanation for how NSA came to no longer have that spreadsheet just as an investigation into the biggest breach thus far at NSA started. With respect to DTAs, “NSA did not know how many DTAs it had because the manually kept list was corrupted during the months leading up to the security breach.”

There seem to be two possible explanations for the fact that the NSA couldn’t track who had the same kind of access that Snowden exploited to steal so many documents. Either the dog ate their homework: Someone at NSA made the documents unavailable (or they never really existed). Or someone fed the dog their homework: Some adversary made these lists unusable. The former would suggest the NSA had something to hide as it prepared to explain why Snowden had been able to walk away with NSA’s crown jewels. The latter would suggest that someone deliberately obscured who else in the building might walk away with the crown jewels. Obscuring that list would be of particular value if you were a foreign adversary planning on walking away with a bunch of files, such as the set of hacking tools the Shadow Brokers have since released, which are believed to have originated at NSA.

Read the whole thing. Securing against insiders, especially those with technical access, is difficult, but I had assumed the NSA did more post-Snowden.

How to Create an AMI Builder with AWS CodeBuild and HashiCorp Packer – Part 2

Post Syndicated from Heitor Lessa original https://aws.amazon.com/blogs/devops/how-to-create-an-ami-builder-with-aws-codebuild-and-hashicorp-packer-part-2/

Written by AWS Solutions Architects Jason Barto and Heitor Lessa

 
In Part 1 of this post, we described how AWS CodeBuild, AWS CodeCommit, and HashiCorp Packer can be used to build an Amazon Machine Image (AMI) from the latest version of Amazon Linux. In this post, we show how to use AWS CodePipeline, AWS CloudFormation, and Amazon CloudWatch Events to continuously ship new AMIs. We use Ansible by Red Hat to harden the OS on the AMIs through a well-known set of security controls outlined by the Center for Internet Security in its CIS Amazon Linux Benchmark.

You’ll find the source code for this post in our GitHub repo.

At the end of this post, we will have the following architecture:

Requirements

 
To follow along, you will need Git and a text editor. Make sure Git is configured to work with AWS CodeCommit, as described in Part 1.

Technologies

 
In addition to the services and products used in Part 1 of this post, we also use these AWS services and third-party software:

AWS CloudFormation gives developers and systems administrators an easy way to create and manage a collection of related AWS resources, provisioning and updating them in an orderly and predictable fashion.

Amazon CloudWatch Events enables you to react selectively to events in the cloud and in your applications. Specifically, you can create CloudWatch Events rules that match event patterns, and take actions in response to those patterns.

AWS CodePipeline is a continuous integration and continuous delivery service for fast and reliable application and infrastructure updates. AWS CodePipeline builds, tests, and deploys your code every time there is a code change, based on release process models you define.

Amazon SNS is a fast, flexible, fully managed push notification service that lets you send individual messages or to fan out messages to large numbers of recipients. Amazon SNS makes it simple and cost-effective to send push notifications to mobile device users or email recipients. The service can even send messages to other distributed services.

Ansible is a simple IT automation system that handles configuration management, application deployment, cloud provisioning, ad-hoc task-execution, and multinode orchestration.

Getting Started

 
We use CloudFormation to bootstrap the following infrastructure:

Component Purpose
AWS CodeCommit repository Git repository where the AMI builder code is stored.
S3 bucket Build artifact repository used by AWS CodePipeline and AWS CodeBuild.
AWS CodeBuild project Executes the AWS CodeBuild instructions contained in the build specification file.
AWS CodePipeline pipeline Orchestrates the AMI build process, triggered by new changes in the AWS CodeCommit repository.
SNS topic Notifies subscribed email addresses when an AMI build is complete.
CloudWatch Events rule Defines how the AMI builder should send a custom event to notify an SNS topic.
Region AMI Builder Launch Template
N. Virginia (us-east-1)
Ireland (eu-west-1)

After launching the CloudFormation template linked here, we will have a pipeline in the AWS CodePipeline console. (Failed at this stage simply means we don’t have any data in our newly created AWS CodeCommit Git repository.)

Next, we will clone the newly created AWS CodeCommit repository.

If this is your first time connecting to a AWS CodeCommit repository, please see instructions in our documentation on Setup steps for HTTPS Connections to AWS CodeCommit Repositories.

To clone the AWS CodeCommit repository (console)

  1. From the AWS Management Console, open the AWS CloudFormation console.
  2. Choose the AMI-Builder-Blogpost stack, and then choose Output.
  3. Make a note of the Git repository URL.
  4. Use git to clone the repository.

For example: git clone https://git-codecommit.eu-west-1.amazonaws.com/v1/repos/AMI-Builder_repo

To clone the AWS CodeCommit repository (CLI)

# Retrieve CodeCommit repo URL
git_repo=$(aws cloudformation describe-stacks --query 'Stacks[0].Outputs[?OutputKey==`GitRepository`].OutputValue' --output text --stack-name "AMI-Builder-Blogpost")

# Clone repository locally
git clone ${git_repo}

Bootstrap the Repo with the AMI Builder Structure

 
Now that our infrastructure is ready, download all the files and templates required to build the AMI.

Your local Git repo should have the following structure:

.
├── ami_builder_event.json
├── ansible
├── buildspec.yml
├── cloudformation
├── packer_cis.json

Next, push these changes to AWS CodeCommit, and then let AWS CodePipeline orchestrate the creation of the AMI:

git add .
git commit -m "My first AMI"
git push origin master

AWS CodeBuild Implementation Details

 
While we wait for the AMI to be created, let’s see what’s changed in our AWS CodeBuild buildspec.yml file:

...
phases:
  ...
  build:
    commands:
      ...
      - ./packer build -color=false packer_cis.json | tee build.log
  post_build:
    commands:
      - egrep "${AWS_REGION}\:\sami\-" build.log | cut -d' ' -f2 > ami_id.txt
      # Packer doesn't return non-zero status; we must do that if Packer build failed
      - test -s ami_id.txt || exit 1
      - sed -i.bak "s/<<AMI-ID>>/$(cat ami_id.txt)/g" ami_builder_event.json
      - aws events put-events --entries file://ami_builder_event.json
      ...
artifacts:
  files:
    - ami_builder_event.json
    - build.log
  discard-paths: yes

In the build phase, we capture Packer output into a file named build.log. In the post_build phase, we take the following actions:

  1. Look up the AMI ID created by Packer and save its findings to a temporary file (ami_id.txt).
  2. Forcefully make AWS CodeBuild to fail if the AMI ID (ami_id.txt) is not found. This is required because Packer doesn’t fail if something goes wrong during the AMI creation process. We have to tell AWS CodeBuild to stop by informing it that an error occurred.
  3. If an AMI ID is found, we update the ami_builder_event.json file and then notify CloudWatch Events that the AMI creation process is complete.
  4. CloudWatch Events publishes a message to an SNS topic. Anyone subscribed to the topic will be notified in email that an AMI has been created.

Lastly, the new artifacts phase instructs AWS CodeBuild to upload files built during the build process (ami_builder_event.json and build.log) to the S3 bucket specified in the Outputs section of the CloudFormation template. These artifacts can then be used as an input artifact in any later stage in AWS CodePipeline.

For information about customizing the artifacts sequence of the buildspec.yml, see the Build Specification Reference for AWS CodeBuild.

CloudWatch Events Implementation Details

 
CloudWatch Events allow you to extend the AMI builder to not only send email after the AMI has been created, but to hook up any of the supported targets to react to the AMI builder event. This event publication means you can decouple from Packer actions you might take after AMI completion and plug in other actions, as you see fit.

For more information about targets in CloudWatch Events, see the CloudWatch Events API Reference.

In this case, CloudWatch Events should receive the following event, match it with a rule we created through CloudFormation, and publish a message to SNS so that you can receive an email.

Example CloudWatch custom event

[
        {
            "Source": "com.ami.builder",
            "DetailType": "AmiBuilder",
            "Detail": "{ \"AmiStatus\": \"Created\"}",
            "Resources": [ "ami-12cd5guf" ]
        }
]

Cloudwatch Events rule

{
  "detail-type": [
    "AmiBuilder"
  ],
  "source": [
    "com.ami.builder"
  ],
  "detail": {
    "AmiStatus": [
      "Created"
    ]
  }
}

Example SNS message sent in email

{
    "version": "0",
    "id": "f8bdede0-b9d7...",
    "detail-type": "AmiBuilder",
    "source": "com.ami.builder",
    "account": "<<aws_account_number>>",
    "time": "2017-04-28T17:56:40Z",
    "region": "eu-west-1",
    "resources": ["ami-112cd5guf "],
    "detail": {
        "AmiStatus": "Created"
    }
}

Packer Implementation Details

 
In addition to the build specification file, there are differences between the current version of the HashiCorp Packer template (packer_cis.json) and the one used in Part 1.

Variables

  "variables": {
    "vpc": "{{env `BUILD_VPC_ID`}}",
    "subnet": "{{env `BUILD_SUBNET_ID`}}",
         “ami_name”: “Prod-CIS-Latest-AMZN-{{isotime \”02-Jan-06 03_04_05\”}}”
  },
  • ami_name: Prefixes a name used by Packer to tag resources during the Builders sequence.
  • vpc and subnet: Environment variables defined by the CloudFormation stack parameters.

We no longer assume a default VPC is present and instead use the VPC and subnet specified in the CloudFormation parameters. CloudFormation configures the AWS CodeBuild project to use these values as environment variables. They are made available throughout the build process.

That allows for more flexibility should you need to change which VPC and subnet will be used by Packer to launch temporary resources.

Builders

  "builders": [{
    ...
    "ami_name": “{{user `ami_name`| clean_ami_name}}”,
    "tags": {
      "Name": “{{user `ami_name`}}”,
    },
    "run_tags": {
      "Name": “{{user `ami_name`}}",
    },
    "run_volume_tags": {
      "Name": “{{user `ami_name`}}",
    },
    "snapshot_tags": {
      "Name": “{{user `ami_name`}}",
    },
    ...
    "vpc_id": "{{user `vpc` }}",
    "subnet_id": "{{user `subnet` }}"
  }],

We now have new properties (*_tag) and a new function (clean_ami_name) and launch temporary resources in a VPC and subnet specified in the environment variables. AMI names can only contain a certain set of ASCII characters. If the input in project deviates from the expected characters (for example, includes whitespace or slashes), Packer’s clean_ami_name function will fix it.

For more information, see functions on the HashiCorp Packer website.

Provisioners

  "provisioners": [
    {
        "type": "shell",
        "inline": [
            "sudo pip install ansible"
        ]
    }, 
    {
        "type": "ansible-local",
        "playbook_file": "ansible/playbook.yaml",
        "role_paths": [
            "ansible/roles/common"
        ],
        "playbook_dir": "ansible",
        "galaxy_file": "ansible/requirements.yaml"
    },
    {
      "type": "shell",
      "inline": [
        "rm .ssh/authorized_keys ; sudo rm /root/.ssh/authorized_keys"
      ]
    }

We used shell provisioner to apply OS patches in Part 1. Now, we use shell to install Ansible on the target machine and ansible-local to import, install, and execute Ansible roles to make our target machine conform to our standards.

Packer uses shell to remove temporary keys before it creates an AMI from the target and temporary EC2 instance.

Ansible Implementation Details

 
Ansible provides OS patching through a custom Common role that can be easily customized for other tasks.

CIS Benchmark and Cloudwatch Logs are implemented through two Ansible third-party roles that are defined in ansible/requirements.yaml as seen in the Packer template.

The Ansible provisioner uses Ansible Galaxy to download these roles onto the target machine and execute them as instructed by ansible/playbook.yaml.

For information about how these components are organized, see the Playbook Roles and Include Statements in the Ansible documentation.

The following Ansible playbook (ansible</playbook.yaml) controls the execution order and custom properties:

---
- hosts: localhost
  connection: local
  gather_facts: true    # gather OS info that is made available for tasks/roles
  become: yes           # majority of CIS tasks require root
  vars:
    # CIS Controls whitepaper:  http://bit.ly/2mGAmUc
    # AWS CIS Whitepaper:       http://bit.ly/2m2Ovrh
    cis_level_1_exclusions:
    # 3.4.2 and 3.4.3 effectively blocks access to all ports to the machine
    ## This can break automation; ignoring it as there are stronger mechanisms than that
      - 3.4.2 
      - 3.4.3
    # CloudWatch Logs will be used instead of Rsyslog/Syslog-ng
    ## Same would be true if any other software doesn't support Rsyslog/Syslog-ng mechanisms
      - 4.2.1.4
      - 4.2.2.4
      - 4.2.2.5
    # Autofs is not installed in newer versions, let's ignore
      - 1.1.19
    # Cloudwatch Logs role configuration
    logs:
      - file: /var/log/messages
        group_name: "system_logs"
  roles:
    - common
    - anthcourtney.cis-amazon-linux
    - dharrisio.aws-cloudwatch-logs-agent

Both third-party Ansible roles can be easily configured through variables (vars). We use Ansible playbook variables to exclude CIS controls that don’t apply to our case and to instruct the CloudWatch Logs agent to stream the /var/log/messages log file to CloudWatch Logs.

If you need to add more OS or application logs, you can easily duplicate the playbook and make changes. The CloudWatch Logs agent will ship configured log messages to CloudWatch Logs.

For more information about parameters you can use to further customize third-party roles, download Ansible roles for the Cloudwatch Logs Agent and CIS Amazon Linux from the Galaxy website.

Committing Changes

 
Now that Ansible and CloudWatch Events are configured as a part of the build process, commiting any changes to the AWS CodeComit Git Repository will triger a new AMI build process that can be followed through the AWS CodePipeline console.

When the build is complete, an email will be sent to the email address you provided as a part of the CloudFormation stack deployment. The email serves as notification that an AMI has been built and is ready for use.

Summary

 
We used AWS CodeCommit, AWS CodePipeline, AWS CodeBuild, Packer, and Ansible to build a pipeline that continuously builds new, hardened CIS AMIs. We used Amazon SNS so that email addresses subscribed to a SNS topic are notified upon completion of the AMI build.

By treating our AMI creation process as code, we can iterate and track changes over time. In this way, it’s no different from a software development workflow. With that in mind, software patches, OS configuration, and logs that need to be shipped to a central location are only a git commit away.

Next Steps

 
Here are some ideas to extend this AMI builder:

  • Hook up a Lambda function in Cloudwatch Events to update EC2 Auto Scaling configuration upon completion of the AMI build.
  • Use AWS CodePipeline parallel steps to build multiple Packer images.
  • Add a commit ID as a tag for the AMI you created.
  • Create a scheduled Lambda function through Cloudwatch Events to clean up old AMIs based on timestamp (name or additional tag).
  • Implement Windows support for the AMI builder.
  • Create a cross-account or cross-region AMI build.

Cloudwatch Events allow the AMI builder to decouple AMI configuration and creation so that you can easily add your own logic using targets (AWS Lambda, Amazon SQS, Amazon SNS) to add events or recycle EC2 instances with the new AMI.

If you have questions or other feedback, feel free to leave it in the comments or contribute to the AMI Builder repo on GitHub.

Three Men Sentenced Following £2.5m Internet Piracy Case

Post Syndicated from Andy original https://torrentfreak.com/three-men-sentenced-following-2-5m-internet-piracy-case-170622/

While legal action against low-level individual file-sharers is extremely rare in the UK, the country continues to pose a risk for those engaged in larger-scale infringement.

That is largely due to the activities of the Police Intellectual Property Crime Unit and private anti-piracy outfits such as the Federation Against Copyright Theft (FACT). Investigations are often a joint effort which can take many years to complete, but the outcomes can often involve criminal sentences.

That was the profile of another Internet piracy case that concluded in London this week. It involved three men from the UK, Eric Brooks, 43, from Bolton, Mark Valentine, 44, from Manchester, and Craig Lloyd, 33, from Wolverhampton.

The case began when FACT became aware of potentially infringing activity back in February 2011. The anti-piracy group then investigated for more than a year before handing the case to police in March 2012.

On July 4, 2012, officers from City of London Police arrested Eric Brooks’ at his home in Bolton following a joint raid with FACT. Computer equipment was seized containing evidence that Brooks had been running a Netherlands-based server hosting more than £100,000 worth of pirated films, music, games, software and ebooks.

According to police, a spreadsheet on Brooks’ computer revealed he had hundreds of paying customers, all recruited from online forums. Using PayPal or utilizing bank transfers, each paid money to access the server. Police mentioned no group or site names in information released this week.

“Enquiries with PayPal later revealed that [Brooks] had made in excess of £500,000 in the last eight years from his criminal business and had in turn defrauded the film and TV industry alone of more than £2.5 million,” police said.

“As his criminal enterprise affected not only the film and TV but the wider entertainment industry including music, games, books and software it is thought that he cost the wider industry an amount much higher than £2.5 million.”

On the same day police arrested Brooks, Mark Valentine’s home in Manchester had a similar unwelcome visit. A day later, Craig Lloyd’s home in Wolverhampton become the third target for police.

Computer equipment was seized from both addresses which revealed that the pair had been paying for access to Brooks’ servers in order to service their own customers.

“They too had used PayPal as a means of taking payment and had earned thousands of pounds from their criminal actions; Valentine gaining £34,000 and Lloyd making over £70,000,” police revealed.

But after raiding the trio in 2012, it took more than four years to charge the men. In a feature common to many FACT cases, all three were charged with Conspiracy to Defraud rather than copyright infringement offenses. All three men pleaded guilty before trial.

On Monday, the men were sentenced at Inner London Crown Court. Brooks was sentenced to 24 months in prison, suspended for 12 months and ordered to complete 140 hours of unpaid work.

Valentine and Lloyd were each given 18 months in prison, suspended for 12 months. Each was ordered to complete 80 hours unpaid work.

Detective Constable Chris Glover, who led the investigation for the City of London Police, welcomed the sentencing.

“The success of this investigation is a result of co-ordinated joint working between the City of London Police and FACT. Brooks, Valentine and Lloyd all thought that they were operating under the radar and doing something which they thought was beyond the controls of law enforcement,” Glover said.

“Brooks, Valentine and Lloyd will now have time in prison to reflect on their actions and the result should act as deterrent for anyone else who is enticed by abusing the internet to the detriment of the entertainment industry.”

While even suspended sentences are a serious matter, none of the men will see the inside of a cell if they meet the conditions of their sentence for the next 12 months. For a case lasting four years involving such large sums of money, that is probably a disappointing result for FACT and the police.

Nevertheless, the men won’t be allowed to enjoy the financial proceeds of their piracy, if indeed any money is left. City of London Police say the trio will be subject to a future confiscation hearing to seize any proceeds of crime.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

Vranken: The OpenVPN post-audit bug bonanza

Post Syndicated from corbet original https://lwn.net/Articles/726157/rss

Guido Vranken describes
his efforts
to fuzz-test OpenVPN and the bug reports that resulted.
Most of this issues were found through fuzzing. I hate admitting it,
but my chops in the arcane art of reviewing code manually, acquired through
grueling practice, are dwarfed by the fuzzer in one fell swoop; the
mortal’s mind can only retain and comprehend so much information at a time,
and for programs that perform long cycles of complex, deeply nested
operations it is simply not feasible to expect a human to perform an
encompassing and reliable verification.

DynamoDB Accelerator (DAX) Now Generally Available

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/dynamodb-accelerator-dax-now-generally-available/

Earlier this year I told you about Amazon DynamoDB Accelerator (DAX), a fully-managed caching service that sits in front of (logically speaking) your Amazon DynamoDB tables. DAX returns cached responses in microseconds, making it a great fit for eventually-consistent read-intensive workloads. DAX supports the DynamoDB API, and is seamless and easy to use. As a managed service, you simply create your DAX cluster and use it as the target for your existing reads and writes. You don’t have to worry about patching, cluster maintenance, replication, or fault management.

Now Generally Available
Today I am pleased to announce that DAX is now generally available. We have expanded DAX into additional AWS Regions and used the preview time to fine-tune performance and availability:

Now in Five Regions – DAX is now available in the US East (Northern Virginia), EU (Ireland), US West (Oregon), Asia Pacific (Tokyo), and US West (Northern California) Regions.

In Production – Our preview customers are reporting that they are using DAX in production, that they loved how easy it was to add DAX to their application, and have told us that their apps are now running 10x faster.

Getting Started with DAX
As I outlined in my earlier post, it is easy to use DAX to accelerate your existing DynamoDB applications. You simply create a DAX cluster in the desired region, update your application to reference the DAX SDK for Java (the calls are the same; this is a drop-in replacement), and configure the SDK to use the endpoint to your cluster. As a read-through/write-through cache, DAX seamlessly handles all of the DynamoDB read/write APIs.

We are working on SDK support for other languages, and I will share additional information as it becomes available.

DAX Pricing
You pay for each node in the cluster (see the DynamoDB Pricing page for more information) on a per-hour basis, with prices starting at $0.269 per hour in the US East (Northern Virginia) and US West (Oregon) regions. With DAX, each of the nodes in your cluster serves as a read target and as a failover target for high availability. The DAX SDK is cluster aware and will issue round-robin requests to all nodes in the cluster so that you get to make full use of the cluster’s cache resources.

Because DAX can easily handle sudden spikes in read traffic, you may be able to reduce the amount of provisioned throughput for your tables, resulting in an overall cost savings while still returning results in microseconds.

Jeff;

 

Is your product “Powered by Raspberry Pi”?

Post Syndicated from Mike Buffham original https://www.raspberrypi.org/blog/powered-by-raspberry-pi/

One of the most exciting things for us about the growth of the Raspberry Pi community has been the number of companies that have grown up around the platform, and who have chosen to embed our products into their own. While many of these design-ins have been “silent”, a number of people have asked us for a standardised way to indicate that a product contains a Raspberry Pi or a Raspberry Pi Compute Module.

Powered by Raspberry Pi Logo

At the end of last year, we introduced a “Powered by Raspberry Pi” logo to meet this need. It is now included in our trademark rules and brand guidelines, which you can find on our website. Below we’re showing an early example of a “Powered by Raspberry Pi”-branded device, the KUNBUS Revolution Pi industrial PC. It has already made it onto the market, and we think it will inspire you to include our logo on the packaging of your own product.

KUNBUS RevPi
Powered by Raspberry Pi logo on RevPi

Using the “Powered by Raspberry Pi” brand

Adding the “Powered by Raspberry Pi” logo to your packaging design is a great way to remind your customers that a portion of the sale price of your product goes to the Raspberry Pi Foundation and supports our educational work.

As with all things Raspberry Pi, our rules for using this brand are fairly straightforward: the only thing you need to do is to fill out this simple application form. Once you have submitted it, we will review your details and get back to you as soon as possible.

When we approve your application, we will require that you use one of the official “Powered by Raspberry Pi” logos and that you ensure it is at least 30 mm wide. We are more than happy to help you if you have any design queries related to this – just contact us at [email protected]

The post Is your product “Powered by Raspberry Pi”? appeared first on Raspberry Pi.

South Korean Webhost Nayana Pays USD1 Million Ransom

Post Syndicated from Darknet original http://feedproxy.google.com/~r/darknethackers/~3/jTy5T4S7TZQ/

So far this Nayana payout is the biggest ransomware payment I’ve seen reported, there’s probably some bigger ones been paid but kept undercover. Certainly a good deal for the bad actors in this play, and well using an outdated Kernel along with PHP and Apache versions from 2006 you can’t feel too sorry for Nayana. […]

The post South Korean…

Read the full post at darknet.org.uk

Court Grants Subpoenas to Unmask ‘TVAddons’ and ‘ZemTV’ Operators

Post Syndicated from Ernesto original https://torrentfreak.com/court-grants-subpoenas-to-unmask-tvaddons-and-zemtv-operators-170621/

Earlier this month we broke the news that third-party Kodi add-on ZemTV and the TVAddons library were being sued in a federal court in Texas.

In a complaint filed by American satellite and broadcast provider Dish Network, both stand accused of copyright infringement, facing up to $150,000 for each offense.

While the allegations are serious, Dish doesn’t know the full identities of the defendants.

To find out more, the company requested a broad range of subpoenas from the court, targeting Amazon, Github, Google, Twitter, Facebook, PayPal, and several hosting providers.

From Dish’s request

This week the court granted the subpoenas, which means that they can be forwarded to the companies in question. Whether that will be enough to identify the people behind ‘TVAddons’ and ‘ZemTV’ remains to be seen, but Dish has cast its net wide.

For example, the subpoena directed at Google covers any type of information that can be used to identify the account holder of [email protected], which is believed to be tied to ZemTV.

The information requested from Google includes IP address logs with session date and timestamps, but also covers “all communications,” including GChat messages from 2014 onwards.

Similarly, Twitter is required to hand over information tied to the accounts of the users “TV Addons” and “shani_08_kodi” as well as other accounts linked to tvaddons.ag and streamingboxes.com. This also applies the various tweets that were sent through the account.

The subpoena specifically mentions “all communications, including ‘tweets’, Twitter sent to or received from each Twitter Account during the time period of February 1, 2014 to present.”

From the Twitter subpoena

Similar subpoenas were granted for the other services, tailored towards the information Dish hopes to find there. For example, the broadcast provider also requests details of each transaction from PayPal, as well as all debits and credits to the accounts.

In some parts, the subpoenas appear to be quite broad. PayPal is asked to reveal information on any account with the credit card statement “Shani,” for example. Similarly, Github is required to hand over information on accounts that are ‘associated’ with the tvaddons.ag domain, which is referenced by many people who are not directly connected to the site.

The service providers in question still have the option to challenge the subpoenas or ask the court for further clarification. A full overview of all the subpoena requests is available here (Exhibit 2 and onwards), including all the relevant details. This also includes several letters to foreign hosting providers.

While Dish still appears to be keen to find out who is behind ‘TVAddons’ and ‘ZemTV,’ not much has been heard from the defendants in question.

ZemTV developer “Shani” shut down his addon soon after the lawsuit was announced, without mentioning it specifically. TVAddons, meanwhile, has been offline for well over a week, without any notice in public about the reason for the prolonged downtime.

The court’s order granting the subpoenas and letters of request is available here (pdf).

Source: TF, for the latest info on copyright, file-sharing, torrent sites and ANONYMOUS VPN services.

In the Works – AWS Region in Hong Kong

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/in-the-works-aws-region-in-hong-kong/

Last year we launched new AWS Regions in Canada, India, Korea, the UK (London), and the United States (Ohio), and announced that new regions are coming to France (Paris), China (Ningxia), and Sweden (Stockholm).

Coming to Hong Kong in 2018
Today, I am happy to be able to tell you that we are planning to open up an AWS Region in Hong Kong, in 2018. Hong Kong is a leading international financial center, well known for its service oriented economy. It is rated highly on innovation and for ease of doing business. As an evangelist, I get to visit many great cities in the world, and was lucky to have spent some time in Hong Kong back in 2014 and met a number of awesome customers there. Many of these customers have given us feedback that they wanted a local AWS Region.

This will be the eighth AWS Region in Asia Pacific joining six other Regions there — Singapore, Tokyo, Sydney, Beijing, Seoul, and Mumbai, and an additional Region in China (Ningxia) expected to launch in the coming months. Together, these Regions will provide our customers with a total of 19 Availability Zones (AZs) and allow them to architect highly fault tolerant applications.

Today, our infrastructure comprises 43 Availability Zones across 16 geographic regions worldwide, with another three AWS Regions (and eight Availability Zones) in France, China, and Sweden coming online throughout 2017 and 2018, (see the AWS Global Infrastructure page for more info).

We are looking forward to serving new and existing customers in Hong Kong and working with partners across Asia-Pacific. Of course, the new region will also be open to existing AWS customers who would like to process and store data in Hong Kong. Public sector organizations such as government agencies, educational institutions, and nonprofits in Hong Kong will be able to use this region to store sensitive data locally (the AWS in the Public Sector page has plenty of success stories drawn from our worldwide customer base).

If you are a customer or a partner and have specific questions about this Region, you can contact our Hong Kong team.

Help Wanted
If you are interested in learning more about AWS positions in Hong Kong, please visit the Amazon Jobs site and set the location to Hong Kong.

Jeff;

 

Building Loosely Coupled, Scalable, C# Applications with Amazon SQS and Amazon SNS

Post Syndicated from Tara Van Unen original https://aws.amazon.com/blogs/compute/building-loosely-coupled-scalable-c-applications-with-amazon-sqs-and-amazon-sns/

 
Stephen Liedig, Solutions Architect

 

One of the many challenges professional software architects and developers face is how to make cloud-native applications scalable, fault-tolerant, and highly available.

Fundamental to your project success is understanding the importance of making systems highly cohesive and loosely coupled. That means considering the multi-dimensional facets of system coupling to support the distributed nature of the applications that you are building for the cloud.

By that, I mean addressing not only the application-level coupling (managing incoming and outgoing dependencies), but also considering the impacts of of platform, spatial, and temporal coupling of your systems. Platform coupling relates to the interoperability, or lack thereof, of heterogeneous systems components. Spatial coupling deals with managing components at a network topology level or protocol level. Temporal, or runtime coupling, refers to the ability of a component within your system to do any kind of meaningful work while it is performing a synchronous, blocking operation.

The AWS messaging services, Amazon SQS and Amazon SNS, help you deal with these forms of coupling by providing mechanisms for:

  • Reliable, durable, and fault-tolerant delivery of messages between application components
  • Logical decomposition of systems and increased autonomy of components
  • Creating unidirectional, non-blocking operations, temporarily decoupling system components at runtime
  • Decreasing the dependencies that components have on each other through standard communication and network channels

Following on the recent topic, Building Scalable Applications and Microservices: Adding Messaging to Your Toolbox, in this post, I look at some of the ways you can introduce SQS and SNS into your architectures to decouple your components, and show how you can implement them using C#.

Walkthrough

To illustrate some of these concepts, consider a web application that processes customer orders. As good architects and developers, you have followed best practices and made your application scalable and highly available. Your solution included implementing load balancing, dynamic scaling across multiple Availability Zones, and persisting orders in a Multi-AZ Amazon RDS database instance, as in the following diagram.


In this example, the application is responsible for handling and persisting the order data, as well as dealing with increases in traffic for popular items.

One potential point of vulnerability in the order processing workflow is in saving the order in the database. The business expects that every order has been persisted into the database. However, any potential deadlock, race condition, or network issue could cause the persistence of the order to fail. Then, the order is lost with no recourse to restore the order.

With good logging capability, you may be able to identify when an error occurred and which customer’s order failed. This wouldn’t allow you to “restore” the transaction, and by that stage, your customer is no longer your customer.

As illustrated in the following diagram, introducing an SQS queue helps improve your ordering application. Using the queue isolates the processing logic into its own component and runs it in a separate process from the web application. This, in turn, allows the system to be more resilient to spikes in traffic, while allowing work to be performed only as fast as necessary in order to manage costs.


In addition, you now have a mechanism for persisting orders as messages (with the queue acting as a temporary database), and have moved the scope of your transaction with your database further down the stack. In the event of an application exception or transaction failure, this ensures that the order processing can be retired or redirected to the Amazon SQS Dead Letter Queue (DLQ), for re-processing at a later stage. (See the recent post, Using Amazon SQS Dead-Letter Queues to Control Message Failure, for more information on dead-letter queues.)

Scaling the order processing nodes

This change allows you now to scale the web application frontend independently from the processing nodes. The frontend application can continue to scale based on metrics such as CPU usage, or the number of requests hitting the load balancer. Processing nodes can scale based on the number of orders in the queue. Here is an example of scale-in and scale-out alarms that you would associate with the scaling policy.

Scale-out Alarm

aws cloudwatch put-metric-alarm --alarm-name AddCapacityToCustomerOrderQueue --metric-name ApproximateNumberOfMessagesVisible --namespace "AWS/SQS" 
--statistic Average --period 300 --threshold 3 --comparison-operator GreaterThanOrEqualToThreshold --dimensions Name=QueueName,Value=customer-orders
--evaluation-periods 2 --alarm-actions <arn of the scale-out autoscaling policy>

Scale-in Alarm

aws cloudwatch put-metric-alarm --alarm-name RemoveCapacityFromCustomerOrderQueue --metric-name ApproximateNumberOfMessagesVisible --namespace "AWS/SQS" 
 --statistic Average --period 300 --threshold 1 --comparison-operator LessThanOrEqualToThreshold --dimensions Name=QueueName,Value=customer-orders
 --evaluation-periods 2 --alarm-actions <arn of the scale-in autoscaling policy>

In the above example, use the ApproximateNumberOfMessagesVisible metric to discover the queue length and drive the scaling policy of the Auto Scaling group. Another useful metric is ApproximateAgeOfOldestMessage, when applications have time-sensitive messages and developers need to ensure that messages are processed within a specific time period.

Scaling the order processing implementation

On top of scaling at an infrastructure level using Auto Scaling, make sure to take advantage of the processing power of your Amazon EC2 instances by using as many of the available threads as possible. There are several ways to implement this. In this post, we build a Windows service that uses the BackgroundWorker class to process the messages from the queue.

Here’s a closer look at the implementation. In the first section of the consuming application, use a loop to continually poll the queue for new messages, and construct a ReceiveMessageRequest variable.

public static void PollQueue()
{
    while (_running)
    {
        Task<ReceiveMessageResponse> receiveMessageResponse;

        // Pull messages off the queue
        using (var sqs = new AmazonSQSClient())
        {
            const int maxMessages = 10;  // 1-10

            //Receiving a message
            var receiveMessageRequest = new ReceiveMessageRequest
            {
                // Get URL from Configuration
                QueueUrl = _queueUrl, 
                // The maximum number of messages to return. 
                // Fewer messages might be returned. 
                MaxNumberOfMessages = maxMessages, 
                // A list of attributes that need to be returned with message.
                AttributeNames = new List<string> { "All" },
                // Enable long polling. 
                // Time to wait for message to arrive on queue.
                WaitTimeSeconds = 5 
            };

            receiveMessageResponse = sqs.ReceiveMessageAsync(receiveMessageRequest);
        }

The WaitTimeSeconds property of the ReceiveMessageRequest specifies the duration (in seconds) that the call waits for a message to arrive in the queue before returning a response to the calling application. There are a few benefits to using long polling:

  • It reduces the number of empty responses by allowing SQS to wait until a message is available in the queue before sending a response.
  • It eliminates false empty responses by querying all (rather than a limited number) of the servers.
  • It returns messages as soon any message becomes available.

For more information, see Amazon SQS Long Polling.

After you have returned messages from the queue, you can start to process them by looping through each message in the response and invoking a new BackgroundWorker thread.

// Process messages
if (receiveMessageResponse.Result.Messages != null)
{
    foreach (var message in receiveMessageResponse.Result.Messages)
    {
        Console.WriteLine("Received SQS message, starting worker thread");

        // Create background worker to process message
        BackgroundWorker worker = new BackgroundWorker();
        worker.DoWork += (obj, e) => ProcessMessage(message);
        worker.RunWorkerAsync();
    }
}
else
{
    Console.WriteLine("No messages on queue");
}

The event handler, ProcessMessage, is where you implement business logic for processing orders. It is important to have a good understanding of how long a typical transaction takes so you can set a message VisibilityTimeout that is long enough to complete your operation. If order processing takes longer than the specified timeout period, the message becomes visible on the queue. Other nodes may pick it and process the same order twice, leading to unintended consequences.

Handling Duplicate Messages

In order to manage duplicate messages, seek to make your processing application idempotent. In mathematics, idempotent describes a function that produces the same result if it is applied to itself:

f(x) = f(f(x))

No matter how many times you process the same message, the end result is the same (definition from Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions, Hohpe and Wolf, 2004).

There are several strategies you could apply to achieve this:

  • Create messages that have inherent idempotent characteristics. That is, they are non-transactional in nature and are unique at a specified point in time. Rather than saying “place new order for Customer A,” which adds a duplicate order to the customer, use “place order <orderid> on <timestamp> for Customer A,” which creates a single order no matter how often it is persisted.
  • Deliver your messages via an Amazon SQS FIFO queue, which provides the benefits of message sequencing, but also mechanisms for content-based deduplication. You can deduplicate using the MessageDeduplicationId property on the SendMessage request or by enabling content-based deduplication on the queue, which generates a hash for MessageDeduplicationId, based on the content of the message, not the attributes.
var sendMessageRequest = new SendMessageRequest
{
    QueueUrl = _queueUrl,
    MessageBody = JsonConvert.SerializeObject(order),
    MessageGroupId = Guid.NewGuid().ToString("N"),
    MessageDeduplicationId = Guid.NewGuid().ToString("N")
};
  • If using SQS FIFO queues is not an option, keep a message log of all messages attributes processed for a specified period of time, as an alternative to message deduplication on the receiving end. Verifying the existence of the message in the log before processing the message adds additional computational overhead to your processing. This can be minimized through low latency persistence solutions such as Amazon DynamoDB. Bear in mind that this solution is dependent on the successful, distributed transaction of the message and the message log.

Handling exceptions

Because of the distributed nature of SQS queues, it does not automatically delete the message. Therefore, you must explicitly delete the message from the queue after processing it, using the message ReceiptHandle property (see the following code example).

However, if at any stage you have an exception, avoid handling it as you normally would. The intention is to make sure that the message ends back on the queue, so that you can gracefully deal with intermittent failures. Instead, log the exception to capture diagnostic information, and swallow it.

By not explicitly deleting the message from the queue, you can take advantage of the VisibilityTimeout behavior described earlier. Gracefully handle the message processing failure and make the unprocessed message available to other nodes to process.

In the event that subsequent retries fail, SQS automatically moves the message to the configured DLQ after the configured number of receives has been reached. You can further investigate why the order process failed. Most importantly, the order has not been lost, and your customer is still your customer.

private static void ProcessMessage(Message message)
{
    using (var sqs = new AmazonSQSClient())
    {
        try
        {
            Console.WriteLine("Processing message id: {0}", message.MessageId);

            // Implement messaging processing here
            // Ensure no downstream resource contention (parallel processing)
            // <your order processing logic in here…>
            Console.WriteLine("{0} Thread {1}: {2}", DateTime.Now.ToString("s"), Thread.CurrentThread.ManagedThreadId, message.MessageId);
            
            // Delete the message off the queue. 
            // Receipt handle is the identifier you must provide 
            // when deleting the message.
            var deleteRequest = new DeleteMessageRequest(_queueName, message.ReceiptHandle);
            sqs.DeleteMessageAsync(deleteRequest);
            Console.WriteLine("Processed message id: {0}", message.MessageId);

        }
        catch (Exception ex)
        {
            // Do nothing.
            // Swallow exception, message will return to the queue when 
            // visibility timeout has been exceeded.
            Console.WriteLine("Could not process message due to error. Exception: {0}", ex.Message);
        }
    }
}

Using SQS to adapt to changing business requirements

One of the benefits of introducing a message queue is that you can accommodate new business requirements without dramatically affecting your application.

If, for example, the business decided that all orders placed over $5000 are to be handled as a priority, you could introduce a new “priority order” queue. The way the orders are processed does not change. The only significant change to the processing application is to ensure that messages from the “priority order” queue are processed before the “standard order” queue.

The following diagram shows how this logic could be isolated in an “order dispatcher,” whose only purpose is to route order messages to the appropriate queue based on whether the order exceeds $5000. Nothing on the web application or the processing nodes changes other than the target queue to which the order is sent. The rates at which orders are processed can be achieved by modifying the poll rates and scalability settings that I have already discussed.

Extending the design pattern with Amazon SNS

Amazon SNS supports reliable publish-subscribe (pub-sub) scenarios and push notifications to known endpoints across a wide variety of protocols. It eliminates the need to periodically check or poll for new information and updates. SNS supports:

  • Reliable storage of messages for immediate or delayed processing
  • Publish / subscribe – direct, broadcast, targeted “push” messaging
  • Multiple subscriber protocols
  • Amazon SQS, HTTP, HTTPS, email, SMS, mobile push, AWS Lambda

With these capabilities, you can provide parallel asynchronous processing of orders in the system and extend it to support any number of different business use cases without affecting the production environment. This is commonly referred to as a “fanout” scenario.

Rather than your web application pushing orders to a queue for processing, send a notification via SNS. The SNS messages are sent to a topic and then replicated and pushed to multiple SQS queues and Lambda functions for processing.

As the diagram above shows, you have the development team consuming “live” data as they work on the next version of the processing application, or potentially using the messages to troubleshoot issues in production.

Marketing is consuming all order information, via a Lambda function that has subscribed to the SNS topic, inserting the records into an Amazon Redshift warehouse for analysis.

All of this, of course, is happening without affecting your order processing application.

Summary

While I haven’t dived deep into the specifics of each service, I have discussed how these services can be applied at an architectural level to build loosely coupled systems that facilitate multiple business use cases. I’ve also shown you how to use infrastructure and application-level scaling techniques, so you can get the most out of your EC2 instances.

One of the many benefits of using these managed services is how quickly and easily you can implement powerful messaging capabilities in your systems, and lower the capital and operational costs of managing your own messaging middleware.

Using Amazon SQS and Amazon SNS together can provide you with a powerful mechanism for decoupling application components. This should be part of design considerations as you architect for the cloud.

For more information, see the Amazon SQS Developer Guide and Amazon SNS Developer Guide. You’ll find tutorials on all the concepts covered in this post, and more. To can get started using the AWS console or SDK of your choice visit:

Happy messaging!