Tag Archives: support

MPAA Revenue Drops 20% as Movie Studios Cut Back

2018-05-27 Ernesto

Post Syndicated from Ernesto original https://torrentfreak.com/mpaa-revenue-drops-20-as-movie-studios-cut-back-180527/

As a united front for Hollywood, the MPAA has booked many anti-piracy successes in recent years.

Through its involvement in the shutdowns of Popcorn Time, YIFY, isoHunt, Hotfile, Megaupload and several other platforms, the organization has worked hard to get results.

Less visibly but at least as important, the MPAA uses its influence to lobby lawmakers, while orchestrating and managing anti-piracy campaigns both in the United States and abroad.

All this work doesn’t come for free, obviously. To pay the bills the MPAA relies on six major movie studios for financial support. Over the past several years, these revenues had stabilized, but according to its latest tax filing, they are dropping now.

The IRS filing, covering the fiscal year 2016, puts total revenue at $57 million, down from $73 million. The Hollywood studios paid the bulk of this sum through membership fees which total $50 million. That’s a 22% reduction compared to a year earlier.

At the end of the year, this resulted in a significant loss of $8 million. While that’s a lot of money, the MPAA is not in imminent danger, as the organization still has over $10 million in net assets and funds.

We haven’t seen any explanation for the lower membership fees. It could be more permanent, but it may also be an agreed decision, as there’s enough money in the bank.

Going over the numbers, we see that salaries make up a large chunk of the expenses. Chris Dodd, the former MPAA Chairman and CEO, was the highest paid employee with a total income of more than $3.4 million, including a $275,000 bonus.

This compensation was for Dodd’s last full year as CEO. He was replaced by Charles Rivkin last year, another political heavyweight, who previously served as Assistant Secretary of State for Economic and Business Affairs in the Obama administration.

Dodd’s compensation took up nearly 10% of the entire salary budget. The rest is divided over the MPAA’s other 196 employees. This brings the total workforce to 197, which is down as well, from 224 employees a year earlier.

Moving on, it’s always interesting to see where the MPAA’s grants and other types of funding go to.

As reported previously, the group donates handsomely to various research initiatives. This includes a recurring million dollar grant for Carnegie Mellon’s ‘Initiative for Digital Entertainment Analytics’ (IDEA), which focuses on piracy related topics.

Another major beneficiary is the Copyright Alliance, a non-profit that represents copyright holders large and small on a variety of issues. The group was co-founded by the MPAA and received $750,000 in support according to the latest filing.

The total grants budget is $3.1 million and includes many smaller payments, which is not that different from previous years. Other large cost items are the lobbying budget, which totaled $3.6 million, and $5.3 million in legal fees.

Aside from the big dip in revenues, there are no real outliers in the filing.

—

A copy of the MPAA’s latest form 990 is available here (pdf).

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN reviews, discounts, offers and coupons.

Orchestrate Apache Spark applications using AWS Step Functions and Apache Livy

2018-05-25 Tanzir Musabbir

Post Syndicated from Tanzir Musabbir original https://aws.amazon.com/blogs/big-data/orchestrate-apache-spark-applications-using-aws-step-functions-and-apache-livy/

The adoption of Apache Spark has increased significantly over the past few years, and running Spark-based application pipelines is the new normal. Spark jobs that are in an ETL (extract, transform, and load) pipeline have different requirements—you must handle dependencies in the jobs, maintain order during executions, and run multiple jobs in parallel. In most of these cases, you can use workflow scheduler tools like Apache Oozie, Apache Airflow, and even Cron to fulfill these requirements.

Apache Oozie is a widely used workflow scheduler system for Hadoop-based jobs. However, its limited UI capabilities, lack of integration with other services, and heavy XML dependency might not be suitable for some users. On the other hand, Apache Airflow comes with a lot of neat features, along with powerful UI and monitoring capabilities and integration with several AWS and third-party services. However, with Airflow, you do need to provision and manage the Airflow server. The Cron utility is a powerful job scheduler. But it doesn’t give you much visibility into the job details, and creating a workflow using Cron jobs can be challenging.

What if you have a simple use case, in which you want to run a few Spark jobs in a specific order, but you don’t want to spend time orchestrating those jobs or maintaining a separate application? You can do that today in a serverless fashion using AWS Step Functions. You can create the entire workflow in AWS Step Functions and interact with Spark on Amazon EMR through Apache Livy.

In this post, I walk you through a list of steps to orchestrate a serverless Spark-based ETL pipeline using AWS Step Functions and Apache Livy.

Input data

For the source data for this post, I use the New York City Taxi and Limousine Commission (TLC) trip record data. For a description of the data, see this detailed dictionary of the taxi data. In this example, we’ll work mainly with the following three columns for the Spark jobs.

Column name	Column description
RateCodeID	Represents the rate code in effect at the end of the trip (for example, 1 for standard rate, 2 for JFK airport, 3 for Newark airport, and so on).
FareAmount	Represents the time-and-distance fare calculated by the meter.
TripDistance	Represents the elapsed trip distance in miles reported by the taxi meter.

The trip data is in comma-separated values (CSV) format with the first row as a header. To shorten the Spark execution time, I trimmed the large input data to only 20,000 rows. During the deployment phase, the input file tripdata.csv is stored in Amazon S3 in the <<your-bucket>>/emr-step-functions/input/ folder.

The following image shows a sample of the trip data:

Solution overview

The next few sections describe how Spark jobs are created for this solution, how you can interact with Spark using Apache Livy, and how you can use AWS Step Functions to create orchestrations for these Spark applications.

At a high level, the solution includes the following steps:

Trigger the AWS Step Function state machine by passing the input file path.
The first stage in the state machine triggers an AWS Lambda
The Lambda function interacts with Apache Spark running on Amazon EMR using Apache Livy, and submits a Spark job.
The state machine waits a few seconds before checking the Spark job status.
Based on the job status, the state machine moves to the success or failure state.
Subsequent Spark jobs are submitted using the same approach.
The state machine waits a few seconds for the job to finish.
The job finishes, and the state machine updates with its final status.

Let’s take a look at the Spark application that is used for this solution.

Spark jobs

For this example, I built a Spark jar named spark-taxi.jar. It has two different Spark applications:

MilesPerRateCode – The first job that runs on the Amazon EMR cluster. This job reads the trip data from an input source and computes the total trip distance for each rate code. The output of this job consists of two columns and is stored in Apache Parquet format in the output path.

The following are the expected output columns:

rate_code – Represents the rate code for the trip.
total_distance – Represents the total trip distance for that rate code (for example, sum(trip_distance)).

RateCodeStatus – The second job that runs on the EMR cluster, but only if the first job finishes successfully. This job depends on two different input sets:

csv – The same trip data that is used for the first Spark job.
miles-per-rate – The output of the first job.

This job first reads the tripdata.csv file and aggregates the fare_amount by the rate_code. After this point, you have two different datasets, both aggregated by rate_code. Finally, the job uses the rate_code field to join two datasets and output the entire rate code status in a single CSV file.

The output columns are as follows:

rate_code_id – Represents the rate code type.
total_distance – Derived from first Spark job and represents the total trip distance.
total_fare_amount – A new field that is generated during the second Spark application, representing the total fare amount by the rate code type.

Note that in this case, you don’t need to run two different Spark jobs to generate that output. The goal of setting up the jobs in this way is just to create a dependency between the two jobs and use them within AWS Step Functions.

Both Spark applications take one input argument called rootPath. It’s the S3 location where the Spark job is stored along with input and output data. Here is a sample of the final output:

The next section discusses how you can use Apache Livy to interact with Spark applications that are running on Amazon EMR.

Using Apache Livy to interact with Apache Spark

Apache Livy provides a REST interface to interact with Spark running on an EMR cluster. Livy is included in Amazon EMR release version 5.9.0 and later. In this post, I use Livy to submit Spark jobs and retrieve job status. When Amazon EMR is launched with Livy installed, the EMR master node becomes the endpoint for Livy, and it starts listening on port 8998 by default. Livy provides APIs to interact with Spark.

Let’s look at a couple of examples how you can interact with Spark running on Amazon EMR using Livy.

To list active running jobs, you can execute the following from the EMR master node:

curl localhost:8998/sessions

If you want to do the same from a remote instance, just change localhost to the EMR hostname, as in the following (port 8998 must be open to that remote instance through the security group):

curl http://ec2-xx-xx-xx-xx.compute-1.amazonaws.com:8998/sessions

To submit a Spark job through Livy pointing to the application jar in S3, you can do the following:

curl -X POST --data '{"file": "s3://<<bucket-location>/spark.jar", "className": "com.example.SparkApp "]}' -H "Content-Type: application/json" http://ec2-xx-xx-xx-xx.compute-1.amazonaws.com:8998/batches

Spark submit through Livy returns a session ID that starts from 0. Using that session ID, you can retrieve the status of the job as shown following:

curl http://ec2-xx-xx-xx-xx.compute-1.amazonaws.com:8998/batches/0 | python -m json.tool

Through Spark submit, you can pass multiple arguments for the Spark job and Spark configuration settings. You can also do that using Livy, by passing the S3 path through the args parameter, as shown following:

curl -X POST --data '{"file": "s3://<<bucket-location>>/spark.jar", "className": "com.example.SparkApp", “args”: [“s3://bucket-path”]}' -H "Content-Type: application/json" http://ec2-xx-xx-xx-xx.compute-1.amazonaws.com:8998/batches

All Apache Livy REST calls return a response as JSON, as shown in the following image:

If you want to pretty-print that JSON response, you can pipe command with Python’s JSON tool as follows:

curl http://ec2-xx-xx-xx-xx.compute-1.amazonaws.com:8998/batches/3 | python -m json.tool

For a detailed list of Livy APIs, see the Apache Livy REST API page. This post uses GET /batches and POST /batches.

In the next section, you create a state machine and orchestrate Spark applications using AWS Step Functions.

Using AWS Step Functions to create a Spark job workflow

AWS Step Functions automatically triggers and tracks each step and retries when it encounters errors. So your application executes in order and as expected every time. To create a Spark job workflow using AWS Step Functions, you first create a Lambda state machine using different types of states to create the entire workflow.

First, you use the Task state—a simple state in AWS Step Functions that performs a single unit of work. You also use the Wait state to delay the state machine from continuing for a specified time. Later, you use the Choice state to add branching logic to a state machine.

The following is a quick summary of how to use different states in the state machine to create the Spark ETL pipeline:

Task state – Invokes a Lambda function. The first Task state submits the Spark job on Amazon EMR, and the next Task state is used to retrieve the previous Spark job status.
Wait state – Pauses the state machine until a job completes execution.
Choice state – Each Spark job execution can return a failure, an error, or a success state So, in the state machine, you use the Choice state to create a rule that specifies the next action or step based on the success or failure of the previous step.

Here is one of my Task states, MilesPerRateCode, which simply submits a Spark job:

"MilesPerRate Job": {
      "Type": "Task",
      "Resource":"arn:aws:lambda:us-east-1:xxxxxx:function:blog-miles-per-rate-job-submit-function",
      "ResultPath": "$.jobId",
      "Next": "Wait for MilesPerRate job to complete"
 }

This Task state configuration specifies the Lambda function to execute. Inside the Lambda function, it submits a Spark job through Livy using Livy’s POST API. Using ResultPath, it tells the state machine where to place the result of the executing task. As discussed in the previous section, Spark submit returns the session ID, which is captured with $.jobId and used in a later state.

The following code section shows the Lambda function, which is used to submit the MilesPerRateCode job. It uses the Python request library to submit a POST against the Livy endpoint hosted on Amazon EMR and passes the required parameters in JSON format through payload. It then parses the response, grabs id from the response, and returns it. The Next field tells the state machine which state to go to next.

from botocore.vendored import requests
import json

def lambda_handler(event, context):
  headers = { "content-type": "application/json" }
  url = 'http://xxxxxx.compute-1.amazonaws.com:8998/batches'
  payload = {
    'file' : 's3://<<s3-location>>/emr-step-functions/spark-taxi.jar',
    'className' : 'com.example.MilesPerRateCode',
    'args' : [event.get('rootPath')]
  }
  res = requests.post(url, data = json.dumps(payload), headers = headers, verify = False)
  json_data = json.loads(res.text)
  return json_data.get('id')

Just like in the MilesPerRate job, another state submits the RateCodeStatus job, but it executes only when all previous jobs have completed successfully.

Here is the Task state in the state machine that checks the Spark job status:

"Query RateCodeStatus job status": {
   "Type": "Task",
   "Resource": "arn:aws:lambda:us-east-1:xxxxx:function:blog-spark-job-status-function",
   "Next": "RateCodeStatus job complete?",
   "ResultPath": "$.jobStatus"
}

Just like other states, the preceding Task executes a Lambda function, captures the result (represented by jobStatus), and passes it to the next state. The following is the Lambda function that checks the Spark job status based on a given session ID:

from botocore.vendored import requests
import json

def lambda_handler(event, context):
    jobid = event.get('jobId')
    url     = 'http://xxxx.compute-1.amazonaws.com:8998/batches/' + str(jobid)
    res = requests.get(url)
    json_data = json.loads(res.text)
    return json_data.get('state')

In the Choice state, it checks the Spark job status value, compares it with a predefined state status, and transitions the state based on the result. For example, if the status is success, move to the next state (RateCodeJobStatus job), and if it is dead, move to the MilesPerRate job failed state.

"MilesPerRate job complete?": {
   "Type": "Choice",
   "Choices": [{
       "Variable": "$.jobStatus",
       "StringEquals": "success",
       "Next": "RateCodeStatus Job"
   },{
       "Variable": "$.jobStatus",
       "StringEquals": "dead",
       "Next": "MilesPerRate job failed"
   }],
   "Default": "Wait for MilesPerRate job to complete"
}

Walkthrough using AWS CloudFormation

To set up this entire solution, you need to create a few AWS resources. To make it easier, I have created an AWS CloudFormation template. This template creates all the required AWS resources and configures all the resources that are needed to create a Spark-based ETL pipeline on AWS Step Functions.

This CloudFormation template requires you to pass the following four parameters during initiation.

Parameter	Description
`ClusterSubnetID`	The subnet where the Amazon EMR cluster is deployed and Lambda is configured to talk to this subnet.
`KeyName`	The name of the existing EC2 key pair to access the Amazon EMR cluster.
`VPCID`	The ID of the virtual private cloud (VPC) where the EMR cluster is deployed and Lambda is configured to talk to this VPC.
`S3RootPath`	The Amazon S3 path where all required files (input file, Spark job, and so on) are stored and the resulting data is written.

IMPORTANT: These templates are designed only to show how you can create a Spark-based ETL pipeline on AWS Step Functions using Apache Livy. They are not intended for production use without modification. And if you try this solution outside of the us-east-1 Region, download the necessary files from s3://aws-data-analytics-blog/emr-step-functions, upload the files to the buckets in your Region, edit the script as appropriate, and then run it.

To launch the CloudFormation stack, choose Launch Stack:

Launching this stack creates the following list of AWS resources.

Logical ID	Resource Type	Description
`StepFunctionsStateExecutionRole`	IAM role	IAM role to execute the state machine and have a trust relationship with the states service.
`SparkETLStateMachine`	AWS Step Functions state machine	State machine in AWS Step Functions for the Spark ETL workflow.
`LambdaSecurityGroup`	Amazon EC2 security group	Security group that is used for the Lambda function to call the Livy API.
`RateCodeStatusJobSubmitFunction`	AWS Lambda function	Lambda function to submit the RateCodeStatus job.
`MilesPerRateJobSubmitFunction`	AWS Lambda function	Lambda function to submit the MilesPerRate job.
`SparkJobStatusFunction`	AWS Lambda function	Lambda function to check the Spark job status.
`LambdaStateMachineRole`	IAM role	IAM role for all Lambda functions to use the lambda trust relationship.
`EMRCluster`	Amazon EMR cluster	EMR cluster where Livy is running and where the job is placed.

During the AWS CloudFormation deployment phase, it sets up S3 paths for input and output. Input files are stored in the <<s3-root-path>>/emr-step-functions/input/ path, whereas spark-taxi.jar is copied under <<s3-root-path>>/emr-step-functions/.

The following screenshot shows how the S3 paths are configured after deployment. In this example, I passed a bucket that I created in the AWS account s3://tm-app-demos for the S3 root path.

If the CloudFormation template completed successfully, you will see Spark-ETL-State-Machine in the AWS Step Functions dashboard, as follows:

Choose the Spark-ETL-State-Machine state machine to take a look at this implementation. The AWS CloudFormation template built the entire state machine along with its dependent Lambda functions, which are now ready to be executed.

On the dashboard, choose the newly created state machine, and then choose New execution to initiate the state machine. It asks you to pass input in JSON format. This input goes to the first state MilesPerRate Job, which eventually executes the Lambda function blog-miles-per-rate-job-submit-function.

Pass the S3 root path as input:

{

“rootPath”: “s3://tm-app-demos”

}

Then choose Start Execution:

The rootPath value is the same value that was passed when creating the CloudFormation stack. It can be an S3 bucket location or a bucket with prefixes, but it should be the same value that is used for AWS CloudFormation. This value tells the state machine where it can find the Spark jar and input file, and where it will write output files. After the state machine starts, each state/task is executed based on its definition in the state machine.

At a high level, the following represents the flow of events:

Execute the first Spark job, MilesPerRate.
The Spark job reads the input file from the location <<rootPath>>/emr-step-functions/input/tripdata.csv. If the job finishes successfully, it writes the output data to <<rootPath>>/emr-step-functions/miles-per-rate.
If the Spark job fails, it transitions to the error state MilesPerRate job failed, and the state machine stops. If the Spark job finishes successfully, it transitions to the RateCodeStatus Job state, and the second Spark job is executed.
If the second Spark job fails, it transitions to the error state RateCodeStatus job failed, and the state machine stops with the Failed status.
If this Spark job completes successfully, it writes the final output data to the <<rootPath>>/emr-step-functions/rate-code-status/ It also transitions the RateCodeStatus job finished state, and the state machine ends its execution with the Success status.

This following screenshot shows a successfully completed Spark ETL state machine:

The right side of the state machine diagram shows the details of individual states with their input and output.

When you execute the state machine for the second time, it fails because the S3 path already exists. The state machine turns red and stops at MilePerRate job failed. The following image represents that failed execution of the state machine:

You can also check your Spark application status and logs by going to the Amazon EMR console and viewing the Application history tab:

I hope this walkthrough paints a picture of how you can create a serverless solution for orchestrating Spark jobs on Amazon EMR using AWS Step Functions and Apache Livy. In the next section, I share some ideas for making this solution even more elegant.

Next steps

The goal of this post is to show a simple example that uses AWS Step Functions to create an orchestration for Spark-based jobs in a serverless fashion. To make this solution robust and production ready, you can explore the following options:

In this example, I manually initiated the state machine by passing the rootPath as input. You can instead trigger the state machine automatically. To run the ETL pipeline as soon as the files arrive in your S3 bucket, you can pass the new file path to the state machine. Because CloudWatch Events supports AWS Step Functions as a target, you can create a CloudWatch rule for an S3 event. You can then set AWS Step Functions as a target and pass the new file path to your state machine. You’re all set!
You can also improve this solution by adding an alerting mechanism in case of failures. To do this, create a Lambda function that sends an alert email and assigns that Lambda function to a Fail That way, when any part of your state fails, it triggers an email and notifies the user.
If you want to submit multiple Spark jobs in parallel, you can use the Parallel state type in AWS Step Functions. The Parallel state is used to create parallel branches of execution in your state machine.

With Lambda and AWS Step Functions, you can create a very robust serverless orchestration for your big data workload.

Cleaning up

When you’ve finished testing this solution, remember to clean up all those AWS resources that you created using AWS CloudFormation. Use the AWS CloudFormation console or AWS CLI to delete the stack named Blog-Spark-ETL-Step-Functions.

Summary

In this post, I showed you how to use AWS Step Functions to orchestrate your Spark jobs that are running on Amazon EMR. You used Apache Livy to submit jobs to Spark from a Lambda function and created a workflow for your Spark jobs, maintaining a specific order for job execution and triggering different AWS events based on your job’s outcome.
Go ahead—give this solution a try, and share your experience with us!

Additional Reading

If you found this post useful, be sure to check out Building a Real World Evidence Platform on AWS and Building High-Throughput Genomics Batch Workflows on AWS: Workflow Layer (Part 4 of 4).

About the Author

Tanzir Musabbir is an EMR Specialist Solutions Architect with AWS. He is an early adopter of open source Big Data technologies. At AWS, he works with our customers to provide them architectural guidance for running analytics solutions on Amazon EMR, Amazon Athena & AWS Glue. Tanzir is a big Real Madrid fan and he loves to travel in his free time.

Extending AWS CodeBuild with Custom Build Environments for the .NET Framework

2018-05-25 Chris Barclay

Post Syndicated from Chris Barclay original https://aws.amazon.com/blogs/devops/extending-aws-codebuild-with-custom-build-environments-for-the-net-framework/

Thanks to Greg Eppel, Sr. Solutions Architect, Microsoft Platform for this great blog that describes how to create a custom CodeBuild build environment for the .NET Framework.
—
AWS CodeBuild is a fully managed build service that compiles source code, runs tests, and produces software packages that are ready to deploy. CodeBuild provides curated build environments for programming languages and runtimes such as Android, Go, Java, Node.js, PHP, Python, Ruby, and Docker. CodeBuild now supports builds for the Microsoft Windows Server platform, including a prepackaged build environment for .NET Core on Windows. If your application uses the .NET Framework, you will need to use a custom Docker image to create a custom build environment that includes the Microsoft proprietary Framework Class Libraries. For information about why this step is required, see our FAQs. In this post, I’ll show you how to create a custom build environment for .NET Framework applications and walk you through the steps to configure CodeBuild to use this environment.

Build environments are Docker images that include a complete file system with everything required to build and test your project. To use a custom build environment in a CodeBuild project, you build a container image for your platform that contains your build tools, push it to a Docker container registry such as Amazon Elastic Container Registry (Amazon ECR), and reference it in the project configuration. When it builds your application, CodeBuild retrieves the Docker image from the container registry specified in the project configuration and uses the environment to compile your source code, run your tests, and package your application.

Requirements

To follow the steps in this post and build the Docker container image, you need to have Docker for Windows (which is installed if you use a Windows Server with Containers AMI), the AWS Command Line interface, and Git installed. In this post, I’m using Visual Studio Build Tools 2017.

Step 1: Launch EC2 Windows Server 2016 with Containers

In the Amazon EC2 console, in your region, launch an Amazon EC2 instance from a Microsoft Windows Server 2016 Base with Containers AMI.
Increase disk space on the boot volume to at least 50 GB to account for the larger size of containers required to install and run Visual Studio Build Tools.
When the instance is running, connect to it using Remote Desktop.

Step 2: Build and push the Docker image

Open an elevated command prompt (that is, right-click on your favorite shell and choose Run as Administrator).
Create a directory:
```
mkdir C:\BuildTools
cd C:\BuildTools
```

Save the following content to C:\BuildTools\Dockerfile:

# escape=`

FROM microsoft/dotnet-framework:4.7.2-runtime

SHELL ["powershell", "-Command", "$ErrorActionPreference = 'Stop'; $ProgressPreference = 'SilentlyContinue';"]

#Install NuGet CLI
ENV NUGET_VERSION 4.4.1
RUN New-Item -Type Directory $Env:ProgramFiles\NuGet; `
    Invoke-WebRequest -UseBasicParsing https://dist.nuget.org/win-x86-commandline/v$Env:NUGET_VERSION/nuget.exe -OutFile $Env:ProgramFiles\NuGet\nuget.exe

# Install VS Test Agent
RUN Invoke-WebRequest -UseBasicParsing https://download.visualstudio.microsoft.com/download/pr/12210068/8a386d27295953ee79281fd1f1832e2d/vs_TestAgent.exe -OutFile vs_TestAgent.exe; `
    Start-Process vs_TestAgent.exe -ArgumentList '--quiet', '--norestart', '--nocache' -NoNewWindow -Wait; `
    Remove-Item -Force vs_TestAgent.exe; `
# Install VS Build Tools
    Invoke-WebRequest -UseBasicParsing https://download.visualstudio.microsoft.com/download/pr/12210059/e64d79b40219aea618ce2fe10ebd5f0d/vs_BuildTools.exe -OutFile vs_BuildTools.exe; `
    # Installer won't detect DOTNET_SKIP_FIRST_TIME_EXPERIENCE if ENV is used, must use setx /M
    setx /M DOTNET_SKIP_FIRST_TIME_EXPERIENCE 1; `
    Start-Process vs_BuildTools.exe -ArgumentList '--add', 'Microsoft.VisualStudio.Workload.MSBuildTools', '--add', 'Microsoft.VisualStudio.Workload.NetCoreBuildTools', '--add', 'Microsoft.VisualStudio.Workload.WebBuildTools;includeRecommended', '--quiet', '--norestart', '--nocache' -NoNewWindow -Wait; `
    Remove-Item -Force vs_buildtools.exe; `
    Remove-Item -Force -Recurse \"${Env:ProgramFiles(x86)}\Microsoft Visual Studio\Installer\"; `
    Remove-Item -Force -Recurse ${Env:TEMP}\*; `
    Remove-Item -Force -Recurse \"${Env:ProgramData}\Package Cache\"

# Set PATH in one layer to keep image size down.
RUN setx /M PATH $(${Env:PATH} `
    + \";${Env:ProgramFiles}\NuGet\" `
    + \";${Env:ProgramFiles(x86)}\Microsoft Visual Studio\2017\TestAgent\Common7\IDE\CommonExtensions\Microsoft\TestWindow\" `
    + \";${Env:ProgramFiles(x86)}\Microsoft Visual Studio\2017\BuildTools\MSBuild\15.0\Bin\")

# Install Targeting Packs
RUN @('4.0', '4.5.2', '4.6.2', '4.7.2') `
    | %{ `
        Invoke-WebRequest -UseBasicParsing https://dotnetbinaries.blob.core.windows.net/referenceassemblies/v${_}.zip -OutFile referenceassemblies.zip; `
        Expand-Archive -Force referenceassemblies.zip -DestinationPath \"${Env:ProgramFiles(x86)}\Reference Assemblies\Microsoft\Framework\.NETFramework\"; `
        Remove-Item -Force referenceassemblies.zip; `
    }

Run the following command in that directory. This process can take a while. It depends on the size of EC2 instance you launched. In my tests, a t2.2xlarge takes less than 30 minutes to build the image and produces an approximately 15 GB image.
```
docker build -t buildtools2017:latest -m 2GB .
```
Run the following command to test the container and start a command shell with all the developer environment variables:
```
docker run -it buildtools2017
```
Create a repository in the Amazon ECS console. For the repository name, type buildtools2017. Choose Next step and then complete the remaining steps.
Execute the following command to generate authentication details for our registry to the local Docker engine. Make sure you have permissions to the Amazon ECR registry before you execute the command.
```
aws ecr get-login
```

In the same command prompt window, copy and paste the following commands:

docker tag buildtools2017:latest [YOUR ACCOUNT #].dkr.ecr.[YOUR REGION].amazonaws.com/ buildtools2017:latest
docker push [YOUR ACCOUNT #].dkr.ecr.[YOUR REGION].amazonaws.com/buildtools2017:latest

Note: Make sure you replace [YOUR ACCOUNT #] with your AWS account number and [YOUR REGION] with the region you are using.

Step 3: Configure AWS CodeCommit

Before you can access CodeCommit for the first time, you must complete the initial configuration steps.
In the CodeCommit console, create a repository named DotNetFrameworkSampleApp. On the Configure email notifications page, choose Skip.

Clone a .NET Framework Docker sample application from GitHub. The repository includes a sample ASP.NET Framework that we’ll use to demonstrate our custom build environment.On the EC2 instance, open a command prompt and execute the following commands:

git clone https://github.com/Microsoft/dotnet-framework-docker-samples.git
cd dotnet-framework-docker-samples
del /Q /S .git
cd aspnetapp
git init
git add . 
git commit -m "First commit"
git remote add origin https://git-codecommit.[YOURREGION].amazonaws.com/v1/repos/DotNetFrameworkSampleApp
git remote -v
git push -u origin master

Navigate to the CodeCommit repository and confirm that the files you just pushed are there.

Step 4: Configure build spec

To build your .NET Framework application with CodeBuild you use a build spec, which is a collection of build commands and related settings, in YAML format, that AWS CodeBuild can use to run a build. You can include a build spec as part of the source code or you can define a build spec when you create a build project. In this example, I include a build spec as part of the source code.

In the root directory of your source directory, create a YAML file named buildspec.yml.

Copy the following contents to buildspec.yml:

version: 0.2

phases:
  pre_build:
    commands:
     - New-Item -ItemType Junction -Path C:\Src -Value $Env:CODEBUILD_SRC_DIR
     - cd C:\Src  
     - nuget.exe restore
  build:
    commands:
     - msbuild

Save the changes to the buildspec.yml and use the following commands to add the file to the CodeCommit repository:
```
git add . 
git commit -m "Added a build spec file"
git push
```

Step 5: Configure CodeBuild

At this point, we have a Docker image with Visual Studio Build Tools installed and stored in the Amazon ECR registry. We also have a sample ASP.NET Framework application in a CodeCommit repository. Now we are going to set up CodeBuild to build the ASP.NET Framework application.

In the Amazon ECR console, choose the repository that was pushed earlier with the docker push command. On the Permissions tab, choose Add.
1. For Sid, field give it a unique name.
2. For Effect, choose Allow.
3. For Principal, type codebuild.amazonaws.com.
4. For Action, choose Pull only actions.
5. Choose Save All.
Go to the CodeBuild console, and choose Create Project.
For Project name, type DotNetFrameworkSampleApp.
For Source Provider, choose AWS CodeCommit and then choose the called DotNetFrameworkSampleApp repository.
For Environment Image, choose Specify a Docker image.
For Environment type, choose Windows.
For Custom image type, choose Amazon ECR.
For Amazon ECR repository, choose the Docker image with the Visual Studio Build Tools installed, buildtools2017. Your configuration should look like the image below:
Choose Continue and then Save and Build to create your CodeBuild project and start your first build. You can monitor the status of the build in the console. You can also configure notifications that will notify subscribers whenever builds succeed, fail, go from one phase to another, or any combination of these events.

Summary

CodeBuild supports a number of platforms and languages out of the box. By using custom build environments, it can be extended to other runtimes. In this post, I showed you how to build a .NET Framework environment on a Windows container and demonstrated how to use it to build .NET Framework applications in CodeBuild.

We’re excited to see how customers extend and use CodeBuild to enable continuous integration and continuous delivery for their Windows applications. Feel free to share what you’ve learned extending CodeBuild for your own projects. Just leave questions or suggestions in the comments.

Steal This Show S03E16: The TAO of the DAO Pt. 2

2018-05-25 Ernesto

Post Syndicated from Ernesto original https://torrentfreak.com/steal-show-s03e16-tao-dao-pt-2/

stslogo180 ^{If you enjoy this episode, consider becoming a patron and getting involved with the show. Check out Steal This Show’s Patreon campaign: support us and get all kinds of fantastic benefits!}

This is the second part of our interview with Chris Beams, founder of the decentralised cryptocurrency exchange, Bisq. We discuss the inner workings of the Bisq service, how it compares to the widely used platform Local Bitcoins, and the intricacies of designing decentral P2P systems for financial operations.

From there, we move into some of the political/philosophical implications of Bisq as a Distributed Autonomous Organisation (DAO): are we evolving, with Bitcoin and other P2P networks, functionalities which parallel certain present-day institutions, and which could one day eliminate the need for establishment altogether?

And could a future democracy be composed of “opt-in” components that actually do better at providing for our basic human needs?

—

Steal This Show aims to release bi-weekly episodes featuring insiders discussing copyright and file-sharing news. It complements our regular reporting by adding more room for opinion, commentary, and analysis.

The guests for our news discussions will vary, and we’ll aim to introduce voices from different backgrounds and persuasions. In addition to news, STS will also produce features interviewing some of the great innovators and minds.

Host: Jamie King

Guest: Chris Beams

Produced by Jamie King
Edited & Mixed by Riley Byrne
Original Music by David Triana
Web Production by Siraje Amarniss

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN reviews, discounts, offers and coupons.

Enchanting images with Inky Lines, a Pi‑powered polargraph

2018-05-25 Helen Lynn

Post Syndicated from Helen Lynn original https://www.raspberrypi.org/blog/enchanting-images-inky-lines-pi-powered-polargraph/

A hanging plotter, also known as a polar plotter or polargraph, is a machine for drawing images on a vertical surface. It does so by using motors to control the length of two cords that form a V shape, supporting a pen where they meet. We’ve featured one on this blog before: Norbert “HomoFaciens” Heinz’s video is a wonderfully clear introduction to how a polargraph works and what you have to consider when you’re putting one together.

Today, we look at Inky Lines, by John Proudlock. With it, John is creating a series of captivating and beautiful pieces, and with his most recent work, each rendering of an image is unique.

An evolving project

The project isn’t new – John has been working on it for at least a couple of years – but it is constantly evolving. When we first spotted it, John had just implemented code to allow the plotter to produce mesmeric, spiralling patterns.

But we’re skipping ahead. Let’s go back to the beginning.

From pixels to motor movements

John starts by providing an image, usually no more than 100 pixels wide, to a Raspberry Pi. Custom software that he wrote evaluates the darkness of each pixel and selects a pattern of a suitable density to represent it.

The two cords supporting the plotter’s pen are wound around the shafts of two stepper motors, such that the movement of the motors controls the length of the cords: the program next calculates how much each motor must move in order to produce the pattern. The Raspberry Pi passes corresponding instructions to two motor circuits, which transform the signals to a higher voltage and pass them to the stepper motors. These turn by very precise amounts, winding or unwinding the cords and, very slowly, dragging the pen across the paper.

John explains,

Suspended in-between the two motors is a print head, made out of a new 3-d modelling material I’ve been prototyping called cardboard. An old coat hanger and some velcro were also used.

(He’s our kind of maker.)

Unique images

The earlier drawings that John made used a repeatable method to render image files as lines on paper. That is, if the machine drew the same image a number of times, each copy would be identical. More recently, though, he has been using a method that yields random movements of the pen:

The pen point is guided around the image, but moves to each new point entirely at random. Up close this looks like a chaotic squiggle, but from a distance of a couple of meters, the human eye (and brain) make order from the chaos and view an infinite number of shades and a smoother, less mechanical image.

This method means that no matter how many times the polargraph repeats the same image, each copy will be unique.

A gallery of work

Inky Lines’ website and its Instagram feed offer a collection of wonderful pieces John has drawn with his polargraph, and he discusses the different techniques and types of image that he is exploring.

They range from holiday photographs, processed to extract particular features and rendered in silhouette, to portraits, made with a single continuous line that can be several hundred metres long, to generative images spirograph images like those pictured above, created by an algorithm rather than rendered from a source image.

The post Enchanting images with Inky Lines, a Pi‑powered polargraph appeared first on Raspberry Pi.

Integrating JFrog Artifactory with AWS CodePipeline

2018-05-24 Erin McGill

Post Syndicated from Erin McGill original https://aws.amazon.com/blogs/devops/integrating-jfrog-artifactory-with-aws-codepipeline/

When I talk with customers and partners, I find that they are in different stages in the adoption of DevOps methodologies. They are automating the creation of application artifacts and the deployment of their applications to different infrastructure environments. In many cases, they are creating and supporting multiple applications using a variety of coding languages and artifacts.

The management of these processes and artifacts can be challenging, but using the right tools and methodologies can simplify the process.

In this post, I will show you how you can automate the creation and storage of application artifacts through the implementation of a pipeline and custom deploy action in AWS CodePipeline. The example includes a Node.js code base stored in an AWS CodeCommit repository. A Node Package Manager (npm) artifact is built from the code base, and the build artifact is published to a JFrog Artifactory npm repository.

I frequently recommend AWS CodePipeline, the AWS continuous integration and continuous delivery tool. You can use it to quickly innovate through integration and deployment of new features and bug fixes by building a workflow that automates the build, test, and deployment of new versions of your application. And, because AWS CodePipeline is extensible, it allows you to create a custom action that performs customized, automated actions on your behalf.

JFrog’s Artifactory is a universal binary repository manager where you can manage multiple applications, their dependencies, and versions in one place. Artifactory also enables you to standardize the way you manage your package types across all applications developed in your company, no matter the code base or artifact type.

If you already have a Node.js CodeCommit repository, a JFrog Artifactory host, and would like to automate the creation of the pipeline, including the custom action and CodeBuild project, you can use this AWS CloudFormation template to create your AWS CloudFormation stack.

The project code can be found in this GitHub repository: https://github.com/aws-samples/aws-codepipeline-custom-job-worker-for-jfrog-artifactory.

The AWS CodePipeline workflow

This figure shows the path defined in the pipeline for this project. It starts with a change to Node.js source code committed to a private code repository in AWS CodeCommit. With this change, CodePipeline triggers AWS CodeBuild to create the npm package from the node.js source code. After the build, CodePipeline triggers the custom action job worker to commit the build artifact to the designated artifact repository in Artifactory.

This blog post assumes you have already:

· Created a CodeCommit repository that contains a Node.js project.

· Configured a two-stage pipeline in AWS CodePipeline.

The Source stage of the pipeline is configured to poll the Node.js CodeCommit repository. The Build stage is configured to use a CodeBuild project to build the npm package using a buildspec.yml file located in the code repository.

If you do not have a Node.js repository, you can create a CodeCommit repository that contains this simple ‘Hello World’ project. This project also includes a buildspec.yml file that is used when you define your CodeBuild project. It defines the steps to be taken by CodeBuild to create the npm artifact.

If you do not already have a pipeline set up in CodePipeline, you can use this template to create a pipeline with a CodeCommit source action and a CodeBuild build action through the AWS Command Line Interface (AWS CLI). If you do not want to install the AWS CLI on your local machine, you can use AWS Cloud9, our managed integrated development environment (IDE), to interact with AWS APIs.

In your development environment, open your favorite editor and fill out the template with values appropriate to your project. For information, see the readme in the GitHub repository.

Use this CLI command to create the pipeline from the template:

aws codepipeline create-pipeline --cli-input-json file://source-build-actions-codepipeline.json --region 'us-west-2'

It creates a pipeline that has a CodeCommit source action and a CodeBuild build action.

Integrating JFrog Artifactory

JFrog Artifactory provides default repositories for your project needs. For my NPM package repository, I am using the default virtual npm repository (named npm) that is available in Artifactory Pro. You might want to consider creating a repository per project but for the example used in this post, using the default lets me get started without having to configure a new repository.

I can use the steps in the Set Me Up -> npm section on the landing page to configure my worker to interact with the default NPM repository.

Custom actions in AWS CodePipeline

A custom action in AWS CodePipeline contains:

· custom action definition

Describes the required values to run the custom action. I will define my custom action in the ‘Deploy’ category, identify the provider as ‘Artifactory’, of version ‘1’, and specify a variety of configurationProperties whose values will be defined when this stage is added to my pipeline.

· custom action job worker

Polls CodePipeline for a job, scanning for its action-definition properties. In this blog post, after a job has been found, the job worker does the work required to publish the npm artifact to the Artifactory repository.

My custom action definition in JSON:

{
    "category": "Deploy",
    "configurationProperties": [{
        "name": "TypeOfArtifact",
        "required": true,
        "key": true,
        "secret": false,
        "description": "Package type, ex. npm for node packages",
        "type": "String"
    },
    {   "name": "RepoKey",
        "required": true,
        "key": true,
	"secret": false,
	"type": "String",
	"description": "Name of the repository in which this artifact should be stored"
    },
    {   "name": "UserName",
        "required": true,
        "key": true,
	"secret": false,
	"type": "String",
	"description": "Username for authenticating with the repository"
    },
    {   "name": "Password",
        "required": true,
        "key": true,
	"secret": true,
	"type": "String",
	"description": "Password for authenticating with the repository"
    },
    {   "name": "EmailAddress",
        "required": true,
        "key": true,
	"secret": false,
	"type": "String",
	"description": "Email address used to authenticate with the repository"
    },
    {   "name": "ArtifactoryHost",
        "required": true,
        "key": true,
	"secret": false,
	"type": "String",
	"description": "Public address of Artifactory host, ex: https://myexamplehost.com or http://myexamplehost.com:8080"
    }],
    "provider": "Artifactory",
    "version": "1",
    "settings": {
        "entityUrlTemplate": "{Config:ArtifactoryHost}/artifactory/webapp/#/artifacts/browse/tree/General/{Config:RepoKey}"
    },
    "inputArtifactDetails": {
        "maximumCount": 5,
        "minimumCount": 1
    },
    "outputArtifactDetails": {
        "maximumCount": 5,
        "minimumCount": 0
    }
}

There are seven sections to the custom action definition:

category: This is the stage in which you will be creating this action. It can be Source, Build, Deploy, Test, Invoke, Approval. Except for source actions, the category section simply allows us to organize our actions. I am setting the category for my action as ‘Deploy’ because I’m using it to publish my node artifact to my Artifactory instance.
configurationProperties: These are the parameters or variables required for your project to authenticate and commit your artifact. In the case of my custom worker, I need:
- TypeOfArtifact: In this case, npm, because it’s for the Node Package Manager.
- RepoKey: The name of the repository. In this case, it’s the default npm.
- UserName and Password for the user to authenticate with the Artifactory repository.
- EmailAddress used to authenticate with the repository.
- Artifactory host name or IP address.
provider: The name you define for your custom action stage. I have named the provider Artifactory.
version: Version number for the custom action. Because this is the first version, I set the version number to 1.
entityUrlTemplate: This URL is presented to your users for the deploy stage along with the title you define in your provider. The link takes the user to their artifact repository page in the Artifactory host.
inputArtifactDetails: The number of artifacts to expect from the previous stage in the pipeline.
outputArtifactDetails: The number of artifacts that should be the result from the custom action stage. Later in this blog post, I define 0 for my output artifacts because I am publishing the artifact to the Artifactory repository as the final action.

After I define the custom action in a JSON file, I use the AWS CLI to create the custom action type in CodePipeline:

aws codepipeline create-custom-action-type --cli-input-json file://artifactory_custom_action_deploy_npm.json --region='us-west-2'

After I create the custom action type in the same region as my pipeline, I edit the pipeline to add a Deploy stage and configure it to use the custom action I created for Artifactory:

I have created a custom worker for the actions required to commit the npm artifact to the Artifactory repository. The worker is in Python and it runs in a loop on an Amazon EC2 instance. My custom worker polls for a deploy job and publishes the NPM artifact to the Artifactory repository.

The EC2 instance is running Amazon Linux and has an IAM instance role attached that gives the worker permission to access CodePipeline. The worker process is as follows:

Take the configuration properties from the custom worker and poll CodePipeline for a custom action job.
After there is a job in the job queue with the appropriate category, provider, and version, acknowledge the job.
Download the zipped artifact created in the previous Build stage from the provided S3 buckets with the provided temporary credentials.
Unzip the artifact into a temporary directory.
A user-defined Artifactory user name and password is used to receive a temporary API key from Artifactory.
To avoid having to write the password to a file, use that temporary API key and user name to authenticate with the NPM repository.
Publish the Node.js package to the specified repository.

Because I am running my custom worker on an Amazon Linux EC2 instance, I installed npm with the following command:

sudo yum install nodejs npm --enablerepo=epel

For my custom worker, I used pip to install the required Python libraries:

pip install boto3 requests

For a full Python package list, see requirements.txt in the GitHub repository.

Let’s take a look at some of the code snippets from the worker.

First, the worker polls for jobs:

def action_type():
    ActionType = {
        'category': 'Deploy',
        'owner': 'Custom',
        'provider': 'Artifactory',
        'version': '1' }
    return(ActionType)

def poll_for_jobs():
    try:
        artifactory_action_type = action_type()
        print(artifactory_action_type)
        jobs = codepipeline.poll_for_jobs(actionTypeId=artifactory_action_type)
        while not jobs['jobs']:
            time.sleep(10)
            jobs = codepipeline.poll_for_jobs(actionTypeId=artifactory_action_type)
            if jobs['jobs']:
                print('Job found')
        return jobs['jobs'][0]
    except ClientError as e:
        print("Received an error: %s" % str(e))
        raise

When there is a job in the queue, the poller returns a number of values from the queue such as jobId, the input and output S3 buckets for artifacts, temporary credentials to access the S3 buckets, and other configuration details from the stage in the pipeline.

Here is an example of the return response:

{
	'jobs': [
		{
			'nonce': '3',
			'data': {
				'inputArtifacts': [
					{
						'name': 'Output',
						'location': {
							'type': 'S3',
							's3Location': {
								'objectKey': 'ArtifactoryNPMwithCo/Output/Key,
							'bucketName': '123456789012-codepipelineartifact-us-west-2'
							}
						}
					}
				],
				'pipelineContext': {
						'action': {
							'name': 'Deploy'
						},
						'pipelineName': 'ArtifactoryNPMwithCodeDeploy',
						'stage': {
							'name': 'Deploy'
						}
				},
				'actionTypeId': {
					'category': 'Deploy',
					'owner': 'Custom',
					'version': '1',
					'provider': 'Artifactory'
				},
				'outputArtifacts': [
					{
						'name': 'ArtifactoryOut',
						'location': {
							'type': 'S3',
							's3Location': {
								'objectKey': 'ArtifactoryNPMwithCo/Artifactor/Key,
								'bucketName': '123456789012-codepipelineartifact-us-west-2'
							}
						}
					}
				],
				'actionConfiguration': {
					'configuration': {
						'UserName': 'admin',
						'ArtifactoryHost': 'https://artifactory.myexamplehost.com',
						'Password': 'xxx',
						'EmailAddress': '[email protected]',
						'TypeOfArtifact': 'npm',
						'RepoKey': 'npm'
					}
				},
				'artifactCredentials': {
					'secretAccessKey': 'SECRET',
			               'sessionToken':‘FQoDYXdz...XdndMF',
					'accessKeyId': 'ACCESSKEY'
					}
				},
				'id': 'a0eb',
				'accountId': '123456789012
			}
		],
		'ResponseMetadata': {
			'RetryAttempts': 0,
			'HTTPStatusCode': 200,
			'RequestId': a88b-cdbd5d08b9de',
			'HTTPHeaders': {
				'x-amzn-requestid': '77343c2d-eff4’,
				'content-length': '2461',
				'content-type': 'application/x-amz-json-1.1'
			}
		}
}

After successfully receiving the job details, the worker sends an acknowledgement to CodePipeline to ensure that the work on the job is not duplicated by other workers watching for the same job:

def job_acknowledge(jobId, nonce):
    try:
        print('Acknowledging job')
        result = codepipeline.acknowledge_job(jobId=jobId, nonce=nonce)
        return result
    except Exception as e:
        print("Received an error when trying to acknowledge the job: %s" % str(e))
        raise

With the job now acknowledged, the worker publishes the source code artifact into the desired repository. The worker gets the value of the artifact S3 bucket and objectKey from the inputArtifacts in the response from the poll_for_jobs API request. Next, the worker creates a new directory in /tmp and downloads the S3 object into this directory:

def get_bucket_location(bucketName, init_client):
    region = init_client.get_bucket_location(Bucket=bucketName)['LocationConstraint']
    if not region:
        region = 'us-east-1'
    return region


def get_s3_artifact(bucketName, objectKey, ak, sk, st):
    init_s3 = boto3.client('s3')
    region = get_bucket_location(bucketName, init_s3)
    session = Session(aws_access_key_id=ak,
                      aws_secret_access_key=sk,
                      aws_session_token=st)

    s3 = session.resource('s3',
                          region_name=region,
                          config=botocore.client.Config(signature_version='s3v4'))
    try:
        tempdirname = tempfile.mkdtemp()
    except OSError as e:
        print('Could not write temp directory %s' % tempdirname)
        raise
    bucket = s3.Bucket(bucketName)
    obj = bucket.Object(objectKey)
    filename = tempdirname + '/' + objectKey
    try:
        if os.path.dirname(objectKey):
            directory = os.path.dirname(filename)
            os.makedirs(directory)
        print('Downloading the %s object and writing it to disk in %s location' % (objectKey, tempdirname))
        with open(filename, 'wb') as data:
            obj.download_fileobj(data)
    except ClientError as e:
        print('Downloading the object and writing the file to disk raised this error: ' + str(e))
        raise
    return(filename, tempdirname)

Because the downloaded artifact from S3 is a zip file, the worker must unzip it first. To have a clean area in which to work, I extract the downloaded zip archive into a new directory:

def unzip_codepipeline_artifact(artifact, origtmpdir):
    # create a new temp directory
    # Unzip artifact into new directory
    try:
        newtempdir = tempfile.mkdtemp()
        print('Extracting artifact %s into temporary directory %s' % (artifact, newtempdir))
        zip_ref = zipfile.ZipFile(artifact, 'r')
        zip_ref.extractall(newtempdir)
        zip_ref.close()
        shutil.rmtree(origtmpdir)
        return(os.listdir(newtempdir), newtempdir)
    except OSError as e:
        if e.errno != errno.EEXIST:
            shutil.rmtree(newtempdir)
            raise

The worker now has the npm package that I want to store in my Artifactory NPM repository.

To authenticate with the NPM repository, the worker requests a temporary token from the Artifactory host. After receiving this temporary token, it creates a .npmrc file in the worker user’s home directory that includes a hash of the user name and temporary token. After it has authenticated, the worker runs npm config set registry <URL OF REPOSITORY> to configure the npm registry value to be the Artifactory host. Next, the worker runs npm publish –registry <URL OF REPOSITORY>, which publishes the node package to the NPM repository in the Artifactory host.

def push_to_npm(configuration, artifact_list, temp_dir, jobId):
    reponame = configuration['RepoKey']
    art_type = configuration['TypeOfArtifact']
    print("Putting artifact into NPM repository " + reponame)
    token, hostname, username = gen_artifactory_auth_token(configuration)
    npmconfigfile = create_npmconfig_file(configuration, username, token)
    url = hostname + '/artifactory/api/' + art_type + '/' + reponame
    print("Changing directory to " + str(temp_dir))
    os.chdir(temp_dir)
    try:
        print("Publishing following files to the repository: %s " % os.listdir(temp_dir))
        print("Sending artifact to Artifactory NPM registry URL: " + url)
        subprocess.call(["npm", "config", "set", "registry", url])
        req = subprocess.call(["npm", "publish", "--registry", url])
        print("Return code from npm publish: " + str(req))
        if req != 0:
            err_msg = "npm ERR! Recieved non OK response while sending response to Artifactory. Return code from npm publish: " + str(req)
            signal_failure(jobId, err_msg)
        else:
            signal_success(jobId)
    except requests.exceptions.RequestException as e:
       print("Received an error when trying to commit artifact %s to repository %s: " % (str(art_type), str(configuration['RepoKey']), str(e)))
       raise
    return(req, npmconfigfile)

If the return value from publishing to the repository is not 0, the worker signals a failure to CodePipeline. If the value is 0, the worker signals success to CodePipeline to indicate that the stage of the pipeline has been completed successfully.

For the custom worker code, see npm_job_worker.py in the GitHub repository.

I run my custom worker on an EC2 instance using the command python npm_job_worker.py, with an optional --version flag that can be used to specify worker versions other than 1. Then I trigger a release change in my pipeline:

From my custom worker output logs, I have just committed a package named node_example at version 1.0.3:

On artifact: index.js
Committing to the repo: https://artifactory.myexamplehost.com/artifactory/api/npm/npm
Sending artifact to Artifactory URL: https:// artifactoryhost.myexamplehost.com/artifactory/api/npm/npm
npm config: 0
npm http PUT https://artifactory.myexamplehost.com/artifactory/api/npm/npm/node_example
npm http 201 https://artifactory.myexamplehost.com/artifactory/api/npm/npm/node_example
+ [email protected]
Return code from npm publish: 0
Signaling success to CodePipeline

After that has been built successfully, I can find my artifact in my Artifactory repository:

To help you automate this process, I have created this AWS CloudFormation template that automates the creation of the CodeBuild project, the custom action, and the CodePipeline pipeline. It also launches the Amazon EC2-based custom job worker in an AWS Auto Scaling group. This template requires you to have a VPC and CodeCommit repository for your Node.js project. If you do not currently have a VPC in which you want to run your custom worker EC2 instances, you can use this AWS QuickStart to create one. If you do not have an existing Node.js project, I’ve provided a sample project in the GitHub repository.

Conclusion

I‘ve shown you the steps to integrate your JFrog Artifactory repository with your CodePipeline workflow. I’ve shown you how to create a custom action in CodePipeline and how to create a custom worker that works in your CI/CD pipeline. To dig deeper into custom actions and see how you can integrate your Artifactory repositories into your AWS CodePipeline projects, check out the full code base on GitHub.

If you have any questions or feedback, feel free to reach out to us through the AWS CodePipeline forum.

Erin McGill is a Solutions Architect in the AWS Partner Program with a focus on DevOps and automation tooling.

Replacing macOS Server with Synology NAS

2018-05-24 Roderick Bauer

Post Syndicated from Roderick Bauer original https://www.backblaze.com/blog/replacing-macos-server-with-synology-nas/

Businesses and organizations that rely on macOS server for essential office and data services are facing some decisions about the future of their IT services.

Apple recently announced that it is deprecating a significant portion of essential network services in macOS Server, as they described in a support statement posted on April 24, 2018, “Prepare for changes to macOS Server.” Apple’s note includes:

macOS Server is changing to focus more on management of computers, devices, and storage on your network. As a result, some changes are coming in how Server works. A number of services will be deprecated, and will be hidden on new installations of an update to macOS Server coming in spring 2018.

The note lists the services that will be removed in a future release of macOS Server, including calendar and contact support, Dynamic Host Configuration Protocol (DHCP), Domain Name Services (DNS), mail, instant messages, virtual private networking (VPN), NetInstall, Web server, and the Wiki.

Apple assures users who have already configured any of the listed services that they will be able to use them in the spring 2018 macOS Server update, but the statement ends with links to a number of alternative services, including hosted services, that macOS Server users should consider as viable replacements to the features it is removing. These alternative services are all FOSS (Free and Open-Source Software).

As difficult as this could be for organizations that use macOS server, this is not unexpected. Apple left the server hardware space back in 2010, when Steve Jobs announced the company was ending its line of Xserve rackmount servers, which were introduced in May, 2002. Since then, macOS Server has hardly been a prominent part of Apple’s product lineup. It’s not just the product itself that has lost some luster, but the entire category of SMB office and business servers, which has been undergoing a gradual change in recent years.

Some might wonder how important the news about macOS Server is, given that macOS Server represents a pretty small share of the server market. macOS Server has been important to design shops, agencies, education users, and small businesses that likely have been on Macs for ages, but it’s not a significant part of the IT infrastructure of larger organizations and businesses.

What Comes After macOS Server?

Lovers of macOS Server don’t have to fear having their Mac minis pried from their cold, dead hands quite yet. Installed services will continue to be available. In the fall of 2018, new installations and upgrades of macOS Server will require users to migrate most services to other software. Since many of the services of macOS Server were already open-source, this means that a change in software might not be required. It does mean more configuration and management required from those who continue with macOS Server, however.

Users can continue with macOS Server if they wish, but many will see the writing on the wall and look for a suitable substitute.

The Times They Are A-Changin’

For many people working in organizations, what is significant about this announcement is how it reflects the move away from the once ubiquitous server-based IT infrastructure. Services that used to be centrally managed and office-based, such as storage, file sharing, communications, and computing, have moved to the cloud.

In selecting the next office IT platforms, there’s an opportunity to move to solutions that reflect and support how people are working and the applications they are using both in the office and remotely. For many, this means including cloud-based services in office automation, backup, and business continuity/disaster recovery planning. This includes Software as a Service, Platform as a Service, and Infrastructure as a Service (Saas, PaaS, IaaS) options.

IT solutions that integrate well with the cloud are worth strong consideration for what comes after a macOS Server-based environment.

Synology NAS as a macOS Server Alternative

One solution that is becoming popular is to replace macOS Server with a device that has the ability to provide important office services, but also bridges the office and cloud environments. Using Network-Attached Storage (NAS) to take up the server slack makes a lot of sense. Many customers are already using NAS for file sharing, local data backup, automatic cloud backup, and other uses. In the case of Synology, their operating system, Synology DiskStation Manager (DSM), is Linux based, and integrates the basic functions of file sharing, centralized backup, RAID storage, multimedia streaming, virtual storage, and other common functions.

Synology NAS

Since DSM is based on Linux, there are numerous server applications available, including many of the same ones that are available for macOS Server, which shares conceptual roots with Linux as it comes from BSD Unix.

Synology DiskStation Manager Package Center

According to Ed Lukacs, COO at 2FIFTEEN Systems Management in Salt Lake City, their customers have found the move from macOS Server to Synology NAS not only painless, but positive. DSM works seamlessly with macOS and has been faster for their customers, as well. Many of their customers are running Adobe Creative Suite and Google G Suite applications, so a workflow that combines local storage, remote access, and the cloud, is already well known to them. Remote users are supported by Synology’s QuickConnect or VPN.

Business continuity and backup are simplified by the flexible storage capacity of the NAS. Synology has built-in backup to Backblaze B2 Cloud Storage with Synology’s Cloud Sync, as well as a choice of a number of other B2-compatible applications, such as Cloudberry, Comet, and Arq.

Customers have been able to get up and running quickly, with only initial data transfers requiring some time to complete. After that, management of the NAS can be handled in-house or with the support of a Managed Service Provider (MSP).

Are You Sticking with macOS Server or Moving to Another Platform?

If you’re affected by this change in macOS Server, please let us know in the comments how you’re planning to cope. Are you using Synology NAS for server services? Please tell us how that’s working for you.

The post Replacing macOS Server with Synology NAS appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

C is to low level

2018-05-23 Robert Graham

Post Syndicated from Robert Graham original https://blog.erratasec.com/2018/05/c-is-too-low-level.html

I’m in danger of contradicting myself, after previously pointing out that x86 machine code is a high-level language, but this article claiming C is a not a low level language is bunk. C certainly has some problems, but it’s still the closest language to assembly. This is obvious by the fact it’s still the fastest compiled language. What we see is a typical academic out of touch with the real world.

The author makes the (wrong) observation that we’ve been stuck emulating the PDP-11 for the past 40 years. C was written for the PDP-11, and since then CPUs have been designed to make C run faster. The author imagines a different world, such as where CPU designers instead target something like LISP as their preferred language, or Erlang. This misunderstands the state of the market. CPUs do indeed supports lots of different abstractions, and C has evolved to accommodate this.

The author criticizes things like “out-of-order” execution which has lead to the Spectre sidechannel vulnerabilities. Out-of-order execution is necessary to make C run faster. The author claims instead that those resources should be spent on having more slower CPUs, with more threads. This sacrifices single-threaded performance in exchange for a lot more threads executing in parallel. The author cites Sparc Tx CPUs as his ideal processor.

But here’s the thing, the Sparc Tx was a failure. To be fair, it’s mostly a failure because most of the time, people wanted to run old C code instead of new Erlang code. But it was still a failure at running Erlang.

Time after time, engineers keep finding that “out-of-order”, single-threaded performance is still the winner. A good example is ARM processors for both mobile phones and servers. All the theory points to in-order CPUs as being better, but all the products are out-of-order, because this theory is wrong. The custom ARM cores from Apple and Qualcomm used in most high-end phones are so deeply out-of-order they give Intel CPUs competition. The same is true on the server front with the latest Qualcomm Centriq and Cavium ThunderX2 processors, deeply out of order supporting more than 100 instructions in flight.

The Cavium is especially telling. Its ThunderX CPU had 48 simple cores which was replaced with the ThunderX2 having 32 complex, deeply out-of-order cores. The performance increase was massive, even on multithread-friendly workloads. Every competitor to Intel’s dominance in the server space has learned the lesson from Sparc Tx: many wimpy cores is a failure, you need fewer beefy cores. Yes, they don’t need to be as beefy as Intel’s processors, but they need to be close.

Even Intel’s “Xeon Phi” custom chip learned this lesson. This is their GPU-like chip, running 60 cores with 512-bit wide “vector” (sic) instructions, designed for supercomputer applications. Its first version was purely in-order. Its current version is slightly out-of-order. It supports four threads and focuses on basic number crunching, so in-order cores seems to be the right approach, but Intel found in this case that out-of-order processing still provided a benefit. Practice is different than theory.

As an academic, the author of the above article focuses on abstractions. The criticism of C is that it has the wrong abstractions which are hard to optimize, and that if we instead expressed things in the right abstractions, it would be easier to optimize.

This is an intellectually compelling argument, but so far bunk.

The reason is that while the theoretical base language has issues, everyone programs using extensions to the language, like “intrinsics” (C ‘functions’ that map to assembly instructions). Programmers write libraries using these intrinsics, which then the rest of the normal programmers use. In other words, if your criticism is that C is not itself low level enough, it still provides the best access to low level capabilities.

Given that C can access new functionality in CPUs, CPU designers add new paradigms, from SIMD to transaction processing. In other words, while in the 1980s CPUs were designed to optimize C (stacks, scaled pointers), these days CPUs are designed to optimize tasks regardless of language.

The author of that article criticizes the memory/cache hierarchy, claiming it has problems. Yes, it has problems, but only compared to how well it normally works. The author praises the many simple cores/threads idea as hiding memory latency with little caching, but misses the point that caches also dramatically increase memory bandwidth. Intel processors are optimized to read a whopping 256 bits every clock cycle from L1 cache. Main memory bandwidth is orders of magnitude slower.

The author goes onto criticize cache coherency as a problem. C uses it, but other languages like Erlang don’t need it. But that’s largely due to the problems each languages solves. Erlang solves the problem where a large number of threads work on largely independent tasks, needing to send only small messages to each other across threads. The problems C solves is when you need many threads working on a huge, common set of data.

For example, consider the “intrusion prevention system”. Any thread can process any incoming packet that corresponds to any region of memory. There’s no practical way of solving this problem without a huge coherent cache. It doesn’t matter which language or abstractions you use, it’s the fundamental constraint of the problem being solved. RDMA is an important concept that’s moved from supercomputer applications to the data center, such as with memcached. Again, we have the problem of huge quantities (terabytes worth) shared among threads rather than small quantities (kilobytes).

The fundamental issue the author of the the paper is ignoring is decreasing marginal returns. Moore’s Law has gifted us more transistors than we can usefully use. We can’t apply those additional registers to just one thing, because the useful returns we get diminish.

For example, Intel CPUs have two hardware threads per core. That’s because there are good returns by adding a single additional thread. However, the usefulness of adding a third or fourth thread decreases. That’s why many CPUs have only two threads, or sometimes four threads, but no CPU has 16 threads per core.

You can apply the same discussion to any aspect of the CPU, from register count, to SIMD width, to cache size, to out-of-order depth, and so on. Rather than focusing on one of these things and increasing it to the extreme, CPU designers make each a bit larger every process tick that adds more transistors to the chip.

The same applies to cores. It’s why the “more simpler cores” strategy fails, because more cores have their own decreasing marginal returns. Instead of adding cores tied to limited memory bandwidth, it’s better to add more cache. Such cache already increases the size of the cores, so at some point it’s more effective to add a few out-of-order features to each core rather than more cores. And so on.

The question isn’t whether we can change this paradigm and radically redesign CPUs to match some academic’s view of the perfect abstraction. Instead, the goal is to find new uses for those additional transistors. For example, “message passing” is a useful abstraction in languages like Go and Erlang that’s often more useful than sharing memory. It’s implemented with shared memory and atomic instructions, but I can’t help but think it couldn’t better be done with direct hardware support.

Of course, as soon as they do that, it’ll become an intrinsic in C, then added to languages like Go and Erlang.

Summary

Academics live in an ideal world of abstractions, the rest of us live in practical reality. The reality is that vast majority of programmers work with the C family of languages (JavaScript, Go, etc.), whereas academics love the epiphanies they learned using other languages, especially function languages. CPUs are only superficially designed to run C and “PDP-11 compatibility”. Instead, they keep adding features to support other abstractions, abstractions available to C. They are driven by decreasing marginal returns — they would love to add new abstractions to the hardware because it’s a cheap way to make use of additional transitions. Academics are wrong believing that the entire system needs to be redesigned from scratch. Instead, they just need to come up with new abstractions CPU designers can add.

[$] Case-insensitive filesystem lookups

2018-05-23 jake

Post Syndicated from jake original https://lwn.net/Articles/754508/rss

Case-insensitive file name lookups are a feature that is fairly frequently
raised at the Linux
Storage, Filesystem, and Memory-Management Summit (LSFMM). At the 2018
summit, Gabriel Bertazi proposed a new way to support
the feature, though it met with a rather skeptical reception—with one
notable exception. Ted Ts’o seemed favorably disposed to the idea, in part
because
it would potentially be a way to get rid of some longstanding Android ugliness:
wrapfs.

BPI Wants Piracy Dealt With Under New UK Internet ‘Clean-Up’ Laws

2018-05-23 Andy

Post Syndicated from Andy original https://torrentfreak.com/bpi-wants-music-piracy-dealt-with-under-uk-internet-clean-up-laws-180523/

For the past several years, the UK Government has expressed a strong desire to “clean up” the Internet.

Strong emphasis has been placed on making the Internet safer for children but that’s just the tip of a much larger iceberg.

This week, the Government published its response to the Internet Safety Strategy green paper, stating unequivocally that more needs to be done to tackle “online harm”.

Noting that six out of ten people report seeing inappropriate or harmful content online, the Government said that work already underway with social media companies to protect users had borne fruit but overall industry response has been less satisfactory.

As a result, the Government will now carry through with its threat to introduce new legislation, albeit with the assistance of technology companies, children’s charities and other stakeholders.

“Digital technology is overwhelmingly a force for good across the world and we must always champion innovation and change for the better,” said Matt Hancock, Secretary of State for Digital, Culture, Media and Sport.

“At the same time I have been clear that we have to address the Wild West elements of the Internet through legislation, in a way that supports innovation. We strongly support technology companies to start up and grow, and we want to work with them to keep our citizens safe.”

While emphasis is being placed on hot-button topics such as cyberbullying and online child exploitation, the Government is clear that it wishes to tackle “the full range” of online harms. That has been greeted by UK music group BPI with a request that the Government introduces new measures to tackle Internet piracy.

In a statement issued this week, BPI chief executive Geoff Taylor welcomed the move towards legislative change and urged the Government to encompass the music industry and beyond.

“This is a vital opportunity to protect consumers and boost the UK’s music and creative industries. The BPI has long pressed for internet intermediaries and online platforms to take responsibility for the content that they promote to users,” Taylor said.

“Government should now take the power in legislation to require online giants to take effective, proactive measures to clean illegal content from their sites and services. This will keep fans away from dodgy sites full of harmful content and prevent criminals from undermining creative businesses that create UK jobs.”

The BPI has published four initial requests, each of which provides food for thought.

The demand to “establish a new fast-track process for blocking illegal sites” is not entirely unexpected, particularly given the expense of launching applications for blocking injunctions at the High Court.

“The BPI has taken a large number of actions against individual websites – 63 injunctions are in place against sites that are wholly or mainly infringing and whose business is simply to profit from criminal activity,” the BPI says.

Those injunctions can be expanded fairly easily to include new sites operating under similar banners or facilitating access to those already covered, but it’s clear the BPI would like something more streamlined. Voluntary schemes, such as the one in place in Portugal, could be an option but it’s unclear how troublesome that could be for ISPs. New legislation could solve that dilemma, however.

Another big thorn in the side for groups like the BPI are people and entities that post infringing content. The BPI is very good at taking these listings down from sites and search engines in particular (more than 600 million requests to date) but it’s a game of whac-a-mole the group would rather not engage in.

With that in mind, the BPI would like the Government to impose new rules that would compel online platforms to stop content from being re-posted after it’s been taken down while removing the accounts of repeat infringers.

Thirdly, the BPI would like the Government to introduce penalties for “online operators” who do not provide “transparent contact and ownership information.” The music group isn’t any more specific than that, but the suggestion is that operators of some sites have a tendency to hide in the shadows, something which frustrates enforcement activity.

Finally, and perhaps most interestingly, the BPI is calling on the Government to legislate for a new “duty of care” for online intermediaries and platforms. Specifically, the BPI wants “effective action” taken against businesses that use the Internet to “encourage” consumers to access content illegally.

While this could easily encompass pirate sites and services themselves, this proposal has the breadth to include a wide range of offenders, from people posting piracy-focused tutorials on monetized YouTube channels to those selling fully-loaded Kodi devices on eBay or social media.

Overall, the BPI clearly wants to place pressure on intermediaries to take action against piracy when they’re in a position to do so, and particularly those who may not have shown much enthusiasm towards industry collaboration in the past.

“Legislation in this Bill, to take powers to intervene with respect to operators that do not co-operate, would bring focus to the roundtable process and ensure that intermediaries take their responsibilities seriously,” the BPI says.

The Department for Digital, Culture, Media & Sport and the Home Office will now work on a White Paper, to be published later this year, to set out legislation to tackle “online harms”. The BPI and similar entities will hope that the Government takes their concerns on board.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN reviews, discounts, offers and coupons.

Acunetix v12 – More Comprehensive More Accurate & 2x Faster

2018-05-23 Darknet

Post Syndicated from Darknet original https://www.darknet.org.uk/2018/05/acunetix-v12-more-comprehensive-more-accurate-2x-faster/?utm_source=rss&utm_medium=social&utm_campaign=darknetfeed

Acunetix, the pioneer in automated web application security software, has announced the release of Acunetix v12. This new version provides support for JavaScript ES7 to better analyse sites which rely heavily on JavaScript such as SPAs. This coupled with a new AcuSensor for Java web applications, sets Acunetix ahead of the curve in its ability to comprehensively and accurately scan all types of websites.

With v12 also comes a brand new scanning engine, re-engineered and re-written from the ground up, making Acunetix the fastest scanning engine in the industry.

Read the rest of Acunetix v12 – More Comprehensive More Accurate & 2x Faster now! Only available at Darknet.

[$] SMB/CIFS compounding support

2018-05-22 jake

Post Syndicated from jake original https://lwn.net/Articles/754507/rss

In a filesystem-track session at the 2018 Linux Storage, Filesystem, and
Memory-Management Summit (LSFMM), Ronnie Sahlberg talked about some changes
he has made to add support for compounding to the SMB/CIFS
implementation in Linux. Compounding is a way to combine multiple
operations into a single request that can help reduce network round-trips.

Working with the Scout Association on digital skills for life

2018-05-22 Philip Colligan

Post Syndicated from Philip Colligan original https://www.raspberrypi.org/blog/working-with-scout-association-digital-skills-for-life/

Today we’re launching a new partnership between the Scouts and the Raspberry Pi Foundation that will help tens of thousands of young people learn crucial digital skills for life. In this blog post, I want to explain what we’ve got planned, why it matters, and how you can get involved.

This is personal

First, let me tell you why this partnership matters to me. As a child growing up in North Wales in the 1980s, Scouting changed my life. My time with 2nd Rhyl provided me with countless opportunities to grow and develop new skills. It taught me about teamwork and community in ways that continue to shape my decisions today.

As my own kids (now seven and ten) have joined Scouting, I’ve seen the same opportunities opening up for them, and like so many parents, I’ve come back to the movement as a volunteer to support their local section. So this is deeply personal for me, and the same is true for many of my colleagues at the Raspberry Pi Foundation who in different ways have been part of the Scouting movement.

That shouldn’t come as a surprise. Scouting and Raspberry Pi share many of the same values. We are both community-led movements that aim to help young people develop the skills they need for life. We are both powered by an amazing army of volunteers who give their time to support that mission. We both care about inclusiveness, and pride ourselves on combining fun with learning by doing.

Raspberry Pi

Raspberry Pi started life in 2008 as a response to the problem that too many young people were growing up without the skills to create with technology. Our goal is that everyone should be able to harness the power of computing and digital technologies, for work, to solve problems that matter to them, and to express themselves creatively.

In 2012 we launched our first product, the world’s first $35 computer. Just six years on, we have sold over 20 million Raspberry Pi computers and helped kickstart a global movement for digital skills.

The Raspberry Pi Foundation now runs the world’s largest network of volunteer-led computing clubs (Code Clubs and CoderDojos), and creates free educational resources that are used by millions of young people all over the world to learn how to create with digital technologies. And lots of what we are able to achieve is because of partnerships with fantastic organisations that share our goals. For example, through our partnership with the European Space Agency, thousands of young people have written code that has run on two Raspberry Pi computers that Tim Peake took to the International Space Station as part of his Mission Principia.

Digital makers

Today we’re launching the new Digital Maker Staged Activity Badge to help tens of thousands of young people learn how to create with technology through Scouting. Over the past few months, we’ve been working with the Scouts all over the UK to develop and test the new badge requirements, along with guidance, project ideas, and resources that really make them work for Scouting. We know that we need to get two things right: relevance and accessibility.

Relevance is all about making sure that the activities and resources we provide are a really good fit for Scouting and Scouting’s mission to equip young people with skills for life. From the digital compass to nature cameras and the reinvented wide game, we’ve had a lot of fun thinking about ways we can bring to life the crucial role that digital technologies can play in the outdoors and adventure.

Compass Coding with Raspberry Pi

We are beyond excited to be launching a new partnership with the Raspberry Pi Foundation, which will help tens of thousands of young people learn digital skills for life.

We also know that there are great opportunities for Scouts to use digital technologies to solve social problems in their communities, reflecting the movement’s commitment to social action. Today we’re launching the first set of project ideas and resources, with many more to follow over the coming weeks and months.

Accessibility is about providing every Scout leader with the confidence, support, and kit to enable them to offer the Digital Maker Staged Activity Badge to their young people. A lot of work and care has gone into designing activities that require very little equipment: for example, activities at Stages 1 and 2 can be completed with a laptop without access to the internet. For the activities that do require kit, we will be working with Scout Stores and districts to make low-cost kit available to buy or loan.

We’re producing accessible instructions, worksheets, and videos to help leaders run sessions with confidence, and we’ll also be planning training for leaders. We will work with our network of Code Clubs and CoderDojos to connect them with local sections to organise joint activities, bringing both kit and expertise along with them.

Get involved

Today’s launch is just the start. We’ll be developing our partnership over the next few years, and we can’t wait for you to join us in getting more young people making things with technology.

Take a look at the brand-new Raspberry Pi resources designed especially for Scouts, to get young people making and creating right away.

The post Working with the Scout Association on digital skills for life appeared first on Raspberry Pi.

Despite US Criticism, Ukraine Cybercrime Chief Receives Few Piracy Complaints

2018-05-22 Andy

Post Syndicated from Andy original https://torrentfreak.com/despite-us-criticism-ukraine-cybercrime-chief-receives-few-piracy-complaints-180522/

On a large number of occasions over the past decade, Ukraine has played host to some of the world’s largest pirate sites.

At various points over the years, The Pirate Bay, KickassTorrents, ExtraTorrent, Demonoid and raft of streaming portals could be found housed in the country’s data centers, reportedly taking advantage of laws more favorable than those in the US and EU.

As a result, Ukraine has been regularly criticized for not doing enough to combat piracy but when placed under pressure, it does take action. In 2010, for example, the local government expressed concerns about the hosting of KickassTorrents in the country and in August the same year, the site was kicked out by its host.

“Kickasstorrents.com main web server was shut down by the hosting provider after it was contacted by local authorities. One way or another I’m afraid we must say goodbye to Ukraine and move the servers to other countries,” the site’s founder told TF at the time.

In the years since, Ukraine has launched sporadic action against pirate sites and has taken steps to tighten up copyright law. The Law on State Support of Cinematography came into force during April 2017 and gave copyright owners new tools to combat infringement by forcing (in theory, at least) site operators and web hosts to respond to takedown requests.

But according to the United States and Europe, not enough is being done. After the EU Commission warned that Ukraine risked damaging relations with the EU, last September US companies followed up with another scathing attack.

In a recommendation to the U.S. Government, the IIPA, which counts the MPAA, RIAA, and ESA among its members, asked U.S. authorities to suspend or withdraw Ukraine’s trade benefits until the online piracy situation improves.

“Legislation is needed to institute proper notice and takedown provisions, including a requirement that service providers terminate access to individuals (or entities) that have repeatedly engaged in infringement, and the retention of information for law enforcement, as well as to provide clear third party liability regarding ISPs,” the IIPA wrote.

But amid all the criticism, Ukraine cyber police chief Sergey Demedyuk says that while his department is committed to tackling piracy, it can only do so when complaints are filed with him.

“Yes, we are engaged in piracy very closely. The problem is that piracy is a crime of private accusation. So here we deal with them only in cases where we are contacted,” Demedyuk said in an Interfax interview published yesterday.

Surprisingly, given the number of dissenting voices, it appears that complaints about these matters aren’t exactly prevalent. So are there many at all?

“Unfortunately, no. In the media, many companies claim that their rights are being violated by pirates. But if you count the applications that come to us, they are one,” Demedyuk reveals.

“In general, we are handling Ukrainian media companies, who produce their own product and are worried about its fate. Also on foreign films, the ‘Anti-Piracy Agency’ refers to us, but not as intensively as before.”

Why complaints are going down, Demedyuk does not know, but when his unit is asked to take action it does so, he claims. Indeed, Demedyuk cites two particularly significant historical operations against a pair of large ‘pirate’ sites.

In 2012, Ukraine shut down EX.ua, a massive cyberlocker site following a six-month investigation initiated by international tech companies including Microsoft, Graphisoft and Adobe. Around 200 servers were seized, together hosting around 6,000 terabytes of data.

Then in November 2016, following a complaint from the MPAA, police raided FS.to, one of Ukraine’s most popular pirate sites. Initial reports indicated that 60 servers were seized and 19 people were arrested.

“To see the effect of combating piracy, this should not be done at the level of cyberpolicy, but at the state level,” Demedyuk advises.

“This requires constant close interaction between law enforcement agencies and rights holders. Only by using all these tools will we be able to effectively counteract copyright infringements.”

Meanwhile, the Office of the United States Trade Representative has maintained Ukraine’s position on the Priority Watchlist of its latest Special 301 Report and there a no signs it will be leaving anytime soon.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN reviews, discounts, offers and coupons.

[$] Network filesystem topics

2018-05-21 jake

Post Syndicated from jake original https://lwn.net/Articles/754506/rss

At the 2018 Linux Storage, Filesystem, and
Memory-Management Summit (LSFMM), Steve French led a discussion of various
problem areas for network filesystems. Unlike previous sessions (in 2016 and 2017), there was some good news to report
because the long-awaited statx()
system call was released in Linux 4.11. But there
is still plenty of work to be done to better support network filesystems in
Linux.

Williams: Introducing Git protocol version 2

2018-05-18 corbet

Post Syndicated from corbet original https://lwn.net/Articles/754872/rss

Brandon Williams writes
about the new Git remote protocol that will debut in the 2.18 release.
“We recently rolled out support for protocol version 2 at Google and
have seen a performance improvement of 3x for no-op fetches of a single
branch on repositories containing 500k references. Protocol v2 has also
enabled a reduction of 8x of the overhead bytes (non-packfile) sent from
googlesource.com servers. A majority of this improvement is due to
filtering references advertised by the server to the refs the client has
expressed interest in.”

TVAddons Denies Copyright Infringement Claims in Court

2018-05-18 Ernesto

Post Syndicated from Ernesto original https://torrentfreak.com/tvaddons-denies-copyright-infringement-claims-in-court-180518/

Last year, American satellite and broadcast provider Dish Network targeted two well-known players in the third-party Kodi add-on ecosystem.

In a complaint filed in a federal court in Texas, add-on ZemTV and the TVAddons library were accused of copyright infringement. As a result, both are facing up to $150,000 in damages for each offense.

The owner and operator of TVAddons, Adam Lackman, and ZemTV developer, Shahjahan Durrani, previously asked the court to dismiss the case, because neither reside in the United States.

The request was recently denied and the case continues. This means that the defendants must respond to the allegations at the Texas District Court. Yesterday, TVAddons’ lawyer Jason Sweet submitted the answers of defendant Adam Lackman, who denies many of the claims put forward by Dish.

TVAddons’ operator denies that he had the “ability to supervise and control” the alleged infringing activity of ZemTV, as Dish stated, and also refutes the claims that he received a “direct financial benefit” and “refused to take any action” to stop the infringement.

Lackman does confirm that ZemTV was available for download through TVAddons and that Dish sent a takedown notice to have it removed. TVAddons received this notice and forwarded it to the developer of the addon.

The answers are very minimal and mostly deny the complaint’s claims. However, the filing also includes several affirmative defenses, which provide some more insight and detail.

In the complaint, TVAddons’ operator stands accused of “contributory / inducing copyright infringement,” but his lawyer points out that these are two different claims with separate thresholds which can’t be combined.

One requires knowledge of and a material contribution to the infringement, for example, while the other deals with the distribution of a device or product through which the infringing use is promoted.

“Contributory infringement and inducing infringement are two distinct causes of action and cannot be combined when pled. Federal Rule of Civil Procedure 10(b) requires separate counts for separate claims,” Sweet writes.

And there are other points of confusion highlighted by the defense. Dish has stated that the copyrighted works at issue have not been registered, as that is no longer required to file a lawsuit under the Copyright Act.

While that is correct, TVAddons’ lawyer points out that it prevents Dish from seeking statutory damages and attorneys fees or costs, because that does require copyright registration.

“Plaintiff is not entitled to statutory damages, including attorney’s fees and costs because registration is required for foreign works to gain the procedural benefits of a prima facie presumption of the validity of a copyright, statutory damages, and attorney’s fees..,” the defense writes.

Adding to that, TVAddons’ operator denies that he engaged in or contributed to any of the alleged infringements. And if there was any wrongdoing, this was certainly not intended.

“Defendant was not aware and had no reason to believe that any of his acts constituted an infringement of copyright. Any infringement by Defendant was innocent and not willful.”

The response is just the start of the case and both sides are expected to conduct further discovery to back up their respective positions. ZemTV’s operator, whose alleged infringements are central to the TVAddons case, has yet to file his answers.

TVAddons, meanwhile, remains operational through TVAddons.co with a reduced library of addons. After it was decimated last year, the site has started to regain its user base, in the hope that they will support the legal battle.

“If you are tired of seeing big companies act like they own the law, please consider making a donation to help us pay our lawyers. This lawsuit is about more than just us, it’s about the expansion of copyright law and a big bad corporation trying to bully us into submission,” TVAddons wrote last week.

—

A copy of TVAddons answer to the amended complaint is available here (pdf).

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN reviews, discounts, offers and coupons.

Vim 8.1 released

2018-05-18 corbet

Post Syndicated from corbet original https://lwn.net/Articles/754866/rss

Version 8.1 of the Vim
editor is available. “The main new feature of Vim 8.1 is support
for running a terminal in a Vim window. This builds on top of the
asynchronous features added in Vim 8.0.”

ExtraTorrent Replacement Displays Warning On Predecessor’s Shutdown Anniversary

2018-05-18 Andy

Post Syndicated from Andy original https://torrentfreak.com/extratorrent-replacement-displays-warning-on-predecessors-shutdown-anniversary-180518/

Exactly one year ago, millions of users in the BitTorrent community went into mourning with the shock depature of one of its major players.

ExtraTorrent was founded in back in November 2006, at a time when classic platforms such as TorrentSpy and Mininova were dominating the torrent site landscape. But with dedication and determination, the site amassed millions of daily visitors, outperforming every other torrent site apart from the mighty Pirate Bay.

Then, on May 17, 2017, everything came crashing down.

“ExtraTorrent has shut down permanently,” a note in the site read. “ExtraTorrent with all mirrors goes offline. We permanently erase all data. Stay away from fake ExtraTorrent websites and clones. Thx to all ET supporters and torrent community. ET was a place to be….”

While ExtraTorrent staff couldn’t be more clear in advising people to stay away from clones, few people listened to their warnings. Within hours, new sites appeared claiming to be official replacements for the much-loved torrent site and people flocked to them in their millions.

One of those was ExtraTorrent.ag, a torrent site connected to the operators of EZTV.ag, which appeared as a replacement in the wake of the official EZTV’s demise. Graphically very similar to the original ExtraTorrent, the .ag ‘replacement’ had none of its namesake’s community or unique content. But that didn’t dent its popularity.

ExtraTorrent.ag

At the start of this week, ExtraTorrent.ag was one of the most popular torrent sites on the Internet. With an Alexa rank of around 2,200, it would’ve clinched ninth position in our Top 10 Torrent Sites report earlier this year. However, after registering the site’s domain a year ago, something seems to have gone wrong.

Yesterday, on the anniversary of ExtraTorrent’s shutdown and exactly a year after the ExtraTorrent.ag domain was registered, ExtraTorrent.ag disappeared only to be replaced by a generic landing page, as shown below.

ExtraTorrent.ag landing page

This morning, however, there appear to be additional complications. Accessing with Firefox produces the page above but attempting to do so with Chrome produces an ominous security warning.

Chrome warning

Indeed, those protected by MalwareBytes won’t be able to access the page at all, since ExtraTorrent.ag redirects to the domain FindBetterResults.com, which the anti-malware app flags as malicious.

The change was reported to TF by the operator of domain unblocking site Unblocked.lol, which offers torrent site proxies as well as access to live TV and sports.

“I noticed when I started receiving emails saying ExtraTorrent was redirecting to some parked domain. When I jumped on the PC and checked myself it was just redirecting to a blank page,” he informs us.

“First I thought they’d blocked our IP address so I used some different ones. But I soon discovered the domain was in fact parked.”

So what has happened to this previously-functioning domain?

Whois records show that ExtraTorrent.ag was created on May 17, 2017 and appears to have been registered for a year. Yesterday, on May 17, 2018, the domain was updated to list what could potentially be a new owner, with an expiry date of May 17, 2019.

Once domains have expired, they usually enter an ‘Auto-Renew Grace Period’ for up to 45 days. This is followed by a 30-day ‘Redemption Grace Period’. At the end of this second period, domains cannot be renewed and are released for third-parties to register. That doesn’t appear to have been the case here.

So, to find out more about the sudden changes we reached out to the email address listed in the WHOIS report but received no response. Should we hear more we’ll update this report but in the meantime the Internet has lost one of its largest torrent sites and gained a rather pointless landing page with potential security risks.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN reviews, discounts, offers and coupons.

‘Blocking Pirate Sites Through Court is Uncertain, Slow and Expensive’

2018-05-17 Ernesto

Post Syndicated from Ernesto original https://torrentfreak.com/blocking-pirate-sites-through-court-is-uncertain-slow-and-expensive-180517/

FairPlay Canada, a coalition of copyright holders and major players in the telco industry, wants to institute a national pirate site blocking scheme.

The group submitted its plan to the Canadian telecoms regulator CRTC earlier this year, which subsequently asked the public for input.

This consultation triggered a wave of responses. Those opposed to the blocklist idea highlight the risk of over-blocking, net neutrality threats, and the lack of judicial oversight, among other things.

Yesterday, the Fairplay Coalition responded to these comments in a new filing. Providing additional evidence, the group countered the opposition head-on, accusing some commenters of spreading false and inaccurate information.

The coalition also responded to the common argument that there is no need for a separate blocking scheme. Copyright holders can already request injunctive relief from the courts, demanding that ISPs block pirate sites, as is common in many other countries.

In its reply, Fairplay counters that this may not be as straightforward as some claim. Section 36 of the Telecommunications Act suggests that, in addition to a court order, Commission approval is needed to block a site. This is complex and makes it uncertain if courts will be willing to grant these blockades.

“It is possible a court would be dissuaded from making an order against ISPs to disable to access to a piracy site given section 36 and the Commission’s view of its impact,” Fairplay’s response reads.

In other words, the coalition suggests that with proper judicial oversight under current law, there may not be any blockades. It’s not clear how that helps their argument, as that might be the exact point of the critics, but there is more.

In addition to the uncertainty of getting a blocking order through the courts, Fairplay argues that this route will also be very expensive. To make this point, the coalition hired the law firm Hayes eLaw to calculate the potential costs and time required to complete the process.

According to this analysis, it may take more than two years before a blocking order is final, with hundreds of thousands of dollars in legal expenses for just one site. This is too slow and too expensive, the coalition concludes.

“[T]he process involves first completing litigation against each egregious piracy site, and could take up to 765 days and cost up to $338,000 to address a single site,” Fairplay writes.

“While copyright enforcement actions are a crucial and powerful tool in many cases, it is not reasonable to suggest that rightsholders should spend this much time and resources to address every case in which their content is being stolen.”

Finally, Fairplay notes that those commenters who suggest the judicial route are apparently not against site blocking, but only against how these blockades are administered.

Arguments against the court option

As is often the case with consultations, both sides of the argument will present issues in a light that suits them best.

However, Fairplay goes even further and suggests that many consultation responses are based on misleading information, which is the result of online activists.

Among other things, these responses suggest that the plan would allow ISPs to unilaterally decide to block websites. However, Fairplay counters that ISPs can only block sites if they’re ordered to do so by the Commission, not on their own accord.

“The fact that the Commission received such interventions is not surprising, as every indication is that they were driven by online campaigns that made exactly this false claim,” they write.

“Indeed, the petitions or form letters submitted by CIPPIC/OpenMedia, SumOfUs, and LeadNow all explicitly contain this particular point of misinformation.”

In addition to the misinformation, Fairplay also notes that some interventions are false, while thousands of petitions are mere duplicates.

“There are a number of obviously false interventions and the identity, veracity, and location of the others can generally not be confirmed. In the case of the petitions, there are more than 14,000 identified duplicate entries, and an unknowable number of other false entries.”

Fairplay doesn’t ask the CRTC to ignore these submissions. It just points out that they cannot be relied upon, as they are not representative or based on faulty assumptions about the actual proposal.

Instead, the coalition comes up with a survey of its own. Fairplay hired Nanos Research to ask random Canadians whether their country should have less, the same, or more protection than countries that currently block piracy sites, such as the United Kingdom, Australia, and France.

According to the results, 77% of Canadians believed Canada should have the same or more protection than those countries, suggesting that Canadians are not anti-site-blocking at all. That said, the above mentioned foreign blockades are court sanctioned.

The entire response from Fairplay Canada is available here (pdf). It totals more than 60 pages and further addresses the economic impact of piracy, the effectiveness of the plan, how blocking is consistent with net neutrality and freedom of speech, as well as a wide range of other topics.

While the extra context will be useful to the CRTC, it’s unlikely to sway the opposition.

Around the same time as the coalition submitted its response, a new controversy emerged. Documents published by the Forum for Research and Policy in Communications suggest that Bell discussed the site blocking plan privately with the CRTC before it was made public. While it’s apparent that site blocking was on the agenda, Bell told Mobile Syrup that there’s “nothing procedurally unusual” in this case.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN reviews, discounts, offers and coupons.

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Tag Archives: support

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