Tag Archives: SAM

Managing AWS Lambda Function Concurrency

Post Syndicated from Chris Munns original https://aws.amazon.com/blogs/compute/managing-aws-lambda-function-concurrency/

One of the key benefits of serverless applications is the ease in which they can scale to meet traffic demands or requests, with little to no need for capacity planning. In AWS Lambda, which is the core of the serverless platform at AWS, the unit of scale is a concurrent execution. This refers to the number of executions of your function code that are happening at any given time.

Thinking about concurrent executions as a unit of scale is a fairly unique concept. In this post, I dive deeper into this and talk about how you can make use of per function concurrency limits in Lambda.

Understanding concurrency in Lambda

Instead of diving right into the guts of how Lambda works, here’s an appetizing analogy: a magical pizza.
Yes, a magical pizza!

This magical pizza has some unique properties:

  • It has a fixed maximum number of slices, such as 8.
  • Slices automatically re-appear after they are consumed.
  • When you take a slice from the pizza, it does not re-appear until it has been completely consumed.
  • One person can take multiple slices at a time.
  • You can easily ask to have the number of slices increased, but they remain fixed at any point in time otherwise.

Now that the magical pizza’s properties are defined, here’s a hypothetical situation of some friends sharing this pizza.

Shawn, Kate, Daniela, Chuck, Ian and Avleen get together every Friday to share a pizza and catch up on their week. As there is just six of them, they can easily all enjoy a slice of pizza at a time. As they finish each slice, it re-appears in the pizza pan and they can take another slice again. Given the magical properties of their pizza, they can continue to eat all they want, but with two very important constraints:

  • If any of them take too many slices at once, the others may not get as much as they want.
  • If they take too many slices, they might also eat too much and get sick.

One particular week, some of the friends are hungrier than the rest, taking two slices at a time instead of just one. If more than two of them try to take two pieces at a time, this can cause contention for pizza slices. Some of them would wait hungry for the slices to re-appear. They could ask for a pizza with more slices, but then run the same risk again later if more hungry friends join than planned for.

What can they do?

If the friends agreed to accept a limit for the maximum number of slices they each eat concurrently, both of these issues are avoided. Some could have a maximum of 2 of the 8 slices, or other concurrency limits that were more or less. Just so long as they kept it at or under eight total slices to be eaten at one time. This would keep any from going hungry or eating too much. The six friends can happily enjoy their magical pizza without worry!

Concurrency in Lambda

Concurrency in Lambda actually works similarly to the magical pizza model. Each AWS Account has an overall AccountLimit value that is fixed at any point in time, but can be easily increased as needed, just like the count of slices in the pizza. As of May 2017, the default limit is 1000 “slices” of concurrency per AWS Region.

Also like the magical pizza, each concurrency “slice” can only be consumed individually one at a time. After consumption, it becomes available to be consumed again. Services invoking Lambda functions can consume multiple slices of concurrency at the same time, just like the group of friends can take multiple slices of the pizza.

Let’s take our example of the six friends and bring it back to AWS services that commonly invoke Lambda:

  • Amazon S3
  • Amazon Kinesis
  • Amazon DynamoDB
  • Amazon Cognito

In a single account with the default concurrency limit of 1000 concurrent executions, any of these four services could invoke enough functions to consume the entire limit or some part of it. Just like with the pizza example, there is the possibility for two issues to pop up:

  • One or more of these services could invoke enough functions to consume a majority of the available concurrency capacity. This could cause others to be starved for it, causing failed invocations.
  • A service could consume too much concurrent capacity and cause a downstream service or database to be overwhelmed, which could cause failed executions.

For Lambda functions that are launched in a VPC, you have the potential to consume the available IP addresses in a subnet or the maximum number of elastic network interfaces to which your account has access. For more information, see Configuring a Lambda Function to Access Resources in an Amazon VPC. For information about elastic network interface limits, see Network Interfaces section in the Amazon VPC Limits topic.

One way to solve both of these problems is applying a concurrency limit to the Lambda functions in an account.

Configuring per function concurrency limits

You can now set a concurrency limit on individual Lambda functions in an account. The concurrency limit that you set reserves a portion of your account level concurrency for a given function. All of your functions’ concurrent executions count against this account-level limit by default.

If you set a concurrency limit for a specific function, then that function’s concurrency limit allocation is deducted from the shared pool and assigned to that specific function. AWS also reserves 100 units of concurrency for all functions that don’t have a specified concurrency limit set. This helps to make sure that future functions have capacity to be consumed.

Going back to the example of the consuming services, you could set throttles for the functions as follows:

Amazon S3 function = 350
Amazon Kinesis function = 200
Amazon DynamoDB function = 200
Amazon Cognito function = 150
Total = 900

With the 100 reserved for all non-concurrency reserved functions, this totals the account limit of 1000.

Here’s how this works. To start, create a basic Lambda function that is invoked via Amazon API Gateway. This Lambda function returns a single “Hello World” statement with an added sleep time between 2 and 5 seconds. The sleep time simulates an API providing some sort of capability that can take a varied amount of time. The goal here is to show how an API that is underloaded can reach its concurrency limit, and what happens when it does.
To create the example function

  1. Open the Lambda console.
  2. Choose Create Function.
  3. For Author from scratch, enter the following values:
    1. For Name, enter a value (such as concurrencyBlog01).
    2. For Runtime, choose Python 3.6.
    3. For Role, choose Create new role from template and enter a name aligned with this function, such as concurrencyBlogRole.
  4. Choose Create function.
  5. The function is created with some basic example code. Replace that code with the following:

import time
from random import randint
seconds = randint(2, 5)

def lambda_handler(event, context):
time.sleep(seconds)
return {"statusCode": 200,
"body": ("Hello world, slept " + str(seconds) + " seconds"),
"headers":
{
"Access-Control-Allow-Headers": "Content-Type,X-Amz-Date,Authorization,X-Api-Key,X-Amz-Security-Token",
"Access-Control-Allow-Methods": "GET,OPTIONS",
}}

  1. Under Basic settings, set Timeout to 10 seconds. While this function should only ever take up to 5-6 seconds (with the 5-second max sleep), this gives you a little bit of room if it takes longer.

  1. Choose Save at the top right.

At this point, your function is configured for this example. Test it and confirm this in the console:

  1. Choose Test.
  2. Enter a name (it doesn’t matter for this example).
  3. Choose Create.
  4. In the console, choose Test again.
  5. You should see output similar to the following:

Now configure API Gateway so that you have an HTTPS endpoint to test against.

  1. In the Lambda console, choose Configuration.
  2. Under Triggers, choose API Gateway.
  3. Open the API Gateway icon now shown as attached to your Lambda function:

  1. Under Configure triggers, leave the default values for API Name and Deployment stage. For Security, choose Open.
  2. Choose Add, Save.

API Gateway is now configured to invoke Lambda at the Invoke URL shown under its configuration. You can take this URL and test it in any browser or command line, using tools such as “curl”:


$ curl https://ofixul557l.execute-api.us-east-1.amazonaws.com/prod/concurrencyBlog01
Hello world, slept 2 seconds

Throwing load at the function

Now start throwing some load against your API Gateway + Lambda function combo. Right now, your function is only limited by the total amount of concurrency available in an account. For this example account, you might have 850 unreserved concurrency out of a full account limit of 1000 due to having configured a few concurrency limits already (also the 100 concurrency saved for all functions without configured limits). You can find all of this information on the main Dashboard page of the Lambda console:

For generating load in this example, use an open source tool called “hey” (https://github.com/rakyll/hey), which works similarly to ApacheBench (ab). You test from an Amazon EC2 instance running the default Amazon Linux AMI from the EC2 console. For more help with configuring an EC2 instance, follow the steps in the Launch Instance Wizard.

After the EC2 instance is running, SSH into the host and run the following:


sudo yum install go
go get -u github.com/rakyll/hey

“hey” is easy to use. For these tests, specify a total number of tests (5,000) and a concurrency of 50 against the API Gateway URL as follows(replace the URL here with your own):


$ ./go/bin/hey -n 5000 -c 50 https://ofixul557l.execute-api.us-east-1.amazonaws.com/prod/concurrencyBlog01

The output from “hey” tells you interesting bits of information:


$ ./go/bin/hey -n 5000 -c 50 https://ofixul557l.execute-api.us-east-1.amazonaws.com/prod/concurrencyBlog01

Summary:
Total: 381.9978 secs
Slowest: 9.4765 secs
Fastest: 0.0438 secs
Average: 3.2153 secs
Requests/sec: 13.0891
Total data: 140024 bytes
Size/request: 28 bytes

Response time histogram:
0.044 [1] |
0.987 [2] |
1.930 [0] |
2.874 [1803] |∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
3.817 [1518] |∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
4.760 [719] |∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
5.703 [917] |∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
6.647 [13] |
7.590 [14] |
8.533 [9] |
9.477 [4] |

Latency distribution:
10% in 2.0224 secs
25% in 2.0267 secs
50% in 3.0251 secs
75% in 4.0269 secs
90% in 5.0279 secs
95% in 5.0414 secs
99% in 5.1871 secs

Details (average, fastest, slowest):
DNS+dialup: 0.0003 secs, 0.0000 secs, 0.0332 secs
DNS-lookup: 0.0000 secs, 0.0000 secs, 0.0046 secs
req write: 0.0000 secs, 0.0000 secs, 0.0005 secs
resp wait: 3.2149 secs, 0.0438 secs, 9.4472 secs
resp read: 0.0000 secs, 0.0000 secs, 0.0004 secs

Status code distribution:
[200] 4997 responses
[502] 3 responses

You can see a helpful histogram and latency distribution. Remember that this Lambda function has a random sleep period in it and so isn’t entirely representational of a real-life workload. Those three 502s warrant digging deeper, but could be due to Lambda cold-start timing and the “second” variable being the maximum of 5, causing the Lambda functions to time out. AWS X-Ray and the Amazon CloudWatch logs generated by both API Gateway and Lambda could help you troubleshoot this.

Configuring a concurrency reservation

Now that you’ve established that you can generate this load against the function, I show you how to limit it and protect a backend resource from being overloaded by all of these requests.

  1. In the console, choose Configure.
  2. Under Concurrency, for Reserve concurrency, enter 25.

  1. Click on Save in the top right corner.

You could also set this with the AWS CLI using the Lambda put-function-concurrency command or see your current concurrency configuration via Lambda get-function. Here’s an example command:


$ aws lambda get-function --function-name concurrencyBlog01 --output json --query Concurrency
{
"ReservedConcurrentExecutions": 25
}

Either way, you’ve set the Concurrency Reservation to 25 for this function. This acts as both a limit and a reservation in terms of making sure that you can execute 25 concurrent functions at all times. Going above this results in the throttling of the Lambda function. Depending on the invoking service, throttling can result in a number of different outcomes, as shown in the documentation on Throttling Behavior. This change has also reduced your unreserved account concurrency for other functions by 25.

Rerun the same load generation as before and see what happens. Previously, you tested at 50 concurrency, which worked just fine. By limiting the Lambda functions to 25 concurrency, you should see rate limiting kick in. Run the same test again:


$ ./go/bin/hey -n 5000 -c 50 https://ofixul557l.execute-api.us-east-1.amazonaws.com/prod/concurrencyBlog01

While this test runs, refresh the Monitoring tab on your function detail page. You see the following warning message:

This is great! It means that your throttle is working as configured and you are now protecting your downstream resources from too much load from your Lambda function.

Here is the output from a new “hey” command:


$ ./go/bin/hey -n 5000 -c 50 https://ofixul557l.execute-api.us-east-1.amazonaws.com/prod/concurrencyBlog01
Summary:
Total: 379.9922 secs
Slowest: 7.1486 secs
Fastest: 0.0102 secs
Average: 1.1897 secs
Requests/sec: 13.1582
Total data: 164608 bytes
Size/request: 32 bytes

Response time histogram:
0.010 [1] |
0.724 [3075] |∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
1.438 [0] |
2.152 [811] |∎∎∎∎∎∎∎∎∎∎∎
2.866 [11] |
3.579 [566] |∎∎∎∎∎∎∎
4.293 [214] |∎∎∎
5.007 [1] |
5.721 [315] |∎∎∎∎
6.435 [4] |
7.149 [2] |

Latency distribution:
10% in 0.0130 secs
25% in 0.0147 secs
50% in 0.0205 secs
75% in 2.0344 secs
90% in 4.0229 secs
95% in 5.0248 secs
99% in 5.0629 secs

Details (average, fastest, slowest):
DNS+dialup: 0.0004 secs, 0.0000 secs, 0.0537 secs
DNS-lookup: 0.0002 secs, 0.0000 secs, 0.0184 secs
req write: 0.0000 secs, 0.0000 secs, 0.0016 secs
resp wait: 1.1892 secs, 0.0101 secs, 7.1038 secs
resp read: 0.0000 secs, 0.0000 secs, 0.0005 secs

Status code distribution:
[502] 3076 responses
[200] 1924 responses

This looks fairly different from the last load test run. A large percentage of these requests failed fast due to the concurrency throttle failing them (those with the 0.724 seconds line). The timing shown here in the histogram represents the entire time it took to get a response between the EC2 instance and API Gateway calling Lambda and being rejected. It’s also important to note that this example was configured with an edge-optimized endpoint in API Gateway. You see under Status code distribution that 3076 of the 5000 requests failed with a 502, showing that the backend service from API Gateway and Lambda failed the request.

Other uses

Managing function concurrency can be useful in a few other ways beyond just limiting the impact on downstream services and providing a reservation of concurrency capacity. Here are two other uses:

  • Emergency kill switch
  • Cost controls

Emergency kill switch

On occasion, due to issues with applications I’ve managed in the past, I’ve had a need to disable a certain function or capability of an application. By setting the concurrency reservation and limit of a Lambda function to zero, you can do just that.

With the reservation set to zero every invocation of a Lambda function results in being throttled. You could then work on the related parts of the infrastructure or application that aren’t working, and then reconfigure the concurrency limit to allow invocations again.

Cost controls

While I mentioned how you might want to use concurrency limits to control the downstream impact to services or databases that your Lambda function might call, another resource that you might be cautious about is money. Setting the concurrency throttle is another way to help control costs during development and testing of your application.

You might want to prevent against a function performing a recursive action too quickly or a development workload generating too high of a concurrency. You might also want to protect development resources connected to this function from generating too much cost, such as APIs that your Lambda function calls.

Conclusion

Concurrent executions as a unit of scale are a fairly unique characteristic about Lambda functions. Placing limits on how many concurrency “slices” that your function can consume can prevent a single function from consuming all of the available concurrency in an account. Limits can also prevent a function from overwhelming a backend resource that isn’t as scalable.

Unlike monolithic applications or even microservices where there are mixed capabilities in a single service, Lambda functions encourage a sort of “nano-service” of small business logic directly related to the integration model connected to the function. I hope you’ve enjoyed this post and configure your concurrency limits today!

16-Year-Old Boy Arrested for Running Pirate TV Service

Post Syndicated from Andy original https://torrentfreak.com/16-year-old-boy-arrested-for-running-pirate-tv-service-171211/

After more than a decade and a half in existence, public pirate sites, services, and apps remain a thorn in the side of entertainment industry groups who are determined to close them down.

That trend continued last week when French anti-piracy group ALPA teamed up with police in the Bordeaux region to raid and arrest the founder and administrator of piracy service ARTV.

According to the anti-piracy group, the ARTV.watch website first appeared during April 2017 but quickly grew to become a significant source of streaming TV piracy. Every month the site had around 150,000 visitors and in less than eight months amassed 800,000 registered users.

“Artv.watch was a public site offering live access to 176 free and paid French TV channels that are members of ALPA: Canal + Group, M6 Group, TF1 Group, France Télévision Group, Paramount, Disney, and FOX. Other thematic and sports channels were broadcast,” an ALPA statement reads.

This significant offering was reportedly lucrative for the site’s operator. While probably best taken with a grain of salt, ALPA estimates the site generated around 3,000 euros per month from advertising revenue. That’s a decent amount for anyone but even more so when one learns that ARTV’s former operator is just 16 years old.

“ARTV.WATCH it’s over. ARTV is now closed for legal reasons. Thank you for your understanding! The site was indeed illegal,” a notice on the site now reads.

“Thank you all for this experience that I have acquired in this project. And thanks to you who have believed in me.”

Closure formalities aside, ARTV’s founder also has a message for anyone else considering launching a similar platform.

“Notice to anyone wanting to do a site of the same kind, I strongly advise against it. On the criminal side, the punishment can go up to three years of imprisonment and a 300,000 euro fine. If [individual] complaints of channels (or productions) are filed against you, it will be more complicated to determine,” ARTV’s owner warns.

ALPA says that in addition to closing down the site, ARTV’s owner also deactivated the site’s Android app, which had been available for download on Google Play. The anti-piracy group adds that this action against IPTV and live streaming was a first in France.

For anyone who speaks French, the 16-year-old has published a video on YouTube talking about his predicament.

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

Roguelike Simulator

Post Syndicated from Eevee original https://eev.ee/release/2017/12/09/roguelike-simulator/

Screenshot of a monochromatic pixel-art game designed to look mostly like ASCII text

On a recent game night, glip and I stumbled upon bitsy — a tiny game maker for “games where you can walk around and talk to people and be somewhere.” It’s enough of a genre to have become a top tag on itch, so we flicked through a couple games.

What we found were tiny windows into numerous little worlds, ill-defined yet crisply rendered in chunky two-colored pixels. Indeed, all you can do is walk around and talk to people and be somewhere, but the somewheres are strangely captivating. My favorite was the last days of our castle, with a day on the town in a close second (though it cheated and extended the engine a bit), but there are several hundred of these tiny windows available. Just single, short, minimal, interactive glimpses of an idea.

I’ve been wanting to do more of that, so I gave it a shot today. The result is Roguelike Simulator, a game that condenses the NetHack experience into about ninety seconds.


Constraints breed creativity, and bitsy is practically made of constraints — the only place you can even make any decisions at all is within dialogue trees. There are only three ways to alter the world: the player can step on an ending tile to end the game, step on an exit tile to instantly teleport to a tile on another map (or not), or pick up an item. That’s it. You can’t even implement keys; the best you can do is make an annoying maze of identical rooms, then have an NPC tell you the solution.

In retrospect, a roguelike — a genre practically defined by its randomness — may have been a poor choice.

I had a lot of fun faking it, though, and it worked well enough to fool at least one person for a few minutes! Some choice hacks follow. Probably play the game a couple times before reading them?

  • Each floor reveals itself, of course, by teleporting you between maps with different chunks of the floor visible. I originally intended for this to be much more elaborate, but it turns out to be a huge pain to juggle multiple copies of the same floor layout.

  • Endings can’t be changed or randomized; even the text is static. I still managed to implement multiple variants on the “ascend” ending! See if you can guess how. (It’s not that hard.)

  • There are no Boolean operators, but there are arithmetic operators, so in one place I check whether you have both of two items by multiplying together how many of each you have.

  • Monsters you “defeat” are actually just items you pick up. They’re both drawn in the same color, and you can’t see your inventory, so you can’t tell the difference.

Probably the best part was writing the text, which is all completely ridiculous. I really enjoy writing a lot of quips — which I guess is why I like Twitter — and I’m happy to see they’ve made people laugh!


I think this has been a success! It’s definitely made me more confident about making smaller things — and about taking the first idea I have and just running with it. I’m going to keep an eye out for other micro game engines to play with, too.

CrimeStoppers Campaign Targets Pirate Set-Top Boxes & Their Users

Post Syndicated from Andy original https://torrentfreak.com/crimestoppers-campaign-targets-pirate-set-top-boxes-their-users-171209/

While many people might believe CrimeStoppers to be an official extension of the police in the UK, the truth is a little more subtle.

CrimeStoppers is a charity that operates a service through which members of the public can report crime anonymously, either using a dedicated phone line or via a website. Callers are not required to give their name, meaning that for those concerned about reprisals or becoming involved in a case for other sensitive reasons, it’s the perfect buffer between them and the authorities.

The people at CrimeStoppers deal with all kinds of crime but perhaps a little surprisingly, they’ve just got involved in the set-top box controversy in the UK.

“Advances in technology have allowed us to enjoy on-screen entertainment in more ways than ever before, with ever increasing amounts of exciting and original content,” the CrimeStoppers campaign begins.

“However, some people are avoiding paying for this content by using modified streaming hardware devices, like a set-top box or stick, in conjunction with software such as illegal apps or add-ons, or illegal mobile apps which allow them to watch new movie releases, TV that hasn’t yet aired, and subscription sports channels for free.”

The campaign has been launched in partnership with the Intellectual Property Office and unnamed “industry partners”. Who these companies are isn’t revealed but given the standard messages being portrayed by the likes of ACE, Premier League and Federation Against Copyright Theft lately, it wouldn’t be a surprise if some or all of them were involved.

Those messages are revealed in a series of four video ads, each taking a different approach towards discouraging the public from using devices loaded with pirate software.

The first video clearly targets the consumer, dispelling the myth that watching pirate video isn’t against the law. It is, that’s not in any doubt, but from the constant tone of the video, one could be forgiven that it’s an extremely serious crime rather than something which is likely to be a civil matter, if anything at all.

It also warns people who are configuring and selling pirate devices that they are breaking the law. Again, this is absolutely true but this activity is clearly several magnitudes more serious than simply viewing. The video blurs the boundaries for what appears to be dramatic effect, however.

Selling and watching is illegal

The second video is all about demonizing the people and groups who may offer set-top boxes to the public.

Instead of portraying the hundreds of “cottage industry” suppliers behind many set-top box sales in the UK, the CrimeStoppers video paints a picture of dark organized crime being the main driver. By buying from these people, the charity warns, criminals are being welcomed in.

“It is illegal. You could also be helping to fund organized crime and bringing it into your community,” the video warns.

Are you funding organized crime?

The third video takes another approach, warning that set-top boxes have few if any parental controls. This could lead to children being exposed to inappropriate content, the charity warns.

“What are your children watching. Does it worry you?” the video asks.

Of course, the same can be said about the Internet, period. Web browsers don’t filter what content children have access to unless parents take pro-active steps to configure special services or software for the purpose.

There’s always the option to supervise children, of course, but Netflix is probably a safer option for those with a preference to stand off. It’s also considerably more expensive, a fact that won’t have escaped users of these devices.

Got kids? Take care….

Finally, video four picks up a theme that’s becoming increasingly common in anti-piracy campaigns – malware and identity theft.

“Why risk having your identity stolen or your bank account or home network hacked. If you access entertainment or sports using dodgy streaming devices or apps, or illegal addons for Kodi, you are increasing the risks,” the ad warns.

Danger….Danger….

Perhaps of most interest is that this entire campaign, which almost certainly has Big Media behind the scenes in advisory and financial capacities, barely mentions the entertainment industries at all.

Indeed, the success of the whole campaign hinges on people worrying about the supposed ill effects of illicit streaming on them personally and then feeling persuaded to inform on suppliers and others involved in the chain.

“Know of someone supplying or promoting these dodgy devices or software? It is illegal. Call us now and help stop crime in your community,” the videos warn.

That CrimeStoppers has taken on this campaign at all is a bit of a head-scratcher, given the bigger crime picture. Struggling with severe budget cuts, police in the UK are already de-prioritizing a number of crimes, leading to something called “screening out”, a process through which victims are given a crime number but no investigation is carried out.

This means that in 2016, 45% of all reported crimes in Greater Manchester weren’t investigated and a staggering 57% of all recorded domestic burglaries weren’t followed up by the police. But it gets worse.

“More than 62pc of criminal damage and arson offenses were not investigated, along with one in three reported shoplifting incidents,” MEN reports.

Given this backdrop, how will police suddenly find the resources to follow up lots of leads from the public and then subsequently prosecute people who sell pirate boxes? Even if they do, will that be at the expense of yet more “screening out” of other public-focused offenses?

No one is saying that selling pirate devices isn’t a crime or at least worthy of being followed up, but is this niche likely to be important to the public when they’re being told that nothing will be done when their homes are emptied by intruders? “NO” says a comment on one of the CrimeStoppers videos on YouTube.

“This crime affects multi-million dollar corporations, I’d rather see tax payers money invested on videos raising awareness of crimes committed against the people rather than the 0.001%,” it concludes.

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

Movie Company Has No Right to Sue, Accused Pirate Argues

Post Syndicated from Ernesto original https://torrentfreak.com/movie-company-has-no-right-to-sue-accused-pirate-argues-171208/

In recent years, a group of select companies have pressured hundreds of thousands of alleged pirates to pay significant settlement fees, or face legal repercussions.

These so-called “copyright trolling” efforts have also been a common occurrence in the United States for more than half a decade, and still are today.

While copyright holders should be able to take legitimate piracy claims to court, not all cases are as strong as they first appear. Many defendants have brought up flaws, often in relation to the IP-address evidence, but an accused pirate in Oregon takes things up a notch.

Lingfu Zhang, represented by attorney David Madden, has turned the tables on the makers of the film Fathers & Daughters. The man denies having downloaded the movie but also points out that the filmmakers have signed away their online distribution rights.

The issue was brought up in previous months, but the relevant findings were only unsealed this week. They show that the movie company (F&D), through a sales agent, sold the online distribution rights to a third party.

While this is not uncommon in the movie business, it means that they no longer have the right to distribute the movie online, a right Zhang was accused of violating. This is also what his attorney pointed out to the court, asking for a judgment in favor of his client.

“ZHANG denies downloading the movie but Defendant’s current motion for summary judgment challenges a different portion of F&D’s case: Defendant argues that F&D has alienated all of the relevant rights necessary to sue for infringement under the Copyright Act,” Madden writes.

The filmmakers opposed the request and pointed out that they still had some rights. However, this is irrelevant according to the defense, since the distribution rights are not owned by them, but by a company that’s not part of the lawsuit.

“Plaintiff claims, for example, that it still owns the right to exploit the movie on airlines and oceangoing vessels. That may or may not be true – Plaintiff has not submitted any evidence on the question – but ZHANG is not accused of showing the movie on an airplane or a cruise ship.

“He is accused of downloading it over the Internet, which is an infringement that affects only an exclusive right owned by non-party DISTRIBUTOR 2,” Madden adds.

Interestingly, an undated addendum to the licensing agreement, allegedly created after the lawsuit was started, states that the filmmakers would keep their “anti-piracy” rights, as can be seen below.

Anti-Piracy rights?

This doesn’t save the filmmaker, according to the defense. The “licensor” who keeps these anti-piracy and enforcement rights refers to the sales agent, not the filmmaker, Madden writes. In addition, the case is about copyright infringement, and despite the addendum, the filmmakers don’t have the exclusive rights that apply here.

“Plaintiff represented to this Court that it was the ‘proprietor of all copyrights and interests need to bring suit’ […] notwithstanding that it had – years earlier – transferred away all its exclusive rights under Section 106 of the Copyright Act,” the defense lawyer concludes.

“Even viewing all Plaintiff’s agreements in the light most favorable to it, Plaintiff holds nothing more than a bare right to sue, which is not a cognizable right that may be exercised in the courts of this Circuit.”

While the court has yet to decide on the motion, this case could turn into a disaster for the makers of Fathers & Daughters.

If the court agrees that they don’t have the proper rights, defendants in other cases may argue the same. It’s easy to see how their entire trolling scheme would then collapse.

The original memorandum in support of the motion for summary judgment is available here (pdf) and a copy of the reply brief can be found here (pdf).

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

Security updates for Friday

Post Syndicated from jake original https://lwn.net/Articles/740997/rss

Security updates have been issued by Arch Linux (chromium and vlc), Debian (erlang), Mageia (ffmpeg, tor, and wireshark), openSUSE (chromium, opensaml, openssh, openvswitch, and php7), Oracle (postgresql), Red Hat (chromium-browser, postgresql, rh-postgresql94-postgresql, rh-postgresql95-postgresql, and rh-postgresql96-postgresql), SUSE (firefox, java-1_6_0-ibm, opensaml, and xen), and Ubuntu (kernel, linux, linux-aws, linux-kvm, linux-raspi2, linux-snapdragon, linux, linux-raspi2, linux-azure, linux-gcp, linux-hwe, linux-lts-trusty, linux-lts-xenial, linux-aws, and rsync).

Security Vulnerabilities in Certificate Pinning

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/12/security_vulner_10.html

New research found that many banks offer certificate pinning as a security feature, but fail to authenticate the hostname. This leaves the systems open to man-in-the-middle attacks.

From the paper:

Abstract: Certificate verification is a crucial stage in the establishment of a TLS connection. A common security flaw in TLS implementations is the lack of certificate hostname verification but, in general, this is easy to detect. In security-sensitive applications, the usage of certificate pinning is on the rise. This paper shows that certificate pinning can (and often does) hide the lack of proper hostname verification, enabling MITM attacks. Dynamic (black-box) detection of this vulnerability would typically require the tester to own a high security certificate from the same issuer (and often same intermediate CA) as the one used by the app. We present Spinner, a new tool for black-box testing for this vulnerability at scale that does not require purchasing any certificates. By redirecting traffic to websites which use the relevant certificates and then analysing the (encrypted) network traffic we are able to determine whether the hostname check is correctly done, even in the presence of certificate pinning. We use Spinner to analyse 400 security-sensitive Android and iPhone apps. We found that 9 apps had this flaw, including two of the largest banks in the world: Bank of America and HSBC. We also found that TunnelBear, one of the most popular VPN apps was also vulnerable. These apps have a joint user base of tens of millions of users.

News article.

Resilient TVAddons Plans to Ditch Proactive ‘Piracy’ Screening

Post Syndicated from Ernesto original https://torrentfreak.com/resilient-tvaddons-plans-to-ditch-proactive-piracy-screening-171207/

After years of smooth sailing, this year TVAddons became a poster child for the entertainment industry’s war on illicit streaming devices.

The leading repository for unofficial Kodi addons was sued for copyright infringement in the US by satellite and broadcast provider Dish Network. Around the same time, a similar case was filed by Bell, TVA, Videotron, and Rogers in Canada.

The latter case has done the most damage thus far, as it caused the addon repository to lose its domain names and social media accounts. As a result, the site went dead and while many believed it would never return, it made a blazing comeback after a few weeks.

Since the original TVAddons.ag domain was seized, the site returned on TVaddons.co. And that was not the only difference. A lot of the old add-ons, for which it was unclear if they linked to licensed content, were no longer listed in the repository either.

TVAddons previously relied on the DMCA to shield it from liability but apparently, that wasn’t enough. As a result, they took the drastic decision to check all submitted add-ons carefully.

“Since complying with the law is clearly not enough to prevent frivolous legal action from being taken against you, we have been forced to implement a more drastic code vetting process,” a TVAddons representative told us previously.

Despite the absence of several of the most used add-ons, the repository has managed to regain many of its former users. Over the past month, TVAddons had over 12 million unique users. These all manually installed the new repository on their devices.

“We’re not like one of those pirate sites that are shut down and opens on a new domain the next day, getting users to actually manually install a new repo isn’t an easy feat,” a TVAddons representative informs TorrentFreak.

While it’s still far away from the 40 million unique users it had earlier this year, before the trouble began, it’s still a force to be reckoned with.

Interestingly, the vast majority of all TVAddons traffic comes from the United States. The UK is second at a respectable distance, followed by Canada, Germany, and the Netherlands.

While many former users have returned, the submission policy changes didn’t go unnoticed. The relatively small selection of add-ons is a major drawback for some, but that’s about to change as well, we are informed.

TVAddons plans to return to the old submission model where developers can upload their code more freely. Instead of proactive screening, TVAddons will rely on a standard DMCA takedown policy, relying on copyright holders to flag potentially infringing content.

“We intend on returning to a standard DMCA compliant add-on submission policy shortly, there’s no reason why we should be held to a higher standard than Facebook, Twitter, YouTube or Reddit given the fact that we don’t even host any form of streaming content in the first place.

“Our interim policy isn’t pragmatic, it’s nearly impossible for us to verify the global licensing of all forms of protected content. When you visit a website, there’s no way of verifying licensing beyond trusting them based on reputation.”

The upcoming change doesn’t mean that TVAddons will ignore its legal requirements. If they receive a legitimate takedown notice, proper action will be taken, as always. As such, they would operate in the same fashion as other user-generated sites.

“Right now our interim addon submission policy is akin to North Korea. We always followed the law and will always continue to do so. Anytime we’ve received a legitimate complaint we’ve acted upon it in an expedited manner.

“Facebook, Twitter, Reddit and other online communities would have never existed if they were required to approve the contents of each user’s submissions prior to public posting.”

The change takes place while the two court cases are still pending. TVAddons is determined to keep up this fight. Meanwhile, they are also asking the public to support the project financially.

While some copyright holders, including those who are fighting the service in court, might not like the change, TVAddons believes that this is well within their rights. And with support from groups such as the Electronic Frontier Foundation, they don’t stand alone in this.

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

Movie & TV Companies Tackle Pirate IPTV in Australia Federal Court

Post Syndicated from Andy original https://torrentfreak.com/movie-tv-companies-tackle-pirate-iptv-in-australia-federal-court-171207/

As movie and TV show piracy has migrated from the desktop towards mobile and living room-based devices, copyright holders have found the need to adapt to a new enemy.

Dealing with streaming services is now high on the agenda, with third-party Kodi addons and various Android apps posing the biggest challenge. Alongside is the much less prevalent but rapidly growing pay IPTV market, in which thousands of premium channels are delivered to homes for a relatively small fee.

In Australia, copyright holders are treating these services in much the same way as torrent sites. They feel that if they can force ISPs to block them, the problem can be mitigated. Most recently, movie and TV show giants Village Roadshow, Disney, Universal, Warner Bros, Twentieth Century Fox, and Paramount filed an application targeting HDSubs+, a pirate IPTV operation servicing thousands of Australians.

Filed in October, the application for the injunction targets Australia’s largest ISPs including Telstra, Optus, TPG, and Vocus, plus their subsidiaries. The movie and TV show companies want them to quickly block HDSubs+, to prevent it from reaching its audience.

HDSubs+ IPTV package
However, blocking isn’t particularly straightforward. Due to the way IPTV services are setup a number of domains need to be blocked, including their sales platforms, EPG (electronic program guide), software (such as an Android app), updates, and sundry other services. In HDSubs+ case around ten domains need to be restricted but in court today, Village Roadshow revealed that probably won’t deal with the problem.

HDSubs+ appears to be undergoing some kind of transformation, possibly to mitigate efforts to block it in Australia. ComputerWorld reports that it is now directing subscribers to update to a new version that works in a more evasive manner.

If they agree, HDSubs+ customers are being migrated over to a service called PressPlayPlus. It works in the same way as the old system but no longer uses the domain names cited in Village Roadshow’s injunction application. This means that DNS blocks, the usual weapon of choice for local ISPs, will prove futile.

Village Roadshow says that with this in mind it may be forced to seek enhanced IP address blocking, unless it is granted a speedy hearing for its application. This, in turn, may result in the normally cooperative ISPs returning to court to argue their case.

“If that’s what you want to do, then you’ll have to amend the orders and let the parties know,” Judge John Nicholas said.

“It’s only the former [DNS blocking] that carriage service providers have agreed to in the past.”

As things stand, Village Roadshow will return to court on December 15 for a case management hearing but in the meantime, the Federal Court must deal with another IPTV-related blocking request.

In common with its Australian and US-based counterparts, Hong Kong-based broadcaster Television Broadcasts Limited (TVB) has launched a similar case asking local ISPs to block another IPTV service.

“Television Broadcasts Limited can confirm that we have commenced legal action in Australia to protect our copyright,” a TVB spokesperson told Computerworld.

TVB wants ISPs including Telstra, Optus, Vocus, and TPG plus their subsidiaries to block access to seven Android-based services named as A1, BlueTV, EVPAD, FunTV, MoonBox, Unblock, and hTV5.

Court documents list 21 URLs maintaining the services. They will all need to be blocked by DNS or other means, if the former proves futile. Online reports suggest that there are similarities among the IPTV products listed above. A demo for the FunTV IPTV service is shown below.

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

Libertarians are against net neutrality

Post Syndicated from Robert Graham original http://blog.erratasec.com/2017/12/libertarians-are-against-net-neutrality.html

This post claims to be by a libertarian in support of net neutrality. As a libertarian, I need to debunk this. “Net neutrality” is a case of one-hand clapping, you rarely hear the competing side, and thus, that side may sound attractive. This post is about the other side, from a libertarian point of view.

That post just repeats the common, and wrong, left-wing talking points. I mean, there might be a libertarian case for some broadband regulation, but this isn’t it.

This thing they call “net neutrality” is just left-wing politics masquerading as some sort of principle. It’s no different than how people claim to be “pro-choice”, yet demand forced vaccinations. Or, it’s no different than how people claim to believe in “traditional marriage” even while they are on their third “traditional marriage”.

Properly defined, “net neutrality” means no discrimination of network traffic. But nobody wants that. A classic example is how most internet connections have faster download speeds than uploads. This discriminates against upload traffic, harming innovation in upload-centric applications like DropBox’s cloud backup or BitTorrent’s peer-to-peer file transfer. Yet activists never mention this, or other types of network traffic discrimination, because they no more care about “net neutrality” than Trump or Gingrich care about “traditional marriage”.

Instead, when people say “net neutrality”, they mean “government regulation”. It’s the same old debate between who is the best steward of consumer interest: the free-market or government.

Specifically, in the current debate, they are referring to the Obama-era FCC “Open Internet” order and reclassification of broadband under “Title II” so they can regulate it. Trump’s FCC is putting broadband back to “Title I”, which means the FCC can’t regulate most of its “Open Internet” order.

Don’t be tricked into thinking the “Open Internet” order is anything but intensely politically. The premise behind the order is the Democrat’s firm believe that it’s government who created the Internet, and all innovation, advances, and investment ultimately come from the government. It sees ISPs as inherently deceitful entities who will only serve their own interests, at the expense of consumers, unless the FCC protects consumers.

It says so right in the order itself. It starts with the premise that broadband ISPs are evil, using illegitimate “tactics” to hurt consumers, and continues with similar language throughout the order.

A good contrast to this can be seen in Tim Wu’s non-political original paper in 2003 that coined the term “net neutrality”. Whereas the FCC sees broadband ISPs as enemies of consumers, Wu saw them as allies. His concern was not that ISPs would do evil things, but that they would do stupid things, such as favoring short-term interests over long-term innovation (such as having faster downloads than uploads).

The political depravity of the FCC’s order can be seen in this comment from one of the commissioners who voted for those rules:

FCC Commissioner Jessica Rosenworcel wants to increase the minimum broadband standards far past the new 25Mbps download threshold, up to 100Mbps. “We invented the internet. We can do audacious things if we set big goals, and I think our new threshold, frankly, should be 100Mbps. I think anything short of that shortchanges our children, our future, and our new digital economy,” Commissioner Rosenworcel said.

This is indistinguishable from communist rhetoric that credits the Party for everything, as this booklet from North Korea will explain to you.

But what about monopolies? After all, while the free-market may work when there’s competition, it breaks down where there are fewer competitors, oligopolies, and monopolies.

There is some truth to this, in individual cities, there’s often only only a single credible high-speed broadband provider. But this isn’t the issue at stake here. The FCC isn’t proposing light-handed regulation to keep monopolies in check, but heavy-handed regulation that regulates every last decision.

Advocates of FCC regulation keep pointing how broadband monopolies can exploit their renting-seeking positions in order to screw the customer. They keep coming up with ever more bizarre and unlikely scenarios what monopoly power grants the ISPs.

But the never mention the most simplest: that broadband monopolies can just charge customers more money. They imagine instead that these companies will pursue a string of outrageous, evil, and less profitable behaviors to exploit their monopoly position.

The FCC’s reclassification of broadband under Title II gives it full power to regulate ISPs as utilities, including setting prices. The FCC has stepped back from this, promising it won’t go so far as to set prices, that it’s only regulating these evil conspiracy theories. This is kind of bizarre: either broadband ISPs are evilly exploiting their monopoly power or they aren’t. Why stop at regulating only half the evil?

The answer is that the claim “monopoly” power is a deception. It starts with overstating how many monopolies there are to begin with. When it issued its 2015 “Open Internet” order the FCC simultaneously redefined what they meant by “broadband”, upping the speed from 5-mbps to 25-mbps. That’s because while most consumers have multiple choices at 5-mbps, fewer consumers have multiple choices at 25-mbps. It’s a dirty political trick to convince you there is more of a problem than there is.

In any case, their rules still apply to the slower broadband providers, and equally apply to the mobile (cell phone) providers. The US has four mobile phone providers (AT&T, Verizon, T-Mobile, and Sprint) and plenty of competition between them. That it’s monopolistic power that the FCC cares about here is a lie. As their Open Internet order clearly shows, the fundamental principle that animates the document is that all corporations, monopolies or not, are treacherous and must be regulated.

“But corporations are indeed evil”, people argue, “see here’s a list of evil things they have done in the past!”

No, those things weren’t evil. They were done because they benefited the customers, not as some sort of secret rent seeking behavior.

For example, one of the more common “net neutrality abuses” that people mention is AT&T’s blocking of FaceTime. I’ve debunked this elsewhere on this blog, but the summary is this: there was no network blocking involved (not a “net neutrality” issue), and the FCC analyzed it and decided it was in the best interests of the consumer. It’s disingenuous to claim it’s an evil that justifies FCC actions when the FCC itself declared it not evil and took no action. It’s disingenuous to cite the “net neutrality” principle that all network traffic must be treated when, in fact, the network did treat all the traffic equally.

Another frequently cited abuse is Comcast’s throttling of BitTorrent.Comcast did this because Netflix users were complaining. Like all streaming video, Netflix backs off to slower speed (and poorer quality) when it experiences congestion. BitTorrent, uniquely among applications, never backs off. As most applications become slower and slower, BitTorrent just speeds up, consuming all available bandwidth. This is especially problematic when there’s limited upload bandwidth available. Thus, Comcast throttled BitTorrent during prime time TV viewing hours when the network was already overloaded by Netflix and other streams. BitTorrent users wouldn’t mind this throttling, because it often took days to download a big file anyway.

When the FCC took action, Comcast stopped the throttling and imposed bandwidth caps instead. This was a worse solution for everyone. It penalized heavy Netflix viewers, and prevented BitTorrent users from large downloads. Even though BitTorrent users were seen as the victims of this throttling, they’d vastly prefer the throttling over the bandwidth caps.

In both the FaceTime and BitTorrent cases, the issue was “network management”. AT&T had no competing video calling service, Comcast had no competing download service. They were only reacting to the fact their networks were overloaded, and did appropriate things to solve the problem.

Mobile carriers still struggle with the “network management” issue. While their networks are fast, they are still of low capacity, and quickly degrade under heavy use. They are looking for tricks in order to reduce usage while giving consumers maximum utility.

The biggest concern is video. It’s problematic because it’s designed to consume as much bandwidth as it can, throttling itself only when it experiences congestion. This is what you probably want when watching Netflix at the highest possible quality, but it’s bad when confronted with mobile bandwidth caps.

With small mobile devices, you don’t want as much quality anyway. You want the video degraded to lower quality, and lower bandwidth, all the time.

That’s the reasoning behind T-Mobile’s offerings. They offer an unlimited video plan in conjunction with the biggest video providers (Netflix, YouTube, etc.). The catch is that when congestion occurs, they’ll throttle it to lower quality. In other words, they give their bandwidth to all the other phones in your area first, then give you as much of the leftover bandwidth as you want for video.

While it sounds like T-Mobile is doing something evil, “zero-rating” certain video providers and degrading video quality, the FCC allows this, because they recognize it’s in the customer interest.

Mobile providers especially have great interest in more innovation in this area, in order to conserve precious bandwidth, but they are finding it costly. They can’t just innovate, but must ask the FCC permission first. And with the new heavy handed FCC rules, they’ve become hostile to this innovation. This attitude is highlighted by the statement from the “Open Internet” order:

And consumers must be protected, for example from mobile commercial practices masquerading as “reasonable network management.”

This is a clear declaration that free-market doesn’t work and won’t correct abuses, and that that mobile companies are treacherous and will do evil things without FCC oversight.

Conclusion

Ignoring the rhetoric for the moment, the debate comes down to simple left-wing authoritarianism and libertarian principles. The Obama administration created a regulatory regime under clear Democrat principles, and the Trump administration is rolling it back to more free-market principles. There is no principle at stake here, certainly nothing to do with a technical definition of “net neutrality”.

The 2015 “Open Internet” order is not about “treating network traffic neutrally”, because it doesn’t do that. Instead, it’s purely a left-wing document that claims corporations cannot be trusted, must be regulated, and that innovation and prosperity comes from the regulators and not the free market.

It’s not about monopolistic power. The primary targets of regulation are the mobile broadband providers, where there is plenty of competition, and who have the most “network management” issues. Even if it were just about wired broadband (like Comcast), it’s still ignoring the primary ways monopolies profit (raising prices) and instead focuses on bizarre and unlikely ways of rent seeking.

If you are a libertarian who nonetheless believes in this “net neutrality” slogan, you’ve got to do better than mindlessly repeating the arguments of the left-wing. The term itself, “net neutrality”, is just a slogan, varying from person to person, from moment to moment. You have to be more specific. If you truly believe in the “net neutrality” technical principle that all traffic should be treated equally, then you’ll want a rewrite of the “Open Internet” order.

In the end, while libertarians may still support some form of broadband regulation, it’s impossible to reconcile libertarianism with the 2015 “Open Internet”, or the vague things people mean by the slogan “net neutrality”.

How to Easily Apply Amazon Cloud Directory Schema Changes with In-Place Schema Upgrades

Post Syndicated from Mahendra Chheda original https://aws.amazon.com/blogs/security/how-to-easily-apply-amazon-cloud-directory-schema-changes-with-in-place-schema-upgrades/

Now, Amazon Cloud Directory makes it easier for you to apply schema changes across your directories with in-place schema upgrades. Your directory now remains available while Cloud Directory applies backward-compatible schema changes such as the addition of new fields. Without migrating data between directories or applying code changes to your applications, you can upgrade your schemas. You also can view the history of your schema changes in Cloud Directory by using version identifiers, which help you track and audit schema versions across directories. If you have multiple instances of a directory with the same schema, you can view the version history of schema changes to manage your directory fleet and ensure that all directories are running with the same schema version.

In this blog post, I demonstrate how to perform an in-place schema upgrade and use schema versions in Cloud Directory. I add additional attributes to an existing facet and add a new facet to a schema. I then publish the new schema and apply it to running directories, upgrading the schema in place. I also show how to view the version history of a directory schema, which helps me to ensure my directory fleet is running the same version of the schema and has the correct history of schema changes applied to it.

Note: I share Java code examples in this post. I assume that you are familiar with the AWS SDK and can use Java-based code to build a Cloud Directory code example. You can apply the concepts I cover in this post to other programming languages such as Python and Ruby.

Cloud Directory fundamentals

I will start by covering a few Cloud Directory fundamentals. If you are already familiar with the concepts behind Cloud Directory facets, schemas, and schema lifecycles, you can skip to the next section.

Facets: Groups of attributes. You use facets to define object types. For example, you can define a device schema by adding facets such as computers, phones, and tablets. A computer facet can track attributes such as serial number, make, and model. You can then use the facets to create computer objects, phone objects, and tablet objects in the directory to which the schema applies.

Schemas: Collections of facets. Schemas define which types of objects can be created in a directory (such as users, devices, and organizations) and enforce validation of data for each object class. All data within a directory must conform to the applied schema. As a result, the schema definition is essentially a blueprint to construct a directory with an applied schema.

Schema lifecycle: The four distinct states of a schema: Development, Published, Applied, and Deleted. Schemas in the Published and Applied states have version identifiers and cannot be changed. Schemas in the Applied state are used by directories for validation as applications insert or update data. You can change schemas in the Development state as many times as you need them to. In-place schema upgrades allow you to apply schema changes to an existing Applied schema in a production directory without the need to export and import the data populated in the directory.

How to add attributes to a computer inventory application schema and perform an in-place schema upgrade

To demonstrate how to set up schema versioning and perform an in-place schema upgrade, I will use an example of a computer inventory application that uses Cloud Directory to store relationship data. Let’s say that at my company, AnyCompany, we use this computer inventory application to track all computers we give to our employees for work use. I previously created a ComputerSchema and assigned its version identifier as 1. This schema contains one facet called ComputerInfo that includes attributes for SerialNumber, Make, and Model, as shown in the following schema details.

Schema: ComputerSchema
Version: 1

Facet: ComputerInfo
Attribute: SerialNumber, type: Integer
Attribute: Make, type: String
Attribute: Model, type: String

AnyCompany has offices in Seattle, Portland, and San Francisco. I have deployed the computer inventory application for each of these three locations. As shown in the lower left part of the following diagram, ComputerSchema is in the Published state with a version of 1. The Published schema is applied to SeattleDirectory, PortlandDirectory, and SanFranciscoDirectory for AnyCompany’s three locations. Implementing separate directories for different geographic locations when you don’t have any queries that cross location boundaries is a good data partitioning strategy and gives your application better response times with lower latency.

Diagram of ComputerSchema in Published state and applied to three directories

Legend for the diagrams in this post

The following code example creates the schema in the Development state by using a JSON file, publishes the schema, and then creates directories for the Seattle, Portland, and San Francisco locations. For this example, I assume the schema has been defined in the JSON file. The createSchema API creates a schema Amazon Resource Name (ARN) with the name defined in the variable, SCHEMA_NAME. I can use the putSchemaFromJson API to add specific schema definitions from the JSON file.

// The utility method to get valid Cloud Directory schema JSON
String validJson = getJsonFile("ComputerSchema_version_1.json")

String SCHEMA_NAME = "ComputerSchema";

String developmentSchemaArn = client.createSchema(new CreateSchemaRequest()
        .withName(SCHEMA_NAME))
        .getSchemaArn();

// Put the schema document in the Development schema
PutSchemaFromJsonResult result = client.putSchemaFromJson(new PutSchemaFromJsonRequest()
        .withSchemaArn(developmentSchemaArn)
        .withDocument(validJson));

The following code example takes the schema that is currently in the Development state and publishes the schema, changing its state to Published.

String SCHEMA_VERSION = "1";
String publishedSchemaArn = client.publishSchema(
        new PublishSchemaRequest()
        .withDevelopmentSchemaArn(developmentSchemaArn)
        .withVersion(SCHEMA_VERSION))
        .getPublishedSchemaArn();

// Our Published schema ARN is as follows
// arn:aws:clouddirectory:us-west-2:XXXXXXXXXXXX:schema/published/ComputerSchema/1

The following code example creates a directory named SeattleDirectory and applies the published schema. The createDirectory API call creates a directory by using the published schema provided in the API parameters. Note that Cloud Directory stores a version of the schema in the directory in the Applied state. I will use similar code to create directories for PortlandDirectory and SanFranciscoDirectory.

String DIRECTORY_NAME = "SeattleDirectory"; 

CreateDirectoryResult directory = client.createDirectory(
        new CreateDirectoryRequest()
        .withName(DIRECTORY_NAME)
        .withSchemaArn(publishedSchemaArn));

String directoryArn = directory.getDirectoryArn();
String appliedSchemaArn = directory.getAppliedSchemaArn();

// This code section can be reused to create directories for Portland and San Francisco locations with the appropriate directory names

// Our directory ARN is as follows 
// arn:aws:clouddirectory:us-west-2:XXXXXXXXXXXX:directory/XX_DIRECTORY_GUID_XX

// Our applied schema ARN is as follows 
// arn:aws:clouddirectory:us-west-2:XXXXXXXXXXXX:directory/XX_DIRECTORY_GUID_XX/schema/ComputerSchema/1

Revising a schema

Now let’s say my company, AnyCompany, wants to add more information for computers and to track which employees have been assigned a computer for work use. I modify the schema to add two attributes to the ComputerInfo facet: Description and OSVersion (operating system version). I make Description optional because it is not important for me to track this attribute for the computer objects I create. I make OSVersion mandatory because it is critical for me to track it for all computer objects so that I can make changes such as applying security patches or making upgrades. Because I make OSVersion mandatory, I must provide a default value that Cloud Directory will apply to objects that were created before the schema revision, in order to handle backward compatibility. Note that you can replace the value in any object with a different value.

I also add a new facet to track computer assignment information, shown in the following updated schema as the ComputerAssignment facet. This facet tracks these additional attributes: Name (the name of the person to whom the computer is assigned), EMail (the email address of the assignee), Department, and department CostCenter. Note that Cloud Directory refers to the previously available version identifier as the Major Version. Because I can now add a minor version to a schema, I also denote the changed schema as Minor Version A.

Schema: ComputerSchema
Major Version: 1
Minor Version: A 

Facet: ComputerInfo
Attribute: SerialNumber, type: Integer 
Attribute: Make, type: String
Attribute: Model, type: Integer
Attribute: Description, type: String, required: NOT_REQUIRED
Attribute: OSVersion, type: String, required: REQUIRED_ALWAYS, default: "Windows 7"

Facet: ComputerAssignment
Attribute: Name, type: String
Attribute: EMail, type: String
Attribute: Department, type: String
Attribute: CostCenter, type: Integer

The following diagram shows the changes that were made when I added another facet to the schema and attributes to the existing facet. The highlighted area of the diagram (bottom left) shows that the schema changes were published.

Diagram showing that schema changes were published

The following code example revises the existing Development schema by adding the new attributes to the ComputerInfo facet and by adding the ComputerAssignment facet. I use a new JSON file for the schema revision, and for the purposes of this example, I am assuming the JSON file has the full schema including planned revisions.

// The utility method to get a valid CloudDirectory schema JSON
String schemaJson = getJsonFile("ComputerSchema_version_1_A.json")

// Put the schema document in the Development schema
PutSchemaFromJsonResult result = client.putSchemaFromJson(
        new PutSchemaFromJsonRequest()
        .withSchemaArn(developmentSchemaArn)
        .withDocument(schemaJson));

Upgrading the Published schema

The following code example performs an in-place schema upgrade of the Published schema with schema revisions (it adds new attributes to the existing facet and another facet to the schema). The upgradePublishedSchema API upgrades the Published schema with backward-compatible changes from the Development schema.

// From an earlier code example, I know the publishedSchemaArn has this value: "arn:aws:clouddirectory:us-west-2:XXXXXXXXXXXX:schema/published/ComputerSchema/1"

// Upgrade publishedSchemaArn to minorVersion A. The Development schema must be backward compatible with 
// the existing publishedSchemaArn. 

String minorVersion = "A"

UpgradePublishedSchemaResult upgradePublishedSchemaResult = client.upgradePublishedSchema(new UpgradePublishedSchemaRequest()
        .withDevelopmentSchemaArn(developmentSchemaArn)
        .withPublishedSchemaArn(publishedSchemaArn)
        .withMinorVersion(minorVersion));

String upgradedPublishedSchemaArn = upgradePublishedSchemaResult.getUpgradedSchemaArn();

// The Published schema ARN after the upgrade shows a minor version as follows 
// arn:aws:clouddirectory:us-west-2:XXXXXXXXXXXX:schema/published/ComputerSchema/1/A

Upgrading the Applied schema

The following diagram shows the in-place schema upgrade for the SeattleDirectory directory. I am performing the schema upgrade so that I can reflect the new schemas in all three directories. As a reminder, I added new attributes to the ComputerInfo facet and also added the ComputerAssignment facet. After the schema and directory upgrade, I can create objects for the ComputerInfo and ComputerAssignment facets in the SeattleDirectory. Any objects that were created with the old facet definition for ComputerInfo will now use the default values for any additional attributes defined in the new schema.

Diagram of the in-place schema upgrade for the SeattleDirectory directory

I use the following code example to perform an in-place upgrade of the SeattleDirectory to a Major Version of 1 and a Minor Version of A. Note that you should change a Major Version identifier in a schema to make backward-incompatible changes such as changing the data type of an existing attribute or dropping a mandatory attribute from your schema. Backward-incompatible changes require directory data migration from a previous version to the new version. You should change a Minor Version identifier in a schema to make backward-compatible upgrades such as adding additional attributes or adding facets, which in turn may contain one or more attributes. The upgradeAppliedSchema API lets me upgrade an existing directory with a different version of a schema.

// This upgrades ComputerSchema version 1 of the Applied schema in SeattleDirectory to Major Version 1 and Minor Version A
// The schema must be backward compatible or the API will fail with IncompatibleSchemaException

UpgradeAppliedSchemaResult upgradeAppliedSchemaResult = client.upgradeAppliedSchema(new UpgradeAppliedSchemaRequest()
        .withDirectoryArn(directoryArn)
        .withPublishedSchemaArn(upgradedPublishedSchemaArn));

String upgradedAppliedSchemaArn = upgradeAppliedSchemaResult.getUpgradedSchemaArn();

// The Applied schema ARN after the in-place schema upgrade will appear as follows
// arn:aws:clouddirectory:us-west-2:XXXXXXXXXXXX:directory/XX_DIRECTORY_GUID_XX/schema/ComputerSchema/1

// This code section can be reused to upgrade directories for the Portland and San Francisco locations with the appropriate directory ARN

Note: Cloud Directory has excluded returning the Minor Version identifier in the Applied schema ARN for backward compatibility and to enable the application to work across older and newer versions of the directory.

The following diagram shows the changes that are made when I perform an in-place schema upgrade in the two remaining directories, PortlandDirectory and SanFranciscoDirectory. I make these calls sequentially, upgrading PortlandDirectory first and then upgrading SanFranciscoDirectory. I use the same code example that I used earlier to upgrade SeattleDirectory. Now, all my directories are running the most current version of the schema. Also, I made these schema changes without having to migrate data and while maintaining my application’s high availability.

Diagram showing the changes that are made with an in-place schema upgrade in the two remaining directories

Schema revision history

I can now view the schema revision history for any of AnyCompany’s directories by using the listAppliedSchemaArns API. Cloud Directory maintains the five most recent versions of applied schema changes. Similarly, to inspect the current Minor Version that was applied to my schema, I use the getAppliedSchemaVersion API. The listAppliedSchemaArns API returns the schema ARNs based on my schema filter as defined in withSchemaArn.

I use the following code example to query an Applied schema for its version history.

// This returns the five most recent Minor Versions associated with a Major Version
ListAppliedSchemaArnsResult listAppliedSchemaArnsResult = client.listAppliedSchemaArns(new ListAppliedSchemaArnsRequest()
        .withDirectoryArn(directoryArn)
        .withSchemaArn(upgradedAppliedSchemaArn));

// Note: The listAppliedSchemaArns API without the SchemaArn filter returns all the Major Versions in a directory

The listAppliedSchemaArns API returns the two ARNs as shown in the following output.

arn:aws:clouddirectory:us-west-2:XXXXXXXXXXXX:directory/XX_DIRECTORY_GUID_XX/schema/ComputerSchema/1
arn:aws:clouddirectory:us-west-2:XXXXXXXXXXXX:directory/XX_DIRECTORY_GUID_XX/schema/ComputerSchema/1/A

The following code example queries an Applied schema for current Minor Version by using the getAppliedSchemaVersion API.

// This returns the current Applied schema's Minor Version ARN 

GetAppliedSchemaVersion getAppliedSchemaVersionResult = client.getAppliedSchemaVersion(new GetAppliedSchemaVersionRequest()
	.withSchemaArn(upgradedAppliedSchemaArn));

The getAppliedSchemaVersion API returns the current Applied schema ARN with a Minor Version, as shown in the following output.

arn:aws:clouddirectory:us-west-2:XXXXXXXXXXXX:directory/XX_DIRECTORY_GUID_XX/schema/ComputerSchema/1/A

If you have a lot of directories, schema revision API calls can help you audit your directory fleet and ensure that all directories are running the same version of a schema. Such auditing can help you ensure high integrity of directories across your fleet.

Summary

You can use in-place schema upgrades to make changes to your directory schema as you evolve your data set to match the needs of your application. An in-place schema upgrade allows you to maintain high availability for your directory and applications while the upgrade takes place. For more information about in-place schema upgrades, see the in-place schema upgrade documentation.

If you have comments about this blog post, submit them in the “Comments” section below. If you have questions about implementing the solution in this post, start a new thread in the Directory Service forum or contact AWS Support.

– Mahendra

 

Running Windows Containers on Amazon ECS

Post Syndicated from Nathan Taber original https://aws.amazon.com/blogs/compute/running-windows-containers-on-amazon-ecs/

This post was developed and written by Jeremy Cowan, Thomas Fuller, Samuel Karp, and Akram Chetibi.

Containers have revolutionized the way that developers build, package, deploy, and run applications. Initially, containers only supported code and tooling for Linux applications. With the release of Docker Engine for Windows Server 2016, Windows developers have started to realize the gains that their Linux counterparts have experienced for the last several years.

This week, we’re adding support for running production workloads in Windows containers using Amazon Elastic Container Service (Amazon ECS). Now, Amazon ECS provides an ECS-Optimized Windows Server Amazon Machine Image (AMI). This AMI is based on the EC2 Windows Server 2016 AMI, and includes Docker 17.06 Enterprise Edition and the ECS Agent 1.16. This AMI provides improved instance and container launch time performance. It’s based on Windows Server 2016 Datacenter and includes Docker 17.06.2-ee-5, along with a new version of the ECS agent that now runs as a native Windows service.

In this post, I discuss the benefits of this new support, and walk you through getting started running Windows containers with Amazon ECS.

When AWS released the Windows Server 2016 Base with Containers AMI, the ECS agent ran as a process that made it difficult to monitor and manage. As a service, the agent can be health-checked, managed, and restarted no differently than other Windows services. The AMI also includes pre-cached images for Windows Server Core 2016 and Windows Server Nano Server 2016. By caching the images in the AMI, launching new Windows containers is significantly faster. When Docker images include a layer that’s already cached on the instance, Docker re-uses that layer instead of pulling it from the Docker registry.

The ECS agent and an accompanying ECS PowerShell module used to install, configure, and run the agent come pre-installed on the AMI. This guarantees there is a specific platform version available on the container instance at launch. Because the software is included, you don’t have to download it from the internet. This saves startup time.

The Windows-compatible ECS-optimized AMI also reports CPU and memory utilization and reservation metrics to Amazon CloudWatch. Using the CloudWatch integration with ECS, you can create alarms that trigger dynamic scaling events to automatically add or remove capacity to your EC2 instances and ECS tasks.

Getting started

To help you get started running Windows containers on ECS, I’ve forked the ECS reference architecture, to build an ECS cluster comprised of Windows instances instead of Linux instances. You can pull the latest version of the reference architecture for Windows.

The reference architecture is a layered CloudFormation stack, in that it calls other stacks to create the environment. Within the stack, the ecs-windows-cluster.yaml file contains the instructions for bootstrapping the Windows instances and configuring the ECS cluster. To configure the instances outside of AWS CloudFormation (for example, through the CLI or the console), you can add the following commands to your instance’s user data:

Import-Module ECSTools
Initialize-ECSAgent

Or

Import-Module ECSTools
Initialize-ECSAgent –Cluster MyCluster -EnableIAMTaskRole

If you don’t specify a cluster name when you initialize the agent, the instance is joined to the default cluster.

Adding -EnableIAMTaskRole when initializing the agent adds support for IAM roles for tasks. Previously, enabling this setting meant running a complex script and setting an environment variable before you could assign roles to your ECS tasks.

When you enable IAM roles for tasks on Windows, it consumes port 80 on the host. If you have tasks that listen on port 80 on the host, I recommend configuring a service for them that uses load balancing. You can use port 80 on the load balancer, and the traffic can be routed to another host port on your container instances. For more information, see Service Load Balancing.

Create a cluster

To create a new ECS cluster, choose Launch stack, or pull the GitHub project to your local machine and run the following command:

aws cloudformation create-stack –template-body file://<path to master-windows.yaml> --stack-name <name>

Upload your container image

Now that you have a cluster running, step through how to build and push an image into a container repository. You use a repository hosted in Amazon Elastic Container Registry (Amazon ECR) for this, but you could also use Docker Hub. To build and push an image to a repository, install Docker on your Windows* workstation. You also create a repository and assign the necessary permissions to the account that pushes your image to Amazon ECR. For detailed instructions, see Pushing an Image.

* If you are building an image that is based on Windows layers, then you must use a Windows environment to build and push your image to the registry.

Write your task definition

Now that your image is built and ready, the next step is to run your Windows containers using a task.

Start by creating a new task definition based on the windows-simple-iis image from Docker Hub.

  1. Open the ECS console.
  2. Choose Task Definitions, Create new task definition.
  3. Scroll to the bottom of the page and choose Configure via JSON.
  4. Copy and paste the following JSON into that field.
  5. Choose Save, Create.
{
   "family": "windows-simple-iis",
   "containerDefinitions": [
   {
     "name": "windows_sample_app",
     "image": "microsoft/iis",
     "cpu": 100,
     "entryPoint":["powershell", "-Command"],
     "command":["New-Item -Path C:\\inetpub\\wwwroot\\index.html -Type file -Value '<html><head><title>Amazon ECS Sample App</title> <style>body {margin-top: 40px; background-color: #333;} </style> </head><body> <div style=color:white;text-align:center><h1>Amazon ECS Sample App</h1> <h2>Congratulations!</h2> <p>Your application is now running on a container in Amazon ECS.</p></body></html>'; C:\\ServiceMonitor.exe w3svc"],
     "portMappings": [
     {
       "protocol": "tcp",
       "containerPort": 80,
       "hostPort": 8080
     }
     ],
     "memory": 500,
     "essential": true
   }
   ]
}

You can now go back into the Task Definition page and see windows-simple-iis as an available task definition.

There are a few important aspects of the task definition file to note when working with Windows containers. First, the hostPort is configured as 8080, which is necessary because the ECS agent currently uses port 80 to enable IAM roles for tasks required for least-privilege security configurations.

There are also some fairly standard task parameters that are intentionally not included. For example, network mode is not available with Windows at the time of this release, so keep that setting blank to allow Docker to configure WinNAT, the only option available today.

Also, some parameters work differently with Windows than they do with Linux. The CPU limits that you define in the task definition are absolute, whereas on Linux they are weights. For information about other task parameters that are supported or possibly different with Windows, see the documentation.

Run your containers

At this point, you are ready to run containers. There are two options to run containers with ECS:

  1. Task
  2. Service

A task is typically a short-lived process that ECS creates. It can’t be configured to actively monitor or scale. A service is meant for longer-running containers and can be configured to use a load balancer, minimum/maximum capacity settings, and a number of other knobs and switches to help ensure that your code keeps running. In both cases, you are able to pick a placement strategy and a specific IAM role for your container.

  1. Select the task definition that you created above and choose Action, Run Task.
  2. Leave the settings on the next page to the default values.
  3. Select the ECS cluster created when you ran the CloudFormation template.
  4. Choose Run Task to start the process of scheduling a Docker container on your ECS cluster.

You can now go to the cluster and watch the status of your task. It may take 5–10 minutes for the task to go from PENDING to RUNNING, mostly because it takes time to download all of the layers necessary to run the microsoft/iis image. After the status is RUNNING, you should see the following results:

You may have noticed that the example task definition is named windows-simple-iis:2. This is because I created a second version of the task definition, which is one of the powerful capabilities of using ECS. You can make the task definitions part of your source code and then version them. You can also roll out new versions and practice blue/green deployment, switching to reduce downtime and improve the velocity of your deployments!

After the task has moved to RUNNING, you can see your website hosted in ECS. Find the public IP or DNS for your ECS host. Remember that you are hosting on port 8080. Make sure that the security group allows ingress from your client IP address to that port and that your VPC has an internet gateway associated with it. You should see a page that looks like the following:

This is a nice start to deploying a simple single instance task, but what if you had a Web API to be scaled out and in based on usage? This is where you could look at defining a service and collecting CloudWatch data to add and remove both instances of the task. You could also use CloudWatch alarms to add more ECS container instances and keep up with the demand. The former is built into the configuration of your service.

  1. Select the task definition and choose Create Service.
  2. Associate a load balancer.
  3. Set up Auto Scaling.

The following screenshot shows an example where you would add an additional task instance when the CPU Utilization CloudWatch metric is over 60% on average over three consecutive measurements. This may not be aggressive enough for your requirements; it’s meant to show you the option to scale tasks the same way you scale ECS instances with an Auto Scaling group. The difference is that these tasks start much faster because all of the base layers are already on the ECS host.

Do not confuse task dynamic scaling with ECS instance dynamic scaling. To add additional hosts, see Tutorial: Scaling Container Instances with CloudWatch Alarms.

Conclusion

This is just scratching the surface of the flexibility that you get from using containers and Amazon ECS. For more information, see the Amazon ECS Developer Guide and ECS Resources.

– Jeremy, Thomas, Samuel, Akram

Security updates for Wednesday

Post Syndicated from ris original https://lwn.net/Articles/740799/rss

Security updates have been issued by CentOS (samba4), Mageia (libxcursor and libxfont/libxfont2), openSUSE (exim, GraphicsMagick, graphviz, pdns, and pdns-recursor), Oracle (firefox and liblouis), Red Hat (java-1.7.0-openjdk), Scientific Linux (java-1.7.0-openjdk), SUSE (firefox, shibboleth-sp, and xen), and Ubuntu (linux-firmware).

Game night 1: Lisa, Lisa, MOOP

Post Syndicated from Eevee original https://eev.ee/blog/2017/12/05/game-night-1-lisa-lisa-moop/

For the last few weeks, glip (my partner) and I have spent a couple hours most nights playing indie games together. We started out intending to play a short list of games that had been recommended to glip, but this turns out to be a nice way to wind down, so we’ve been keeping it up and clicking on whatever looks interesting in the itch app.

Most of the games are small and made by one or two people, so they tend to be pretty tightly scoped and focus on a few particular kinds of details. I’ve found myself having brain thoughts about all that, so I thought I’d write some of them down.

I also know that some people (cough) tend not to play games they’ve never heard of, even if they want something new to play. If that’s you, feel free to play some of these, now that you’ve heard of them!

Also, I’m still figuring the format out here, so let me know if this is interesting or if you hope I never do it again!

First up:

  • Lisa: The Painful
  • Lisa: The Joyful
  • MOOP

These are impressions, not reviews. I try to avoid major/ending spoilers, but big plot points do tend to leave impressions.

Lisa: The Painful

long · classic rpg · dec 2014 · lin/mac/win · $10 on itch or steam · website

(cw: basically everything??)

Lisa: The Painful is true to its name. I hesitate to describe it as fun, exactly, but I’m glad we played it.

Everything about the game is dark. It’s a (somewhat loose) sequel to another game called Lisa, whose titular character ultimately commits suicide; her body hanging from a noose is the title screen for this game.

Ah, but don’t worry, it gets worse. This game takes place in a post-apocalyptic wasteland, where every female human — women, children, babies — is dead. You play as Brad (Lisa’s brother), who has discovered the lone exception: a baby girl he names Buddy and raises like a daughter. Now, Buddy has been kidnapped, and you have to go rescue her, presumably from being raped.

Ah, but don’t worry, it gets worse.


I’ve had a hard time putting my thoughts in order here, because so much of what stuck with me is the way the game entangles the plot with the mechanics.

I love that kind of thing, but it’s so hard to do well. I can’t really explain why, but I feel like most attempts to do it fall flat — they have a glimmer of an idea, but they don’t integrate it well enough, or they don’t run nearly as far as they could have. I often get the same feeling as, say, a hyped-up big moral choice that turns out to be picking “yes” or “no” from a menu. The idea is there, but the execution is so flimsy that it leaves no impact on me at all.

An obvious recent success here is Undertale, where the entire story is about violence and whether you choose to engage or avoid it (and whether you can do that). If you choose to eschew violence, not only does the game become more difficult, it arguably becomes a different game entirely. Granted, the contrast is lost if you (like me) tried to play as a pacifist from the very beginning. I do feel that you could go further with the idea than Undertale, but Undertale itself doesn’t feel incomplete.

Christ, I’m not even talking about the right game any more.

Okay, so: this game is a “classic” RPG, by which I mean, it was made with RPG Maker. (It’s kinda funny that RPG Maker was designed to emulate a very popular battle style, and now the only games that use that style are… made with RPG Maker.) The main loop, on the surface, is standard RPG fare: you walk around various places, talk to people, solve puzzles, recruit party members, and get into turn-based fights.

Now, Brad is addicted to a drug called Joy. He will regularly go into withdrawal, which manifests in the game as a status effect that cuts his stats (even his max HP!) dramatically.

It is really, really, incredibly inconvenient. And therein lies the genius here. The game could have simply told me that Brad is an addict, and I don’t think I would’ve cared too much. An addiction to a fantasy drug in a wasteland doesn’t mean anything to me, especially about this tiny sprite man I just met, so I would’ve filed this away as a sterile fact and forgotten about it. By making his addiction affect me, I’m now invested in it. I wish Brad weren’t addicted, even if only because it’s annoying. I found a party member once who turned out to have the same addiction, and I felt dread just from seeing the icon for the status effect. I’ve been looped into the events of this story through the medium I use to interact with it: the game.

It’s a really good use of games as a medium. Even before I’m invested in the characters, I’m invested in what’s happening to them, because it impacts the game!

Incidentally, you can get Joy as an item, which will temporarily cure your withdrawal… but you mostly find it by looting the corpses of grotesque mutant flesh horrors you encounter. I don’t think the game would have the player abruptly mutate out of nowhere, but I wasn’t about to find out, either. We never took any.


Virtually every staple of the RPG genre has been played with in some way to tie it into the theme/setting. I love it, and I think it works so well precisely because it plays with expectations of how RPGs usually work.

Most obviously, the game is a sidescroller, not top-down. You can’t jump freely, but you can hop onto one-tile-high boxes and climb ropes. You can also drop off off ledges… but your entire party will take fall damage, which gets rapidly more severe the further you fall.

This wouldn’t be too much of a problem, except that healing is hard to come by for most of the game. Several hub areas have campfires you can sleep next to to restore all your health and MP, but when you wake up, something will have happened to you. Maybe just a weird cutscene, or maybe one of your party members has decided to leave permanently.

Okay, so use healing items instead? Good luck; money is also hard to come by, and honestly so are shops, and many of the healing items are woefully underpowered.

Grind for money? Good luck there, too! While the game has plenty of battles, virtually every enemy is a unique overworld human who only appears once, and then is dead, because you killed him. Only a handful of places have unlimited random encounters, and grinding is not especially pleasant.

The “best” way to get a reliable heal is to savescum — save the game, sleep by the campfire, and reload if you don’t like what you wake up to.

In a similar vein, there’s a part of the game where you’re forced to play Russian Roulette. You choose a party member; he and an opponent will take turns shooting themselves in the head until someone finds a loaded chamber. If your party member loses, he is dead. And you have to keep playing until you win three times, so there’s no upper limit on how many people you might lose. I couldn’t find any way to influence who won, so I just had to savescum for a good half hour until I made it through with minimal losses.

It was maddening, but also a really good idea. Games don’t often incorporate the existence of saves into the gameplay, and when they do, they usually break the fourth wall and get all meta about it. Saves are never acknowledged in-universe here (aside from the existence of save points), but surely these parts of the game were designed knowing that the best way through them is by reloading. It’s rarely done, it can easily feel unfair, and it drove me up the wall — but it was certainly painful, as intended, and I kinda love that.

(Naturally, I’m told there’s a hard mode, where you can only use each save point once.)

The game also drives home the finality of death much better than most. It’s not hard to overlook the death of a redshirt, a character with a bit part who simply doesn’t appear any more. This game permanently kills your party members. Russian Roulette isn’t even the only way you can lose them! Multiple cutscenes force you to choose between losing a life or some other drastic consequence. (Even better, you can try to fight the person forcing this choice on you, and he will decimate you.) As the game progresses, you start to encounter enemies who can simply one-shot murder your party members.

It’s such a great angle. Just like with Brad’s withdrawal, you don’t want to avoid their deaths because it’d be emotional — there are dozens of party members you can recruit (though we only found a fraction of them), and most of them you only know a paragraph about — but because it would inconvenience you personally. Chances are, you have your strongest dudes in your party at any given time, so losing one of them sucks. And with few random encounters, you can’t just grind someone else up to an appropriate level; it feels like there’s a finite amount of XP in the game, and if someone high-level dies, you’ve lost all the XP that went into them.


The battles themselves are fairly straightforward. You can attack normally or use a special move that costs MP. SP? Some kind of points.

Two things in particular stand out. One I mentioned above: the vast majority of the encounters are one-time affairs against distinct named NPCs, who you then never see again, because they are dead, because you killed them.

The other is the somewhat unusual set of status effects. The staples like poison and sleep are here, but don’t show up all that often; more frequent are statuses like weird, drunk, stink, or cool. If you do take Joy (which also cures depression), you become joyed for a short time.

The game plays with these in a few neat ways, besides just Brad’s withdrawal. Some party members have a status like stink or cool permanently. Some battles are against people who don’t want to fight at all — and so they’ll spend most of the battle crying, purely for flavor impact. Seeing that for the first time hit me pretty hard; until then we’d only seen crying as a mechanical side effect of having sand kicked in one’s face.


The game does drag on a bit. I think we poured 10 in-game hours into it, which doesn’t count time spent reloading. It doesn’t help that you walk not super fast.

My biggest problem was with getting my bearings; I’m sure we spent a lot of that time wandering around accomplishing nothing. Most of the world is focused around one of a few hub areas, and once you’ve completed one hub, you can move onto the next one. That’s fine. Trouble is, you can go any of a dozen different directions from each hub, and most of those directions will lead you to very similar-looking hills built out of the same tiny handful of tiles. The connections between places are mostly cave entrances, which also largely look the same. Combine that with needing to backtrack for puzzle or progression reasons, and it’s incredibly difficult to keep track of where you’ve been, what you’ve done, and where you need to go next.

I don’t know that the game is wrong here; the aesthetic and world layout are fantastic at conveying a desolate wasteland. I wouldn’t even be surprised if the navigation were deliberately designed this way. (On the other hand, assuming every annoyance in a despair-ridden game is deliberate might be giving it too much credit.) But damn it’s still frustrating.

I felt a little lost in the battle system, too. Towards the end of the game, Brad in particular had over a dozen skills he could use, but I still couldn’t confidently tell you which were the strongest. New skills sometimes appear in the middle of the list or cost less than previous skills, and the game doesn’t outright tell you how much damage any of them do. I know this is the “classic RPG” style, and I don’t think it was hugely inconvenient, but it feels weird to barely know how my own skills work. I think this puts me off getting into new RPGs, just generally; there’s a whole new set of things I have to learn about, and games in this style often won’t just tell me anything, so there’s this whole separate meta-puzzle to figure out before I can play the actual game effectively.

Also, the sound could use a little bit of… mastering? Some music and sound effects are significantly louder and screechier than others. Painful, you could say.


The world is full of side characters with their own stuff going on, which is also something I love seeing in games; too often, the whole world feels like an obstacle course specifically designed for you.

Also, many of those characters are, well, not great people. Really, most of the game is kinda fucked up. Consider: the weird status effect is most commonly inflicted by the “Grope” skill. It makes you feel weird, you see. Oh, and the currency is porn magazines.

And then there are the gangs, the various spins on sex clubs, the forceful drug kingpins, and the overall violence that permeates everything (you stumble upon an alarming number of corpses). The game neither condones nor condemns any of this; it simply offers some ideas of how people might behave at the end of the world. It’s certainly the grittiest interpretation I’ve seen.

I don’t usually like post-apocalypses, because they try to have these very hopeful stories, but then at the end the world is still a blighted hellscape so what was the point of any of that? I like this game much better for being a blighted hellscape throughout. The story is worth following to see where it goes, not just because you expect everything wrapped up neatly at the end.

…I realize I’ve made this game sound monumentally depressing throughout, but it manages to pack in a lot of funny moments as well, from the subtle to the overt. In retrospect, it’s actually really good at balancing the mood so it doesn’t get too depressing. If nothing else, it’s hilarious to watch this gruff, solemn, battle-scarred, middle-aged man pedal around on a kid’s bike he found.


An obvious theme of the game is despair, but the more I think about it, the more I wonder if ambiguity is a theme as well. It certainly fits the confusing geography.

Even the premise is a little ambiguous. Is/was Olathe a city, a country, a whole planet? Did the apocalypse affect only Olathe, or the whole world? Does it matter in an RPG, where the only world that exists is the one mapped out within the game?

Towards the end of the game, you catch up with Buddy, but she rejects you, apparently resentful that you kept her hidden away for her entire life. Brad presses on anyway, insisting on protecting her.

At that point I wasn’t sure I was still on Brad’s side. But he’s not wrong, either. Is he? Maybe it depends on how old Buddy is — but the game never tells us. Her sprite is a bit smaller than the men’s, but it’s hard to gauge much from small exaggerated sprites, and she might just be shorter. In the beginning of the game, she was doing kid-like drawings, but we don’t know how much time passed after that. Everyone seems to take for granted that she’s capable of bearing children, and she talks like an adult. So is she old enough to be making this decision, or young enough for parent figure Brad to overrule her? What is the appropriate age of agency, anyway, when you’re the last girl/woman left more than a decade after the end of the world?

Can you repopulate a species with only one woman, anyway?


Well, that went on a bit longer than I intended. This game has a lot of small touches that stood out to me, and they all wove together very well.

Should you play it? I have absolutely no idea.

FINAL SCORE: 1 out of 6 chambers

Lisa: The Joyful

fairly short · classic rpg · aug 2015 · lin/mac/win · $5 on itch or steam

Surprise! There’s a third game to round out this trilogy.

Lisa: The Joyful is much shorter, maybe three hours long — enough to be played in a night rather than over the better part of a week.

This one picks up immediately after the end of Painful, with you now playing as Buddy. It takes a drastic turn early on: Buddy decides that, rather than hide from the world, she must conquer it. She sets out to murder all the big bosses and become queen.

The battle system has been inherited from the previous game, but battles are much more straightforward this time around. You can’t recruit any party members; for much of the game, it’s just you and a sword.

There is a catch! Of course.

The catch is that you do not have enough health to survive most boss battles without healing. With no party members, you cannot heal via skills. I don’t think you could buy healing items anywhere, either. You have a few when the game begins, but once you run out, that’s it.

Except… you also have… some Joy. Which restores you to full health and also makes you crit with every hit. And drops off of several enemies.

We didn’t even recognize Joy as a healing item at first, since we never used it in Painful; it’s description simply says that it makes you feel nothing, and we’d assumed the whole point of it was to stave off withdrawal, which Buddy doesn’t experience. Luckily, the game provided a hint in the form of an NPC who offers to switch on easy mode:

What’s that? Bad guys too tough? Not enough jerky? You don’t want to take Joy!? Say no more, you’ve come to the right place!

So the game is aware that it’s unfairly difficult, and it’s deliberately forcing you to take Joy, and it is in fact entirely constructed around this concept. I guess the title is a pretty good hint, too.

I don’t feel quite as strongly about Joyful as I do about Painful. (Admittedly, I was really tired and starting to doze off towards the end of Joyful.) Once you get that the gimmick is to force you to use Joy, the game basically reduces to a moderate-difficulty boss rush. Other than that, the only thing that stood out to me mechanically was that Buddy learns a skill where she lifts her shirt to inflict flustered as a status effect — kind of a lingering echo of how outrageous the previous game could be.

You do get a healthy serving of plot, which is nice and ties a few things together. I wouldn’t say it exactly wraps up the story, but it doesn’t feel like it’s missing anything either; it’s exactly as murky as you’d expect.

I think it’s worth playing Joyful if you’ve played Painful. It just didn’t have the same impact on me. It probably doesn’t help that I don’t like Buddy as a person. She seems cold, violent, and cruel. Appropriate for the world and a product of her environment, I suppose.

FINAL SCORE: 300 Mags

MOOP

fairly short · inventory game · nov 2017 · win · free on itch

Finally, as something of a palate cleanser, we have MOOP: a delightful and charming little inventory game.

I don’t think “inventory game” is a real genre, but I mean the kind of game where you go around collecting items and using them in the right place. Puzzle-driven, but with “puzzles” that can largely be solved by simply trying everything everywhere. I’d put a lot of point and click adventures in the same category, despite having a radically different interface. Is that fair? Yes, because it’s my blog.

MOOP was almost certainly also made in RPG Maker, but it breaks the mold in a very different way by not being an RPG. There are no battles whatsoever, only interactions on the overworld; you progress solely via dialogue and puzzle-solving. Examining something gives you a short menu of verbs — use, talk, get — reminiscent of interactive fiction, or perhaps the graphical “adventure” games that took inspiration from interactive fiction. (God, “adventure game” is the worst phrase. Every game is an adventure! It doesn’t mean anything!)

Everything about the game is extremely chill. I love the monochrome aesthetic combined with a large screen resolution; it feels like I’m peeking into an alternate universe where the Game Boy got bigger but never gained color. I played halfway through the game before realizing that the protagonist (Moop) doesn’t have a walk animation; they simply slide around. Somehow, it works.

The puzzles are a little clever, yet low-pressure; the world is small enough that you can examine everything again if you get stuck, and there’s no way to lose or be set back. The music is lovely, too. It just feels good to wander around in a world that manages to make sepia look very pretty.

The story manages to pack a lot into a very short time. It’s… gosh, I don’t know. It has a very distinct texture to it that I’m not sure I’ve seen before. The plot weaves through several major events that each have very different moods, and it moves very quickly — but it’s well-written and doesn’t feel rushed or disjoint. It’s lighthearted, but takes itself seriously enough for me to get invested. It’s fucking witchcraft.

I think there was even a non-binary character! Just kinda nonchalantly in there. Awesome.

What a happy, charming game. Play if you would like to be happy and charmed.

FINAL SCORE: 1 waxing moon

Implementing Dynamic ETL Pipelines Using AWS Step Functions

Post Syndicated from Tara Van Unen original https://aws.amazon.com/blogs/compute/implementing-dynamic-etl-pipelines-using-aws-step-functions/

This post contributed by:
Wangechi Dole, AWS Solutions Architect
Milan Krasnansky, ING, Digital Solutions Developer, SGK
Rian Mookencherry, Director – Product Innovation, SGK

Data processing and transformation is a common use case you see in our customer case studies and success stories. Often, customers deal with complex data from a variety of sources that needs to be transformed and customized through a series of steps to make it useful to different systems and stakeholders. This can be difficult due to the ever-increasing volume, velocity, and variety of data. Today, data management challenges cannot be solved with traditional databases.

Workflow automation helps you build solutions that are repeatable, scalable, and reliable. You can use AWS Step Functions for this. A great example is how SGK used Step Functions to automate the ETL processes for their client. With Step Functions, SGK has been able to automate changes within the data management system, substantially reducing the time required for data processing.

In this post, SGK shares the details of how they used Step Functions to build a robust data processing system based on highly configurable business transformation rules for ETL processes.

SGK: Building dynamic ETL pipelines

SGK is a subsidiary of Matthews International Corporation, a diversified organization focusing on brand solutions and industrial technologies. SGK’s Global Content Creation Studio network creates compelling content and solutions that connect brands and products to consumers through multiple assets including photography, video, and copywriting.

We were recently contracted to build a sophisticated and scalable data management system for one of our clients. We chose to build the solution on AWS to leverage advanced, managed services that help to improve the speed and agility of development.

The data management system served two main functions:

  1. Ingesting a large amount of complex data to facilitate both reporting and product funding decisions for the client’s global marketing and supply chain organizations.
  2. Processing the data through normalization and applying complex algorithms and data transformations. The system goal was to provide information in the relevant context—such as strategic marketing, supply chain, product planning, etc. —to the end consumer through automated data feeds or updates to existing ETL systems.

We were faced with several challenges:

  • Output data that needed to be refreshed at least twice a day to provide fresh datasets to both local and global markets. That constant data refresh posed several challenges, especially around data management and replication across multiple databases.
  • The complexity of reporting business rules that needed to be updated on a constant basis.
  • Data that could not be processed as contiguous blocks of typical time-series data. The measurement of the data was done across seasons (that is, combination of dates), which often resulted with up to three overlapping seasons at any given time.
  • Input data that came from 10+ different data sources. Each data source ranged from 1–20K rows with as many as 85 columns per input source.

These challenges meant that our small Dev team heavily invested time in frequent configuration changes to the system and data integrity verification to make sure that everything was operating properly. Maintaining this system proved to be a daunting task and that’s when we turned to Step Functions—along with other AWS services—to automate our ETL processes.

Solution overview

Our solution included the following AWS services:

  • AWS Step Functions: Before Step Functions was available, we were using multiple Lambda functions for this use case and running into memory limit issues. With Step Functions, we can execute steps in parallel simultaneously, in a cost-efficient manner, without running into memory limitations.
  • AWS Lambda: The Step Functions state machine uses Lambda functions to implement the Task states. Our Lambda functions are implemented in Java 8.
  • Amazon DynamoDB provides us with an easy and flexible way to manage business rules. We specify our rules as Keys. These are key-value pairs stored in a DynamoDB table.
  • Amazon RDS: Our ETL pipelines consume source data from our RDS MySQL database.
  • Amazon Redshift: We use Amazon Redshift for reporting purposes because it integrates with our BI tools. Currently we are using Tableau for reporting which integrates well with Amazon Redshift.
  • Amazon S3: We store our raw input files and intermediate results in S3 buckets.
  • Amazon CloudWatch Events: Our users expect results at a specific time. We use CloudWatch Events to trigger Step Functions on an automated schedule.

Solution architecture

This solution uses a declarative approach to defining business transformation rules that are applied by the underlying Step Functions state machine as data moves from RDS to Amazon Redshift. An S3 bucket is used to store intermediate results. A CloudWatch Event rule triggers the Step Functions state machine on a schedule. The following diagram illustrates our architecture:

Here are more details for the above diagram:

  1. A rule in CloudWatch Events triggers the state machine execution on an automated schedule.
  2. The state machine invokes the first Lambda function.
  3. The Lambda function deletes all existing records in Amazon Redshift. Depending on the dataset, the Lambda function can create a new table in Amazon Redshift to hold the data.
  4. The same Lambda function then retrieves Keys from a DynamoDB table. Keys represent specific marketing campaigns or seasons and map to specific records in RDS.
  5. The state machine executes the second Lambda function using the Keys from DynamoDB.
  6. The second Lambda function retrieves the referenced dataset from RDS. The records retrieved represent the entire dataset needed for a specific marketing campaign.
  7. The second Lambda function executes in parallel for each Key retrieved from DynamoDB and stores the output in CSV format temporarily in S3.
  8. Finally, the Lambda function uploads the data into Amazon Redshift.

To understand the above data processing workflow, take a closer look at the Step Functions state machine for this example.

We walk you through the state machine in more detail in the following sections.

Walkthrough

To get started, you need to:

  • Create a schedule in CloudWatch Events
  • Specify conditions for RDS data extracts
  • Create Amazon Redshift input files
  • Load data into Amazon Redshift

Step 1: Create a schedule in CloudWatch Events
Create rules in CloudWatch Events to trigger the Step Functions state machine on an automated schedule. The following is an example cron expression to automate your schedule:

In this example, the cron expression invokes the Step Functions state machine at 3:00am and 2:00pm (UTC) every day.

Step 2: Specify conditions for RDS data extracts
We use DynamoDB to store Keys that determine which rows of data to extract from our RDS MySQL database. An example Key is MCS2017, which stands for, Marketing Campaign Spring 2017. Each campaign has a specific start and end date and the corresponding dataset is stored in RDS MySQL. A record in RDS contains about 600 columns, and each Key can represent up to 20K records.

A given day can have multiple campaigns with different start and end dates running simultaneously. In the following example DynamoDB item, three campaigns are specified for the given date.

The state machine example shown above uses Keys 31, 32, and 33 in the first ChoiceState and Keys 21 and 22 in the second ChoiceState. These keys represent marketing campaigns for a given day. For example, on Monday, there are only two campaigns requested. The ChoiceState with Keys 21 and 22 is executed. If three campaigns are requested on Tuesday, for example, then ChoiceState with Keys 31, 32, and 33 is executed. MCS2017 can be represented by Key 21 and Key 33 on Monday and Tuesday, respectively. This approach gives us the flexibility to add or remove campaigns dynamically.

Step 3: Create Amazon Redshift input files
When the state machine begins execution, the first Lambda function is invoked as the resource for FirstState, represented in the Step Functions state machine as follows:

"Comment": ” AWS Amazon States Language.", 
  "StartAt": "FirstState",
 
"States": { 
  "FirstState": {
   
"Type": "Task",
   
"Resource": "arn:aws:lambda:xx-xxxx-x:XXXXXXXXXXXX:function:Start",
    "Next": "ChoiceState" 
  } 

As described in the solution architecture, the purpose of this Lambda function is to delete existing data in Amazon Redshift and retrieve keys from DynamoDB. In our use case, we found that deleting existing records was more efficient and less time-consuming than finding the delta and updating existing records. On average, an Amazon Redshift table can contain about 36 million cells, which translates to roughly 65K records. The following is the code snippet for the first Lambda function in Java 8:

public class LambdaFunctionHandler implements RequestHandler<Map<String,Object>,Map<String,String>> {
    Map<String,String> keys= new HashMap<>();
    public Map<String, String> handleRequest(Map<String, Object> input, Context context){
       Properties config = getConfig(); 
       // 1. Cleaning Redshift Database
       new RedshiftDataService(config).cleaningTable(); 
       // 2. Reading data from Dynamodb
       List<String> keyList = new DynamoDBDataService(config).getCurrentKeys();
       for(int i = 0; i < keyList.size(); i++) {
           keys.put(”key" + (i+1), keyList.get(i)); 
       }
       keys.put(”key" + T,String.valueOf(keyList.size()));
       // 3. Returning the key values and the key count from the “for” loop
       return (keys);
}

The following JSON represents ChoiceState.

"ChoiceState": {
   "Type" : "Choice",
   "Choices": [ 
   {

      "Variable": "$.keyT",
     "StringEquals": "3",
     "Next": "CurrentThreeKeys" 
   }, 
   {

     "Variable": "$.keyT",
    "StringEquals": "2",
    "Next": "CurrentTwooKeys" 
   } 
 ], 
 "Default": "DefaultState"
}

The variable $.keyT represents the number of keys retrieved from DynamoDB. This variable determines which of the parallel branches should be executed. At the time of publication, Step Functions does not support dynamic parallel state. Therefore, choices under ChoiceState are manually created and assigned hardcoded StringEquals values. These values represent the number of parallel executions for the second Lambda function.

For example, if $.keyT equals 3, the second Lambda function is executed three times in parallel with keys, $key1, $key2 and $key3 retrieved from DynamoDB. Similarly, if $.keyT equals two, the second Lambda function is executed twice in parallel.  The following JSON represents this parallel execution:

"CurrentThreeKeys": { 
  "Type": "Parallel",
  "Next": "NextState",
  "Branches": [ 
  {

     "StartAt": “key31",
    "States": { 
       “key31": {

          "Type": "Task",
        "InputPath": "$.key1",
        "Resource": "arn:aws:lambda:xx-xxxx-x:XXXXXXXXXXXX:function:Execution",
        "End": true 
       } 
    } 
  }, 
  {

     "StartAt": “key32",
    "States": { 
     “key32": {

        "Type": "Task",
       "InputPath": "$.key2",
         "Resource": "arn:aws:lambda:xx-xxxx-x:XXXXXXXXXXXX:function:Execution",
       "End": true 
      } 
     } 
   }, 
   {

      "StartAt": “key33",
       "States": { 
          “key33": {

                "Type": "Task",
             "InputPath": "$.key3",
             "Resource": "arn:aws:lambda:xx-xxxx-x:XXXXXXXXXXXX:function:Execution",
           "End": true 
       } 
     } 
    } 
  ] 
} 

Step 4: Load data into Amazon Redshift
The second Lambda function in the state machine extracts records from RDS associated with keys retrieved for DynamoDB. It processes the data then loads into an Amazon Redshift table. The following is code snippet for the second Lambda function in Java 8.

public class LambdaFunctionHandler implements RequestHandler<String, String> {
 public static String key = null;

public String handleRequest(String input, Context context) { 
   key=input; 
   //1. Getting basic configurations for the next classes + s3 client Properties
   config = getConfig();

   AmazonS3 s3 = AmazonS3ClientBuilder.defaultClient(); 
   // 2. Export query results from RDS into S3 bucket 
   new RdsDataService(config).exportDataToS3(s3,key); 
   // 3. Import query results from S3 bucket into Redshift 
    new RedshiftDataService(config).importDataFromS3(s3,key); 
   System.out.println(input); 
   return "SUCCESS"; 
 } 
}

After the data is loaded into Amazon Redshift, end users can visualize it using their preferred business intelligence tools.

Lessons learned

  • At the time of publication, the 1.5–GB memory hard limit for Lambda functions was inadequate for processing our complex workload. Step Functions gave us the flexibility to chunk our large datasets and process them in parallel, saving on costs and time.
  • In our previous implementation, we assigned each key a dedicated Lambda function along with CloudWatch rules for schedule automation. This approach proved to be inefficient and quickly became an operational burden. Previously, we processed each key sequentially, with each key adding about five minutes to the overall processing time. For example, processing three keys meant that the total processing time was three times longer. With Step Functions, the entire state machine executes in about five minutes.
  • Using DynamoDB with Step Functions gave us the flexibility to manage keys efficiently. In our previous implementations, keys were hardcoded in Lambda functions, which became difficult to manage due to frequent updates. DynamoDB is a great way to store dynamic data that changes frequently, and it works perfectly with our serverless architectures.

Conclusion

With Step Functions, we were able to fully automate the frequent configuration updates to our dataset resulting in significant cost savings, reduced risk to data errors due to system downtime, and more time for us to focus on new product development rather than support related issues. We hope that you have found the information useful and that it can serve as a jump-start to building your own ETL processes on AWS with managed AWS services.

For more information about how Step Functions makes it easy to coordinate the components of distributed applications and microservices in any workflow, see the use case examples and then build your first state machine in under five minutes in the Step Functions console.

If you have questions or suggestions, please comment below.

Glenn’s Take on re:Invent 2017 – Part 3

Post Syndicated from Glenn Gore original https://aws.amazon.com/blogs/architecture/glenns-take-on-reinvent-2017-part-3/

Glenn Gore here, Chief Architect for AWS. I was in Las Vegas last week — with 43K others — for re:Invent 2017. I checked in to the Architecture blog here and here with my take on what was interesting about some of the bigger announcements from a cloud-architecture perspective.

In the excitement of so many new services being launched, we sometimes overlook feature updates that, while perhaps not as exciting as Amazon DeepLens, have significant impact on how you architect and develop solutions on AWS.

Amazon DynamoDB is used by more than 100,000 customers around the world, handling over a trillion requests every day. From the start, DynamoDB has offered high availability by natively spanning multiple Availability Zones within an AWS Region. As more customers started building and deploying truly-global applications, there was a need to replicate a DynamoDB table to multiple AWS Regions, allowing for read/write operations to occur in any region where the table was replicated. This update is important for providing a globally-consistent view of information — as users may transition from one region to another — or for providing additional levels of availability, allowing for failover between AWS Regions without loss of information.

There are some interesting concurrency-design aspects you need to be aware of and ensure you can handle correctly. For example, we support the “last writer wins” reconciliation where eventual consistency is being used and an application updates the same item in different AWS Regions at the same time. If you require strongly-consistent read/writes then you must perform all of your read/writes in the same AWS Region. The details behind this can be found in the DynamoDB documentation. Providing a globally-distributed, replicated DynamoDB table simplifies many different use cases and allows for the logic of replication, which may have been pushed up into the application layers to be simplified back down into the data layer.

The other big update for DynamoDB is that you can now back up your DynamoDB table on demand with no impact to performance. One of the features I really like is that when you trigger a backup, it is available instantly, regardless of the size of the table. Behind the scenes, we use snapshots and change logs to ensure a consistent backup. While backup is instant, restoring the table could take some time depending on its size and ranges — from minutes to hours for very large tables.

This feature is super important for those of you who work in regulated industries that often have strict requirements around data retention and backups of data, which sometimes limited the use of DynamoDB or required complex workarounds to implement some sort of backup feature in the past. This often incurred significant, additional costs due to increased read transactions on their DynamoDB tables.

Amazon Simple Storage Service (Amazon S3) was our first-released AWS service over 11 years ago, and it proved the simplicity and scalability of true API-driven architectures in the cloud. Today, Amazon S3 stores trillions of objects, with transactional requests per second reaching into the millions! Dealing with data as objects opened up an incredibly diverse array of use cases ranging from libraries of static images, game binary downloads, and application log data, to massive data lakes used for big data analytics and business intelligence. With Amazon S3, when you accessed your data in an object, you effectively had to write/read the object as a whole or use the range feature to retrieve a part of the object — if possible — in your individual use case.

Now, with Amazon S3 Select, an SQL-like query language is used that can work with delimited text and JSON files, as well as work with GZIP compressed files. We don’t support encryption during the preview of Amazon S3 Select.

Amazon S3 Select provides two major benefits:

  • Faster access
  • Lower running costs

Serverless Lambda functions, where every millisecond matters when you are being charged, will benefit greatly from Amazon S3 Select as data retrieval and processing of your Lambda function will experience significant speedups and cost reductions. For example, we have seen 2x speed improvement and 80% cost reduction with the Serverless MapReduce code.

Other AWS services such as Amazon Athena, Amazon Redshift, and Amazon EMR will support Amazon S3 Select as well as partner offerings including Cloudera and Hortonworks. If you are using Amazon Glacier for longer-term data archival, you will be able to use Amazon Glacier Select to retrieve a subset of your content from within Amazon Glacier.

As the volume of data that can be stored within Amazon S3 and Amazon Glacier continues to scale on a daily basis, we will continue to innovate and develop improved and optimized services that will allow you to work with these magnificently-large data sets while reducing your costs (retrieval and processing). I believe this will also allow you to simplify the transformation and storage of incoming data into Amazon S3 in basic, semi-structured formats as a single copy vs. some of the duplication and reformatting of data sometimes required to do upfront optimizations for downstream processing. Amazon S3 Select largely removes the need for this upfront optimization and instead allows you to store data once and process it based on your individual Amazon S3 Select query per application or transaction need.

Thanks for reading!

Glenn contemplating why CSV format is still relevant in 2017 (Italy).

GoMovies/123Movies Launches Anime Streaming Site

Post Syndicated from Ernesto original https://torrentfreak.com/gomovies123movies-launches-anime-streaming-site-171204/

Pirate video streaming sites are booming. Their relative ease of use through on-demand viewing makes them a viable alternative to P2P file-sharing, which traditionally dominated the piracy arena.

The popular movie streaming site GoMovies, formerly known as 123movies, is one of the most-used streaming sites. Despite the rebranding and several domain changes, it has built a steady base of millions of users over the past year and a half.

And it’s not done yet, we learn today.

The site, currently operating from the Gostream.is domain name, recently launched a new spinoff targeting anime fans. Animehub.to is currently promoted on GoMovies and the site’s operators aim to turn it into the leading streaming site for anime content.

Animehub.to

Someone connected to GoMovies told us that they’ve received a lot of requests from users to add anime content. Anime has traditionally been a large niche on file-sharing sites and the same is true on streaming platforms.

Technically speaking, GoMovies could have easily filled up the original site with anime content, but the owners prefer a different outlet.

With a separate anime site, they hope to draw in more visitors, TorrentFreak was told by an insider. For one, this makes it possible to rank better in search engines. It also allows the operators to cater specifically to the anime audience, with anime specific categories and release schedules.

Anime copyright holders will not be pleased with the new initiative, that’s for sure, but GoMovies is not new to legal pressure.

Earlier this year the US Ambassador to Vietnam called on the local Government to criminally prosecute people behind 123movies, the previous iteration of the site. In addition, the MPAA reported the site to the US Government in its recent overview of notorious pirate sites.

Pressure or not, it appears that GoMovies has no intention of slowing down or changing its course, although we’ve heard that yet another rebranding is on the horizon.

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

Mozilla releases its speech-recognition system

Post Syndicated from corbet original https://lwn.net/Articles/740611/rss

Mozilla has announced
the initial releases from its “Project DeepSpeech” and “Project Common
Voice” efforts. “I’m excited to announce the initial release of
Mozilla’s open source speech recognition model that has an accuracy
approaching what humans can perceive when listening to the same
recordings. We are also releasing the world’s second largest publicly
available voice dataset, which was contributed to by nearly 20,000 people
globally.