Secondly, are you saying that bitcoin exists solely for the purpose of money laundering and tax evasion?

I personally tend to think that in the vast majority of cases govt spending of tax money does more for the greater good than whatever a self-appointed authority would. There are many exception to this, but I still think this is largely true in democracies. But then again I tend to identify as a social-democrat.

People there will happily pay 60% tax if they get even Rome level of infrastructure access

So, it's no brainer a lot of them move their money offshore.

Edit: people who feel they are not getting fair share of their infra quality, with this line of thinking will move money aboard doesn't matter if it's ethical/legal thing to do or not.

As an aside, I also find the non-recursive, breadth-first, form easy to derive thru a process of code transformations of the depth-first form; explanations that start breadth-first are somewhat bewildering

[1] https://cnx.org/contents/ulXtQbN7@15/Implementing-FFTs-in-Pr...

Check this out (javascript):

  function permute1(x) { 
      if (x.length == 1) return x;
      let even = [];
      let odd = []; 
      for (let i = 0; i < x.length; i += 2) { 
           even[i / 2] = x[i];
           odd[i / 2] = x[i + 1];
      }
      return [].concat(permute1(even), permute1(odd));
  }

  function permute2(x, offset, stride) {
      if (!offset) offset = 0;
      if (!stride) stride = 1;
      if (stride >= x.length) return [x[offset]];
      return [].concat(permute2(x, offset, stride * 2), permute2(x, offset + stride, stride * 2));
  }
  
  function permute3(x) {
      let result = [];
      for (let i = 0; i < x.length; i++) {
          let k = i;
          // pretend 32-bit ints
          k = ((k >> 1) & 0x55555555) | ((k & 0x55555555) << 1);
          k = ((k >> 2) & 0x33333333) | ((k & 0x33333333) << 2);
          k = ((k >> 4) & 0x0F0F0F0F) | ((k & 0x0F0F0F0F) << 4);
          k = ((k >> 8) & 0x00FF00FF) | ((k & 0x00FF00FF) << 8);
          k = ( k >> 16             ) | ( k               << 16); 
          k = k >> (64 - Math.log2(x.length));
          if (k < 0) k += x.length; // fix up due to signed ints
          result[i] = x[k];
      }
      return result;
  }

edit: also, i think i may have misunderstood the relationship between your js version and your lambdatalk version. They seem to be the same to me?

Yes there is a relationship between the JS version and its translation into lambdatalk. My project is to replace the array based version by a list based version so that I can replace in this page http://lambdaway.free.fr/lambdaspeech/?view=PLR the inefficient unary numeration based implementation of numbers (using standard Church numbers or just lists) by a decimal position numeration. Standard multiplication of words seen as polynoms being O(n^2) I need to go further and implement fast multiplication. So my interest in FFT.

As you could see in http://lambdaway.free.fr/lambdaspeech/meca/JS.js, the lambdatalk's interpreter is a regular expression window running on the code (not an AST) and replacing in situ expressions by their values. A kind of Turing machine. I like the idea of overcoming limits of JS numbers using nothing but words and simple substitutions on words.

For database, we use RDS/Dynamodb

Redis for cache.

Dynamodb is better in cases where we want to localize the latency of our regional lambdas.

RDS for everything else like dashboard entity storage etc..

Cloudwatch prints logs, kinesis takes the log to s3 where it's transformed in batches with lambda then data is moved to Redshift. Redshift for stats/reports.

Converted whole ad network to Serverless. Used Rust Lambda runtime for CPU intensive tasks.

Using Go for the rest of the Lambdas.

I love Go and Rust and optimizing just one Lambda at a time brought back the programme joy in my life

Used Apex+Terrform to manage whole infra for the ad network.

We managed to deploy Lambda in all AWS regions ensuring minium latency for the ad viewers.

The thing which took over 50 (tech side only) person team, now takes 10 people to run the whole ad network.

Network is doing 20M profit per year/9 billion clicks per day.

It's my greatest achievement so far because we made it from scratch without any investor money.

But one the other side, we'll have to shrink our team size next year as growth opportunity is limited and we want to optimize efficiency further.

I'm currently planing to write a book about AWS. It should teach people how to build their MVPs without restricting themselves in the future.

Are you available for an interview in January?

I think I'll put up a small splashpage for email gathering in the next days to keep people up to date :)

I'll start gathering informations in January, feel free to share this form.

50 person team to run an adnetwork on tech side only? I am really curious why did it take that many people before going to Lambdas. We are in the adtech space also and there is a 5 persons team (on-call ops+2 devs) to run our own datacollection, third party data providers, RTB doing half a million QPS and own adservers doing hundreds of millions of impressions daily.

Think about drilldown to 3 level, based on device, os, placement, country, ISP etc... along with click stats per variable.

I've never used elastic search for this.

Before that used bigquery but every query takes atleast 2 seconds.

So we had to move to a dedicated redshift cluster.

Quoting myself:

> unless you were huge enough to have your own locations

Those locations are millions, sometimes hundreds of millions of dollars investments with backup power generators large enough to provide power to a comfortably sized village. So, "large enough to a) need and b) able to afford owning such a location just for your own needs", e.g. Google, Amazon. Even companies like large banks have their servers co-hosted in a separate section but in the location owned by a 3rd party co-hosting provider. To own one you either are one of those providers or you are in the "Google tier". For the purposes of the current context, the linked article, one would even need to have multiple such locations all over the world. I think that qualifies as "huge" (the company owning such infrastructure just to run their own servers, co-hosting firms do it for others).

Cloud has talent working in the background on AWS's payroll, they've better ability too hire at scale than what we can do.

So decided to use them, no we don't regret. It's a more reliable cost then hiring and managing a team which might prove to be less reliable.

Loadbalancer is shared across the user accounts, so amazon has to stop the ddos.

They've very effective network level ddos detector/filtering

Once you have setup Lambda in one region

You just need to loop through the list of regions and deploy your lambda in ALL AVAILABLE REGIONS. Yes, it's that simple!

API gateway doesn't charge for 4xx response, so it's very good for defying level 7 ddos too.

Add cognito and use lambda authorizer, it generates API keys and emails it to your users.

Add a Latency Based DNS routing using route 53 on top and you ensure minium latency in all regions!

This rules out small clouds for us.

So, we use GCP Azure AWS exclusively because of their ability to defy network level ddos.

Why? Mostly because of cost and it seemed simple than building out stuff on cloud services.

Every Friday night, our services got ddosed by our competitors.

Provider would nullroute our IPs and our service goes down

We struggled with it a lot since we were not big enough to afford a premium ddos solution.

Once we realized that big cloud like aws, gcp do not suffer from this, we had to make a switch.

When you say GCP, Azure and AWS have the capacity to defy the ddos, what capacity are you reffering to?

Are you talking about actually scaling and serving the bogus requests? Or capacity to have enoough bandwith and firewall power to fend it off?

Shield (https://aws.amazon.com/shield/) is AWS's DDOS protection service. It's free and is basic protection against L3/4 attacks.

Shield Advanced (same URL as above) is a big step up in price, but gives you access to 'improved protection' and a global response team.

Cloudfront (https://aws.amazon.com/cloudfront) is a CDN with global edge locations.

WAF (https://aws.amazon.com/waf) is AWS's web application firewall service. It's less about DDOS and more about specific application attacks, but is part of the whole solution.

For more detail, you can have a look at AWS's DDOS whitepaper: https://d0.awsstatic.com/whitepapers/Security/DDoS_White_Pap...

You probably would have been better off using a cloud mitigator from the start. Their pricing is competitive when you factor in all of the costs.

They've very effective network level ddos detector/filtering

So you're saved then.

I wonder how much DDoS it takes before a cloud provider starts dropping a customer’s packets now. Do they even bother anymore?