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• Inter-bank transfer systems (see a research paper by Narula et al.)
• Privacy-focused management of digital assets (see a proof of concept by J.P. Morgan and zCash)
• KYC (see a proof of concept by ING)
• Self-sovereign identity (see an attribute-based credentials EU project)
• Voting (see a proxy voting prototype by Russian National Security Depository)

• Average DDoS attack duration dropped to 2.5 hours;
• During 2018, the capability appeared for attacks at hundreds of gigabits-per-second within a country or region, bringing us to the verge of “quantum theory of bandwidth relativity”;
• The frequency of DDoS attacks continues to grow;
• The continuing growth of HTTPS-enabled (SSL) attacks;
• PC is dead: most of the legitimate traffic today comes from smartphones, which is a challenge for DDoS actors today and would be the next challenge for DDoS mitigation companies;
• BGP finally became an attack vector, 2 years later than we expected;
• DNS manipulation has become the most damaging attack vector;
• Other new amplification vectors are possible, like memcached & CoAP;
• There are no more “safe industries” that are invulnerable to cyberattacks of any kind.

This article contains a brief squeeze from my own experience and that of my colleagues, with whom I had been fighting incidents day and night. And many incidents would never have occurred if all these microservices that we love so much were written at least a little more carefully.

Unfortunately, some programmers seriously believe that a Dockerfile with any team at all inside is a microservice in itself and can be deployed even now. Dockers are running — money are incoming. This approach turns into problems starting from performance degradation, inability to debug, service failures and ending in a nightmare called Data Inconsistency.

If you feel that the time has come to launch one more app in Kubernetes / ECS / whatever, then I have something to object to.

Hi, I'm one of the developers of the sharded blockchain Near Protocol, and in this article want to talk about what blockchain sharding is, how it is implemented, and what problems exist in blockchain sharding designs.

It is well-known that Ethereum, the most used general purpose blockchain at the time of this writing, can only process less than 20 transactions per second on the main chain. This limitation, coupled with the popularity of the network, leads to high gas prices (the cost of executing a transaction on the network) and long confirmation times; despite the fact that at the time of this writing a new block is produced approximately every 10–20 seconds the average time it actually takes for a transaction to be added to the blockchain is 1.2 minutes, according to ETH Gas Station. Low throughput, high prices, and high latency all make Ethereum not suitable to run services that need to scale with adoption.

If you are working with Kubernetes environment then you probably make use of several existing templating tools, some of them being a part of package managers such as Helm or Ksonnet, or just templating languages (Jinja2, Go template etc.). All of them have their own drawbacks as well as advantages and we are going to go through them and write our own tool that will try to combine the best features.

I'd like to share my story about migration monolith application into microservices. Please, keep in mind that it was during 2012 — 2014. It is transcription of my presentation at dotnetconf(RU). I'm going to share a story about changing every part of the infrastructure.

Monitoring is the most important part of your infrastructure. Monitoring is system engineers basics. However, everyone has his own way to understand it. My way consist of denial. anger & acceptance.

The module was created as a part of my master thesis in the 2010 year. The master thesis theme is Keylogging in Linux kernel. The main idea was to find out a way to intercept system calls for x64 arch Linux kernel, especially for kernel 2.6.34.7-61.fc13.x86_64.

It is text version of the presentation 2018-04-25 at Saint-Petersburg Linux User Group. Configuration example locates at https://github.com/ultral/ansible-role-testing

I suppose that that you make configuration management, not bash. It means that you have to test it some how. Have you ever tested ansible roles? How do you do it?

Russian version

Let's imagine that you are developing software and hardware appliance. The appliance consists of custom OS distributive, upscale servers, a lot of business logic, as a result, it has to use real hardware. If you release broken appliance, your users will not be happy. How to do stable releases?

I'd like to share my story how we dealt with it.