Which CI is the fastest?

Vladimir Strakhov - Evrone PMThe developers tested the performance of the most popular CI’s.
29 May 2017   2144
Ruby

A dynamic, open source programming language with a focus on simplicity and productivity.

 

Continuous integration

In software engineering, continuous integration (CI) is the practice of merging all developer working copies to a shared mainline several times a day

Rake - one of the most popular libraries of the programming language Ruby was taken to test the performance of CI. The following results were obtained:

  rake      
   average, sec launch 1 launch 2 launch 3
TravicCI 71 71 68 74
CodeShip 56 53 47 69
Semaphore   failed failed failed
CircleCI 105 108 109 99
Vexor 31 34 30 30
GitlabCI 103 127 95 87

Comparison of the performance of various CIs

I was interested in comparing the speed of different CIs work. But speed is not always the main criteria when choosing CI. System’s services and their price is also very important.

 

Vladimir Strakhov

Evrone.com PM

 

Which CI do you use?

In software engineering, continuous integration (CI) is the practice of merging all developer working copies to a shared mainline several times a day. There are a lot of different continious integration solutions with strong and weak sides.
Take part in the survey of our portal. Which Continuous integration system do you use?

Vexor
37% (11 votes)
CircleCI
23% (7 votes)
Jenkins
17% (5 votes)
TravicCI
10% (3 votes)
GitlabCI
7% (2 votes)
Teamcity
3% (1 vote)
Atlassian Bamboo
3% (1 vote)
Apache Maven
0% (0 votes)
CodeShip
0% (0 votes)
Semaphore
0% (0 votes)
Total votes: 30

Vexor at HighLoad++ 2017

Alexandr Kirillov reported about how to build a cluster to calculate thousands of high-CPU / high-MEM tasks at one of the biggest Russian IT conferences
12 December 2017   4221

The HighLoad++ is professional conference for developers of high-load systems is the key professional event for everyone involved in the creation of large, heavily-frequented, and complex projects.

Main purpose of the event is to exchange knowledge and experience among leading developers of high-performance systems, which support millions of users simultaneously.

Agenda consists of all crucial web development aspects, such as:

  • Large scale architectures,
  • databases and storage systems,
  • system administration,
  • load testing,
  • project maintenance, etc.

This year the conference program will be dazzled with current trends: IoTBlockchainNeural networksArtificial Intelligence, as well as Architecture & Front-end performance.

The 11th HighLoad++ conference took place on the 7th and 8th of November 2017. 

  • 66% of participants work in large companies (of 30+ employees), 
  • 60% earn above the market, 
  • 55% hold leadership positions and have subordinates. 
  • 9% of conference visitors work as technical directors,
  • 12% work as heads of technical departments, and 29% work as lead developers and team leads.

Alexandr Kirillov, CTO at Evrone, had a speech at HighLoad++ 2017 "How to build a cluster to calculate thousands of high-CPU / high-MEM tasks and not go broke"

Alexandr Kirillov at HighLoad++ 2017
Alexandr Kirillov at HighLoad++ 2017
Alexandr Kirillov at HighLoad++ 2017
Alexandr Kirillov at HighLoad++ 2017
Alexandr Kirillov at HighLoad++ 2017
Alexandr Kirillov at HighLoad++ 2017
 

Our project is a cloud-based CI-service, where users run tests of developed projects.
This year the system of auto purchase of our project purchased 37218 machines (Amazon Instances). This allowed us to process 189,488 "tasks" (test runs) of our customers.
 

Tests are always resource-intensive tasks with the maximum consumption of processor capacities and memory. We can not predict how many parallel computations and at what point in time it will be. Before us was the task of building the architecture of the system, which can very quickly increase, as well as rapidly reduce the power of the cluster.
 

All this was complicated by the fact that the resource-intensive calculations did not allow us to use the classic tools AWS or GoogleComputeEngine. We decided to write our own system of automatic scaling, taking into account the requirements of our subject area.
 

Alexandr Kirillov
CTO, Evrone

At his report, Alexandr told about how they designed and built the architecture of the service, which is the system of automatic procurement of machines.

Additionally, he told more about the main architectural blocks of projects that solve similar problems.