Altoros Labs

The goal: SwanPowers, LLC turned to Altoros to apply best practices in cloud and Ruby development to their existing system in order to satisfy the high requirements to the level of concurrency, load, response times, etc.

As a result, Having analyzed the infrastructure, software architecture, and application code, we were able to implement improvements that have resolved all the issues mentioned above. The optimization included reconfiguring the Amazon EC2 instances, implementing a Redis pub/sub mechanism to decouple jobs from DB operations, managing social networks quotas internally, so that the application would never exceed the allowed number of requests, and much more.

The application’s overall uptime and performance have been improved significantly. Taking into account the LikeFolio’s focus on social networks, Altoros made sure that it complies with the required API quota/limits.

Technology stack:

Server Platform - Amazon Web services (EC2, Route 53, CloudWatch, RDS), Redis
Technologies - Ruby on Rails, Sidekiq, Capistrano
Programming Language - Ruby

For more information, feel free to contact us [email protected]

The customeris National Settlement Depository (NSD), Russia’s largest securities depository.

The goal was to develop a blockchain-powered prototype platform for issuing bonds. The solution was to connect three parties: NSD (the depository), MegaFon (the bond issuer), and Raiffeisenbank Russia (the investor). Along with automation of bond placement and accounting, the system should minimize risks of reconciliation, ensure transparency, and comply with government regulations.

As a result, the solution automates the issuing of bonds worth $10M, ensures transaction confidentiality, maintains secure cross-datacenter communication, and validates compliance with government regulations due to integration with a third-party service.

For more information, feel free to contact us [email protected]

The goal: The system is an innovative augmented reality application that recognizes visual objects and enables consumers to find information about what they see on a TV screen, billboards, or anywhere else right in the moment. 

As a result, to improve the availability and performance of the system, the team suggested dividing the stored data into two groups and keep images separately from the text descriptions. The indexed text data is stored in a new database with a fast search.

Altoros’s engineers also helped to setup and manage a computing cluster that was hosted in the Profitbricks virtual environment. This SaaS solution was selected because of its live vertical scaling feature. Currently the system is being tested under different types of tasks to identify the maximum load it can deal with. If necessary, a number of improvements will be made to reach a response time of 1 second for 1,000 concurrent users.

Technology stack:

Server Platform - Ubuntu 12.04.2
Programming Languages - Java
Databases - MongoDB

For more information, feel free to contact us [email protected]

The goal: The customer turned to Altoros to improve its biotechnology system that analyzes DNA samples for mutations in the early stages. The legacy tool was able to de-duplicate only 1,000 samples maximum—due to memory and CPU limitations—and it still took hours (or even days) to process the pipeline. The goal was to fix performance bottlenecks as well as enable linear scalability for processing 10,000+ biosamples at a time.

As a result: Altoros has delivered a highly scalable analytical system for de-duplication of genome samples — as a part of the customer’s analytical platform. Thousands of hospitals and laboratories worldwide use the system to detect DNA mutations, saving thousands of lives. The analysis takes minutes now, not hours; it allows for processing 10x more genome samples—compared to the performance of the legacy system.

Altoros’s engineers have also proposed a reference architecture for updating a reporting solution. Inspired by our recommendations, the customer went on improving the system with open-source data analytics technologies, which will eventually allow for saving thousands of dollars.

Technology stack:

Server Platform - Linux
Programming Languages - Java, Perl
Technologies - Apache Hadoop (Cloudera CDH 5.2.1), MapReduce, Apache Spark (Spark SQL), bash

For more information, feel free to contact us [email protected]

The customer: Toyota, one of the leading companies in the automobile industry.

The goal: Toyota turned to Altoros to develop the system for holding and managing tenders. The application had to automate the selection of a vendor (goods/parts) and services according to the key parameters.

As a result, Altoros .NET development team created the system that enables users to upload the tender conditions and a list of the possible participants for further processing. The system automatically generates separate templates for participation that are sent out to each vendor.

Additionally, Altoros developed other automation systems and subsystems for Toyota: the generator of reports based on the entered parameters (previously, it was done manually), the system for viewing files of rare formats for the corporate application, the subsystem for managing draft approvals, and some other.

Technology stack:

Technologies - .NET 3.5, VSTO 2005, XML
Programming Language - C#
Software Type - Business function specific software

For more information, feel free to contact us [email protected]

The goal: A warehousing solution for real-time workload monitoring that consists of a Client-Server administration part, a Web portal for remote partners and agents, and a mobile client for warehouse workers.

As a result, The customer focused on in-house resources on core strategic business activities, while Altoros managed the software product life cycle. The company now sells Effect Warehouse to small and medium-sized warehouses. The software product developed by Altoros is steadily gaining popularity as it pays off very quickly. Better productivity, almost 100 % balance accuracy, and improved quality of process selection result in considerable savings. The effects of real-time workload monitoring, traceability, and shorter lead-times are vital improvements to the warehousing business.

Technology stack:
Technologies - .NET 3.5 / 2.0, .NET CF 2.0 / 1.0, ASP.NET, SCSF, CAB, MS Enterprise Library, AJAX, Hibernate, LINQ
Programming Language - C# 1.0 / 2.0 / 3.5, C++

For more information, feel free to contact us [email protected]