Technologies We Use

Technologies

  • Apache, Tomcat, Eclipse
  • Java
  • JavaScript
  • Template engines
  • Unix/Linux
  • Relational Dtabases
  • Perl
  • PHP
  • Subversion
  • Web App Security
  • NoSQL Databases
  • Parallel Processing
  • Distributed Applications
  • Payment Gateways
  • Cloud Technologies

TECHNOLOGIES USED HERE EVERYDAY

THE REGULAR STUFF

MEAN Stack

For Node, the speed of the Javascript runtime, coupled with the event-based parallelism makes it a very powerful serverside platform. After using Java and PHP for many years we started using Node for fullstack development when we started developing mobile apps and web applications using Angular. We have worked with very popular and flexible Express to robust Hapi to develop web applications.

Spring and Spring Boot

When we started working on a microservices architecture for one biggest BFSI company SpingBoot was the obvious choice for the large enterprise applications. With SpringBoot and Netflix’s microservices stack we could implement robust and flexible system architecture.

Python

Python comes with batteries Included. This means that many common tasks can be easily accomplished using just the standard library. The results are productivity and uniformity. For startups, the main advantage of using Python is speed and ease. We have used Python for various embedded and web development projects for startups.

ELK Stack

Having already used Solr in Broadside we were already familiar with search engines. But while exploring potential technologies to design the solution for log repository and analytics system, Bitlogg, we chose ELK stack. Later, we could use the same stack for developing a NOC system as well.

Git

Git helps Agile. It can be integrated into an Agile workflow very easily. It is built for iteration, for breaking down large projects into small issues using its branching model. The lightweight branches allow an Agile team to break each issue onto a separate branch. After using SVN for a decade switching to Git was one of the most significant thing we did to become an agile organization.

PostgreSQL

If your database is architected the right way, PostgreSQL can be scaled to hundreds of thousands of inserts per second, at billions of rows, even on a single node with a modest amount of RAM. With HStore and JSONB PostgreSQL can be used as a NoSQL database as well. GiN and GIST indexes are some of the most flexible index structure to have in an RDBMS. PostgreSQL has become our go-to database. Along with typical web applications we have used PostgreSQL cluster for multiple TBs of data stores for financial data, for storing and indexing geolocations and as a time series data for IoT as well.

THE COOL AND LATEST TECHNOLOGIES USED

THE SPECIAL STUFF

AI/ML

We have worked in this area both to tighten the security vulnerabilities of Web apps we write, and to build systems which can monitor and report on suspicious behaviour in the access patterns of an existing Web application.

NoSQL Databases

We have been using Solar since 2010 in production applications. We are also studying MongoDB and CouchDB for specific applications. We have often used Berkeley DB instead of relational databases for large dataset problems.

Parallel Processing

We regularly use parallel processing in the applications we design and build. This could be as simple as forking Unix processes to share workload, or as sophisticated as PRISM. We have often used multi-threading in Java code.

Distributed Applications

We have built a few systems which required components to execute on separate servers and communicate among themselves. We have sometimes built our own simple message-based communication layer, and have begun to study Java messaging implementations (ActiveMQ, Qpid) recently.

DevOps

We have integrated various Indian online payment gateways with Web applications for our customers. Each payment gateway has its own approach and performance parameters which impact performance.

Microservices Architecture

We have begun developing and deploying applications on IaaS cloud infrastructure. We have been using Amazon EC2/ EBS/ S3 since 2011 for production applications. We are also working on toolsets to manage virtual machine instances on AWS remotely.