Software Used Most Often to Develop Cloud-Based Applications
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To gather insights for DZone's Cloud Research Guide, scheduled for release in April, 2016, we spoke to 28 executives, from 23 companies, who develop and deploy application in the cloud for their own company or for their clients.
Here's who we talked to:
Neeraj Gupta, S.V.P. Product & Engineering, Apcera | Jad Naous, Product Lead, AppDynamics | Ez Natarajan, V.P. Head Cloud Services Business Unit, Beyondsoft | Alon Girmonsky, CEO and Founder, BlazeMeter | Kunal Bharati, Cloud Architect and Nishant Patel, CTO, Built.io | Sacha Labourey, CEO, Cloudbees | Deirdre Mahon, CMO and Fraser McKay, V.P. of Products, Cloud Cruiser | Flint Brenton, CEO, CollabNet | Ali Din, Senior V.P. and CMO and Walid Elemary, V.P. Product Development, dinCloud | Mike Masterson, Director of Strategic Business Development, Dynatrace | Gabe Monroy, CTO and Jasen Hansen, Chief Architect, Engine Yard | Fred Simon, Co-Founder and Chief Architect, JFrog | Jim Frey, V.P. of Products and Ian Pye, Co-Founder and Principal Engineer, Kentik | Johan den Haan, CTO, Mendix | Mounil Patel, V.P. Strategic Field Engagement, Mimecast | Faisal Memon, Product Manager, NGINX | Arvind Mehrotra, President and Global Business Head – Infrastructure Management Services, NIIT Technologies | Jens Eckels, Director, PaaS Business Group, Oracle | Pat Harper, SVP Operations, PGi | Joan Wrabetz, CTO, Quali | Partha Seetala, CTO, Robin Systems | Nick Kephart, Senior Director Product Marketing, ThousandEyes | Kiran Bondalapati, CTO and Co-Founder, ZeroStack.
When we asked these executives "What software do you use most often to develop cloud-based applications?" here's what they told us:
Run in Amazon and IBM public clouds. Support Cassandra, PostgreSQL et. al. – we are software neutral.
All languages (Ruby, Python, Node.js, Java, Clojure, Scala, Play, PHP, Perl, Dart and Go) and everything in a Docker container. We run on-premise or in the cloud.
We're a cloud management platform that is software agnostic.
We started with cloud software to see if we could find software to fit our needs. We ended up building our own apps focused on orchestration built around the needs of our customers.
It depends on the layer of the stack you are working in. Ops is using Chef, Puppet, and Ansible. One level above is using Docker containers. If they’re not using Docker, they’re using virtual machines with EC2 and APIs. Applications include NodeJS, Python, Java. C++ is fading, and Go is growing.
We use our own software to measure and build analytics around the UX to alert the client to issues and the root causes. We identify the problem, pattern replay automation with machine learning and artificial intelligence. We eliminate the noise and provide an accurate signal and diagnose ways to resolve the problem. The scale factor is critically important. How to manage existing data and be ready for smarter, flexible and scalable data.
We have our own; however, we don’t replace what the clients are using, we integrate with it. It's a three legged stool: 1) ALM (application lifecycle management); 2) Virt Con; and 3) Subversion. We support the enterprise version of Git enabling companies to deploy applications as they are built that are secure and scalable. Customers can consume our products as a service, on premise, or both.
We work with products in the insurance space around risk mitigation and underwriting. We redevelop tech migration in Citrix until we move to the cloud and then re-platform in the .Net stack.
We use Google Dremel cluster, similar to Cassandra and other big data solutions. We use Go as our applicant code as well as Node.JS and web stack with a backbone on top.
- Build from scratch using the AWS stack, Elastic Search for analytics, Chef for orchestration, Angular for the UI, the Spring framework, and a spectrum of other technology including 52 micro services. If you don’t want to run on one cloud you can move to another. We are architected to be platform agnostic using Couchbase.
When developing software, we have the identification converted into production implemented by developers. If the steps between development and operations happen manually then it’s not scalable. To launch more frequently you need an automated pipeline. All steps need to be organized in the pipeline. Jenkins implements a repeatable logic that can be automated.
Different technologies. We started with Ruby on Rails and it wasn’t scalable so we rewrote everything in Node.JS. We also use MongoDB for our databases, Redis for caching, and we were an early adopter of Docker almost three years ago before there was a community. We built our own management layer.
Microsoft technologies — .Net, SQL, Python, MySQL, Ruby on Rails, Web Logic. We are migrating front end applications and running a balanced platform.
Use visual process design to design a data model running on Cloud Foundry. We work on the entire lifecycle of an app – operating, use, monitoring, closed-loop.
NGINX was developed by Igor Sysoev in 2002 to handle more traffic without additional hardware.
Tools used include: Java, Ruby on Rails, .Net. We also work on Apple iOS and Google Android. We run on Amazon Hosted Services and Open Stack.
We're a wide, multi-tenant platform using primarily C++ and Java.
SQL, MySQL for transactions and account setting. MongoDB for events related data. Sharding of MySQL by customer account to scale out over time. We support geographic expansion. We’re doing more work that includes Europe. This has increased requirements for data storage and transfer and can add constraints on scaling the data architecture.
Is this consistent with the software you and your organization use to develop and deploy applications in the cloud?
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