At Gandapps we provide a wide range of enterprise solutions such as custom built software, networking infrastructure, computing, data storage and data analytics. Our team of experienced professionals works tirelessly to ensure we provide our clients with updated and secure ict solutions.
Hybrid Enterprise IT Infrastructure
Benefits of this Infrastructure
Time to market. If you have a new application to launch, you can focus on developing features rather than provisioning infrastructure. There is also no lead-time for server purchasing, setup, and configuration. With experience, you could code a proof of concept in a morning and have it running on a cloud server the same afternoon.
Scale. Often, you don't know what kind of load your applications will encounter. You then have to walk the thin line between over provisioning for load that might never materialize and under provisioning, causing performance problems until you can purchase, configure, and deploy additional hardware. With cloud-based infrastructures, you can launch a minimal set of instances and automatically scale the number of instances if the load increases.
Flexibility. With auto-scaling in a cloud-based infrastructure, it is possible to dynamically change the number of server instances. So, if you have a substantial difference between peak loads (times of the day, when special events launch, when ads run, and so on) and average loads, you don't have to provision and pay for enough instances for peak load 24x7.
Simplicity. Architecting and deploying scalable applications in-house require you to handle a lot of complexity. You need to research, select, and configure load balancers; develop solutions for scripting the reconfiguration of IP addresses on hardware failure; design scalable messaging-based e-mail services; and work out how to implement backup and disaster recovery capabilities for critical data. Most cloud providers include proven solutions to these problems that you can use.
Easy testing. When you use a cloud-based infrastructure, you can easily spin up additional instances for either functional or load testing, so you don't have to keep expensive hardware available 24x7 for running tests.
Initial cost. With no capital costs up front, cloud computing also reduces the cost of getting a new project to market, and the hosting costs only become significant if the application is popular. That is a high-quality problem to have.
Recovery. Because of the way you have to architect and develop applications for the cloud, it's usually much easier to handle backing up important data and automated recovery from hardware or network failures.
Accelerate Production with Machine Learning
Computers are still not as sophisticated as the human brain, but there’s been great progress in artificial intelligence (AI) over the last 50 years. In fact, computers can do many things better than humans. Machine learning and the related field of deep learning are the most pragmatic approaches to AI — and both offer striking benefits.
Even as machine-learning datasets continue to grow, deep learning requires orders of magnitude more data to train models — which, in turn, complicates and burdens compute systems as well as data movement overhead.
Gandapps’s unique history in big data and analytics has given us front-line experience in pushing the limits of CPU and GPU integration, network scale, tuning for analytics, and optimizing for both model and data parallelization. Particularly important to machine learning is our holistic approach to parallelism and performance, which includes extremely scalable compute, storage and analytics. Gandapps systems, software and toolkits help organizations accelerate their machine learning and deep learning projects.