Cloud Infrastructure

Context
Cloud infrastructure consists of hardware and software components -- such as servers, storage, virtualization software and operating systems -- needed to meet the computing requirements of a cloud infrastructure model. Cloud has been gaining steam with more and more services are being hosted on the Cloud providing greater flexibility and better utilization of infrastructure resources.
We have a seasoned team in US and India that can consult, design, deploy and maintain cloud infrastructure for small to large enterprises.

What We Do
Our experienced team helps you identify the right mix of technologies in the market to architect a solution tailored to your business needs. Our team ensures that we help you procure and deploy infrastructure in a time and cost efficient manner. All services are over looked by our Project Management Office to ensure quality delivery and deployment.

Our services ensure that companies can:
- Maximize the efficiency of your servers, storage, and databases
- Reduce costs across resources and clouds
- Increase uptime with high availability and disaster recovery best practices
- Reduce risks associated with change management

Our Infrastructure offering encompasses all stand-alone elements which if needed can be clubbed together to create an end-to-end solution:
Assessment - Wireless / Network / Storage / Backup / Virtualization
Networks - LAN / WAN / VoIP
Storage - SAN / NAS
Cisco Unified Computing Systems
Virtualization - Server / Desktop virtualization and licensing
Mobility Device Management
VCE Cloud Infrastructure
Datacenter Monitoring
Backup, Recovery, Archive and Disaster Recovery solutions

Our Experience
Since 2012, iLEAD along with its US partner Synapse has advised many enterprises on the best path to cloud success:
- Deployed numerous applications hosted on Cloud Foundry (CF) platform
- Created Big-Data-Lake Architecture & Implemented using Extract-Load-Transform (ETL) processes to store all row data in a repository and use this historical data for predictive reporting.