Redapt | Operations
With many enterprises looking to change the way they use technology in response to increasing competition and expectations, accelerating the delivery of high-quality products is critical.
Artificial Intelligence (AI) has graduated from buzzword to technical reality. For many enterprises, however, large hurdles remain in actually adopting AI into their businesses.
By some estimates, close to 90% of Machine Learning (ML) projects developed by data scientists fail. This translates into wasted resources and the potential of ML being deployed at a snail’s pace.
It used to be that working on monolithic applications was a tedious process, vulnerable to catastrophic crashes that made an entire application inoperable for an extended period of time.
Building out your datacenter is about more than simply doing rack and stack. Without having a firm grasp of your needs, you risk blindly throwing money at the project and the very real potential...
At Redapt, we try to remain relatively tech agnostic. Every client we work with has specific needs, and those needs often require an array of technical skills, infrastructure, and tools.
Modern datacenters provide companies with the flexibility and capacity they need to effectively utilize the sheer amount of data being produced every day.
Making an investment in modernizing data...
The sheer number of data storage solutions currently on the market can be overwhelming. Finding what your organization needs — and ignoring what it doesn’t — is time-consuming and resource-intensive.
Originally developed by Google, Kubernetes (or K8s) are now the standard for container orchestration, supported by everyone from AWS and Azure, to Cisco, IBM, and VMware.
The following is an excerpt from our latest white paper, A Strategic Approach to Data Storage: How Your Organization Can Leverage Big Data. You can download the full white paper here.
Storage is just...