With the economies of many countries heading towards recession, increasing regulations, growing security threats and increasing costs, financial services firms need practical solutions, now more than ever. Many of the financial technology firms (‘fintechs’) and mobile app-based challenger banks have taken advantage of modern application architectures and DevOps practices that are associated with cloud native technologies.
Canonical has been working closely with NVIDIA for many years to fuel innovation and support open source software with the power of accelerated processing. That already allowed us to jointly deliver GPU acceleration into Linux, OpenStack and container workloads on traditional datacenter servers. We continued working together, with Ubuntu forming the base operating system for NVIDIA DGX systems, including the latest NVIDIA DGX A100 system.
In environments with large numbers of client machines, configuration management tools are often used to simplify and standardize the target state of each host in a seamless, automated and consistent manner. Software like CFEngine, Chef, Ansible, and others offer a high degree of granular control over software packaging and system configurations.
The next 10 years will redefine banking. What will differentiate top banks from their competitors? Data and derived insights.
Databases like MongoDB, a NoSQL document database, are commonly used in environments where flexibility is required with big, unstructured data with ever-changing schemas. This post explains what a NoSQL database is, and provides an overview of MongoDB, its use cases and a solution for running an open source MongoDB database at scale.
One of the defining features of snaps is their strong security. Snaps are designed to run isolated from the underlying system, with granular control and access to specific resources made possible through a mechanism of interfaces. Think of it as a virtual USB cable – an interface connects a plug with a slot. Security and privacy conscious users will certainly be interested in knowing more about their snaps – what they can do and which resources they need at runtime.
The myriad of different fields that make up robotics makes QA practices difficult to settle on. Field testing is the go-to, since a functioning robot is often proof enough that a system is working. But online tests are slow. The physical environment must be set up. The entire system has to be in a workable state. Multiple runs are needed to build confidence. This grinds development to a halt.
