Multi-Core and Distributed Programming in Python
In the age of big data we often find ourselves facing CPU-intensive data processing tasks, therefore it is useful to understand how to harness all available CPU power to tackle a particular problem. Recently we came across a Python script which was CPU-intensive, but when the analyst viewed their overall CPU usage it was only showing ~25% utilization. This was because the script was only running in a single process, and therefore only fully utilizing a single core. For those of us with a few notches on our belts, this should seem fairly obvious, but I think it is a good exercise and teaching example to talk about the different methods of multi-core/multi-node programming in Python. This isn’t meant to be an all-encompassing tutorial on multi-core and distributed programming, but it should provide an overview of the available approaches in Python.
Effectively Measuring Risk Associated with Vulnerabilities in Web Applications
An objective risk rating framework enables our team to compare a standardized measurement of risk across an organization. It also allows our clients to prioritize steps needed in an action plan to mitigate, accept, or transfer organizational risk. Prioritization of vulnerability remediation should be organized objectively based on factors used in the risk rating framework, such as: ease of exploitation, severity of impact if exploited, and level of effort to remedy. If you are considering adopting a risk-rating framework, it is important to tailor a solution that best suits your organizational needs. The following risk rating scale was developed to satisfy the specific needs of our clients, and we hope it provides you with valuable guidance as you plan for the management of risk within your organization…