Posts under Docker
It should come as no surprise that behind the rapid adoption of Docker containers are a set of slam-dunk cost and operational benefits. According to Docker, enterprise IT budgets are heavily consumed by maintenance and upkeep of legacy applications on the order of 80%. Containers drastically change that equation, and the customers that leverage them are realizing massive improvements in resource utilization, resulting in a 50%-60% drop in virtual machines (VMs)– and ultimately, hypervisor licenses– required to run the refactored application.
Container technology is fundamentally changing the way incident response (IR) is handled within the enterprise, and it is putting agile organizations back in a position of strength against their attackers. Microservices and containers comprise an infrastructure that can be leveraged as a security orchestrator and responder, which allows for radical improvements in both the scale and speed of threat detection, response, and prevention. IR in a traditional environment Today’s systems have become too distributed, integrate too many programs, and present too many attack surfaces for security analysts to thwart attacks effectively.
Enterprise organizations across diverse verticals, such as 3M, Adobe, Kellogg’s, and Netflix, have been ramping up their use of the public cloud to the point where that usage accounts for a substantial portion of their annual IT spend. ‘Enterprises with big budgets, data centers, and complex applications are now looking at cloud as a viable place to run core business applications’, according to Dave Bartoletti, an analyst at Forrester Research.
By now, details of the massive Equifax breach that saw 143 million personal records compromised has made its way around the global news, as well as the broader security and enterprise IT communities. Within these circles, you can bet that anyone responsible for resolving application vulnerabilities is worried about becoming the next headline. There’s little argument that patching applications is a big deal; both in terms of criticality to the organization’s security posture, and in terms of the onerous process it can be when performed in traditional application environments.
The last few decades have seen tremendous progress in machine learning (ML) algorithms and techniques. This progress, combined with various open-source efforts to curate implementations of a large number of ML algorithms has lead to the true democratization of ML. It has become possible for practitioners with and without a background in statistical inference or optimization – the theoretical underpinnings of ML – to apply ML to problems in their domain.
Forensics in the age of containers You’ve seen it countless times in television’s most popular dramas: professional investigators descend on the scene of a crime to meticulously record and analyze every detail and clue before anyone else can disrupt the scene. If the crime appears to be related to other ongoing cases, clues are tacked to the peg board back at headquarters. Only once all the pieces have been assembled do patterns emerge.
Introduction Container technology has radically changed the way that applications are being developed and deployed. Notably, containers dramatically ease dependency management, so shipping new features or code is faster than ever before. While Docker containers and Kubernetes are great for DevOps, they also present new security challenges that both security practitioners and developers must understand and address with diligence. Docker’s team of security experts has built some valuable security features into the Docker platform over the last several years.
WAF the heck do I do to protect against attacks on my container-based web applications? The hackers who want your organization’s valuable data will invariably target your web applications. Despite the steady increase in distributed denial-of-service (DDoS) attacks and ransomware, web application attacks represent the most common cause of data breaches.1 The vast majority of these attacks are executed by botnets, operated by organized crime2. Their goals: stealing credentials, growing the size of the botnet, and, of course, exfiltrating information that can be used for financial gain.