Building Resilient Cloud Architectures for Post-Disaster IT Recovery
A resilient cloud architecture is designed to maintain functionality and service quality during disruptive events. These architectures ensure that critical business applications remain accessible, data remains secure, and recovery times are minimized, allowing organizations to maintain operations even under adverse conditions. To achieve resilience, cloud architectures must be built with redundancy, reliability, and scalability in mind. This involves a combination of technologies, strategies, and architectural patterns that, when applied collect ... Cloud-based DRaaS solutions allow organizations to recover critical workloads quickly by replicating environments in a secondary cloud region. This ensures that essential services can be restored promptly in the event of a disruption. Automated backups, on the other hand, ensure that all extracted data is continually saved and stored in a secure environment. Using regular snapshots can also provide rapid restoration points, giving teams the ability to revert systems to a pre-disaster state efficiently. ... Infrastructure as code (IaC) allows for the automated setup and configuration of cloud resources, providing a faster recovery process after an incident.
Agile Security Sprints: Baking Security into the SDLC
Making agile security sprints effective requires organizations to embrace security as a continuous, collaborative effort. The first step? Integrating security tasks into the product backlog right alongside functional requirements. This approach ensures that security considerations are tackled within the same sprint, allowing teams to address potential vulnerabilities as they arise — not after the fact when they're harder and more expensive to fix. ... By addressing security iteratively, teams can continuously improve their security posture, reducing the risk of vulnerabilities becoming unmanageable. Catching security issues early in the development lifecycle minimizes delays, enabling faster, more secure releases, which is critical in a competitive development landscape. The emphasis on collaboration between development and security teams breaks down silos, fostering a culture of shared responsibility and enhancing the overall security-consciousness of the organization. Quickly addressing security issues is often far more cost-effective than dealing with them post-deployment, making agile security sprints a necessary choice for organizations looking to balance speed with security.
The new paradigm: Architecting the data stack for AI agents
With the semantic layer and historical data-based reinforcement loop in place,
organizations can power strong agentic AI systems. However, it’s important to
note that building a data stack this way does not mean downplaying the usual
best practices. This essentially means that the platform being used should
ingest and process data in real-time from all major sources, have systems in
place for ensuring the quality/richness of the data and then have robust access,
governance and security policies in place to ensure responsible agent use.
“Governance, access control, and data quality actually become more important in
the age of AI agents. The tools to determine what services have access to what
data become the method for ensuring that AI systems behave in compliance with
the rules of data privacy. Data quality, meanwhile, determines how well an agent
can perform a task,” Naveen Rao, VP of AI at Databricks, told VentureBeat. ...
“No agent, no matter how high the quality or impressive the results, should see
the light of day if the developers don’t have confidence that only the right
people can access the right information/AI capability. This is why we started
with the governance layer with Unity Catalog and have built our AI stack on top
of that,” Rao emphasized.
Enhancing visibility for better security in multi-cloud and hybrid environments
The number one challenge for infrastructure and cloud security teams is
visibility into their overall risk–especially in complex environments like
cloud, hybrid cloud, containers, and Kubernetes. Kubernetes is now the tool of
choice for orchestrating and running microservices in containers, but it has
also been one of the last areas to catch speed from a security perspective,
leaving many security teams feeling caught on their heels. This is true even if
they have deployed admission control or have other container security measures
in place. Teams need a security tool in place that can show them who is
accessing their workloads and what is happening in them at any given moment, as
these environments have an ephemeral nature to them. A lot of legacy tooling
just has not kept up with this demand. The best visibility is achieved with
tooling that allows for real-time visibility and real-time detection, not
point-in-time snapshotting, which does not keep up with the ever-changing nature
of modern cloud environments. To achieve better visibility in the cloud,
automate security monitoring and alerting to reduce manual effort and ensure
comprehensive coverage. Centralize security data using dashboards or log
aggregation tools to consolidate insights from across your cloud platforms.
How Augmented Reality is Shaping EV Development and Design
Traditionally, prototyping has been a costly and time-consuming stage in
vehicle development, often requiring multiple physical models and extensive
trial and error. AR is disrupting this process by enabling engineers to create
and test virtual prototypes before building physical ones. Through immersive
visualizations, teams can virtually assess design aspects like fit, function,
and aesthetics, streamlining modifications and significantly shortening
development cycles. ... One of the key shifts in EV manufacturing is the
emphasis on consumer-centric design. EV buyers today expect not just
efficiency but also vehicles that reflect their lifestyle choices, from
customizable interiors to cutting-edge tech features. AR offers manufacturers
a way to directly engage consumers in the design process, offering a virtual
showroom experience that enhances the customization journey. ... AR-assisted
training is one frontier seeing a lot of adoption. By removing humans from
dangerous scenarios while still allowing them to interact with those same
scenarios, companies can increase safety while still offering practical
training. In one example from Volvo, augmented reality is allowing first
responders to assess damage on EV vehicles and proceed with caution.
Digital twins: The key to unlocking end-to-end supply chain growth
Digital twins can be used to model the interaction between physical and
digital processes all along the supply chain—from product ideation and
manufacturing to warehousing and distribution, from in-store or online
purchases to shipping and returns. Thus, digital twins paint a clear picture
of an optimal end-to-end supply chain process. What’s more, paired with
today’s advances in predictive AI, digital twins can become both predictive
and prescriptive. They can predict future scenarios to suggest areas for
improvement or growth, ultimately leading to a self-monitoring and
self-healing supply chain. In other words, digital twins empower the switch
from heuristic-based supply chain management to dynamic and granular
optimization, providing a 360-degree view of value and performance leakage. To
understand how a self-healing supply chain might work in practice, let’s look
at one example: using digital twins, a retailer sets dynamic SKU-level safety
stock targets for each fulfillment center that dynamically evolve with
localized and seasonal demand patterns. Moreover, this granular optimization
is applied not just to inventory management but also to every part of the
end-to-end supply chain—from procurement and product design to manufacturing
and demand forecasting.
Illegal Crypto Mining: How Businesses Can Prevent Themselves From Being ‘Cryptojacked’
Business leaders might believe that illegal crypto mining programs pose no
risks to their operations. Considering the number of resources most businesses
dedicate to cybersecurity, it might seem like a low priority in comparison to
other risks. However, the successful deployment of malicious crypto mining
software can lead to even more risks for businesses, putting their
cybersecurity posture in jeopardy. Malware and other forms of malicious
software can drain computing resources, cutting the life expectancy of
computer hardware. This can decrease the long-term performance and
productivity of all infected computers and devices. Additionally, the large
amount of energy required to support the high computing power of crypto mining
can drain electricity across the organization. But one of the most severe
risks associated with malicious crypto mining software is that it can include
other code that exploits existing vulnerabilities. ... While powerful
cybersecurity tools are certainly important, there’s no single solution to
combat illegal crypto mining. But there are different strategies that business
leaders can implement to reduce the likelihood of a breach, and mitigating
human error is among the most important.
10 Most Impactful PAM Use Cases for Enhancing Organizational Security
Security extends beyond internal employees as collaborations with third
parties also introduce vulnerabilities. PAM solutions allow you to provide
vendors with time-limited, task-specific access to your systems and monitor
their activity in real time. With PAM, you can also promptly revoke
third-party access when a project is completed, ensuring no dormant accounts
remain unattended. Suppose you engage third-party administrators to manage
your database. In this case, PAM enables you to restrict their access based on
a "need-to-know" basis, track their activities within your systems, and
automatically remove their access once they complete the job. ... Reused or
weak passwords are easy targets for attackers. Relying on manual password
management adds another layer of risk, as it is both tedious and prone to
human error. That's where PAM solutions with password management capabilities
can make a difference. Such solutions can help you secure passwords throughout
their entire lifecycle — from creation and storage to automatic rotation. By
handling credentials with such PAM solutions and setting permissions according
to user roles, you can make sure all the passwords are accessible only to
authorized users.
The Information Value Chain as a Framework for Tackling Disinformation
The information value chain has three stages: production, distribution, and
consumption. Claire Wardle proposed an early version of this framework in 2017.
Since then, scholars have suggested tackling disinformation through an economics
lens. Using this approach, we can understand production as supply, consumption
as demand, and distribution as a marketplace. In so doing, we can single out key
stakeholders at each stage and determine how best to engage them to combat
disinformation. By seeing disinformation as a commodity, we can better identify
and address the underlying motivations ... When it comes to the disinformation
marketplace, disinformation experts mostly agree it is appropriate to point the
finger at Big Tech. Profit-driven social media platforms have understood for
years that our attention is the ultimate gold mine and that inflammatory content
is what attracts the most attention. There is, therefore, a direct correlation
between how much disinformation circulates on a platform and how much money it
makes from advertising. ... To tackle disinformation, we must think like
economists, not just like fact-checkers, technologists, or investigators. We
must understand the disinformation value chain and identify the actors and their
incentives, obstacles, and motivations at each stage.
Why do developers love clean code but hate writing documentation?
In fast-paced development environments, particularly those adopting Agile
methodologies, maintaining up-to-date documentation can be challenging.
Developers often deprioritize documentation due to tight deadlines and a focus
on delivering working code. This leads to informal, hard-to-understand
documentation that quickly becomes outdated as the software evolves. Another
significant issue is that documentation is frequently viewed as unnecessary
overhead. Developers may believe that code should be self-explanatory or that
documentation slows down the development process. ... To prevent documentation
from becoming a second-class citizen in the software development lifecycle,
Ferri-Beneditti argues that documentation needs to be observable, something that
can be measured against the KPIs and goals developers and their managers often
use when delivering projects. ... By offloading the burden of documentation
creation onto AI, developers are free to stay in their flow state, focusing on
the tasks they enjoy—building and problem-solving—while still ensuring that the
documentation remains comprehensive and up-to-date. Perhaps most importantly,
this synergy between GenAI and human developers does not remove human
oversight.
Quote for the day:
"The harder you work for something,
the greater you'll feel when you achieve it." -- Unknown
