October 22, 2023
Kannan Subbiah
FCA | CISA | CGEIT | CCISO | IT Security, Strategy & Governance | Independent Director | Enterprise & Solution Architecture | 3 decades of IT experience and 2 decades of Mutual Funds domain experience.
Compute will still evolve, but how fast is the question? The Internet led to the massively distributed data center approach, which we know as the cloud, a terrible term, but I digress. But today the power of computing can only increase so much. Moore’s Law looks increasingly impossible to keep pace with as we develop transistors the size of an atom. Infrastructure limitations are causing all sorts of headaches for software vendors who now face a litany of options for maximizing AI systems to be more efficient with precious compute resources. ... It’s all about the data and its compounding growth. Having transition data ready and analytic, too, with speed and efficiency, makes for the ability to scale AI systems. As we’ve seen, AI systems must be fast and SingleStore markets that capability with its in-memory and disk capabilities. There’s also the flexibility that customers demand — a hybrid approach that cuts across cloud services and on-premises. With SinglStore vector indexing and JSON handling, the capabilities opened further.
To effectively support the transition, leaders must commit to a culture of platform engineering. Simply adopting technology isn’t enough. It needs to be backed by a thorough strategy that allows developers to truly benefit from the tools and structures of platform engineering. What does this look like? Success requires leaders and developers to encourage collaboration and break down silos between operations and development teams. It’s possible to build a bridge between developers and operations by committing to cloud migration, creating a centralized platform and investing in collaborative tools and the strategy to back it up. To engage in platform engineering requires dedication to a collaborative culture instigated from the top, empowered by overall strategic decisions and operations. This includes continued learning for developers to stay on top of new languages, trends, challenges and priorities, internally and externally. Teams are more successful when they utilize performance metrics to track workflows that help them conduct effective maintenance and improve on a consistent and ongoing basis.
Maintaining independent reporting structures for the CDO and CISO, separate from the Chief Information Officer (CIO), is crucial. That’s because when they report directly to the executive leadership or the CEO, they can provide independent updates on data governance and cybersecurity, ensuring clarity and objectivity in decision-making for critical data-related matters. Due to this arrangement, senior management will have a holistic view of risk management, compliance, and strategic decision-making, without any biases that may arise from reporting to the CIO. Biases, in this context, can manifest in several ways. For example, a CIO might prioritise IT initiatives that align with the department’s goals or budget constraints, potentially overlooking or downplaying certain data governance or security concerns. Hence, this hierarchical reporting structure, with the CIO in the middle, can unintentionally filter or influence the information that reaches senior management, which could impact their ability to make well-informed, impartial decisions.
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Diamond Sleet was observed using two attack paths: the first consisted in the deployment of ForestTiger backdoor while the second deployed payloads for DLL search-order hijacking attacks. Onyx Sleet used a different attack path: After successfully exploiting the TeamCity vulnerability, the threat actor creates a user account (named krtbgt), runs system discovery commands and finally deploys a proxy tool named HazyLoad to establish persistent connection. “In past operations, Diamond Sleet and other North Korean threat actors have successfully carried out software supply chain attacks by infiltrating build environments,” Microsoft noted. North Korean state-sponsored hackers have been linked to a social engineering campaign targeting software developers through GitHub. By pretending to be a developer or a recruiter, the attacker managed to convince the victim to collaborate on a GitHub repository and ultimately download and execute malware on its device.
Almost any organisation can use DRaaS because it requires little in the way of hardware or up-front investment. However, its use is most common in organisations that want to minimise downtime, but cannot justify investment in redundant hardware, either on-premise or in a datacentre or colocation facility. This is likely to involve a trade-off between performance and recovery times, and cost. DRaaS that runs in the public cloud will be slower than dedicated systems, but it will still be faster to recover from than basic cloud-based backup or BaaS. Another application for DRaaS is where conventional DR systems are less practical. This includes branch and remote offices that may have lower bandwidth connections and little in the way of on-site IT support. There is also a trend towards use of DRaaS to provide resilience for cloud-based infrastructure. Such cloud-to-cloud disaster recovery can range from replicating entire cloud production environments or specific VMs to a secondary cloud location, to providing additional redundancy and continuity for SaaS applications and even Microsoft 365.
In order to reduce risks and downtime when releasing new versions or updates of an application, blue-green deployment is a software deployment strategy. It entails running two parallel instances of the same production environment, with the “blue” environment serving as a representation of the current stable version and the “green” environment. With this configuration, switching between the two environments can be done without upsetting end users. without disrupting end-users. The fundamental idea behind blue-green deployment is to automatically route user traffic to the blue environment to protect the production system's stability and dependability. Developers and QA teams can validate the new version while the green environment is being set up and thoroughly tested before it is made available to end users. ... The advantages of blue-green deployment are numerous. By maintaining parallel environments, organizations can significantly reduce downtime during deployments.
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