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  • AI
  • cloud
  • cybersecurity
  • safety and security

A Quick Run Down: Mission Critical Architecture for Modern Security Solutions

Mordekhay Shushan Brian St.Onge Mordekhay Shushan Brian St.Onge

Tue, 20 Jun 2023 20:21:51 -0000

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Nowadays, end users view their security data as mission critical. This means having uninterrupted access to recorded video and ensuring that recorders and archivers remain functional, which are essential for daily business operations. As a result, designs need to prioritize uptime while also taking other end user considerations into account.

A key consideration is storage efficiency. Stacking 2U NVRs for storage purposes is highly inefficient, both in terms of sustainability and rack space. To avoid over-procuring compute nodes to expand storage, it is better to build a proper on-premises storage solution that can scale at the petabyte scale. This ensures that the end user has sufficient storage capacity without compromising on the availability of compute nodes.

In addition to availability, regulatory compliance is another critical issue for end users. Achieving six 9s availability is possible, but if a node requires servicing, there may be no access to recorded video, leading to potential compliance issues. To mitigate this risk, it is recommended to shift from a RAID appliance to a node-based NAS storage system that uses erasure coding. This enables the end user to drop a full node of 20 HDDs and still record and access the video with six 9s availability.

In mission-critical environments such as airports and casinos, operations must continue during storage maintenance. For that reason, it’s important to have a storage solution that allows for maintenance that won’t affect daily operations. To sum it up: designing a storage solution that prioritizes efficiency, scalability, and regulatory compliance is critical for meeting the needs of end users in mission-critical environments.

What about Cloud?

Over the past several years, the trend of implementing a cloud-first strategy has been no secret. However, this strategy has posed numerous challenges for end-users. Although it is simple and fast to ramp up with a third-party cloud provider, and it provides a finance model that does not require large capital, over time the costs escalate with network access and egress fees. This has surprised many clients, causing them to re-evaluate this model.

The SIA Security Industry Privacy Guide suggests that best practice would not be to share security data with a third-party. These third-party contracts can also be through another third-party, such as a hardware manufacturer that has a third-party cloud contract and resells cloud services. As a result, it becomes challenging to manage risks as control of the data is no longer within the organization, yet the organization still holds liability for the security of the data being collected. This has led many organizations to repatriate to an on-premises or hybrid model for better control of their data.

We are now seeing a shift from a cloud-first to a cloud-smart strategy, where clients are becoming more selective about what they keep on-premises and what they store in a public cloud to maintain control and apply their policies to the data volumes more easily. This approach enables organizations to maintain control over sensitive data while still taking advantage of the benefits of cloud technology. In this way, adopting a cloud-smart strategy allows organizations to balance the benefits of cloud technology with the need for data control and security.

Cyber Security by Design  

In today's security landscape, protecting sensitive privacy data and intellectual property is a top priority for most organizations. Unfortunately, we have witnessed high-profile incidents, such as the loss of biometric data for millions of people, resulting in privacy breaches and legislative action against end users. Even with the use of cloud providers, organizations must recognize that they are ultimately responsible for the security of the data they collect and store. Cloud environments are also susceptible to cyber breaches, which can be costly and time-consuming to recover from. Many organizations are still struggling to recover from incidents that occurred a year ago, causing significant operational disruptions and financial losses.A picture containing text, screenshot, diagram, font

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To mitigate the risks associated with cyber threats, today's mission critical architecture should prioritize cyber recovery by design. One effective strategy is to secure data in a cyber recovery vault that is offline and separated from the production cluster through an air gap. This approach allows for rapid recovery, enabling an end user to quickly regain control and resume operations with a clean data set. The recovery of a PB of data can now be achieved within an hour, as opposed to months in the past. By adopting a cyber recovery by design approach, organizations can proactively safeguard their data and minimize the impact of cyber incidents.

Embracing AI

Video is no longer just a tool for security purposes: it has become a valuable source of metadata that can be leveraged by multiple stakeholders within an organization. In fact, I have seen up to 14 different stakeholders within a single organization look to video metadata for a variety of non-security-related business outcomes. One such example is the retail industry, where video data has been used to enhance the overall customer experience.

As we shift towards using video for data science, new challenges arise for data scientists in achieving meaningful outcomes for their stakeholders. According to recent studies, data scientists spend 79% of their time searching for data in various silos to leverage. This is particularly true in LUN environments, where data silos are numerous, and correlating the appropriate camera feed to the disk group can be time-consuming and complex.

To address this challenge, organizations can create a single-volume data lake to store all necessary data. This allows data scientists to quickly map data targets and dramatically reduces the time-to-market for AI projects, making their time more productive and allowing them to focus on actual data science work rather than wrangling with data.

Summary

To sum up, we’ve discussed the importance of mission-critical architecture for modern security solutions, and highlighted the need for storage efficiency, scalability, and regulatory compliance to meet the needs of end-users in mission-critical environments. We discussed the shift from a cloud-first to a cloud-smart strategy, with a focus on maintaining control and security of data. Cybersecurity is a top priority for organizations, and we stress the need to prioritize cyber recovery by design to minimize the impact of cyber incidents. Finally, we touched upon the use of AI and the challenges of data silos and suggested creating a single-volume data lake to store all necessary data for AI projects, allowing data scientists to focus on actual data science work.

Thanks for reading! To learn more about modern security solutions, see:

Info Hub: https://infohub.delltechnologies.com/t/safety-security

Authors:

Mordekhay Shushan, Solution Architect

Brian St.Onge, Business Development Manager, Video Surveillance

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