Data Security and Compliance in a Hybrid Cloud Setup: Ensuring Consistency
Bhawna Agarwal is responsible for developing the growth strategy for India and designing programs and setting direction for its execution. She acts as a key advisor to senior leadership in exploring new growth opportunities, focusing on exploring the right market strategies and partnerships to enhance the overall portfolio delivering growth in new and existing market segments in India.
In a conversation with Charulatha, a correspondent in Siliconindia Magazine. Bhawna discussed challenges in hybrid cloud management and ways organizations can optimize costs during workload repatriation.
What are the potential challenges or risks associated with managing a hybrid cloud environment? How can they be mitigated?
Many companies still stick to traditional technology procurement models with upfront capital expenditures, despite the need for agility in today's fast-changing market landscape. Some businesses avoid cloud adoption due to prior investments, security concerns, or lack of cloud expertise. But there's a way to get that flexibility and speed they need: enter hybrid cloud solutions.
Organizations today are dealing with scattered data silos that not only holds back innovation but also ramps up IT costs, raises the risk of cyber attacks, and could even mean losing valuable data. IT leaders are looking for an immediate plan to fend off ransomware and malware.
Then there's the issue of inconsistent data protection policies. It's like having one set of rules for on-premises data and a completely different set for stuff in the cloud. That lack of uniformity is a major risk factor for data security. What IT leaders really need is a way to manage everything across this hybrid cloud seamlessly.
So, the trick to ensuring data availability in these hybrid cloud setups boils down to having agile and robust data protection. And, of course, keeping an eye on priorities like cost efficiency, simplicity, performance, scalability, and future readiness.
Can you discuss the role of data security and compliance in a hybrid cloud setup? How can organizations ensure consistent security across on-premises and cloud resources?
Instead of rigid legacy systems, organizations today are looking for something “more modern, more flexible, and more dynamic”. A hybrid cloud approach allows the best of both worlds – flexibility, and security.
In a hybrid cloud, we prioritize data security and compliance, allowing control over data location and security policies. However, security disparities can arise in some cloud architectures like SaaS.
To tackle these challenges, we've developed a robust security strategy starting at the hardware level with encryption and zero-trust protocols. We use micro-segmentation, firewalls, and a centralized dashboard for monitoring diverse environments. Our approach includes strict access controls, a zero-trust model, and AI-driven threat detection for consistent security and compliance across on-premises and cloud resources.
What are the economic considerations involved in cloud repatriation? How can organizations optimize costs and resource allocation when deciding to repatriate workloads?
Cloud repatriation involves a critical economic evaluation. The movement of workloads back to on-premises infrastructure impacts short-term and long-term financial aspects. The hybrid cloud's pay-as-you-go model aligns costs with actual usage, but deciding which workloads to repatriate depends on specific requirements.
Conducting a comprehensive cost analysis is crucial, considering technical administration, connectivity, security, business continuity, and hardware replacement expenses. Beyond initial migration, maintaining, governing, and managing risks in on-premises infrastructure presents economic challenges. Time for project planning and scaling workloads must be factored in for a thorough economic assessment. Careful evaluation enables organizations to optimize economic efficiency and resource allocation during cloud repatriation.
"The process of managing a hybrid cloud model is much more than merely lifting and shifting applications into the cloud"
In what situations might a company choose to move workloads from the cloud back to on-premises infrastructure? Can you provide real-world examples?
As digital transformation initiatives near completion, enterprises are shifting their focus from simple straightforward migration to a more sophisticated, data-first modernization. Within this paradigm, the concept that every project must be entirely cloud-centric is evolving rapidly, and organizations are now recalibrating by moving workloads back to on-premises operations when and wherever it makes sense.
One common situation that could result in the migration of workload to on-premises infra- structure is data gravity and real-time processing requirements. When dealing with massive data volumes generated at the edge, such as in manufacturing or IoT environments, organizations opt to keep workloads on-premises to minimize latency and efficiently process data at the source. For instance, a manufacturing facility reliant on IoT sensors for real-time quality control would find on-premises processing essential to ensure immediate responses and reduce downtime.
Application entanglement is another factor influencing the decision. The migration of legacy applications that have intricate dependencies or close integration with on-premises systems can be problematic when transitioning to the cloud. These applications, either due to technical constraints or the considerable expense and complexity associated with adapting them for cloud deployment, continue to operate on on-premises servers. For example, a custom-built legacy ERP system that relies on a particular on-premises infrastructure serves.
Economic considerations also play a significant role. Some workloads operating cost-effecti- vely in a fixed environment may not justify transitioning to a variable cost-based cloud architecture. Small businesses with stable computing demands, for instance, may find it more economical to maintain certain workloads on dedicated on-premises servers, avoiding ongoing cloud expenses.
Moreover, regulatory and compliance requirements are critical drivers. Certain industries and regions have strict data sovereignty and privacy regulations, compelling organizations to keep specific workloads and data within defined geographical boundaries. Financial institutions, healthcare providers, and government agencies often face such constraints, necessitating the retention of workloads on-premises to meet compliance obligations.
Today, companies recognize that not all workloads are suited for the public cloud. They strategically position workloads on-premises to balance performance, security, and cost with the flexibility of the cloud. For instance, a retail company may maintain core transactional systems on-premises while leveraging the cloud for seasonal or burst workloads during peak shopping periods.
How can effective management and monitoring tools contribute to the success of a hybrid cloud strategy?
Businesses use hybrid cloud services by mixing local, on-premises resources with private cloud and third-party public cloud services. Organization splits instrumentation between the three so workloads can move between the public and private cloud platforms as computing needs change.
However, the process of managing a hybrid cloud model is much more than merely lifting and shifting applications into the cloud. An IT department also needs to configure resources to enable them to communicate. In addition, there’s the time needed to train users and ensure both successful deployment and maintenance over the long haul that add to the investment.
Ultimately, the effective deployment and ongoing operation of a hybrid cloud infrastructure heavily rely on robust management and monitoring tools. These tools not only facilitate seamless coordination between on-premises and cloud resources but also empower businesses to adapt, optimize, and sustain their hybrid environments for long-term success in today's ever-evolving tech landscape.
In a conversation with Charulatha, a correspondent in Siliconindia Magazine. Bhawna discussed challenges in hybrid cloud management and ways organizations can optimize costs during workload repatriation.
As digital transformation initiatives near completion, enterprises are shifting their focus from simple straightforward migration to a more sophisticated, data-first modernization
What are the potential challenges or risks associated with managing a hybrid cloud environment? How can they be mitigated?
Many companies still stick to traditional technology procurement models with upfront capital expenditures, despite the need for agility in today's fast-changing market landscape. Some businesses avoid cloud adoption due to prior investments, security concerns, or lack of cloud expertise. But there's a way to get that flexibility and speed they need: enter hybrid cloud solutions.
Organizations today are dealing with scattered data silos that not only holds back innovation but also ramps up IT costs, raises the risk of cyber attacks, and could even mean losing valuable data. IT leaders are looking for an immediate plan to fend off ransomware and malware.
Then there's the issue of inconsistent data protection policies. It's like having one set of rules for on-premises data and a completely different set for stuff in the cloud. That lack of uniformity is a major risk factor for data security. What IT leaders really need is a way to manage everything across this hybrid cloud seamlessly.
So, the trick to ensuring data availability in these hybrid cloud setups boils down to having agile and robust data protection. And, of course, keeping an eye on priorities like cost efficiency, simplicity, performance, scalability, and future readiness.
Can you discuss the role of data security and compliance in a hybrid cloud setup? How can organizations ensure consistent security across on-premises and cloud resources?
Instead of rigid legacy systems, organizations today are looking for something “more modern, more flexible, and more dynamic”. A hybrid cloud approach allows the best of both worlds – flexibility, and security.
In a hybrid cloud, we prioritize data security and compliance, allowing control over data location and security policies. However, security disparities can arise in some cloud architectures like SaaS.
To tackle these challenges, we've developed a robust security strategy starting at the hardware level with encryption and zero-trust protocols. We use micro-segmentation, firewalls, and a centralized dashboard for monitoring diverse environments. Our approach includes strict access controls, a zero-trust model, and AI-driven threat detection for consistent security and compliance across on-premises and cloud resources.
What are the economic considerations involved in cloud repatriation? How can organizations optimize costs and resource allocation when deciding to repatriate workloads?
Cloud repatriation involves a critical economic evaluation. The movement of workloads back to on-premises infrastructure impacts short-term and long-term financial aspects. The hybrid cloud's pay-as-you-go model aligns costs with actual usage, but deciding which workloads to repatriate depends on specific requirements.
Conducting a comprehensive cost analysis is crucial, considering technical administration, connectivity, security, business continuity, and hardware replacement expenses. Beyond initial migration, maintaining, governing, and managing risks in on-premises infrastructure presents economic challenges. Time for project planning and scaling workloads must be factored in for a thorough economic assessment. Careful evaluation enables organizations to optimize economic efficiency and resource allocation during cloud repatriation.
"The process of managing a hybrid cloud model is much more than merely lifting and shifting applications into the cloud"
In what situations might a company choose to move workloads from the cloud back to on-premises infrastructure? Can you provide real-world examples?
As digital transformation initiatives near completion, enterprises are shifting their focus from simple straightforward migration to a more sophisticated, data-first modernization. Within this paradigm, the concept that every project must be entirely cloud-centric is evolving rapidly, and organizations are now recalibrating by moving workloads back to on-premises operations when and wherever it makes sense.
One common situation that could result in the migration of workload to on-premises infra- structure is data gravity and real-time processing requirements. When dealing with massive data volumes generated at the edge, such as in manufacturing or IoT environments, organizations opt to keep workloads on-premises to minimize latency and efficiently process data at the source. For instance, a manufacturing facility reliant on IoT sensors for real-time quality control would find on-premises processing essential to ensure immediate responses and reduce downtime.
Application entanglement is another factor influencing the decision. The migration of legacy applications that have intricate dependencies or close integration with on-premises systems can be problematic when transitioning to the cloud. These applications, either due to technical constraints or the considerable expense and complexity associated with adapting them for cloud deployment, continue to operate on on-premises servers. For example, a custom-built legacy ERP system that relies on a particular on-premises infrastructure serves.
Economic considerations also play a significant role. Some workloads operating cost-effecti- vely in a fixed environment may not justify transitioning to a variable cost-based cloud architecture. Small businesses with stable computing demands, for instance, may find it more economical to maintain certain workloads on dedicated on-premises servers, avoiding ongoing cloud expenses.
Moreover, regulatory and compliance requirements are critical drivers. Certain industries and regions have strict data sovereignty and privacy regulations, compelling organizations to keep specific workloads and data within defined geographical boundaries. Financial institutions, healthcare providers, and government agencies often face such constraints, necessitating the retention of workloads on-premises to meet compliance obligations.
Today, companies recognize that not all workloads are suited for the public cloud. They strategically position workloads on-premises to balance performance, security, and cost with the flexibility of the cloud. For instance, a retail company may maintain core transactional systems on-premises while leveraging the cloud for seasonal or burst workloads during peak shopping periods.
How can effective management and monitoring tools contribute to the success of a hybrid cloud strategy?
Businesses use hybrid cloud services by mixing local, on-premises resources with private cloud and third-party public cloud services. Organization splits instrumentation between the three so workloads can move between the public and private cloud platforms as computing needs change.
However, the process of managing a hybrid cloud model is much more than merely lifting and shifting applications into the cloud. An IT department also needs to configure resources to enable them to communicate. In addition, there’s the time needed to train users and ensure both successful deployment and maintenance over the long haul that add to the investment.
Ultimately, the effective deployment and ongoing operation of a hybrid cloud infrastructure heavily rely on robust management and monitoring tools. These tools not only facilitate seamless coordination between on-premises and cloud resources but also empower businesses to adapt, optimize, and sustain their hybrid environments for long-term success in today's ever-evolving tech landscape.
