Hello people. My name is Vanka Cheru. I'm a senior infrastructure engineer in the Orange County area. I the today, the topic I want to present to you about, is optimizing hybrid object-based storage for scalability, performance, and cost across on-premises and cloud environment went of social media and advancements in healthcare and financial industry. There has been a massive increase in unstructured, data like, videos, images, IOT sensor data. Which led to, a need for scalable and cost effective storage solution. This presentation explores, how object-based storage architecture seamlessly integrate. OnPrem on premises infrastructure with cloud environments and to optimize enterprise data management addresses critical challenges faced today by IT industry. We'll go through the various implementation strategies, cost advantages, and performance improvements to help you develop and, effective strategy for your organization. Organizations, today, face an unprecedented, challenge in managing the exponential data growth. The object-based storage, can handle, large volumes of unstructured data more efficiently than, a traditional file. Or, block storage organizations facing exponential data growth in Glo, in the, in global data footprint, that byte, by 2025. So organizations must embrace and innovative storage solutions. That balance, performance, cost, and, compliance, regulatory requirements. Hybrid object-based storage has emerged as an, critical foundation for enterprises seeking competitive advantage in data-driven economy, saving about 40% of annual operational and maintenance cost. Let's talk about hybrid architecture of the hybrid, object based storage. Hybrid ob object based storage architecture establishes, E echo seal echo system where data can rec reside on premises. Or in multiple clouds while presenting a single unified, strategy stor while pro, while providing a single unified storage repository to the, for all the applications. This architecture implements industry standard APIs and protocols, ensuring seamless interoperability and consistent data access methods, across local infrastructure and cloud environments. To talk about the architecture. the architecture typically consists of, four layers, a management layer, an application layer, orchestration layer, and storage. and storage. so coming to the management layer, is management layer, basically consists of. it's a software frontend interface, helps us access the entire infrastructure. And, the application layer is nothing but, user facing services and APIs connecting backend storage and cloud, in the orchestration layer. it's it functions. The orchestration layer functions as the core of the system making data placement, decisions, based on the analysis of data access patterns, performance requirements and cost parameters, it continuously evaluates, and automatically migrates data between. Appropriate storage tiers, optimizing both performance and cost, without any manual intervention. The storage layer, is nothing but a physical backend integrated hybrid storage. Let's talk more about orchestration. let's talk more about, the orchestration or data tiering architecture, the intelligent, tiering, Engine continuously analyzes metadata, and the access patterns and business policies to automatically orchestrate data placement across performance tiers. This zero touch optimization ensures each data set. Resides on most economically efficient storage layer while maintaining compliance requirements and performance service level agreements. Data tier can broadly be classified in two four tiers, hot tier, cold tier, and archive, vomit tier and archive tier. And my. Hot tier is nothing but emission critical workloads with high latency requirements and maximum throughput. We can leverage on-prem storage platforms with, which has, flash or high performance, SSD drives. in it, coming to the Walmart tier, the data that is not frequently accessed, but it is quite important enough to maintain for future use. Cold tier is, nothing but is data, that can be stored in cloud, like historical data sets, reporting data. Things like that. And in the archive tier it's nothing. But, it's mostly about, comes to the data protection suite, where data, with data that requires an infinite or long-term retentions to encompass companies, regulatory requirements. Best use case examples are healthcare and financial sectors where they got to maintain, maintain, longer retentions. Here are some of the strategies, to achieve cost optimization by analyzing data lifecycle, identifying data, access patterns, use, tier storage solutions to store data based on its frequency of access, hot data on high performance, like our expensive storage. And coal data on cost effective, slower storage implementing by implementing tiering policies, automating a data movement across performance and slower storage. continuously monitoring, and analyzing the performance metrics and refined data placement strategies. And, optimizing cloud resources strategically select appropriate storage tiers and geographical regions. based upon the organization, location, you can choose, the local, availability zones or something. far from your organization, which could be, most cost effective option. So organizations implementing these strategies or hybrid object storage solutions consistently has achieved about 30% or greater reductions in their total cloud, cloud storage expenditures. Through sophisticated tiering strategies. So by conducting comprehensive analysis of access, data access patterns and regulatory requirements, IT departments can establish automated governance policies that dynamically position data in the most cost effective location without requiring any manual intervention. On-premises Infrastructure investments can also be maximized by this strategy by allocating high performance capacity. exclusively to latency sensitive workloads while maintaining, simultaneous, while simultaneously leveraging, cloud economics for substantial majority of, enterprise data that doesn't demand a sub. Second response times are consistent IOPS performance, hybrid object storage architecture meets, industry's regulatory compliance and data. Sovereign with an unified API layer. with 75 per up, up to 75% of the global organizations are now, navigating multiple overlapping regulatory frameworks. Hybrid storage architectures deliver, the essential flexibility needed to address complex challenges. Forward-thinking enterprises can securely maintain sensitive workload on premises while simultaneously leveraging cloud economics to optimize. cost for less regulated information assets. So with this unified API layer, we can maintain data sovereignty, retention policies, encryption, and audit trail implementation, best practices. it is always recommended to implement these, solutions, these hybrid based solutions or hybrid storage solutions or any solutions with industry standard best practices. by successful, any successful hybrid storage, implementation, approach, organizations to start with non-critical workloads to refine their approach. as they go before me migrating more sensitive applications to begin with, you start with an initial infrastructure or environment assessment by evaluating the existing infrastructure data, access patterns, and, getting through the compliant, getting to know the compliance requirements of that particular organization. And, identify, performance sensitive workloads, and data that could benefit from tiering. Also to document, it's always best practice to document all these regulatory constraints and the infrastructure information, that will view, that will further influence the architecture decisions coming to the architecture design. it's better to develop a blueprint for integration between. on premises and cloud resources, selecting the appropriate storage technologies for each tier, and defining the API integration points and establishing the performance baselines and expectations. Policy development, is key in creating, to create, automated data tier policies based upon the access patterns and, business defining the go governance frameworks for consistent management across the environments and documenting all these, the security controls and compliance measures. Implementing and testing. So deploying integration components and validate performance against the benchmarks. So test, a failover scenarios, testing a failover scenario and data recovery process, and also defining R-P-O-R-T-O, recovery point objective, recovery time objective, and, verify the policy enforcement and audit capabilities are met across the environment. And also testing the RPO. testing the defined RP one are, are being achieved with this solution, with the implemented solution. let's, now let's go through, a case study. Where the financial services, financial organization was meeting, having a challenge and, where, they had five petabytes of data increase, which is data is, has been increasing and their infrastructure, existing infrastructure could not be scaled, due to financial constraints. with the, by the way, the global economy is, tumbling, to meet, the growing analytic, to meet the growing analytics and the workloads. While strict regulations, required certain data to remain on premises, the solution that they chose was, the firm implemented. a hybrid based storage architecture with high performance flash on, with high performance flash discs on premises for active trading data and other customer records. and all their, unstructured data integrated that with the cloud storage for historical analysis, and long-term retention, to meet the regulatory requirements. So they also adopted an intelligent tiering. algorithm, which automatically moves data based on access pattern while unified, while a unified, interface provided consistent policy enforce enforcement across all storage locations. So the result was, reduced storage cost by about, 30% in the first year. And improved the analytics per, improved the performance by about 35%, and they were, yet achieved, they yet achieved 99.9 in compliance requirements, that was being set to their organization. And also, and also they have decreased the storage management overhead by about 40%, and accelerated, new application deployments by 60%. So when their organization had to invest less on implementing the storage, implementing, storage, implementation and their op storage operational costs. They focused, and they leveraged that, that financial budget towards deploying new applications, which, which helps their organization, big time. So let's talk about, future trends in the hybrid storage. So the hybrid storage landscape continues to evolve rapidly with the emerging technologies, enabling more intelligent and seamless integration between different environments. So organizations should prepare for these advancements by building a flexible architectures that can adapt to future innovations. So industry analysts, predict that by 2025, by end of 2025, more than 70% of the enterprise data will be managed through unified hybrid storage platforms. That dynamic, that dynamically optimizes pla that dynamically optimize placement, based on real time data placement based on the real time analysis of workload requirements. key takeaway from this presentation are. to assess your current environment before, you implement the solution and developing a solid tiering strategy, which plays a CLO crucial role. And also implementing a unified management, solution by deploying a robust orchestration tools that provide comprehensive visibility and control across your entire storage ecosystem and prioritizing the APIs. implementing the standard industry best in industry, adapted APIs and interfaces to ensure any, frictionless operations regardless of data, location and storage medium. And finally, defining a clear success metrics, what altering of the performance and cost efficiency. And, making sure compliance, regulatory compliance are met. Leveraging these analytics to continuously refine your hybrid storage architecture and ensuring alignment with evolving business objectives. So hybrid object based storage deliver delivers, transformative advantages for organizations confronting exponential data growth challenges through the strategic implementation of these solutions. it, teams can provide superior, performance, unlimited scalability, robust compliance capabilities, while significantly optimizing cost across the entire data lifecycle. this sends my, talk and the presentation. Thank you so much for, listening to me. Thanks for your time.