Hyper-Converged Infrastructure
Article | October 10, 2023
Pacific Electric Wire & Cable Co. (PEWC) is a manufacturer in Taiwan with subsidiaries in China, Singapore, Thailand, and Australia. Like many companies, they had been facing the looming change over to SAP HANA. They were ready to switch over from their older SAP software and take advantage of SAP HANA apps and databases. They also had a goal of speeding up operational analytics and insights. But with the change to HANA, they needed all new infrastructure, certified by SAP, to support it.
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Application Storage, Data Storage
Article | July 12, 2023
Revolutionize data management with HCI: Unveil the modernized storage solutions and implementation strategies for enhanced efficiency, scalability, sustainable growth and future-ready performance.
Contents
1. Introduction to Modernized Storage Solutions and HCI
2. Software-Defined Storage in HCI
3. Benefits of Modern Storage HCI in Data Management
3.1 Data Security and Privacy in HCI Storage
3.2 Data Analytics and Business Intelligence Integration
3.3 Hybrid and Multi-Cloud Data Management
4. Implementation Strategies for Modern Storage HCI
4.1 Workload Analysis
4.2 Software-Defined Storage
4.3 Advanced Networking
4.4 Data Tiering and Caching
4.5 Continuous Monitoring and Optimization
5. Future Trends in HCI Storage and Data Management
1. Introduction to Modernized Storage Solutions and HCI
Modern businesses face escalating data volumes, necessitating efficient and scalable storage solutions. Modernized storage solutions, such as HCI, integrate computing, networking, and storage resources into a unified system, streamlining operations and simplifying data management.
By embracing modernized storage solutions and HCI, organizations can unlock numerous benefits, including enhanced agility, simplified management, improved performance, robust data protection, and optimized costs. As technology evolves, leveraging these solutions will be instrumental in achieving competitive advantages and future-proofing the organization's IT infrastructure.
2. Software-Defined Storage in HCI
By embracing software-defined storage in HCI, organizations can benefit from simplified storage management, scalability, improved performance, cost efficiency, and seamless integration with hybrid cloud environments. These advantages empower businesses to optimize their storage infrastructure, increase agility, and effectively manage growing data demands, ultimately driving success in the digital era.
Software-defined storage in HCI revolutionizes traditional, hardware-based storage arrays by replacing them with virtualized storage resources managed through software. This centralized approach simplifies data storage management, allowing IT teams to allocate and oversee storage resources efficiently. With software-defined storage, organizations can seamlessly scale their storage infrastructure as needed without the complexities associated with traditional hardware setups. By abstracting storage from physical hardware, software-defined storage brings greater agility and flexibility to the storage infrastructure, enabling organizations to adapt quickly to changing business demands.
Software-defined storage in HCI empowers organizations with seamless data mobility, allowing for the smooth movement of workloads and data across various infrastructure environments, including private and public clouds. This flexibility enables organizations to implement hybrid cloud strategies, leveraging the advantages of both on-premises and cloud environments. With software-defined storage, data migration, replication, and synchronization between different data storage locations become simplified tasks. This simplification enhances data availability and accessibility, facilitating efficient data management across other storage platforms and enabling organizations to make the most of their hybrid cloud deployments.
3. Benefits of Modern Storage HCI in Data Management
Software-defined storage HCI simplifies hybrid and multi-cloud data management. Its single platform lets enterprises easily move workloads and data between on-premises infrastructure, private clouds, and public clouds. The centralized management interface of software-defined storage HCI ensures comprehensive data governance, unifies control, ensures compliance, and improves visibility across the data management ecosystem, complementing this flexibility and scalability optimization.
3.1 Data Security and Privacy in HCI Storage
Modern software-defined storage HCI solutions provide robust data security measures, including encryption, access controls, and secure replication. By centralizing storage management through software-defined storage, organizations can implement consistent security policies across all storage resources, minimizing the risk of data breaches. HCI platforms offer built-in features such as snapshots, replication, and disaster recovery capabilities, ensuring data integrity, business continuity, and resilience against potential threats.
3.2 Data Analytics and Business Intelligence Integration
These HCI platforms seamlessly integrate with data analytics and business intelligence tools, enabling organizations to gain valuable insights and make informed decisions. By consolidating storage, compute, and analytics capabilities, HCI minimizes data movement and latency, enhancing the efficiency of data analysis processes. The scalable architecture of software-defined storage HCI supports processing large data volumes, accelerating data analytics, predictive modeling, and facilitating data-driven strategies for enhanced operational efficiency and competitiveness.
3.3 Hybrid and Multi-Cloud Data Management
Software-defined storage HCI simplifies hybrid and multi-cloud data management by providing a unified platform for seamless data movement across different environments. Organizations can easily migrate workloads and data between on-premises infrastructure, private clouds, and public clouds, optimizing flexibility and scalability. The centralized management interface of software-defined storage HCI enables consistent data governance, ensuring control, compliance, and visibility across the entire data management ecosystem.
4. Implementation Strategies for Modern Storage Using HCI
4.1 Workload Analysis
A comprehensive workload analysis is essential before embarking on an HCI implementation journey. Start by thoroughly assessing the organization's workloads, delving into factors like application performance requirements, data access patterns, and peak usage times. Prioritize workloads based on their criticality to business operations, ensuring that those directly impacting revenue or customer experiences are addressed first.
4.2 Software-Defined Storage
Software-defined storage (SDS) offers flexibility and abstraction of storage resources from hardware. SDS solutions are often vendor-agnostic, enabling organizations to choose storage hardware that aligns best with their needs. Scalability is a hallmark of SDS, as it can easily adapt to accommodate growing data volumes and evolving performance requirements. Adopt SDS for a wide range of data services, including snapshots, deduplication, compression, and automated tiering, all of which enhance storage efficiency.
4.3 Advanced Networking
Leverage Software-Defined Networking technologies within the HCI environment to enhance agility, optimize network resource utilization, and support dynamic workload migrations. Implementing network segmentation allows organizations to isolate different workload types or security zones within the HCI infrastructure, bolstering security and compliance. Quality of Service (QoS) controls come into play to prioritize network traffic based on specific application requirements, ensuring optimal performance for critical workloads.
4.4 Data Tiering and Caching
Intelligent data tiering and caching strategies play a pivotal role in optimizing storage within the HCI environment. These strategies automate the movement of data between different storage tiers based on usage patterns, ensuring that frequently accessed data resides on high-performance storage while less-accessed data is placed on lower-cost storage. Caching techniques, such as read and write caching, accelerate data access by storing frequently accessed data on high-speed storage media. Consider hybrid storage configurations, combining solid-state drives (SSDs) for caching and traditional hard disk drives (HDDs) for cost-effective capacity storage.
4.5 Continuous Monitoring and Optimization
Implement real-time monitoring tools to provide visibility into the HCI environment's performance, health, and resource utilization, allowing IT teams to address potential issues proactively. Predictive analytics come into play to forecast future resource requirements and identify potential bottlenecks before they impact performance. Resource balancing mechanisms automatically allocate compute, storage, and network resources to workloads based on demand, ensuring efficient resource utilization. Continuous capacity monitoring and planning help organizations avoid resource shortages in anticipation of future growth.
5. Future Trends in HCI Storage and Data Management
Modernized storage solutions using HCI have transformed data management practices, revolutionizing how organizations store, protect, and utilize their data. HCI offers a centralized and software-defined approach to storage, simplifying management, improving scalability, and enhancing operational efficiency. The abstraction of storage from physical hardware grants organizations greater agility and flexibility in their storage infrastructure, adapting to evolving business needs. With HCI, organizations implement consistent security policies across their storage resources, reducing the risk of data breaches and ensuring data integrity. This flexibility empowers organizations to optimize resource utilization scale as needed. This drives informed decision-making, improves operational efficiency, and fosters data-driven strategies for organizational growth.
The future of Hyper-Converged Infrastructure storage and data management promises exciting advancements that will revolutionize the digital landscape. As edge computing gains momentum, HCI solutions will adapt to support edge deployments, enabling organizations to process and analyze data closer to the source. Composable infrastructure will enable organizations to build flexible and adaptive IT infrastructures, dynamically allocating compute, storage, and networking resources as needed. Data governance and compliance will be paramount, with HCI platforms providing robust data classification, encryption, and auditability features to ensure regulatory compliance. Optimized hybrid and multi-cloud integration will enable seamless data mobility, empowering organizations to leverage the benefits of different cloud environments. By embracing these, organizations can unlock the full potential of HCI storage and data management, driving innovation and achieving sustainable growth in the ever-evolving digital landscape.
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Hyper-Converged Infrastructure, Application Infrastructure
Article | July 19, 2023
Firms face challenges with managing their resources, and ensuring security & cost optimization, adding complexity to their operations. IaaS solves this need to maintain and manage IT infrastructure.
Contents
1. Infrastructure as a Service: Future of Cloud Computing
2. Upcoming Trends in IaaS
2.1 The Rise of Edge Computing
2.2 Greater Focus on Security
2.3 Enhancement in Serverless Architecture
2.4 Evolution of Green Computing
2.5 Emergence of Containerization
3. Final Thoughts
1. Infrastructure as a Service: Future of Cloud Computing
As digital transformation continues to reshape the business landscape, cloud computing is emerging as a critical enabler for companies of all sizes. With infrastructure-as-a-service (IaaS), businesses can outsource their hardware and data center management to a third-party provider, freeing up resources and allowing them to focus on their core competencies, reducing operational costs while maintaining the agility to adapt to changing market conditions.
With the increasing need for scalable computing solutions, IaaS is set to become a pivotal player in shaping the future of computing. IaaS is already emerging as a prominent solution for organizations looking to modernize their computing capabilities. This article will delve into the recent trends of IaaS and its potential impact on the computing industry, implying why IaaS is important for emerging businesses.
2. Upcoming Trends in IaaS
2.1 The Rise of Edge Computing
The rise in IoT and mobile computing has led to a challenge in the amount of data that can be transferred across a network in a certain period.
Due to its many uses, such as improving reaction times for self-driving cars and safeguarding confidential health information, the market for edge computing infrastructure is expected to reach a value of $450 billion.
(Source: CB Insights)
Edge computing is a technology that enables data processing to occur closer to its origin, thereby reducing the volume of data that needs to be transmitted to and from the cloud.
A mesh network of micro data centers that process or store critical data locally and push all received data to a central data center or cloud storage repository in a footprint of less than 100 square feet.
(Source: IDC)
Edge computing represents the fourth major paradigm shift in modern computing, following mainframes, client/server models, and the cloud. A hybrid architecture of interconnected IaaS services allows for low latency through edge computing and high performance, security, and flexibility through a private cloud. Connecting edge devices to an IaaS platform streamlines location management and enables remote work, thus looking forward to smoother future of IaaS.
An edge layer (fog computing) is required to optimize the architecture model with high-speed and reliable 5G connectivity, connecting edge devices with the cloud. This layer acts as autonomous distributed nodes, capable of analyzing and acting on real-time data. Doing so sends only the data required to the central infrastructure in an IaaS instance. By combining the advantages of edge computing in data capture with the storage and processing capabilities of the cloud, companies can take full advantage of the benefits of data analytics to leverage their innovation and optimization capabilities while simultaneously and effectively managing IoT devices on the edge.
IoT devices, also known as edge devices, possess the ability to analyze data in real time through the use of AI, ML, and algorithms, even in the absence of an internet connection. This technology yields numerous advantages, including superior decision-making, early detection of issues, and heightened efficiency. However, an IaaS infrastructure with top-notch computing and storage capabilities is an absolute necessity to analyze the data effectively.
2.2 Greater Focus on Security
Hackers might use cloud-based services to host malware through malware-as-a-service (MaaS) platforms or to distribute malware payloads using cloud-based apps and services. In addition, organizations often need more than they can secure in their IaaS footprint, leading to increased misconfigurations and vulnerabilities. Recognizing and reacting to an attack is called reactive security, whereas anticipating a dangerous event before it happens and intervening to prevent it is predictive safety. Predictive security is the future of cloud security.
The cybersecurity mesh involves setting up a distributed network and infrastructure to create a secure perimeter. This allows companies to centrally manage access to their data while enforcing security policies across the distributed network. It is a critical component of the Zero-Trust architecture. A popular IaaS cloud security trend is the multi-cloud environment. Multi-cloud proves effective when tools like security information and event management (SIEM) and threat intelligence are deployed.
DevSecOps is a methodology that incorporates security protocols at every stage of software development lifecycle (SDLC). This makes it convenient to deal with threats during the lifecycle itself. Since deploying DevOps, software releases have been shortened for every product release. DevSecOps proves to be secure and fast only with a fully automated software development lifecycle. The DevOps and security teams must collaborate to provide massive digital transformation and security. Digital services and applications need stronger and better security in exponential amounts. This methodology must be enforced in a CI/CD pipeline to make it a continuous process.
Secure access service edge (SASE) is a cloud-based architecture that integrates networking and software-as-a-service (SaaS) functions, providing them as a unified cloud service. The architecture combines a software-defined wide area network (SD-WAN) or other WAN with multiple security capabilities, securing network traffic.
2.3 Enhancement in Serverless Architecture
Serverless architecture apps are launched on demand when an event triggers the app code to run. The public cloud provider then assigns the resources necessary for the operation to occur. With serverless apps, containers are deployed and launched on demand when needed. This differs from the traditional IaaS cloud computing model, where users must pre-purchase capacity units for always-on server components to run their apps.
The app will incur minimal charges during off-peak hours with a serverless model. When there is a surge in traffic, it can scale up seamlessly through the provider without requiring DevOps involvement. A serverless database is a type of database that operates as a fully managed database-as-a-service (DBaaS). It automatically adjusts its computing and storage resources to match the demand, making it convenient for users. A serverless database is a cloud based service that eliminates the need to manage infrastructure, scaling, and provisioning. It allows developers to concentrate on constructing applications or digital products without the burden of managing servers, storage, or backups.
2.4 Evolution of Green Computing
In promoting green computing, infrastructure-as-a-service plays a significant role by allowing cloud providers to manage the infrastructure. This helps reduce the environmental impact and boosts efficiency by intelligently utilizing servers at high utilization rates. As a result, studies show that public cloud infrastructure is typically 2-4 times more efficient than traditional data centers, a giant leap forward for sustainable computing practices.
2.5 Emergence of Containerization
Containerization is a type of operating system virtualization where applications are executed in distinct user spaces called containers. These containers operate on the same shared operating system, providing a complete, portable computing environment for virtualized infrastructure. Containers are self-contained software packages operating in any environment, including private data centers, public clouds, or developer laptops. They comprise all the necessary components required for the right functioning of IaaS-adopted cloud computing.
3. Final Thoughts
With the expansion of multi-cloud environments, the emergence of containerization technologies like Docker and Kubernetes, and enhancements in serverless databases, IaaS is poised to become even more powerful and versatile in meeting the diverse computing needs of organizations. These advancements have enabled IaaS providers to offer a wide range of services and capabilities, such as automatic scaling, load balancing, and high availability, making it easier for businesses to build, deploy, and manage their applications swiftly in the cloud.
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Application Infrastructure
Article | December 20, 2021
The pandemic has had a seismic impact on the telecom sector. This is perhaps most notably because where and how the world goes to work has been re-defined, with nearly every business deepening its commitment to mobility. Our homes suddenly became our offices, and workforces went from being centrally managed to widely distributed. This has called for a heightened need for widespread, secure and high-speed connectivity around the clock.
5G has answered the call, and 5G location intelligence and big data can provide service providers with the information they need to optimize their investments.
Case in point: Juniper Research reported in its 5G Monetization study that global revenue from 5G services will reach $73 billion by the end of 2021, rising from just $20 billion last year.
5G flexes as connected devices surge
Market insights firm IoT Analytics estimates there will be more than 30 billion IoT connections by 2025. That's an average of nearly four IoT devices per person. To help meet the pressure this growth in connectivity is putting on telecom providers, the Federal Communications Commission (FCC) is taking action to make additional spectrum available for 5G services and promoting the digital opportunities it provides to Americans. The FCC is urging that investments in 5G infrastructure be prioritized given the "widespread mobility opportunity" it presents, as stated by FCC Chairwoman Jessica Rosenworcel.
While that's a good thing, we must also acknowledge that launching a 5G network presents high financial risk, among other challenges. The competitive pressures are significant, and network performance matters greatly when it comes to new business acquisition and retention. It's imperative to make wise decisions on network build-out to ensure investments yield the anticipated returns.
Thus, telcos need not – and should not – go it blindly when considering where to invest. You don't know what you don't know, which is why 5G location intelligence and big data can provide an incredible amount of clarity (and peace of mind) when it comes to optimizing investments, increasing marketing effectiveness and improving customer satisfaction.
Removing the blindfold
Location data and analytics provide telcos and Communications Service Providers (CSPs) with highly-specific insights to make informed decisions on where to invest in 5G. With this information, companies can not only map strategic expansion, but also better manage assets, operations, customers and products.
For example, with this intelligence, carriers can gain insight into the most desired locations of specific populations and how they want to use bandwidth. They can use this data to arm themselves with a clear understanding of customer location and mobility, mapping existing infrastructure and competitive coverage against market requirements to pinpoint new opportunities. By creating complex customer profiles rich with demographic information like age, income and lifestyle preferences, the guesswork is eliminated for where the telco should or shouldn’t deploy new 5G towers.
Further, by mapping a population of consumers and businesses within a specific region and then aggregating that information by age, income or business type, for example, a vivid picture comes to life of the market opportunity for that area.
This type of granular location intelligence adds important context to existing data and is a key pillar to data integrity, which describes the overall quality and completeness of a dataset. When telcos can clearly understand factors such as boundaries, movement and the customers’ surroundings, predictive insights can be made regarding demographic changes and future telecom requirements within a certain location. This then serves as the basis for a data-backed 5G expansion strategy. Without it, businesses are burdened by the trial-and-error losses that are all too common with 5G build-outs.
Location precision's myriad benefits
Improved location precision has many benefits for telcos looking to pinpoint where to build, market and provision 5G. Among them are:
Better data: Broadening insights on commercial, residential and mixed-use locations through easy-to-consume, scalable datasets provide highly accurate in-depth analyses for marketing and meeting customer demand.
Better serviceability insights: Complete and accurate location insights allow for a comprehensive view of serviceable addresses where products and services can be delivered to current and new customers causing ROI to improve and customers to be adequately served.
Better subscriber returns: Companies that deploy fixed wireless services often experience plan cancellations due to inconsistencies of signal performance, which typically result from the misalignment of sites with network assets. Location-based data provides operators with the ability to adapt their networks for signal consistency and serviceability as sites and structures change.
The 5G future
The role of location intelligence in accelerating development of new broadband services and driving ROI in a 5G world cannot be overstated. It adds a critical element of data integrity that informs network optimization, customer targeting and service provisioning so telecom service providers can ensure their investments are not made with blind hope.
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