Infrastructure, Cloud & DevOps

  • Platform engineering is the foundation of digital transformation success, as this discipline directly affects an organization’s ability to rapidly, continuously, and cost-effectively deliver high-quality software in anticipation of and in response to complex and dynamic market requirements. Today’s landscape of cloud-native tools, technologies, infrastructure resources, and application development paradigms ultimately define optimal platform engineering strategies, but executing those strategies is often a complex and highly demanding task for organizations across all sizes and industries.

    To address these challenges, organizations are turning to platform engineering tools and best practices to accelerate and optimize the process of designing, building, and managing scalable and secure self-service platforms and workflows to optimize developer productivity. To gain further insights into these trends, TechTarget’s Enterprise Strategy Group surveyed 376 application developers and IT professionals at organizations in North America (US and Canada) involved with or responsible for using, evaluating, implementing, and managing platform engineering solutions and practices.

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  • Cloud-native DevOps and platform engineering are key enablers of digital transformation at scale. With the advent and aid of generative AI (GenAI), organizations can significantly improve the maintenance, monitoring, and automation of their environments alongside the steady presence of rapid data growth. As development platforms evolve to support more diverse tools, development teams and their collaborative internal stakeholders are reassessing their methods, policies, and strategies to identify areas for optimization and ensure GenAI-led improvements stay in line with larger corporate goals and policies.

    To gain further insight into the current status and near future of AI in application development, TechTarget’s Enterprise Strategy Group surveyed 325 IT and application development professionals at organizations in North America (US and Canada) involved with AI technology and processes, including generative AI.

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  • Under nearly universal mandates to accelerate IT operations, organizations across industries are turning to AI and GenAI to help automate processes, streamline knowledge management, and more. Recent research by TechTarget’s Enterprise Strategy Group discovered that different industries have diverse priorities and expectations for AI’s potential in these regards.

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  • With data now at the forefront of practically every modern business strategy, IT operations teams carry a massive responsibility to ensure the proper infrastructure is in place to deliver that data to stakeholders with high levels of availability, performance, and security. Recent research by TechTarget’s Enterprise Strategy Group shows that while this burden is consistent across all organization sizes, teams tend to face different requirements depending on the scope of their employee base.

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  • Pure Storage has unveiled Real-time Enterprise File, a wide-ranging software update to its storage platform that enables IT organizations to better respond to the realities of managing modern file storage supporting demanding workloads such as AI, analytics, and VDI. The update is designed to enable customers to more quickly respond to changing application demands in real time, while reducing total cost of ownership.

  • HPE Private Cloud AI Available for Virtual Assistants

    This month, HPE announced that its HPE Private Cloud AI is available to order. This new integrated and pre-validated solution combines hardware and software from both HPE and NVIDIA and it is designed to accelerate deployment of infrastructure for AI and shorten time to value for AI initiatives. The new solution accelerators give enterprises the ability to deploy virtual assistants with one click and operationalize them in seconds, simplifying the process from end to end.

    To learn more, download the free brief, HPE Private Cloud AI Available for Virtual Assistants.

  • This month, IBM announced the 10th generation of its DS8000 enterprise storage solution, designed to deliver mission-critical resilience and high performance to support mainframe environments and provide enterprise-level application consolidation. In this latest generation, IBM integrates multiple enhancements, including upgrades of the internal architecture with NVME technology and PCIe Gen4.

    To learn more, download the free brief, IBM Enhances DS8000 Enterprise Storage in Its 10th Generation.

  • This Complete Survey Results presentation focuses on the impacts of microservices, cloud-native application challenges, containers, multi-cluster and multi-namespace deployments, serverless deployments, infrastructure-as-code, open source tools for cloud management and automation, DevOps practices, and platform engineering.

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  • In the face of ransomware and other cybersecurity threats, organizations are concerned with cyber resilience, especially with the resilience of their sensitive data assets. For most organizations, data is a prime asset that drives core business processes, and in many cases, data is the business. Teams face unique challenges in their data resilience initiatives that typically combine data security posture management, data protection (recoverability), and data governance.

    To gain further insight into these trends, TechTarget’s Enterprise Strategy Group surveyed 370 IT professionals at organizations in North America (US and Canada) familiar with and/or responsible for data security, data protection, and data governance technologies in North America (US and Canada). This survey explored the volume and distribution of sensitive data, the most important data to protect, the automation of sensitive data discovery, data classification strategies, data resilience perceptions and strategies, data security posture management strategies, data resilience stakeholders, and spending plans.

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  • Oracle Cloud World 2024 was an impressive showcase of cutting-edge advancements, particularly in the Oracle Database 23ai and artificial intelligence. The event delivered valuable insights and thought leadership, with one announcement standing out as a potential game changer: Oracle’s collaboration with AWS, which came after its announcements with Google Cloud and Microsoft Azure in the past year. This completes the circle and makes Oracle’s Autonomous Database and Oracle Exadata database capabilities available across these platforms. This strategic move is a significant shift for Oracle, enhancing its multi-cloud offerings and opening new opportunities for customers across these cloud ecosystems.

    This multi-cloud expansion holds tremendous benefits for both Oracle customers and those using AWS, Google Cloud, and Microsoft Azure. By making Oracle’s capabilities available, the company is empowering businesses with greater flexibility, enabling them to leverage the power of Oracle’s high-performance cloud solutions while maintaining their existing investments in other cloud providers. This partnership brings enhanced scalability, flexibility, and innovation. This will be particularly valuable for enterprises looking to integrate Oracle’s AI and database capabilities within their diverse cloud infrastructures while also taking advantage of each cloud’s AI capabilities, such as Amazon Bedrock, and easy access to all leading large language models (LLMs). AWS also offers a wide breadth of tools for generative AI development, which Oracle customers can leverage.

    Aside from the multi-cloud announcement, Oracle’s Database 23ai also introduced exciting new functionalities. Two areas of particular interest were the database’s vector capabilities and its ability to handle relational, graph, and document data models. The inclusion of vector search opens the door to more efficient and powerful AI-driven queries, making it easier to analyze and extract insights from large data sets. This is crucial in modern AI applications, where the ability to search and interpret data points quickly can drive better decisions and innovation with vectors offering advanced similarity capabilities.

    Vector databases, or databases with vector search capabilities, are increasingly becoming essential in the modern landscape of AI and machine learning. They enable the efficient processing of unstructured data, such as text, images, and complex data sets. They do this by transforming data into high-dimensional vectors, which can then be analyzed and searched using algorithms that calculate similarity between these vectors. The value of vector capabilities lies in their ability to perform similarity searches and provide contextually relevant results, which are crucial for AI models such as LLMs, image recognition systems, and recommendation engines. For example, in natural language processing applications, vector search can enable AI to find patterns and relationships between words, sentences, or documents based on meaning rather than just keyword matching. This means that AI can respond with more accurate and relevant information in everything from chatbot responses to complex business queries. At Oracle World, some impressive companies, such as PayPal and Deutsche Bank, shared their use of vector similarity capabilities in unique ways, such as vectorizing images and even support tickets to then use vector search to identify similar cases for comparison. This demonstrates vector capabilities beyond just AI use cases.

    For Oracle 23ai users, this translates into more powerful AI-driven solutions that can access and interpret vast amounts of unstructured data. Whether it’s finding relevant documents based on natural language queries, performing image similarity searches, or enhancing recommendation systems, vector search enables faster, more accurate insights. Additionally, it opens the door for better personalization and contextual understanding, which can be game-changing for industries like e-commerce, finance, and healthcare, where precision and relevance are key. In addition, Oracle 23ai’s flexibility to manage relational, graph, and document data in one database is highly valuable to developers and businesses. This unified approach simplifies the management of diverse data types, enabling organizations to harness their data more effectively for AI, machine learning, and advanced analytics. Oracle Cloud World 2024 demonstrated how Oracle pushes the boundaries of database technology and AI innovation while embracing a multi-cloud future.

  • In an era when IT operations teams are under tremendous pressure to accelerate processes, enable digital transformation, and reduce the unit cost and environmental impact of compute, AI can be a key enabling technology. Whether through generative AI (GenAI)-based tools, copilots, natural language querying, or advanced usage of causal and predictive AI, IT operations teams have an ever-increasing set of tools available to help them achieve their goals, improve stakeholder satisfaction, and optimize for their important metrics. TechTarget’s Enterprise Strategy Group recently surveyed IT professionals involved with observability, ITSM, and AIOps technologies and processes to gain insights into these trends.

    To learn more about these trends, download the free infographic, Generative AI in IT Operations: Fueling the Next Wave of Modernization.

  • The State of IT-driven Sustainability

    This Complete Survey Results presentation focuses on IT sustainability environments, perceptions and practices around sustainability, factors impacting and influencing purchases, the impact of AI, techniques for mitigating the impact of AI on sustainability, and stakeholder groups involved in and most impacted by sustainability initiatives.

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