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Infrastructure, Cloud & DevOps

  • Saturated Application Environments Push AI-led Observability to Its Early Limits

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    Torsten Volk

    Organizations are constantly developing and deploying new applications in an effort to supercharge business processes, enhance employee productivity, deliver unique customer experiences, and more. As a result, many enterprises have ended up with a massive application portfolio. Recent research by Enterprise Strategy Group investigated how application volumes can affect an organization’s observability needs now and in the future.

    Already an Enterprise Strategy Group client? Log in to read the full report. If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us. 

  • Industries Dive Headfirst Into AI-enhanced Observability

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    Torsten Volk

    Observability vendors are in a race to leverage AI to automate root cause analysis, enable self-healing, optimize resources, reduce alert noise, automate log analysis, and deliver contextualized actionable insights to end users. Organizations across industries recognize that implementing AI-enhanced observability tools can give them strategic insights that optimize the economics of their application development and platform engineering practices. However, Enterprise Strategy Group’s recent research reveals that an organization’s industry significantly influences three key aspects of AI-enhanced observability: the specific operational benefits realized, perceived return on investment, and how frequently teams override AI recommendations.

    Already an Enterprise Strategy Group client? Log in to read the full report. If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us. 

  • The State of DevSecOps and Cloud Security Platforms

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    Melinda Marks

    As organizations today face pressure to boost their productivity and scale while efficiently optimizing resources, they are increasingly utilizing cloud services to deliver cloud-native applications. In recognition of the impact of security incidents on their cloud-native applications, cybersecurity teams need to look for ways to gain unified visibility and control to efficiently manage risk and rapidly respond to attacks by incorporating security into DevOps processes (DevSecOps) and utilizing cloud security platforms. Enterprise Strategy Group recently surveyed IT, cybersecurity, and application development professionals to gain insights into these trends.

    To learn more, download the free infographic, The State of DevSecOps and Cloud Security Platforms.

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  • State of DevSecOps and Cloud Security Platforms: Scaling Security Practices to Accommodate Cloud-native Application Development

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    Melinda Marks

    This Complete Survey Results presentation focuses on the scope of cloud-native application development environments, including the top challenges associated with securing cloud-native applications and the security solutions in place to protect cloud infrastructure and applications.

    Already an Enterprise Strategy Group client? Log in to read the full report. If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us. 

  • State of DevSecOps and Cloud Security Platforms: Scaling Security Practices to Accommodate Cloud-native Application Development

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    Melinda Marks

    As organizations today face pressure to boost their productivity and scale while efficiently optimizing resources, they are increasingly utilizing cloud services to deliver cloud-native applications. Cybersecurity teams recognize the impact of security incidents on their cloud-native applications, including application downtime, business disruption, compliance fines, and negative brand reputation. They need effective cybersecurity solutions that address security risk from development to deployment to ensure security teams can support business growth.

    The efforts to modernize application development utilizing cloud services are focused on optimizing efficiency for growth and scale. However, having separate, siloed security tools that work in different parts of the software development lifecycle works against the speed and efficiency that organizations are trying to achieve. As a result, organizations need to look for ways to gain unified visibility and control to efficiently manage risk and rapidly respond to threats and attacks by incorporating DevSecOps and utilizing cloud security platforms.

    To gain insights into these trends, Enterprise Strategy Group surveyed 373 IT, cybersecurity, and application development professionals in North America (U.S. and Canada) responsible for evaluating or purchasing cloud security technology products and services.

    Already an Enterprise Strategy Group client? Log in to read the full report. If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us. 

  • IBM Aims to Boost AI Inferencing With ‘Content Aware’ Storage

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    Simon Robinson

    IBM made a number of announcements recently that highlight its ongoing commitment to help customers accelerate their AI journeys. Of particular note is a pending capability developed by IBM Research that adds ‘content awareness’ to both its own and third-party storage, which when integrated with the NVIDIA Data Platform will bring vector processing closer to the storage layer to substantially improve the effectiveness of RAG-based inferencing.

    To learn more, download the free brief, IBM Aims to Boost AI Inferencing With ‘Content Aware’ Storage.

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  • Open Source LLMs for Everyone at Scale: Red Hat Acquires Neural Magic

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    Torsten Volk

    Red Hat’s acquisition of Neural Magic addresses enterprise demand for greater performance and cost efficiency when building, deploying, and managing AI-driven applications, enabling organizations to select and optimize open source large language models (LLMs) according to their individual requirements. By integrating Neural Magic’s expertise in inference performance engineering and model optimization, Red Hat strengthens its AI portfolio, complementing existing capabilities for scalable AI lifecycle orchestration across hybrid cloud environments. This combination has the potential to notably increase Red Hat’s differentiation in the rapidly evolving generative AI landscape.

    To learn more, download the free brief, Open Source LLMs for Everyone at Scale: Red Hat Acquires Neural Magic.

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  • Observability in Action: Enhancing Developer Productivity in Real-world Scenarios

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    Torsten Volk

    The Dynatrace Observability for Developers platform focuses on addressing the key reasons why developers often do not take advantage of observability.

    To learn more, download the free brief, Observability in Action: Enhancing Developer Productivity in Real-world Scenarios.

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  • Transforming Observability and Monitoring Through AI

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    Torsten Volk

    AI increasingly enables organizations to understand their limitations and then optimally allocate their technology spending, maximizing efficiency and driving superior business outcomes. Organizations that harness AI-driven observability, visibility, and monitoring platforms can receive data-driven, actionable insights that transform the economics of application development and platform engineering. But technology leaders and platform teams are faced with a key challenge: Identifying and deploying AI tools that are ideal for their environment, expertise, and culture. TechTarget’s Enterprise Strategy Group recently surveyed application developers and IT professionals to gain insights into these trends.

    To learn more, download the free infographic, Transforming Observability and Monitoring Through AI.

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  • Transforming Observability and Monitoring Through AI

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    Torsten Volk

    AI increasingly enables organizations to understand their limitations and then optimally allocate their technology spending, maximizing efficiency and driving superior business outcomes. Organizations that harness AI-driven observability, visibility, and monitoring platforms can receive data-driven, actionable insights that transform the economics of application development and platform engineering.

    But technology leaders and platform teams are faced with a key challenge: identifying and deploying AI-driven observability tools that fit their environment, expertise, and culture. Only then can they seamlessly enhance system reliability and performance through transparent and actionable insights. Organizations must prioritize explainability for stakeholders to understand the reasoning behind AI decisions to foster trust and refine AI’s decision-making processes and criteria.

    To gain further insight into these trends, Enterprise Strategy Group surveyed 377 application developers and IT professionals at organizations in North America (U.S. and Canada) involved with observability and monitoring technology and processes at their organization.

    Already an Enterprise Strategy Group client? Log in to read the full report. If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us. 

  • Transforming Observability and Monitoring Through AI

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    Torsten Volk

    This Complete Survey Results presentation focuses on observability environments and teams, full-stack observability capabilities, observability-related tasks, AI recommendation practices, GenAI copilots, AI observability benefits and challenges, observability effectiveness, and spending preferences.

    Already an Enterprise Strategy Group client? Log in to read the full report. If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us. 

  • Pure Storage Deepens AI-at-scale Focus With FlashBlade//EXA

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    Simon Robinson

    Pure Storage is doubling down on the enormous potential market around providing storage and data management for running AI at scale with the recent unveiling of FlashBlade//EXA, a high-performance storage solution designed to handle the most demanding AI and high-performance computing (HPC) workloads. The announcement underscores Pure’s intent to become a force among the large- and hyper-scale players creating storage and data solutions for next-generation AI workloads.

    To learn more, download the free brief, Pure Storage Deepens AI-at-scale Focus With FlashBlade//EXA.

    Download Now