The adoption of Kubernetes-enabled infrastructures and applications has revealed the challenge involved in enabling persistent, reliable data storage in an ephemeral compute…
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GigaOm Sonar Report for Storage as a Service
Storage as a service (STaaS) is a subscription-based model for data storage that provides customers with a cloud-like experience in terms of…
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Cloud Analytics Platform Total Cost of Ownership
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning.…
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Cloud Parallel File Systems
The latest organizational initiatives involving artificial intelligence (AI), machine learning (ML), high performance computing (HPC), and containerized application spaces necessitate a robust…
Read MoreKey Criteria for Evaluating Disaster Recovery and Business Continuity as a Service Solutions
Disaster recovery (DR) provides rapid restoration of one or more applications or systems when the data center where they reside is, or…
Read MoreGigaOm Radar for Network Validation
With business-critical services on the line, managing the network holistically is essential for ensuring operational consistency. Many enterprises address network governance with…
Read MoreGigaOm Radar for Data Migration Tools
Data migration has evolved over the years. Simple use cases such as on-premises migrations linked to hardware lifecycle refreshes or geographical data…
Read MoreGigaOm Radar for Distributed Cloud File Storage
File storage is a critical component of every hybrid cloud strategy—especially for use cases that support collaboration—and distributed cloud file storage that…
Read MoreKey Criteria for Evaluating Digital Experience Platforms
Digital experience platforms (DXPs) have superseded web content management (WCM) platforms as the go-to systems for building engaging, personalized customer experiences for…
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Google Anthos Bare Metal vs. Do-It-Yourself Deployments
The transformative impact of the cloud on businesses has prompted a broad and rapid migration to cloud-first strategies. Yet as organizations transition…
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Transactional and Analytical Workloads
Competitive data-driven organizations rely on data-intensive applications to win in the digital service economy. These applications require a robust data tier that can…
Read MoreEnterprise Readiness of Cloud MLOps: A GigaOm Benchmark Report
MLOps is a practice for collaboration between data science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of machine learning…
Read MoreSQL Transaction Processing and Analytic Performance Price-Performance Testing
The fundamental underpinning of an organization is its transactions. They must be done well, with integrity and performance. Not only has transaction…
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Everbridge xMatters: On-Call Alert and Incident Response
The way enterprise organizations respond to unexpected IT incidents is at a watershed moment. As organizations move their core operations onto SaaS…
Read MoreCosts and Benefits of .NET Application Migration to the Cloud
Thousands of legacy applications written using development frameworks such as ASP.NET are still being used by organizations, often running in on-premises environments.…
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NetApp Cloud Insights: A GigaOm Benchmark Report
This report format incorporates a field test/benchmark with a white paper-level paper. The body of the paper provides only a summary of…
Read MoreHealthcare Natural Language Processing
Growing data volumes and differences in terminology, language, abbreviations, and even spelling in clinical documents make it challenging for medical professionals to…
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API and Microservices Management Benchmark
Application programming interfaces, or APIs, are a ubiquitous method and de facto standard of communication among modern information technologies. The information ecosystems…
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High Performance Application Security Testing
Data, web, and application security have evolved dramatically over the past few years. Just as new threats abound, the architecture of applications—how…
Read MoreEnterprise Readiness of Cloud MLOps
MLOps is a practice for collaboration between data science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of “machine learning”…
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