The cloud stories enterprise IT leaders actually read.
Volume 341, Issue 4 · 16 articles from 6 issues
Public cloud's costs and constraints are pushing enterprises toward dedicated infrastructure over a default cloud-first strategy.
Author Guilherme Soubihe argues the cloud-first approach has exposed operational and financial drawbacks that make it unsuitable as a universal solution.
He cites a Barclays study showing 86% of CIOs plan cloud repatriation, plus compounding data egress fees, resource-contention bottlenecks for latency-sensitive workloads, and data-residency compliance complications.
The recommendation is a shift toward dedicated bare metal infrastructure combined with network-as-a-service, which eliminates virtualization overhead and enables sub-millisecond latency, cost predictability, and simpler compliance.
The core message: infrastructure strategy should prioritize flexibility and transparency rather than defaulting to cloud convenience.
Cloud security monitoring best practices that help K-12 districts catch insider threats before they become breaches.
Insider threats pose significant risks to K-12 schools and often originate from authorized users rather than external attackers.
They can stem from accidental mistakes, compromised user accounts, or employees and students unknowingly exposing sensitive information.
The article recommends continuous user activity monitoring, automated alerts, file sharing oversight, behavioral baselines, and prioritization of high-risk accounts.
It argues that cloud-native tools providing real-time visibility into Google Workspace and Microsoft 365 enable faster investigation and response before incidents escalate into major breaches.
Over 80% of enterprises are rethinking cloud strategy to accommodate expanding AI workloads, favoring hybrid approaches.
An Information Services Group report finds that more than 80% of enterprises are reconsidering their cloud strategies to accommodate expanding AI workloads.
Organizations are increasingly adopting hybrid approaches that combine public cloud, private cloud, colocation, edge, and sovereign environments for greater control and flexibility.
Key drivers include managing escalating compute costs, reducing vendor lock-in, and ensuring data sovereignty for long-term AI governance.
Cloud vendors are responding with AI-optimized infrastructure, and neocloud providers are expected to capture 20% of the $267 billion AI cloud market by 2030.
Mandiant warns that unauthenticated serverless cloud functions are being exploited to steal secrets and service account tokens.
Google's Mandiant security team has identified a rising threat from exposed serverless cloud functions that lack authentication, a risk growing as generative AI adoption accelerates.
Attackers exploit these functions through application-level attacks to extract secrets and service account tokens, potentially gaining access to entire cloud environments.
Researchers recommend multi-layered defenses including code scanning, least-privilege IAM controls, and isolating public-facing services in dedicated cloud projects.
Mandiant notes that hardening Cloud Run services is only one part of a secure architecture, and defense-in-depth using VPC controls is essential to prevent lateral movement after compromise.
Cloud infrastructure revenue exceeded $143B in Q2 2026, growing 43% year on year with AI driving acceleration.
Enterprise cloud infrastructure spending reached over $143 billion in the second quarter of 2026, the fastest growth in eight years at 43% year on year.
AI-specific cloud services grew 165%, becoming the primary driver of market expansion. The big three providers, AWS at 28%, Microsoft Azure at 20%, and Google Cloud at 15%, collectively control 67% of the market, up from 63% a year earlier.
Public IaaS and PaaS platforms expanded 47% during the quarter, with trailing 12-month revenues reaching $500 billion globally.
Cloud computing expertise is now critical for IT professionals due to widespread business adoption and growing career opportunities.
As organizations increasingly migrate applications and data to cloud environments, cloud computing skills have become essential for modern IT professionals.
The article outlines key technical competencies including virtualization, storage solutions, security practices, and automation, while highlighting career paths such as Cloud Engineer and DevOps Engineer.
Learning approaches should focus on foundational networking knowledge, hands-on practice with cloud platforms, and staying current with emerging technologies. Security has evolved into a fundamental requirement alongside infrastructure management, and professionals who develop these skills will remain valuable across multiple industries.
Cloud platforms centralize asset lifecycle tracking and analytics to improve IT asset recovery, data destruction, and compliance.
Cloud technology enables organizations to centralize tracking of IT assets across their full lifecycle, from deployment through retirement.
The article stresses that robust data destruction protocols, including software sanitization and physical shredding, are essential to keep sensitive information out of secondary markets.
Advanced analytics give visibility into asset depreciation rates and residual values, helping companies optimize procurement and recover capital from refurbished equipment.
Certified IT asset recovery services also ensure compliance with environmental regulations and data protection standards while maintaining chain-of-custody documentation for audits.
Cloud native infrastructure provides the essential foundations that enterprise AI systems inherit rather than replace.
Alan Shimel argues that AI workloads are not replacing cloud native technology but rather building upon its established foundations of scheduling, identity, observability, and governance.
He contends that organizations focusing solely on model selection miss the critical operational capabilities-deployment, security, cost controls, and audit trails-that determine whether AI can safely operate in production.
While autonomous agents introduce new challenges around identity and permissions, these represent extensions of existing cloud native capabilities rather than reasons to abandon proven infrastructure patterns.
An annual roundup of the leading tools for tracking, forecasting, and optimizing cloud spending.
Solutions Review's listing of the best cloud spend optimization tools is an annual mashup of products that best represent current market conditions.
Featured tools include Apptio for tracking, forecasting, and budgeting cloud expenses; AWS Cost Explorer for native cost analysis and financial transparency; and Cloudability for monitoring and analyzing cloud costs across environments.
CloudCheckr and Cloud Custodian are highlighted for demystifying the complexity of cloud expenses and helping organizations stay within budget. CloudZero and Datadog also appear as options for cloud cost management and analysis, with the common theme being informed resource allocation decisions.
Eight platforms automate multi-cloud infrastructure design to keep architecture synchronized with operational reality.
Modern cloud environments change too rapidly for static documentation to stay accurate. Tools such as Infros provide real-time multi-cloud relationship mapping, while Cycloid standardizes deployment workflows across teams.
Qovery automates Kubernetes environment provisioning and Kratix enables reusable platform capabilities. High-performing infrastructure teams continuously review architecture, build standardized patterns, and reduce manual design decisions.
Organizations should evaluate platforms on synchronization capability, developer comprehension, standardization support, and future scalability across AWS, Azure, and GCP.
Cloud architects must focus on unified control planes, cost observability, and team capabilities to avoid costly failures.
Organizations deploying cloud infrastructure frequently ignore fundamental engineering principles, producing escalating costs and operational complexity.
David Linthicum identifies three overlooked concepts: establishing common control planes across heterogeneous environments to reduce silos and redundant security tooling, implementing unified cost observability to track spending across providers, and accounting for human factors so teams have the skills to operate what is built.
Without these basics, architectures become expensive to maintain and difficult to run at scale.
Healthcare systems adopt varied cloud strategies driven by AI needs and infrastructure modernization.
Healthcare organizations are pursuing different cloud infrastructure strategies based on their specific priorities and technical requirements.
WellSpan completed a comprehensive migration to AWS, Seattle Children's adopted a multi-cloud approach, and CHOP established a cloud-first policy with exceptions.
Key drivers include improved cloud economics, AI capability demands, and the need to unlock data for innovation.
Successful migrations require strong organizational alignment, standardized processes, workforce training, and realistic timelines rather than purely technical solutions.
Docker images are a major supply chain risk, and vulnerability scanning alone cannot detect zero-days or malicious code.
Docker images have become critical attack vectors in software supply chains, where a single compromised artifact can spread across environments.
Most organizations rely on vulnerability scanning as a baseline, but scanning cannot detect zero-day exploits, obfuscated malicious code or logic-based backdoors.
A comprehensive strategy requires layered defenses: container runtime security tools for real-time monitoring, secure build practices using minimal base images, continuous monitoring across the image lifecycle, and strict CI/CD policy enforcement to block insecure deployments.
Modernization and correct workload placement matter more than moving applications between cloud and on-premises.
Organizations rethinking cloud strategy should ask whether workloads were ever properly modernized rather than simply relocating them.
Many applications were lifted and shifted without redesign for cloud environments, producing poor adoption and cost overruns that repatriation alone will not fix.
The recommended approach is to evaluate each workload's specific requirements, put user needs at the center of modernization, and use AI to inform - not make - placement decisions across hybrid environments.
Multi-cloud deployment reduces vendor lock-in and improves financial control versus single-cloud strategies.
Single-cloud strategies concentrate operational, financial, and regulatory risk through vendor lock-in and service outages. Distributing workloads across providers improves resilience, eases compliance alignment, and opens access to specialized capabilities.
Success requires organizational change, cross-vendor expertise, standardized governance, and disciplined cost management through FinOps practices.
The article recommends tracking deployment velocity, cross-cloud failover time, workload portability, and provider dependency ratios to measure both financial performance and risk reduction.
An argument for auditing cloud-native platform layers against a five-point value framework before adding more.
Author Yogesh Tatwal contends cloud-native platforms accumulate complexity as teams add containers, orchestration, CI/CD, observability and security layers without evaluating their collective cost, since each layer adds hidden burdens beyond licensing: 'configuration, upgrades, monitoring, troubleshooting, security requirements, documentation.'
He warns teams often respond to poor resource utilization by scaling capacity rather than diagnosing root causes, and questions whether automation reduces total engineering effort or 'simply moves that effort somewhere else.' His proposed evaluation framework scores each component on value, usage, cost, dependency and ownership, concluding 'every platform component should earn its place.'