How to Manage Secrets in Kubernetes
Learn how Kubernetes Secrets work, how they differ from ConfigMaps, and how to create and manage secrets safely — including cloud-native secret management options.
Learn how Kubernetes Secrets work, how they differ from ConfigMaps, and how to create and manage secrets safely — including cloud-native secret management options.
Southeast Asia’s cloud computing market is undergoing rapid transformation. From hybrid and multi-cloud adoption to data sovereignty and confidential computing, here are the key trends shaping the region’s digital future.
From enabling remote work to powering AI-driven outbreak prediction, cloud computing has become a critical tool in the global response to COVID-19. Here is how organisations are putting it to work.
Google Cloud launched AI Platform Pipelines in beta to streamline ML workflows, while AWS introduced Bottlerocket, an open-source OS purpose-built for running containers. Here is what both announcements mean for DevOps and platform engineering teams.
Google Cloud announced its Global Mobile Edge Cloud service and Anthos for Telecoms platform, with AT&T becoming the first operator to explore edge compute capabilities alongside 5G.
A study published in Science found that cloud computing output grew 600% between 2010 and 2018 while energy consumption rose only 6%. Efficiency gains from hyperscalers like Google, Microsoft, and Amazon are the primary reason.
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Kubernetes has grown far beyond basic container orchestration. Discover five ways enterprises are extending the platform—from on-premises deployments and stateful applications to AI workloads and full infrastructure control.
HeleCloud CEO Dob Todorov explains why organisations are discovering that AWS does not manage everything for them, why specialist MSPs still add value in the cloud era, and where the market is heading.
AI adoption is accelerating across the enterprise, but failure rates remain high. Learn the three critical factors—organizational education, continuous iteration, and actionable insights—that separate successful AI projects from costly failures.
Data is no longer generated only in traditional data centres. As edge computing, multi-cloud adoption, and AI-driven analytics reshape the landscape, engineering and operations teams must rethink how they manage data wherever it lives.
Edge computing was set to reshape network architecture in 2020 and beyond. Here are the key industry predictions, growth drivers, and practical implications for DevOps and infrastructure teams.
A look back at the most significant technology developments of 2019, including Kubernetes adoption for big data, AI momentum, IoT investment, and the push for data privacy legislation.
AWS SageMaker Studio launched with bold promises as an integrated IDE for machine learning. We examine its key features—Notebooks, Debugger, Model Monitor, AutoPilot, and Experiments—and where the implementation falls short for data scientists.
Cloud computing, AI, and digital transformation have introduced a set of genuine contradictions that engineers and business leaders must grapple with. Understanding these paradoxes can sharpen how teams design systems, hire talent, and derive value from data.
Google Cloud showcased healthcare-focused cloud solutions at RSNA 2019, including managed DICOM services, HIPAA-supported deployments, and AI-powered medical imaging competitions in partnership with Kaggle.
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AWS DeepRacer Evo brings stereo cameras, LIDAR sensors, new race modes, and expanded league events to Amazon’s reinforcement-learning racing platform. Here’s what changed and why it matters for ML developers.
As AWS re:Invent 2019 approached, industry analysts and cloud architects shared their predictions on the technologies and themes AWS was expected to highlight, from AI and machine learning to security by default and multi-cloud support.
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