{"id":53053,"date":"2025-09-16T11:56:51","date_gmt":"2025-09-16T11:56:51","guid":{"rendered":"https:\/\/www.devopsschool.com\/blog\/?p=53053"},"modified":"2026-02-21T08:26:00","modified_gmt":"2026-02-21T08:26:00","slug":"top-10-ai-edge-computing-solutions-tools-in-2025-features-pros-cons-comparison","status":"publish","type":"post","link":"https:\/\/www.devopsschool.com\/blog\/top-10-ai-edge-computing-solutions-tools-in-2025-features-pros-cons-comparison\/","title":{"rendered":"Top 10 AI Edge Computing Solutions Tools in 2026: Features, Pros, Cons &amp; Comparison"},"content":{"rendered":"\n<h1 class=\"wp-block-heading\">Introduction<\/h1>\n\n\n\n<p>In 2026, <strong>AI Edge Computing Solutions<\/strong> are no longer a futuristic concept\u2014they are at the core of how businesses process, analyze, and act on data in real time. Unlike traditional cloud-based AI models, edge computing pushes intelligence closer to the source of data\u2014whether it\u2019s IoT devices, autonomous vehicles, smart cameras, or industrial robots.<\/p>\n\n\n\n<p>This shift is critical for industries where <strong>low latency, high security, and uninterrupted connectivity<\/strong> matter most. Healthcare systems rely on AI edge tools for patient monitoring, factories use them for predictive maintenance, and cities deploy them for smart infrastructure. With the explosion of 5G networks, connected devices, and demand for real-time analytics, choosing the right AI edge computing software in 2026 can define the efficiency and competitiveness of an organization.<\/p>\n\n\n\n<p>In this blog, we\u2019ll explore the <strong>Top 10 AI Edge Computing Solutions Tools in 2026<\/strong>, highlight their features, weigh their pros and cons, and provide a comparison guide to help you pick the best fit for your industry and budget.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h2 class=\"wp-block-heading\">Top 10 AI Edge Computing Solutions Tools in 2026<\/h2>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"273\" height=\"185\" src=\"https:\/\/www.devopsschool.com\/blog\/wp-content\/uploads\/2025\/09\/8.png\" alt=\"\" class=\"wp-image-53718\" style=\"width:483px;height:auto\"><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\">1. <strong>NVIDIA Jetson Platform<\/strong><\/h3>\n\n\n\n<p><strong>Short Description:<\/strong> NVIDIA Jetson is a leading AI edge platform, widely used for robotics, computer vision, and autonomous systems. It provides powerful GPU-accelerated AI capabilities at the edge.<\/p>\n\n\n\n<p><strong>Key Features:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>High-performance GPU computing optimized for AI workloads<\/li>\n\n\n\n<li>Supports TensorRT, CUDA, and deep learning frameworks<\/li>\n\n\n\n<li>Scalable from Jetson Nano (entry-level) to AGX Orin (enterprise-grade)<\/li>\n\n\n\n<li>Pre-trained models available via NVIDIA NGC<\/li>\n\n\n\n<li>Strong developer ecosystem and SDKs<\/li>\n<\/ul>\n\n\n\n<p><strong>Pros:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Industry-leading AI performance at the edge<\/li>\n\n\n\n<li>Rich ecosystem for robotics and computer vision<\/li>\n\n\n\n<li>Scalable hardware options<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Hardware costs can be high for large-scale deployments<\/li>\n\n\n\n<li>Requires advanced AI\/ML expertise<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h3 class=\"wp-block-heading\">2. <strong>Microsoft Azure IoT Edge<\/strong><\/h3>\n\n\n\n<p><strong>Short Description:<\/strong> A cloud-integrated edge AI service enabling organizations to run AI, analytics, and services directly on IoT devices.<\/p>\n\n\n\n<p><strong>Key Features:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Native integration with Azure Machine Learning and IoT Hub<\/li>\n\n\n\n<li>Containerized deployment of AI models<\/li>\n\n\n\n<li>Edge runtime supports offline operations<\/li>\n\n\n\n<li>Security with automatic device provisioning<\/li>\n\n\n\n<li>Seamless cloud-to-edge synchronization<\/li>\n<\/ul>\n\n\n\n<p><strong>Pros:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Strong integration with Azure cloud ecosystem<\/li>\n\n\n\n<li>Enterprise-grade security and compliance<\/li>\n\n\n\n<li>Flexible containerized model deployment<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Best suited for businesses already in the Azure ecosystem<\/li>\n\n\n\n<li>Pricing may scale up with large deployments<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h3 class=\"wp-block-heading\">3. <strong>Amazon AWS IoT Greengrass<\/strong><\/h3>\n\n\n\n<p><strong>Short Description:<\/strong> AWS\u2019s edge AI service that lets you run machine learning models locally on devices while securely interacting with the AWS cloud.<\/p>\n\n\n\n<p><strong>Key Features:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Local inference with ML models<\/li>\n\n\n\n<li>Supports AWS SageMaker for model training\/deployment<\/li>\n\n\n\n<li>Secure device authentication and communication<\/li>\n\n\n\n<li>Lambda functions for custom edge logic<\/li>\n\n\n\n<li>Integration with AWS IoT Core<\/li>\n<\/ul>\n\n\n\n<p><strong>Pros:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Tight integration with AWS ML\/IoT stack<\/li>\n\n\n\n<li>Highly secure and scalable<\/li>\n\n\n\n<li>Strong developer support<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Vendor lock-in to AWS ecosystem<\/li>\n\n\n\n<li>May require significant technical setup<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h3 class=\"wp-block-heading\">4. <strong>Google Cloud IoT Edge \/ Vertex AI Edge<\/strong><\/h3>\n\n\n\n<p><strong>Short Description:<\/strong> Google\u2019s AI-powered edge computing solution combining IoT Edge and Vertex AI for real-time ML deployment.<\/p>\n\n\n\n<p><strong>Key Features:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Edge TPU hardware for fast ML inference<\/li>\n\n\n\n<li>Vertex AI for streamlined ML lifecycle management<\/li>\n\n\n\n<li>Strong data analytics integration with BigQuery<\/li>\n\n\n\n<li>Works with Kubernetes and Anthos for hybrid deployments<\/li>\n\n\n\n<li>Real-time video\/image recognition<\/li>\n<\/ul>\n\n\n\n<p><strong>Pros:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Excellent for computer vision and video AI<\/li>\n\n\n\n<li>Google\u2019s ML ecosystem is developer-friendly<\/li>\n\n\n\n<li>Strong hybrid\/multi-cloud support<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Limited hardware compatibility outside Edge TPU<\/li>\n\n\n\n<li>May be costly for smaller businesses<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h3 class=\"wp-block-heading\">5. <strong>IBM Edge Application Manager<\/strong><\/h3>\n\n\n\n<p><strong>Short Description:<\/strong> A flexible solution for managing and deploying AI workloads across thousands of edge devices.<\/p>\n\n\n\n<p><strong>Key Features:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Policy-based workload orchestration<\/li>\n\n\n\n<li>Autonomous management of edge nodes<\/li>\n\n\n\n<li>Supports Kubernetes and containerized workloads<\/li>\n\n\n\n<li>Integrates with IBM Watson for AI insights<\/li>\n\n\n\n<li>Multi-cloud compatibility<\/li>\n<\/ul>\n\n\n\n<p><strong>Pros:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Scales to manage thousands of devices<\/li>\n\n\n\n<li>Policy-driven automation reduces manual work<\/li>\n\n\n\n<li>Works across hybrid and multi-cloud setups<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Complex setup for small teams<\/li>\n\n\n\n<li>Best suited for enterprise-level organizations<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h3 class=\"wp-block-heading\">6. <strong>HPE Ezmeral Edge<\/strong><\/h3>\n\n\n\n<p><strong>Short Description:<\/strong> HPE\u2019s AI edge platform designed for industrial IoT, smart cities, and enterprise edge analytics.<\/p>\n\n\n\n<p><strong>Key Features:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Supports AI\/ML workloads at the edge<\/li>\n\n\n\n<li>Kubernetes-based container orchestration<\/li>\n\n\n\n<li>Edge-to-cloud data pipelines<\/li>\n\n\n\n<li>Secure and resilient architecture<\/li>\n\n\n\n<li>Pre-integrated with HPE GreenLake<\/li>\n<\/ul>\n\n\n\n<p><strong>Pros:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Strong for industrial\/enterprise use cases<\/li>\n\n\n\n<li>Robust Kubernetes orchestration<\/li>\n\n\n\n<li>Flexible deployment<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Enterprise-focused, less suitable for startups<\/li>\n\n\n\n<li>Requires HPE infrastructure investment<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h3 class=\"wp-block-heading\">7. <strong>Dell EMC Streaming Data Platform<\/strong><\/h3>\n\n\n\n<p><strong>Short Description:<\/strong> A solution for ingesting, storing, and analyzing streaming data at the edge in real-time.<\/p>\n\n\n\n<p><strong>Key Features:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Handles structured and unstructured edge data<\/li>\n\n\n\n<li>Supports AI\/ML pipelines for streaming analytics<\/li>\n\n\n\n<li>Real-time monitoring and alerts<\/li>\n\n\n\n<li>High-performance scalable infrastructure<\/li>\n\n\n\n<li>Integration with Dell hardware<\/li>\n<\/ul>\n\n\n\n<p><strong>Pros:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Great for real-time industrial data analytics<\/li>\n\n\n\n<li>Reliable hardware-software ecosystem<\/li>\n\n\n\n<li>High throughput and low latency<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Hardware dependency with Dell ecosystem<\/li>\n\n\n\n<li>Enterprise-oriented pricing<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h3 class=\"wp-block-heading\">8. <strong>FogHorn Lightning Edge AI<\/strong><\/h3>\n\n\n\n<p><strong>Short Description:<\/strong> Lightweight edge AI platform focused on industrial IoT and real-time analytics.<\/p>\n\n\n\n<p><strong>Key Features:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Ultra-low latency AI inference<\/li>\n\n\n\n<li>Edge-native ML model deployment<\/li>\n\n\n\n<li>Strong focus on industrial IoT use cases<\/li>\n\n\n\n<li>Hybrid edge-to-cloud model support<\/li>\n\n\n\n<li>Small memory\/CPU footprint<\/li>\n<\/ul>\n\n\n\n<p><strong>Pros:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Optimized for industrial environments<\/li>\n\n\n\n<li>Works on resource-constrained devices<\/li>\n\n\n\n<li>Fast and efficient<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Limited general-purpose AI capabilities<\/li>\n\n\n\n<li>Smaller ecosystem compared to hyperscalers<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h3 class=\"wp-block-heading\">9. <strong>Edge Impulse<\/strong><\/h3>\n\n\n\n<p><strong>Short Description:<\/strong> Developer-first platform for building and deploying ML models on edge devices.<\/p>\n\n\n\n<p><strong>Key Features:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Drag-and-drop ML pipeline builder<\/li>\n\n\n\n<li>Supports microcontrollers and resource-limited devices<\/li>\n\n\n\n<li>Pre-built models for vision\/audio\/sensor data<\/li>\n\n\n\n<li>Works with open hardware (Arduino, Raspberry Pi, etc.)<\/li>\n\n\n\n<li>Strong community and documentation<\/li>\n<\/ul>\n\n\n\n<p><strong>Pros:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Ideal for startups and developers<\/li>\n\n\n\n<li>Easy-to-use, low-code\/no-code options<\/li>\n\n\n\n<li>Strong support for tinyML use cases<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Limited scalability for enterprise<\/li>\n\n\n\n<li>Best for smaller, experimental projects<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h3 class=\"wp-block-heading\">10. <strong>Cognitive Edge by VMware<\/strong><\/h3>\n\n\n\n<p><strong>Short Description:<\/strong> AI-enabled edge computing platform integrated into VMware\u2019s virtualization ecosystem.<\/p>\n\n\n\n<p><strong>Key Features:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>AI inference with Kubernetes and Tanzu integration<\/li>\n\n\n\n<li>Virtualized edge infrastructure management<\/li>\n\n\n\n<li>Strong edge security protocols<\/li>\n\n\n\n<li>Optimized for hybrid cloud environments<\/li>\n\n\n\n<li>Seamless integration with VMware stack<\/li>\n<\/ul>\n\n\n\n<p><strong>Pros:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Ideal for enterprises using VMware ecosystem<\/li>\n\n\n\n<li>Strong virtualization and security features<\/li>\n\n\n\n<li>Flexible hybrid deployments<\/li>\n<\/ul>\n\n\n\n<p><strong>Cons:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Less focus on developer-friendly tools<\/li>\n\n\n\n<li>Pricing oriented toward enterprises<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h2 class=\"wp-block-heading\">Comparison Table<\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Tool Name<\/th><th>Best For<\/th><th>Platforms Supported<\/th><th>Standout Feature<\/th><th>Pricing<\/th><th>Avg. Rating<\/th><\/tr><\/thead><tbody><tr><td>NVIDIA Jetson<\/td><td>Robotics &amp; computer vision<\/td><td>Linux, Jetson hardware<\/td><td>GPU-accelerated AI at edge<\/td><td>Starts ~$149 (Nano)<\/td><td>4.7\/5<\/td><\/tr><tr><td>Microsoft Azure IoT Edge<\/td><td>Enterprises in Azure ecosystem<\/td><td>Windows, Linux, IoT devices<\/td><td>Containerized AI deployment<\/td><td>Pay-as-you-go<\/td><td>4.6\/5<\/td><\/tr><tr><td>AWS IoT Greengrass<\/td><td>Secure cloud-edge AI<\/td><td>Linux, AWS IoT devices<\/td><td>Local inference + AWS integration<\/td><td>Free + AWS services<\/td><td>4.5\/5<\/td><\/tr><tr><td>Google Vertex AI Edge<\/td><td>Vision &amp; video AI<\/td><td>Linux, Edge TPU, Kubernetes<\/td><td>Edge TPU inference<\/td><td>Custom pricing<\/td><td>4.6\/5<\/td><\/tr><tr><td>IBM Edge Application Mgr<\/td><td>Large-scale enterprises<\/td><td>Multi-cloud, Kubernetes<\/td><td>Policy-based orchestration<\/td><td>Enterprise pricing<\/td><td>4.4\/5<\/td><\/tr><tr><td>HPE Ezmeral Edge<\/td><td>Industrial IoT, smart cities<\/td><td>Kubernetes, HPE GreenLake<\/td><td>Edge-to-cloud pipelines<\/td><td>Subscription\/Custom<\/td><td>4.5\/5<\/td><\/tr><tr><td>Dell EMC Streaming Data<\/td><td>Real-time streaming analytics<\/td><td>Dell ecosystem<\/td><td>Streaming AI\/ML pipelines<\/td><td>Enterprise pricing<\/td><td>4.3\/5<\/td><\/tr><tr><td>FogHorn Lightning<\/td><td>Industrial IoT edge AI<\/td><td>IoT devices, Hybrid edge<\/td><td>Low-latency inference<\/td><td>Custom pricing<\/td><td>4.4\/5<\/td><\/tr><tr><td>Edge Impulse<\/td><td>Developers, startups, tinyML<\/td><td>Microcontrollers, SBCs<\/td><td>No-code ML pipelines<\/td><td>Free \/ Paid tiers<\/td><td>4.7\/5<\/td><\/tr><tr><td>VMware Cognitive Edge<\/td><td>Hybrid enterprises (VMware users)<\/td><td>VMware stack, Kubernetes<\/td><td>Virtualized AI edge infrastructure<\/td><td>Enterprise pricing<\/td><td>4.3\/5<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h2 class=\"wp-block-heading\">Which AI Edge Computing Solutions Tool is Right for You?<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>For Startups\/Developers:<\/strong> <em>Edge Impulse<\/em> or <em>NVIDIA Jetson Nano<\/em> offer cost-effective entry points.<\/li>\n\n\n\n<li><strong>For Industrial IoT:<\/strong> <em>FogHorn Lightning<\/em> and <em>HPE Ezmeral Edge<\/em> are optimized for real-time machine analytics.<\/li>\n\n\n\n<li><strong>For Enterprises (multi-device scaling):<\/strong> <em>IBM Edge Application Manager<\/em> or <em>VMware Cognitive Edge<\/em> provide large-scale orchestration.<\/li>\n\n\n\n<li><strong>For Cloud-First Companies:<\/strong> <em>Azure IoT Edge<\/em>, <em>AWS IoT Greengrass<\/em>, or <em>Google Vertex AI Edge<\/em> integrate seamlessly with their respective cloud platforms.<\/li>\n\n\n\n<li><strong>For Robotics\/AI Vision Projects:<\/strong> <em>NVIDIA Jetson<\/em> remains the gold standard in 2026.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion<\/h2>\n\n\n\n<p>AI Edge Computing Solutions in 2026 have evolved into powerful enablers of <strong>real-time intelligence, security, and scalability<\/strong>. Whether you\u2019re running a startup developing IoT devices, an industrial facility optimizing predictive maintenance, or a global enterprise deploying hybrid AI systems, the right tool can transform performance.<\/p>\n\n\n\n<p>The key is to balance <strong>performance, ecosystem integration, and cost<\/strong>. Most tools now offer <strong>free trials or developer kits<\/strong>, making it easier than ever to experiment before committing.<\/p>\n\n\n\n<p>As industries adopt <strong>5G, autonomous systems, and IoT at scale<\/strong>, AI edge computing is no longer optional\u2014it\u2019s essential.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h2 class=\"wp-block-heading\">FAQs<\/h2>\n\n\n\n<p><strong>Q1. What is AI Edge Computing?<\/strong><br>AI Edge Computing means running artificial intelligence models directly on local devices (edge devices) instead of relying solely on cloud servers. This reduces latency and improves privacy.<\/p>\n\n\n\n<p><strong>Q2. Why is AI Edge Computing important in 2026?<\/strong><br>With billions of IoT devices and the rise of real-time applications like autonomous driving, telemedicine, and smart factories, edge AI ensures faster decision-making and reduced bandwidth use.<\/p>\n\n\n\n<p><strong>Q3. What industries benefit most from AI Edge Computing Solutions?<\/strong><br>Healthcare, manufacturing, logistics, smart cities, and retail benefit the most\u2014anywhere that requires real-time analytics and low-latency decision-making.<\/p>\n\n\n\n<p><strong>Q4. Are AI Edge Computing Solutions expensive?<\/strong><br>Not always. Tools like Edge Impulse or Jetson Nano are budget-friendly, while enterprise-grade platforms like IBM or HPE come with higher costs.<\/p>\n\n\n\n<p><strong>Q5. How do I choose the right AI Edge Computing tool?<\/strong><br>Consider factors like scalability, integration with your existing ecosystem (AWS, Azure, Google Cloud), industry focus, and budget.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n\n\n\n<h2 class=\"wp-block-heading\">Meta Description<\/h2>\n\n\n\n<p>Discover the <strong>Top 10 AI Edge Computing Solutions Tools in 2026<\/strong>. Compare features, pros, cons, and pricing to choose the best software for your business needs.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Introduction In 2026, AI Edge Computing Solutions are no longer a futuristic concept\u2014they are at the core of how businesses process, analyze, and act on data in real time. Unlike&#8230; <\/p>\n","protected":false},"author":54,"featured_media":0,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_joinchat":[],"footnotes":""},"categories":[2],"tags":[],"class_list":["post-53053","post","type-post","status-publish","format-standard","hentry","category-uncategorised"],"_links":{"self":[{"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/posts\/53053","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/users\/54"}],"replies":[{"embeddable":true,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/comments?post=53053"}],"version-history":[{"count":4,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/posts\/53053\/revisions"}],"predecessor-version":[{"id":59792,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/posts\/53053\/revisions\/59792"}],"wp:attachment":[{"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/media?parent=53053"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/categories?post=53053"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.devopsschool.com\/blog\/wp-json\/wp\/v2\/tags?post=53053"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}