# finops FinOps is an operational framework and cultural practice for maximizing technology value, enabling data-driven decisions, and creating financial accountability through collaboration between engineering, finance, and business teams. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## AI Cost Visibility: Why Policies Don't Stop Surprise Bills DevFeed: [AI Cost Visibility: Why Policies Don't Stop Surprise Bills]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-09-17T00:00:00Z Content type: opinion Language: en Sources: [Harness Blog]() Topics: [Artificial Intelligence](), [finops]() Tags: [ai](), [cost](), [finops](), [governance](), [organizations](), [policies](), [report](), [visibility]() ### AI overview Organizations are establishing AI spending policies but continue to receive unexpected bills because policies do not provide sufficient cost visibility or enforcement. The article argues that AI spending requires FinOps governance capable of tracking actual usage, detecting issues such as oversized models and retry loops, and assigning clear ownership. ### Source excerpt Organizations are writing AI spend policies but still getting surprise bills. Learn why governance alone fails without real policies. | Blog ## Kubernetes Cost Management Tools: The Best Options 2026 DevFeed: [Kubernetes Cost Management Tools: The Best Options 2026]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-09-16T00:00:00Z Content type: comparison Language: en Sources: [Harness Blog]() Topics: [Kubernetes](), [finops](), [Monitoring](), [Cloud]() Tags: [2026](), [cloud](), [compare](), [finops](), [kubernetes](), [monitoring]() ### AI overview A comparison of Kubernetes cost management tools for 2026, including Kubecost, OpenCost, and CloudZero. It explains how these tools allocate shared cloud node costs across namespaces, workloads, and pods, while accounting for idle and unallocated capacity and supporting optimization actions. ### Source excerpt Compare the best Kubernetes cost management tools for 2026, from Kubecost and OpenCost to CloudZero, on allocation depth, scale, and pricing model. | Blog ## Manage Cursor costs with Datadog Cloud Cost Management DevFeed: [Manage Cursor costs with Datadog Cloud Cost Management]() Original publisher: [Read original article]() Author: Dom Nguyen; Doug Gunter Published: 2026-09-15T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [cloud cost management](), [cursor](), [finops](), [ai-coding]() Tags: [ai](), [ai-coding](), [analysis](), [cloud-cost-management](), [configuration](), [datadog](), [features](), [filter](), [finops](), [monitor](), [monitors](), [product](), [software]() ### AI overview This tutorial explains how Datadog Cloud Cost Management helps teams analyze Cursor spending by user, model, usage mode, and billing group. It covers identifying cost drivers, detecting unexpected changes, correlating spend with usage, and using monitors, budgets, and dashboards to manage AI coding costs alongside cloud and SaaS spending. ### Source excerpt Analyze Cursor spend by user and model, catch unexpected cost changes, and manage AI coding costs alongside your cloud and SaaS spend. ## Proactive FinOps Strategies for Optimizing Cloud Savings DevFeed: [Proactive FinOps Strategies for Optimizing Cloud Savings]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-08-10T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [finops](), [cloud cost management](), [Optimization](), [Cloud](), [Automation]() Tags: [automation](), [cloud](), [cloud-cost-management](), [cost-optimization](), [finops](), [forecasting](), [governance](), [optimization]() ### AI overview The article argues that FinOps teams should move beyond reactive overspend reduction toward proactive savings optimization. It describes continuous visibility, automated governance, forecasting, and ongoing optimization as ways to identify missed cloud savings before inefficiency compounds. ### Source excerpt Shift your FinOps paradigm from overspending to under-saving. Discover proactive cloud cost optimization strategies. Learn more with Harness CCM. | Blog ## Cloud Cost Visibility at Scale: Best Practices DevFeed: [Cloud Cost Visibility at Scale: Best Practices]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-08-04T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [Cloud](), [finops](), [cloud cost management](), [Amazon Web Services](), [Amazon EC2](), [Amazon S3](), [Kubernetes](), [Microservice]() Tags: [aws](), [best-practices](), [cloud](), [cloud-cost-management](), [ec2](), [finops](), [how-to](), [kubernetes](), [microservices](), [s3]() ### AI overview The article explains why cloud cost visibility and allocation practices break down as organizations scale across accounts, teams, services, and workloads. It argues that periodic reporting, manual reviews, and static tagging models become ineffective, and highlights FinOps governance and automation as ways to improve control and trust in cost data. ### Source excerpt Discover why cloud cost visibility at scale breaks down and how to regain control. Learn proven FinOps strategies. Explore now. | Blog ## 2026 State of AI in FinOps: Enterprise AI Costs, Waste, and ROI DevFeed: [2026 State of AI in FinOps: Enterprise AI Costs, Waste, and ROI]() Original publisher: [Read original article]() Author: Patrick Brogan Published: 2026-07-29T00:00:00Z Content type: opinion Language: en Sources: [Harness Blog]() Topics: [Artificial Intelligence](), [finops](), [Cloud]() Tags: [ai](), [cloud](), [finops]() ### AI overview This commentary discusses findings from Harness' 2026 State of AI in FinOps report, including rising enterprise AI spending, cost-ownership confusion, governance gaps, and waste reduction. ### Source excerpt Harness' 2026 State of AI in FinOps report reveals why AI costs are surging, where enterprises waste spend, and how mature organizations maximize AI ROI. | Blog ## FinOps: Shift from Reactive Cost Cutting to Proactive Cloud Savings DevFeed: [FinOps: Shift from Reactive Cost Cutting to Proactive Cloud Savings]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-07-24T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [finops](), [Optimization](), [Cloud]() Tags: [cloud](), [cost-optimization](), [finops](), [harness](), [optimization]() ### AI overview The article argues that FinOps teams should shift from reacting to cloud-cost overruns toward proactively preventing unnecessary costs before workloads reach production. It explains that rightsizing, commitment discounts, and resource lifecycle management remain useful but are insufficient alone at scale. ### Source excerpt Shift your FinOps savings optimization strategy from reactive cuts to proactive savings. Learn how Harness helps. Explore now. | Blog ## Cloud Cost Optimization Strategy: Fix Your Approach DevFeed: [Cloud Cost Optimization Strategy: Fix Your Approach]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-07-24T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [cloud cost management](), [finops](), [Optimization]() Tags: [cloud](), [cost](), [cost-optimization](), [dashboards](), [monitoring](), [recommendations]() ### AI overview This article argues that cloud cost optimization often fails when organizations rely on outdated, reactive practices and visibility tools alone. It describes how delayed cost feedback, weak accountability, and disconnected responsibilities across engineering, finance, and platform teams can allow cloud spending to grow, and presents modern FinOps and governance frameworks as a better approach. ### Source excerpt Your cloud cost optimization strategy may be failing. Learn why traditional approaches fall short and how to build a better framework. Explore now. | Blog ## 10 FinOps tools platform engineers should evaluate for 2026 DevFeed: [10 FinOps tools platform engineers should evaluate for 2026]() Original publisher: [Read original article]() Author: Ajay Chankramath Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [cloud cost management](), [finops](), [Platform Engineering](), [Kubernetes](), [GitOps](), [Infrastructure as code](), [Cloud](), [Provisioning]() Tags: [2026](), [cloud](), [cost](), [developer-experience](), [finops](), [iac](), [infrastructure](), [kubernetes](), [management](), [multi-cloud](), [optimization](), [platform](), [platform-engineering]() ### AI overview A guide to evaluating 10 FinOps platforms for platform engineering teams in 2026. It emphasizes Kubernetes-native cost attribution, API-first architecture, GitOps and IaC integration, developer experience, and the 4Rs framework: Report, Recommend, Remediate, and Retain. ### Source excerpt Evaluate 10 FinOps tools platform engineers need in 2026 for Kubernetes-native, multi-cloud cost optimization. Focus on API-first architecture, GitOps, and the 4Rs framework. ## Transforming optimization into an invisible platform capability DevFeed: [Transforming optimization into an invisible platform capability]() Original publisher: [Read original article]() Author: Graziano Casto Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Optimization](), [Platform Engineering](), [finops](), [SRE](), [Automation](), [GitOps](), [Cloud](), [dashboards](), [Deployment](), [Kubernetes]() Tags: [automation](), [cloud](), [cloud-native](), [cost](), [dashboards](), [deployment](), [developer](), [developer-experience](), [finops](), [kubernetes](), [optimization](), [performance](), [platform](), [platform-engineering](), [sre]() ### AI overview The article argues that cloud-native organizations should transform optimization from a manual, reactive activity into an invisible platform capability. It focuses on reducing friction among FinOps professionals, SREs, and developers by continuously balancing cost, performance, and reliability through automation and GitOps. It also highlights the day-two operational gap and the limitations of passive monitoring dashboards and static golden paths. ### Source excerpt Break the FinOps/SRE/Developer friction by transforming optimization into an automated, invisible platform capability. Achieve continuous cost and performance balance through GitOps ## Announcing the State of Platform Engineering Report Vol 4 DevFeed: [Announcing the State of Platform Engineering Report Vol 4]() Original publisher: [Read original article]() Author: Sam Barlien Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [Artificial Intelligence](), [AI Development](), [GPU](), [supply-chain-security](), [MLOps](), [finops]() Tags: [2026](), [ai](), [ai-ml](), [cloud-native](), [engineering](), [infrastructure](), [mlops](), [platform](), [platform-engineering](), [platforms](), [report](), [scale](), [software-supply-chain](), [speed]() ### AI overview The State of Platform Engineering Report Volume 4 presents platform engineering as a foundational discipline for modern enterprises. Based on insights from 518 engineers, it describes a shift from the cloud-native era to an AI-native era, emphasizing "shifting down," AI-powered platforms, platforms for AI, specialized GPU infrastructure, governance, and MLOps requirements. ### Source excerpt Insights from over 500 engineers. Explore the shift to 'AI-native,' the 'dual mandate,' 'shifting down,' and key trends for 2026. ## Engineer Cloud Cost Awareness: Why It Fails & Fixes DevFeed: [Engineer Cloud Cost Awareness: Why It Fails & Fixes]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-07-23T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [Cloud](), [finops](), [engineering-culture](), [systems](), [Development](), [Optimization](), [Automation]() Tags: [automation](), [best-practices](), [cloud](), [culture](), [development](), [engineering](), [finops](), [infrastructure](), [optimization](), [workflows]() ### AI overview This guide explains why engineers often overlook cloud costs: cost data lacks visibility, incentives are misaligned, and feedback is disconnected from development workflows. It recommends embedding cost awareness through automation, real-time feedback, and FinOps practices. ### Source excerpt Discover why engineer cloud cost awareness fails and proven strategies to build accountability. Learn how Harness Cloud & AI Cost Management helps. | Blog ## Strategic Cloud Cost Management: Evolution Guide DevFeed: [Strategic Cloud Cost Management: Evolution Guide]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-07-23T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [cloud cost management](), [finops](), [Optimization](), [Platform Engineering](), [Provisioning]() Tags: [aws](), [cloud-cost-management](), [cost-optimization](), [finops](), [governance](), [optimization](), [platform](), [platform-engineering](), [provisioning]() ### AI overview This guide explains the shift from reactive cloud cost monitoring to strategic cloud cost management. It covers the FinOps maturity path, governance frameworks, cost accountability, and optimization practices for aligning engineering and finance around cloud spending. ### Source excerpt Transform from reactive spending to strategic cloud cost management. Learn the FinOps maturity path and optimization tactics. Explore now. | Blog ## Using an Internal Developer Portal For Superior FinOps Visibility DevFeed: [Using an Internal Developer Portal For Superior FinOps Visibility]() Original publisher: [Read original article]() Author: Aidan O'Connor Published: 2026-07-22T12:04:29Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [finops](), [internal developer portal](), [Cloud](), [Developer experience](), [Optimization](), [data]() Tags: [cloud](), [developer-experience](), [developer-portal](), [finops](), [internal-developer-portal](), [optimization](), [platform](), [resource](), [resources](), [tools]() ### AI overview The article explains how an internal developer portal can improve FinOps visibility by combining cloud cost data with development context. It describes how this helps developers, technical leaders, engineering managers, and FinOps teams understand resource ownership, service costs, budgeting, and optimization opportunities. ### Source excerpt Port transforms FinOps by integrating and contextualizing data from multiple sources to optimize cloud costs efficiently. ## Answer any cost question faster with the Cloud Cost skill in Bits Chat DevFeed: [Answer any cost question faster with the Cloud Cost skill in Bits Chat]() Original publisher: [Read original article]() Author: Dom Nguyen Published: 2026-07-17T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [cloud cost management](), [finops](), [observability](), [Artificial Intelligence](), [anthropic](), [OpenAI]() Tags: [ai](), [analysis](), [anthropic](), [bits-ai](), [cloud](), [cloud-cost-management](), [cost](), [finops](), [metrics](), [monitor](), [observability](), [openai](), [optimization](), [root-cause-analysis](), [saas]() ### AI overview This article introduces the Cloud Cost skill in Bits Chat, a conversational workflow for investigating cloud, SaaS, AI, custom, and Datadog costs. It explains how teams can ask cost questions in plain language, investigate anomalies, identify the teams or services driving spend, compare spending with budgets, and correlate cost changes with observability metrics to support root-cause analysis and optimization. ### Source excerpt Use the Cloud Cost skill in Bits Chat to investigate cost anomalies, perform root cause analysis on cost spikes, and get personalized savings. ## IBM and UC Berkeley Diagnose Why Enterprise Agents Fail Using IT-Bench and MAST DevFeed: [IBM and UC Berkeley Diagnose Why Enterprise Agents Fail Using IT-Bench and MAST]() Original publisher: [Read original article]() Author: Ayhan Sebin; Rohan Arora; Saurabh Jha Published: 2026-02-18T16:15:45Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [Benchmark](), [ibm](), [Large Language Model](), [site-reliability-engineering](), [incident](), [Kubernetes](), [finops](), [Security]() Tags: [agentic](), [agents](), [analysis](), [automation](), [benchmarks](), [enterprise](), [evaluation](), [gpt-oss](), [hallucinations](), [ibm](), [incident](), [kubernetes](), [llm](), [logs](), [loops](), [metrics](), [performance](), [research](), [systems](), [tool]() ### AI overview IBM Research and UC Berkeley analyze why agentic LLM systems fail in enterprise IT automation using ITBench traces and the MAST failure taxonomy. Their analysis of 310 SRE traces compares Gemini-3-Flash, Kimi-K2, and GPT-OSS-120B, identifying verification errors, cascading failures, premature termination, looping, and hallucinations as major reliability problems. ### Source excerpt IBM Research and UC Berkeley collaborated to study how agentic LLM systems break in real-world IT automation, for tasks involving incident triage, logs/metrics queries, and Kubernetes actions in long-horizon tool loops. Benchmarks typically reduce performance to a single number, telling you whether an agent failed but never why. To solve this black-box problem, we applied MAST (Multi-Agent System Failure Taxonomy), an emerging practice for diagnosing agentic reliability ). ## How Pump uses ClickHouse Cloud to bring cloud costs into focus DevFeed: [How Pump uses ClickHouse Cloud to bring cloud costs into focus]() Original publisher: [Read original article]() Author: ClickHouse Published: 2025-12-02T15:36:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [finops](), [Cloud](), [Amazon Web Services](), [data](), [Database]() Tags: [2025](), [architecture](), [aws](), [clickhouse](), [cloud](), [cost](), [data](), [database](), [finops](), [pipeline](), [providers](), [visibility]() ### AI overview Pump built Pump View on ClickHouse Cloud to provide detailed visibility into cloud spending. The platform ingests and analyzes billions of billing records from providers such as AWS and GCP, enabling teams to break costs down by region, usage type, team, and custom tags. ### Source excerpt Pump built their cloud cost visibility platform on ClickHouse Cloud to ingest and analyze 5 billion billing records daily, solving challenges that would have been impossible with Postgres. ## From Cloud Chaos to Governance: How FinOps and DevOps Converge in 2025 DevFeed: [From Cloud Chaos to Governance: How FinOps and DevOps Converge in 2025]() Original publisher: [Read original article]() Author: Urolime Technologies Published: 2025-10-17T06:33:40Z Content type: article Language: en Sources: [Kubernetes Archives - Urolime Blogs]() Topics: [DevOps](), [finops](), [Cloud](), [cloud-infrastructure](), [GitOps](), [Platform Engineering](), [Kubernetes]() Tags: [automation](), [cloud](), [cloud-computing](), [devops](), [finops](), [gitops](), [kubernetes](), [kubernetes-consulting-services](), [platform-engineering]() ### AI overview This article discusses how FinOps and DevOps can work together to address cloud chaos, including rising costs, siloed teams, and inefficient resource use. It describes DevOps practices such as automation, collaboration, GitOps, and platform engineering alongside FinOps practices such as forecasting, resource tagging, and financial accountability. ### Source excerpt Cloud computing fuels today's businesses with the ability to innovate at an unprecedented scale. However, a large number of organizations encounter "cloud chaos" which can be defined through the exploding costs, siloed teams, and a wasteful resource utilization. In 2025, the intersection of FinOps and DevOps is shaping this chaos into managed, optimized cloud infrastructures. [...]