Harness 在 2026年9月 发布了 33 项受追踪的更新。 较 2026年8月 增长 57%。 这是 Harness 在 2026 年最活跃的月份。 主要主题是 content pieces(12)。 活动主要集中在 2026年9月14日 那一周。 亮点:“Harness report reveals AI productivity gap: 31% of dev time spent on invisible validation work”(2026年9月25日)。
浏览 Harness 的其他月份
Harness argues that engineers often overlook cloud cost optimization due to misaligned incentives and lack of visibility, proposing AI-powered cost management agents to embed FinOps governance into wo…
Harness introduced a new connector enabling ChatGPT and Codex to inspect pipeline health, investigate build failures, and execute deployment workflows directly from AI tools. The integration aims to b…
A Harness-commissioned survey of 700 developers found 31% of their time is spent on AI-related invisible validation work (e.g., reviewing AI-generated code) that current metrics fail to capture. 94% o…
Harness found 75% of organizations have deployed AI agents in production despite lacking critical controls, with 87% experiencing agent-related security incidents and 60% overspending budgets. Confide…
Harness published a comprehensive guide on cloud cost optimization for 2026, emphasizing allocation, rightsizing, idle resource management, and commitment strategies. The post highlights three new AI-…
Harness unveiled a new control plane concept enabling AI agents to autonomously manage the full software delivery lifecycle beyond pull requests. The system uses standardized interfaces like MCP to le…
Harness released a blog post detailing 15 AWS cost optimization tactics across compute, storage, networking, and monitoring, accompanied by a quick-reference table. The post links to multiple Harness …
Harness introduced a new integration with Amazon Bedrock AgentCore, providing security teams continuous visibility and real-time threat detection across AI agent interactions on AWS. The integration e…
Harness argues that traditional cloud cost optimization efforts often fail engineers due to misaligned incentives and lack of visibility, advocating for developer-centric FinOps practices. The post hi…
Harness published a blog outlining how machine learning is transforming secure software development lifecycle (SDLC) practices, including AI-assisted code review, automated triage, and new risks like …
Harness published a blog post detailing how embedding security, auditing, and governance into Internal Developer Portals (IDPs) reduces compliance risks without slowing engineering teams. The post hig…
Harness announced a live demo on October 14, 2026, showcasing its Cost Management Agent, which automates cloud and AI spend attribution, optimization, and governance. The agent uses a knowledge graph …
Harness unveiled AI Configs, a runtime-adjustable governance system for AI behavior that mirrors feature flag management. Teams can now swap prompts, models, or settings in production without redeploy…

Harness announced findings from a survey of 700 engineering leaders showing a confidence gap in AI agent controls despite widespread production use. The research highlights rising incidents as agents …
Harness argues that AI spend policies alone are insufficient to prevent surprise bills, emphasizing the need for real-time cost visibility and governance. The post highlights how organizations often o…
Harness argues that Argo CD excels at Kubernetes manifest synchronization but lacks enterprise-scale workflow orchestration, governance, and AI-driven verification. The company positions its new Enter…

A Harness-hosted LeadDev panel argued that traditional governance models fail for AI agents, which act faster than human review cycles. Harness and panelists from Yelp and Platformable emphasized auto…

Harness published a 2026 guide comparing Kubernetes cost management tools, emphasizing the need for namespace-level cost allocation and idle/unallocated cost visibility. The post positions Harness’s C…

Harness published a framework for AI security governance emphasizing four pillars: policy, risk assessment, monitoring, and accountability. The post highlights regulatory pressures like the EU AI Act …

Harness used its own Cloud Management Agent to reduce AI tooling spend without reducing usage by implementing per-developer cost visibility, weekly budgets with graduated alerts, and self-service budg…

Harness explains why engineers ignore cloud costs due to delayed feedback loops and introduces AI Cost Management Agents that provide real-time cost visibility and automated actions within engineering…

Harness launched Policy as Code (PaC) to automate security and compliance rules as version-controlled, testable artifacts, addressing the 'Authorization Gap' in modern software engineering. The soluti…

Harness published a 2026 report revealing a 30–55 point gap between organizations' confidence in AI agent safety and their actual controls, based on a survey of 700 engineering leaders across five cou…

A Harness blog post reveals that 700 surveyed organizations report 74-77% confidence in their AI agents' security, testing, inventory, cost, and rollback controls, but most lack dedicated tooling. Onl…
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Harness launched CLI 3.0, unifying Harness Code with native CI/CD pipelines, AI-powered code reviews, and interactive terminal UIs. The CLI introduces a spec-driven grammar with six core verbs coverin…

Harness launched a contained pen testing feature that runs security experiments directly in CI/CD pipelines, proving system resilience under specific failure conditions without granting broad producti…

Harness argues internal developer portals must integrate natively with CI/CD pipelines to scale beyond visibility into actual velocity. Without this, developers face manual pipeline creation, inconsis…

Harness introduced Resilience Testing (RT) to transform Operational Readiness Testing (ORT) from a one-time pre-launch checklist into a continuous CI/CD pipeline process. RT uses AI agents to predict,…

Harness released a 2026 industry report showing AI spend is accelerating across infrastructure, software, and models, with 80% of organizations seeing increases in the past six months. The report high…
Harness shipped 58 features in August 2026, including an agent-scale code repository, AI Code Review, AI Blast Radius Agent for Terraform/OpenTofu risk scoring, and AI Impact Analysis for SQL changes.…

Harness introduced AI Evals, a feature that tests AI agent quality within CI/CD pipelines using golden datasets and quality gates to block behavioral regressions before production. Unlike traditional …

Gentera modernized its software delivery using Harness, consolidating 600 fragmented pipelines into four golden pipelines. This reduced database rollback failures from 19% to under 1% and cut loan app…

Gentera, a financial services provider in Mexico and Peru, adopted Harness Database DevOps to standardize and govern database changes, reducing rollback failures from 19% to under 1% and cutting loan …
