Operations | Monitoring | ITSM | DevOps | Cloud

Background Music Remover: The Complete Technical Guide

Audio separation technology has revolutionized content creation by solving one of the most persistent challenges: cleanly separating background music from dialogue and primary audio content. Understanding how these systems work-and when to use them-can transform your production workflow and elevate content quality across every project.

{Unscripted} Autonomous Code Maintenance

Nothing drains developer productivity like codebase maintenance. The endless cycle of dependency upgrades, bug fixes, refactoring, and paying down technical debt is tedious, error-prone work that pulls engineers away from building new features. Harness Autonomous Code Maintenance (ACM) turns these manual chores into automated, intent-driven workflows. Developers can now state their intent in plain English, with prompts like, "Upgrade the front end from React 15.6 to 16.4". From there, the Harness AI agent drives the workflow.

{unscripted} AI for DevOps and DBDevOps

Many software engineers are experts in application code but not in the nuances of creating a production-ready delivery pipeline. Architect Mode acts as a seasoned DevOps expert, engaging the user in a conversation to design a pipeline that incorporates organizational best practices for security, quality, and compliance from the very beginning. It’s like having a personal DevOps architect as a partner.

{unscripted} AI Verification and Rollback

Our first AI/ML capability, Continuous Verification, made Harness the first Continuous Delivery tool to understand observability telemetry and trigger rollbacks when deployments caused trouble. We knew we could do more to eliminate the friction involved in its setup. Deploying with confidence shouldn't require a coordination meeting between DevOps, SREs, and developers just to configure the right health checks. That’s why we’re introducing the next generation: AI Verification and Rollback.

{unscripted} AI in Chaos Engineering

Harness AI enhances your chaos engineering capabilities by leveraging artificial intelligence to automate and optimize reliability testing and analysis. One of the challenges of scaling up the Chaos Engineering practice within the organization is skilling up the users to create or run chaos experiments and to come up with solutions to mitigate the risks that are identified during the chaos experiment execution. The Chaos Engineering module comes with an AI Agent called "AI Reliability Agent" that helps in these aspects.

Grafana Labs Co-founder Woods: Market maturity, OpenTelemetry, and AI are reshaping observability

As organizations navigate increasingly complex tech environments, unified observability practices have become essential. That was one of the main takeaways from Grafana Labs Co-founder Anthony Woods’ recent appearance on “Tech Keys by by Mercari India,” a podcast hosted by Vaibhav Khurana, Head of Platform Engineering at Mercari India.

How To Tag AI Cloud Spend: A Practical Framework For FinOps Teams

The world of cloud costs is always evolving, and AI spend is quickly becoming one of the most unpredictable and confusing cost drivers. As more organizations integrate generative AI into their products, FinOps teams are struggling to account for — and control — these new, often mind-boggling cost streams. In fact, 44% of engineering professionals say improving AI explainability is a top priority in AI budgeting, according to CloudZero’s State Of AI Costs In 2025 report.

AI-Powered Chaos Engineering with Harness MCP Server and Cursor

The Harness MCP Server integration with Cursor transforms chaos engineering from a complex, specialized discipline into an accessible, conversational workflow that any developer can leverage directly within their AI-powered IDE. By combining natural language prompts with comprehensive resilience testing tools, teams can discover, execute, and analyze chaos experiments without vendor-specific expertise, democratizing system reliability across DevOps, QA, and SRE functions.