Operations | Monitoring | ITSM | DevOps | Cloud

Just ask AI to add OpenTelemetry to your code

OpenTelemetry instrumentation used to mean hours of manual work, wiring up metrics service by service. Now you can just ask for it. Tell an AI agent what you're trying to observe, something like "add OpenTelemetry so I can track this application's performance," and it turns that into an intent specification, then enriches your existing code with instrumentation to match. OpenTelemetry is open source and on GitHub. Pairing it with an AI agent that actually understands your codebase is what turns "add some metrics" into instrumentation that's useful.

Creating Your 2027 IT Roadmap

We’re back with another roadmap stream! You might think to yourself, “Talking about 2027 already? Isn’t that a bit early? I’m still sweating and lying out by the pool!” But planning this far ahead will give you plenty of time to sort out priorities, talk to relevant parties, set your budget(s), and more. Having these discussions in August may feel extreme but the leaves will fall and the snow will pile up before you know it, so you might as well get started now!

Publicly available doesn't mean safe to pull right now

Open source is the backbone of most software. But should developers trust OSS? npm, PyPI, and Maven don't vet packages before publication, so "publicly available" doesn't automatically mean "safe to pull right now." A secure OSS posture is to trust the ecosystem but verify at ingestion: route packages and dependencies through a controlled layer that runs scanning, age checks, and malware detection before anything reaches a build.

AI's BIGGEST Problem, They're Losing Money!

For every $1 you pay OpenAI or Anthropic, it's costing them about $1.60. AI is running at a loss — so is the whole business model broken? The full bill for AI hasn't landed yet. In this ShipTalk short, Field CTOs Adam and Martin break down the economics of generative AI: why the frontier labs lose money on every prompt, why they'd need to raise prices ~60% just to break even, and the bet the entire industry is making — that inference costs drop fast enough to catch up. Plus the Gartner forecast every CFO should see: by 2028, the AI bill could be bigger than the employment bill.

What Is SOC 2 Compliance? Requirements, Controls, and Evidence

Your largest prospect has asked for your SOC 2 report. The deal sits still until you produce one. Most teams handle the first half of SOC 2 compliance fine. They control access. They run backups. They put changes through approval before anything ships. The second half is what stops them, and that half is proof. Your policy says access gets reviewed every quarter. The auditor wants the dated review, the signature on it, and the same record from eight months ago.

What are the Key Features and Evaluation Criteria for Vulnerability Assessment Tools?

How many findings from your last vulnerability scan have been verified as fixed? For most IT functions, the scan report is easy to produce, and the proof of closure takes far longer to assemble. That difference tends to surface at the worst possible moment, usually an audit or a post-incident review. Vulnerability assessment tools are meant to end that uncertainty. They inspect systems, match what they find against public vulnerability databases, and rank each weakness by how dangerous it is.

AI SAST Explained: Why Traditional Application Security Is Reaching Its Breaking Point | Harness Blog

AI has fundamentally changed software development. Developers are writing more code than ever. AI coding assistants can generate features, tests, documentation, and infrastructure configurations in minutes. Engineering organizations are seeing meaningful productivity gains as AI becomes embedded throughout the software development lifecycle. But there is a catch. Security teams now face a difficult reality: application security was already struggling to keep pace with software delivery before AI arrived.

Chaos Hub in docs, Prompt Library for MCP: what's new in Resilience Testing | Harness Blog

The latest Resilience Testing documentation update brings Chaos Hub directly into the docs, making it easier to discover and use fault, probe, and action templates. It also introduces a Prompt Library with ready-to-use AI prompts for Harness MCP, helping teams run resilience workflows faster using natural language.