Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on APIs, Mobile, AI, Machine Learning, IoT, Open Source and more!

The Unit Economics Of Watering My Lawn: A Lesson On Runaway AI Costs

My wife and I spent hours this summer at home digging in the dirt. We planted new shrubs and perennials and created a small vegetable garden. We spread many square yards of fresh topsoil and grass seed over areas of lawn that needed rejuvenation. It turns out, I should have done all that landscaping with a FinOps leader’s mindset — before my water bill tripled when I wasn’t looking.

Practical Money Help for Tech Teams

On-call rotations, late change windows, and incident bridges demand full focus. Yet many employees carry quiet money worries that follow them into the shift. For staff in Houston who face a sudden bill, a local option like Net Pay Advance in Houston can help bridge a short-term gap without leaving work to find help. Used alongside basic money education and clear policies, timely access to credit can lower stress and keep teams steady.

Harness Acquires Qwiet AI to Power Its Application Security for the AI Era

Harness acquires Qwiet AI to power application security in the AI era, embedding reachability analysis to cut noise and prioritize real risks. By Sanjay Nagaraj, SVP Global Engineering, Harness; Co-founder and CTO, Traceable by Harness Today, I am excited to share that Harness has acquired Qwiet AI (formerly ShiftLeft), a leader in agentic AI-powered vulnerability detection and reachability analysis.

Streamline Software Delivery Right From Your IDE with Amazon Kiro and Harness

The integration of Amazon Kiro and Harness’s MCP server enables developers to manage, troubleshoot, and optimize CI/CD pipelines directly from their IDE using natural language, dramatically reducing manual effort and accelerating software delivery from code generation to production.

Deploying a multimodal RAG application with Gemma 3 and CircleCI on GKE

Retrieval-Augmented Generation (RAG) has transformed how applications interact with Large Language Models (LLMs). RAGs ground LLM responses in external knowledge, improves accuracy, and reduces hallucinations. But traditional RAG systems have a significant limitation: they only process text. Multimodal RAG addresses this limitation by processing and understanding multiple data types (text, images, and potentially audio).

Resolve + Espressive: Accelerating Zero Ticket IT with Agentic AI and Automation

Traditional IT operations are struggling under the weight of manual processes, growing complexity, and escalating expectations for employee experience. Without agentic AI driven by an intelligent orchestration engine, organizations risk falling behind. That’s why Resolve and Espressive have joined forces. Together, we’ll deliver the industry’s most advanced AI agents for enterprises, combining conversational intelligence with powerful automation to eliminate tickets end-to-end.

How GenAI Is Empowering Elastic Workforce

With over 10,000 questions answered and a 99% satisfaction rate in just 90 days, ElasticGPT, our internal generative AI assistant built on Elastic’s Search AI Platform, is transforming how our teams find information, make decisions, and complete day-to-day tasks. Matt Minetola, CIO, explains how ElasticGPT helps employees access company knowledge faster using natural language queries. Learn how we’re using retrieval augmented generation (RAG) and a secure, scalable architecture to deliver trusted, real-time AI experiences across the organization.

Need to do Integration Testing without a real Postgres SQL Database? #speedscale #postgres #sql

Struggling with integration testing because you need a real Postgres SQL database running? This video walks you through how to use Speedscale's proxymock to easily record and mock a live Postgres connection. You'll see how to: By the end, you'll be able to create realistic database mocks for your testing and development, saving you time and hassle.

Accelerating SIEM Migration with AI-Native Data Pipelines

Security teams are increasingly realizing that yesterday’s SIEMs weren’t built for today’s world. Legacy platforms were designed for static, on-prem environments where data sources were relatively predictable and volumes were manageable. But the shift to cloud, SaaS, and dynamic workloads has completely changed the equation. Cloud-friendly, flexible, and cost-conscious SIEMs are now table stakes.