Systems | Development | Analytics | API | Testing

dreamfactory

Identity Passthrough for AI: Why Your LLM Needs to Know Who's Asking

Jan 27, 2026 By Nic Davidson In DreamFactory
When a user asks your AI assistant a question, who actually runs the database query? In most enterprise AI deployments, the answer is troubling: a shared service account with broad access to everything. The user's identity evaporates the moment their request enters the AI system. This architectural pattern creates security gaps, compliance failures, and data leakage risks that undermine enterprise AI adoption.
Read Post

2026 Predictions: What's Next for Data Streaming and AI | Life Is But A Stream

Jan 27, 2026 By Confluent In Confluent
AI isn’t just evolving—it’s reshaping who your customers are, how systems operate, and what real time really means. From machines making purchase decisions to agents increasing query volume across databases, the realities of 2026 are forcing leaders to rethink data architecture and governance strategies at a fundamental level. In this episode, Joseph is joined by Will LaForest (Field CTO, Confluent), Adi Polak (Director of Developer Advocacy & Experience, Confluent), and independent analyst, Sanjeev Mohan, to break down critical insights from Confluent’s 2026 Predictions Report.
View Video

Powering agentic software quality with MCP servers | From the Bear Cave

Jan 27, 2026 By SmartBear In SmartBear
In this From the Bear Cave session, Dan Faulkner, CEO of SmartBear, and Vineeta Puranik, CTO/CPO of SmartBear, discuss why agentic automation is becoming essential in software development and delivery, how MCP Server enables connected autonomy across the SDLC, and what this transformation means for business outcomes and the future of human + AI collaboration.
View Video
thoughtspot

SpotCache: Scale AI-ready data without cloud-spend surprises

Jan 27, 2026 By Shruthi Bezawada In ThoughtSpot
AI is changing how work gets done. But for many data leaders, it’s also creating a new challenge: managing the cloud bill. As more people (and more AI agents) query data, cloud data warehouse (CDW) spend can spike fast. Costs become harder to predict, and teams end up making tradeoffs—scaling AI insights or staying within budget. That tension creates a real bottleneck on the path to becoming AI-ready.
Read Post
tricentis

AI in QA: What leading quality experts want every team to know

Jan 27, 2026 By Sarah Welsh In Tricentis
Our goal with the Tricentis blog is to distill insights that help QA professionals navigate the massive, AI-driven transformation happening across the software delivery landscape. To that end, I reached out to experts across Tricentis, from product and services to marketing and strategy, to hear what they’re really thinking about AI in QA right now. This group brings decades of experience building testing products, guiding enterprise transformations, and shaping how organizations adopt AI.
Read Post
perforce

What is an MCP? Breaking Down the Model Context Protocol

Jan 27, 2026 By Perforce In Perforce
70% of teams are already integrating generative AI tools into their daily workflows, according to our 2025 State of Game Technology Report. Now more than ever, teams are looking to connect their AI tools to the services and applications they rely on to get work done. To address this issue, the industry has begun to standardize using the Model Context Protocol (MCP) to connect their existing tools and LLMs like Claude, GPT, and Gemini.
Read Post
kong

Building Secure AI Agents with Kong's MCP Proxy and Volcano SDK

Jan 27, 2026 By Eugene Tan In Kong
Modern AI applications are no longer just about sending prompts to an LLM and returning text. As soon as AI systems need to interact with real business data, internal APIs, or operational workflows, the problem becomes one of orchestration, security, and control. The challenge is to build secure AI agents without embedding fragile logic or exposing sensitive systems directly to a model. This is where a layered architecture using Volcano SDK, DataKit, and Kong MCP Proxy becomes compelling.
Read Post
TestQuality

Best Practices for AI in CI/CD QA Pipelines

Jan 27, 2026 By Jose Amoros In TestQuality
AI transforms CI/CD testing from reactive bug detection into proactive quality assurance that accelerates release cycles while improving software reliability. Start embedding AI into your testing workflows now because teams that wait will struggle to match the velocity of competitors who already have. Continuous integration and continuous deployment pipelines have become the backbone of modern software delivery.
Read Post
ClearML

Multi-Node Training with ClearML

Jan 26, 2026 By ClearML In ClearML
Orchestrating distributed AI workloads Distributed (multi-node) training has become a requirement rather than an optimization for many modern AI workloads. As model sizes grow, datasets expand, and training timelines tighten, teams increasingly rely on multiple machines, often with multiple GPUs each, to complete training efficiently.
Read Post

Copyright © 2026 OpsMatters™. All rights reserved.