Operations | Monitoring | ITSM | DevOps | Cloud

dbForge - AI-Powered Database Ecosystem for Developers & DBAs

Managing different databases, tools, and environments can slow down your workflow… but dbForge brings everything together. Work with SQL Server, MySQL, MariaDB, PostgreSQL, Oracle, and cloud databases Use AI to generate, explain, fix, and optimize SQL queries Design, develop, test, manage, and automate databases Choose from dbForge Edge, dedicated Studios, standalone tools, and SSMS/Visual Studio add-ins.

How AI is Reshaping IT Operations Management

AI is transforming IT operations through automated incident response, intelligent event correlation, predictive analytics, and agentic AI. But while technology is evolving rapidly, human judgment and strategic decision-making remain essential. In this video, explore what's changing in IT operations, what isn't, and how IT leaders can prepare for an AI-driven future with AIOps, observability, and automation. Learn how Motadata helps organizations build smarter, more proactive IT operations.

Shipped: You're emitting AI telemetry. Point it at an engine that turns it into allocated spend.

Your AI calls already emit OpenTelemetry: your LLM gateway exports it, and it’s the open standard your own services can speak. But you don’t have anywhere to turn those spans into spend you can allocate to an outcome. Now you can. CloudZero exposes an OpenTelemetry endpoint that doesn’t care what’s on the other end.

Why Your Agentic Workflow Succeeds and Still Gets It Wrong

Agentic workflows are reshaping how engineering teams operate, fetching context, synthesizing decisions, and shipping results across systems without human intervention. But the same design that makes them powerful adds risk in production. Agents do not crash when they hit bad data; they synthesize around it, substituting a stale value, an empty page, or a missing field for the result they were supposed to capture.

PagerDuty Report Finds Two-Thirds (66%) of Office Professionals Have Used Unauthorized AI Tools at Work

Three-quarters of office professionals (75%) say they would be likely to look for a new job that offered better AI skills development, a figure that climbs to 80% at companies with $1 billion or more in revenue.

How Skylar MCP Gives Agentic Workflows the Operational Context to Act With Confidence

AI models can reason over language, summarize findings, and explain patterns. What they cannot do on their own is see the real-time operational state of your environment. Ask a model about a critical incident and it will answer from whatever context it is given, which means the answer is only as trustworthy as the input. In operations and compliance workflows, an answer is only useful if it is grounded in current service context and governed access to the systems that define reality.

Shadow AI Is Happening Within Your Organization

A majority of office professionals (72%) believe they understand how to use AI for their job better than the team responsible for managing AI at their company. While it’s encouraging to see employees embrace AI with such confidence, organizations will want to ensure they are providing the tools, guidance, and safeguards needed to help employees use AI safely.

AI at the edge: simplifying infrastructure with Cisco and Canonical

Legacy infrastructure was not designed for the requirements of the AI era. While large-scale model training remains centralized in data centers, test-time inference is rapidly shifting to the edge to reduce latency and bandwidth consumption. This shift creates a new frontier for enterprise AI, but deploying at the edge introduces significant manual complexity, interoperability issues, and security vulnerabilities.