Operations | Monitoring | ITSM | DevOps | Cloud

manageengine

Monitor your Amazon Bedrock workloads with Applications Manager

Aug 5, 2026 By Allan In ManageEngine
Organizations are increasingly integrating GenAI capabilities into their applications to deliver richer, more contextual user experiences—from AI-powered customer support and enterprise search to content generation, virtual assistants, and automated workflows. To build and scale these GenAI-powered experiences, they are turning to platforms such as Amazon Bedrock, which provides access to foundation models that developers can integrate into their applications.
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Avantra

SAP Cloud Connector: Essential for Ground-to-Cloud and AI Operations

Aug 5, 2026 By Robert McDonald In Avantra
When SAP unveiled the Business AI Platform at Sapphire 2026, it folded BTP, Business Data Cloud, and Business AI into a single governed environment. BTP didn’t disappear but became essential architecture underneath SAP’s agentic AI direction. A big part of the repositioning included cloud and AI enablement of existing systems, data and enterprise context: the cloud half of every hybrid SAP estate just got more capable and more strategic, and SAP Cloud Connector plays a central role.
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How Insight Is Transforming Managed Services in the AI Era

Aug 5, 2026 By ScienceLogic In ScienceLogic
How will AI reshape managed services? The next chapter of managed services won't be measured by how fast teams react to alerts, but by how well they anticipate and prevent them. ScienceLogic CEO Dave Link and Paul Neiswinger, VP of Global Managed Services at Insight, a leading Solutions Integrator that helps clients solve technology challenges by combining the right hardware, software, and services, discuss the shift from reactive operations to proactive, outcome-driven service, and what it takes for leaders to get there.
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hyperview

DCIM in the AI Era: The Now, the New, and the Next of Data Center Infrastructure Management

Aug 5, 2026 By Jad Jebara In Hyperview
Data Center Infrastructure Management (DCIM) software is evolving in three overlapping stages: Now (a unified ingestion and observation layer across power, cooling, and IT systems), New (expanded control functions, including bandwidth management), and Next (generative and agentic AI built on top of that monitoring foundation). Understanding which stage a platform actually operates in is the single most useful filter for evaluating DCIM vendors in 2026 and beyond.
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jfrog

The Secret Sauce of SLSA: DevGovOps at the Speed of Agentic AI

Aug 5, 2026 By Paul Davis In JFrog
Software supply chain engineering has reached a critical inflection point. As autonomous AI coding agents transition from generating autocomplete suggestions to planning, writing, reviewing, and deploying entire software pipelines without humans in the loop, the connection between human intent and production binaries is fracturing.
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appsignal

From Claude Code to Production: A Monitoring Checklist for Python Developers

Aug 5, 2026 By Dejan Lukić In AppSignal
Python is the native language of AI-assisted development. Models are really good at writing it, and a lot of people are now shipping it without ever having written much Python themselves. The whole thing is really simple. You prompt an app, Claude Code or Cursor produces a working Flask or FastAPI backend, and you’re live in a few hours. However, there’s still a big difference between “it works on my machine” and “it works in production”.
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civo

NVIDIA B300 vs. NVIDIA B200: Blackwell Ultra vs. Blackwell

Aug 5, 2026 By Dinesh Majrekar In Civo
The Blackwell architecture arrived in 2024 as NVIDIA's answer to the next era of AI compute. The B200 set a new standard for inference performance, memory capacity, and training throughput, and many teams are still ramping up their use of it today. Then came Blackwell Ultra. The B300 is built on the same silicon foundation as the B200: same dual-reticle die design, same TSMC 4NP process node, same NVLink 5 interconnect.
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cloudzero

How to measure AI ROI: metrics and a framework finance can actually run

Aug 5, 2026 By Lyne Carolyne In CloudZero
To measure AI ROI, compare attributable value (revenue lift, cost savings, engineering time recovered, risk reduction) against fully loaded AI spend (API usage, subscriptions, infrastructure, people time) at the unit level: per initiative, per team, per task. The formula is simple. The instrumentation is the hard part, and it's where most organizations are failing: in CloudZero's 2026 survey, 34% of finance leaders couldn't produce a credible ROI number at all.
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logz.io

Open 360 AI's chat is now powered by OrionIQ

Aug 5, 2026 By Gavriel Mor In logz.io
OrionIQ’s agentic investigation is now built into Logz.io Open 360 AI. Ask a question and OrionIQ investigates across your telemetry, shows its work as it goes, links every finding back to the exact query behind it, and tells you how much to trust the answer. Today we’re bringing OrionIQ Chat into Open 360 AI. This is the first OrionIQ product to ship inside the Logz.io platform, and it’s the same agent that powers the standalone OrionIQ app, now available right where you already work.
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harness

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

Aug 5, 2026 By Pritesh Kiri In Harness
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.
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