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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Cut AI coding defects by 33% #mcpserver #aicoding #aiagents #grafana #aitools

Aug 5, 2026 By Speedscale In Speedscale
We spend thousands of dollars "token maxing" and running endless debugging cycles just to walk our LLMs through a problem. But is the AI actually failing, or are we just withholding the right environment? Giving your AI assistant its own sandbox to test hypotheses might just be the missing link in your development workflow.
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honeycomb

Introducing AI BubbleUp

Aug 5, 2026 By Kale Bogdanovs In Honeycomb
BubbleUp has always been the fastest way to figure out what a group of outliers have in common. Draw a box around a band of slow traces, a cluster of errors, or any set of events you're interested in, and BubbleUp compares that selection to the baseline across every dimension you've sent us. It's how Honeycomb users find the "unknown unknowns" that dashboards can’t show you.
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The Hidden Risk of Scaling AI Without a Single Source of Truth

Aug 5, 2026 By Ivanti In Ivanti
AI doesn’t fail because it’s not smart enough—it fails because it can’t see the full picture. In this video, Sterling Parker, Ivanti’s SVP of Technical Solutions and Services, explains why fragmented and "dirty" data is the biggest obstacle holding AI back for organizations today. When AI pulls from disconnected systems, it’s forced to fill in the gaps with its own intelligence, leading to hallucinations and outcomes that are hard to trust. Sterling breaks down how these "cracks in the foundation" can actually create new security vulnerabilities when scaled too quickly.
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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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