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AlmaIQ brings unparalleled level of efficiency and effectiveness for IT teams using Collective IQ

AlmaIQ, the intelligent self-service agent for employees just received an incredible boost that expands its role to uniquely help IT teams. Interacting with users through Microsoft Teams, AlmaIQ answers questions about devices and internal processes in natural language. Whereas that intelligence simplified employees lives on the job, it now enables IT teams to interact with Collective IQ at the level of departments, groups, and collections of devices to spot patterns and trends. The overall result: vastly more productive operations and satisfied employees.
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Did we miss the end of LaMa?

In mid-2024, SAP announced the discontinuation of SAP Landscape Management ("LaMa"). This wasn't a huge surprise, as the 2027 end-of-support date aligns neatly with Solution Manager, Focused Run and standard support for ECC. SAP also terminated work on SAP Landscape Management Cloud, discontinuing that product immediately. Responses to the post were as expected: customers asking, "What now?" and even expressing a bit of dismay. One response from SAP was especially telling: "Moving the ERP system to the cloud hands over the tasks realized with SAP Landscape Management to SAP as cloud vendor.

Network Topology: Types, Diagrams, Tools & Enterprise Best Practices

Network topology describes how devices, connections, and data flows are arranged in a network. It is the blueprint of your network infrastructure. Both matter because they affect performance, scalability, and security. A well-designed topology ensures data reaches its destination quickly and reliably. A poor design creates bottlenecks, security gaps, and troubleshooting nightmares.

Groq vs. GPUs: The future of AI inference in 2026

Back in 2016, Jonathan Ross founded Groq, the AI chip startup, which went on to enter a non-exclusive licensing agreement with NVIDIA for Groq’s inference technology (as part of a $20 billion deal). The name ‘Groq’ is commonly confused with X (formerly Twitter)’s Grok, which was launched in 2023 as a Gen AI chatbot. As demand for real-time AI continues to grow, inference has become one of the most important and expensive parts of the machine learning lifecycle.

Finding performance bottlenecks with Pyroscope and Alloy: An example using TON blockchain

Performance optimization often feels like searching for a needle in a haystack. You know your code is slow, but where exactly is the bottleneck? This is where continuous profiling comes in. In this blog post, we’ll explore how continuous profiling with Alloy and Pyroscope can transform the way you approach performance optimization.

Build Numbers That Actually Make Sense: Branch-Scoped Sequence IDs in Harness CI | Harness Blog

You're tagging Docker images with build numbers. -Build is your latest production release on main. A developer pushes a hotfix to release-v2.1, that run becomes build. -Another merges to develop, build. A week later someone asks: "What build number are we on for production?" You check the registry. -You see,,, on main. The numbers in between? Scattered across feature branches that may never ship. Your build numbers have stopped telling a useful story.

Telegraf Enterprise Beta is Now Available: Centralized Control for Telegraf at Scale

Telegraf is incredibly good at what it does: collecting metrics, logs, and events from just about anywhere and sending them wherever you need. But once Telegraf becomes part of your production telemetry pipeline, spread across environments, teams, regions, and edge locations, the hard part isn’t installing agents; it’s operating them. Configs drift. “Temporary” overrides linger. Rolling out changes across hundreds (or thousands) of agents becomes a careful, manual process.

One CLI, Two Audiences: How We Built for Agents and Human

Half of the Checkly CLI users are already coding agents. This is not a prediction — it's what the data shows today. Since February, more and more agents have been using the CLI to manage and configure their Checkly monitoring setups. Right now, we're at 50% human and 50% agentic CLI users. And we predict that by the end of 2026, it won't be humans using the CLI; the agents will have taken over. The terminal became the primary interface for AI agents doing real work in the Checkly ecosystem.

Checkly and the Agentic Software Layer

November 24th, the Opus 4.5 release turned around the entire tech industry. This was the moment when agents became capable. Capable enough to write solid staff-level code. Capable enough to reason about alerts, investigate root causes much faster than most engineers, and set up the reliability layer faster. For me, this feels like an iPhone moment on steroids; the adoption of AI is accelerating much faster than any adoption curve I’ve seen over the past few decades.

How to Reduce MTTR with AI

The quick download: AI reduces MTTR by helping teams detect issues sooner, pinpoint root causes faster, and resolve incidents with less manual effort. IT downtime costs organizations an average of $9,000 per minute. AI-powered observability can cut incident resolution time by up to 70%. Here’s what it takes to get there. Every minute an incident goes unresolved, the meter is running.