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Kubex

Kubernetes GPU Scheduling for MLOps and GPU Sharing

Aug 6, 2026 By Kubex In Densify
The default Kubernetes scheduler was built for stateless services: web servers, APIs, databases. It schedules a pod, checks that a node has enough of whatever resources were requested, and binds it. For CPU and memory, that model works fine. For GPUs, it falls apart in three specific ways. First, GPUs are treated as an opaque integer resource.
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megaport

Are AI Coding Agents the New CI Bottleneck?

Aug 6, 2026 By Megaport In Megaport
AI coding agents are moving the software bottleneck from writing code to validating it. Here’s what that means for CI infrastructure, capacity planning, and software quality. This topic is explored in more detail in “CI Can’t Keep Up With AI,” an episode of Uplink, where Aditya “JP” Jayaprakash, Co-founder and CEO of Blacksmith, discusses how AI coding agents are reshaping CI and software delivery. Table of Contents.
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elastic

Building trusted agentic AI in financial services: From data to autonomous action

Aug 6, 2026 By Karen Mcdermott In Elastic
As financial institutions move from AI experimentation to autonomous operations, trusted context, governance, and observability become the foundation for enterprise-scale Agentic AI. Artificial intelligence in financial services is entering a new era. Historically, financial services companies have focused on deploying generative AI to improve productivity, enhance customer experiences, accelerate software development, and streamline operations.
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gremlin

What your AI SRE can't see (and what you can do about it)

Aug 6, 2026 By Ryan Detwiller In Gremlin
AI SRE is having a moment. The category pulled in massive funding rounds over the last two years, Gartner published its first market guide, and vendors are promising everything from 90% faster resolution to fully autonomous incident response. If you run an engineering organization, someone has probably pitched you an AI SRE in the last quarter. And let’s be honest: faster triage, less alert fatigue, and automated frontline response are wins for understaffed teams.
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Aiven

Skills as Guardrails: Contributing to Apache Kafka with AI, Without Knowing Every Module

Aug 6, 2026 By Muralidhar Basani | In Aiven
Let me start with something most Kafka contributors think but rarely say out loud: nobody understands all of Kafka. I'm not a core committer and have only contributed a few times, but those contributions I have made have been in part thanks to using coding assistants. There are some issues with this approach though, the Apache Kafka project is huge. It's split into many parts: the core, the server, the client libraries, the streams engine, the storage layer, the consensus code, and more.
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tigera

The New MCP Headers Are a Gift to Gateways

Aug 6, 2026 By Alister Baroi In Tigera
In short, buried in the transport section of the MCP 2026-07-28 release candidate are three changes that matter more to infrastructure teams than to anyone else: mandatory Mcp-Method and Mcp-Name headers, cache-control-style ttlMs and cacheScope fields, and standardized W3C Trace Context propagation. Together with the stateless core, they turn MCP from a protocol that gateways had to fight into one that meets them halfway.
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Install an AI SRE Agent in Kubernetes with AURA and Helm

Aug 6, 2026 By Mezmo In Mezmo
AURA does not have to live on your laptop. Install it into the cluster with Helm and it is still there the next time something breaks. AURA is a fully open source AI agent built specifically for SRE work. Rather than one general assistant, you configure workers: separate agent roles, each scoped to a job like inspecting the cluster.
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Free Open Source AI Agent for SRE and More: Why We Give AURA Away

Aug 6, 2026 By Mezmo In Mezmo
Wondering what the catch is on a free, vendor-backed agent? There is not one in the license. AURA stays Apache 2, fully capable, and free to run. If you are weighing an open source tool with a company behind it, the first question is what the catch is. You have seen the project that turns out to be open core, or that is quietly hindered in one key way. This is Mezmo's answer for AURA.
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Open Source AI Agent for SRE: Why AURA Is Free

Aug 6, 2026 By Mezmo In Mezmo
The most common question since we started 31 Days of AURA: how do you plan to make money? The short answer is the control plane, not the agent. Mezmo sells an enterprise-grade control plane for running large numbers of agents across large environments, where coordinating across environments, governance, access control, and the efficiency of preprocessing MCP data start to matter. If a hundred people run AURA and three or four of them need that, the model works. The more people running AI agents in production, the bigger the market for the tooling underneath them.
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gitkraken

Open Models Are Closing the Gap

Aug 6, 2026 By Chris Griffing In GitKraken
The frontier models have led the pack for a while now. It seems like the big players of Anthropic and OpenAI keep leapfrogging each other by a couple points in benchmark scores every other month. But, a trend we are starting to see is that open weight models are improving by leaps and bounds. They don’t hold the lead and probably won’t for a while, but the fact that open models are scaring the leaders is something to think about.
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