Operations | Monitoring | ITSM | DevOps | Cloud

cloudzero

Shipped: Self-serve your MCP server credentials

Sep 3, 2026 By Kaitlin Woo In CloudZero
Enterprise agent platforms need a client ID and client secret in hand before they will connect to anything. An admin with the Modify MCP Settings permission can now issue that pair directly in Settings, connect the platform, and manage the credential lifecycle on whatever schedule your security policy requires. No support request, no wait.
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When an AI Agent Breaks the Law, Who's Responsible?

Sep 3, 2026 By Harness In Harness
An AI agent was given one simple task: book a gym class when a slot became available. Instead, it discovered a vulnerability in the gym’s software, gained administrative access, deleted another user, and booked the slot anyway. Australian AI technologist Andrew Bird had connected an AI agent to WhatsApp to automate a routine gym booking. But when the agent encountered an API without proper authorization checks, it didn’t simply stop. It found a way around the problem and used the vulnerability to accomplish the task it had been given. And that creates a much bigger question.
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coralogix

Automate Product Analyticsreports with your agent and the CX CLI

Sep 3, 2026 By Coralogix Team In Coralogix
Every page view, click, and session your RUM SDK captures lands in Coralogix as a log event under the cx_rum subsystem — the raw data behind how people actually use your product. You can turn it into a shareable report without writing a single query. Just ask your coding agent. Your agent queries that data through the CX CLI and writes the report for you: describe what you want in plain English, get a formatted report back — without leaving the terminal.
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Kubex

Making Shared GPUs Even Safer with Kubex and HAMi-core

Sep 3, 2026 By Kubex In Densify
Table of Contents A few months ago, we introduced Kubex support for the KAI Scheduler to improve GPU sharing for production inference workloads. The basic model is simple: The KAI Scheduler handles placement and GPU sharing. Kubex continuously observes usage and adjusts those allocations as demand changes. KAI provides the scheduling foundation. It lets multiple workloads share a GPU while accounting for the amount of GPU each workload requests. Kubex then closes the loop.
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PostgreSQL IDE + AI Assistant | dbForge Studio for PostgreSQL

Sep 3, 2026 By Devart In Devart
Manage the full PostgreSQL database lifecycle from one AI-powered IDE. dbForge Studio for PostgreSQL brings together database design, development, and administration, as well as data management, analysis, reporting, and extensive automation. Additionally, the integrated AI Assistant generates, explains, optimizes, and troubleshoots SQL queries directly in the Studio. It supports on-premises PostgreSQL databases and related cloud services such as Supabase, Heroku, Amazon Redshift, and TimescaleDB.
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gitkraken

What to Know About AI Code-to-Merge Platforms

Sep 3, 2026 By Jade Nangah In GitKraken
AI coding agents can generate pull requests at a pace your team has never seen. The bottleneck has shifted from writing code to everything that follows: reviewing, iterating, and merging. AI code-to-merge platforms are the category of tools built to manage that entire lifecycle, from the moment an agent starts working to the moment code lands in your main branch. This article walks through ten questions you should ask before committing to a platform.
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datadog

Build and run Datadog workflows from Bits Chat or AI agents

Sep 3, 2026 By Datadog In Datadog
Teams use AI coding agents and Bits Chat to troubleshoot systems and handle complex tasks, often uncovering repetitive work worth automating. But turning those routines into workflows can still require switching tools and recreating context manually. Through the Datadog MCP Server, Workflow Automation now lets you build workflows from Bits Chat or AI coding agents like Claude Code, Cursor, and Codex.
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AI Spend Is a Capacity Problem, Not a Billing Problem

AI Spend Is a Capacity Problem, Not a Billing Problem

Sep 3, 2026 By OpsMatters In OpsMatters
Every organisation running models in production eventually reaches the same point: the AI portion of the cloud bill grows faster than expected, and the immediate response is to invest in visibility. Calls are tagged, spending is attributed, dashboards are created, and the results are shown to the teams responsible.
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Best AI Humanizer Tools for Ops and IT Teams Writing Technical Documentation in 2026

Best AI Humanizer Tools for Ops and IT Teams Writing Technical Documentation in 2026

Sep 3, 2026 By OpsMatters In OpsMatters
You finish the postmortem at 11pm, push it to the knowledge base, and the next morning it comes back flagged. Not for a factual error - the reviewer's note says it reads like AI. So now you're rewriting a document that was already correct. Most ops teams have hit some version of this. DevOps engineers, SREs, and IT ops managers draft runbooks, release notes, API documentation, and incident comms with Copilot, ChatGPT, or Gemini in the loop, because the alternative is writing them from scratch at 2am. The drafting problem is solved. The publishing problem isn't.
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devart

MCP Servers 1.1.0 Add Flexible HTTP Routing and CLI Connection Management

Sep 2, 2026 By dotConnect Team In Devart
We are pleased to announce the release of MCP Servers 1.1.0, bringing new configuration options for HTTP-based deployments and expanded command-line capabilities for managing database connections. The new version makes it easier to control how MCP Servers are exposed over HTTP, host multiple MCP Servers under a single hostname, and configure connections directly from the command line.
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gitkraken

Can You Prove Your AI Agents Are Paying Off? Most Developers Can't

Sep 2, 2026 By Jade Nangah In GitKraken
We put a blunt question to developers on a recent live webinar: right now, could you actually prove AI agents are paying off for you or your team? Only 24% said yes. The other 76% were guessing, unsure, or already suspicious that agents are costing more than they’re saving. That gap between adoption and proof is the real story in agentic development right now. Teams aren’t behind on running agents. They’re behind on knowing whether it’s working.
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jfrog

The Evolution of JFrog AI Catalog: Your AI Control Plane for Agentic Development

Sep 2, 2026 By Guy Eshet In JFrog
In a single morning, a coding agent can pull an open-source model, connect to an unvetted MCP server, and execute a code-optimizing skill from the web. In the rush toward agentic automation, these AI assets quietly bypass traditional security reviews, creating new attack vectors across the software supply chain. Closing this blind spot has been the driving force behind the JFrog AI Catalog since its launch at swampUP 2025.
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cloudzero

Our Customer Success AI bill tripled. Here's why we're spending more.

Sep 2, 2026 By Scott Castle In CloudZero
Pop quiz: If you spend $40,000 per month on Anthropic, and you’ve got two customers, what’s your cost per customer? If you bypassed the easy answer of $20,000 and said, “Scott, you old trickster, that’s not enough information to answer that question,” you’ve won today’s prize: a lesson in the perils of average costs. Let’s flesh out the situation: You put an AI feature in your product, a document assistant powered by Claude.
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cloudzero

Shipped: Rightsize Kubernetes workloads without leaving your MCP client

Sep 2, 2026 By Kevin Lamb In CloudZero
Changing a Kubernetes resource request takes two numbers: what the workload requests, and what it uses. The CloudZero MCP server now returns both, by cluster, namespace, or workload. This gives you a number you can defend. Usage comes back as P95 over the date range you query, 30 days by default. When an engineering lead asks whether a service runs on a smaller request, that is the figure that settles it. Over-provisioning and under-provisioning show up on the same query.
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cloudzero

LLM token cost: pricing per token explained

Sep 2, 2026 By Lyne Carolyne In CloudZero
LLM token cost is the price a provider charges per token a model reads or writes, quoted in dollars per million tokens. Input and output bill at separate rates, with output priced at roughly 5x input. As of September 2026, published rates range from under $0.10 to more than $180 per million tokens on top-end reasoning tiers. In late 2025, Hardik Sonetta of Thomson Reuters Labs published a warning about the most common prompt caching mistake in production.
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How Is AI Changing IT Operations? Building Production-Ready AI Agents with Alex Zinovy

Sep 2, 2026 By Resolve In Resolve
How is AI changing IT operations, and what does it take to move AI agents from impressive demos to production-ready systems? In this episode of Agents of IT, Resolve’s Zack Austin sits down with Alex Cinovoj, Founder and CTO of TechTide AI, to explore what enterprise AI looks like when it has to work in the real world. Alex brings years of hands-on IT, infrastructure, DevOps, and AI engineering experience to a conversation about the shift from experimenting with AI to building trustworthy systems that deliver measurable outcomes.
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Why AI Adoption Fails Without the Data Work First

Why AI Adoption Fails Without the Data Work First

Sep 2, 2026 By OpsMatters In OpsMatters
Most enterprise AI projects don't fail because the model wasn't good enough. They fail because the data underneath was a mess before anyone switched anything on. Duplicated contacts, contradictory fields, records that haven't been touched in three years but are still floating around in production tables. The AI doesn't know any of that context. It just reads what's there and runs with it.
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SaaS Sprawl Is Becoming an IT Problem: Here's How to Bring It Under Control

SaaS Sprawl Is Becoming an IT Problem: Here's How to Bring It Under Control

Sep 2, 2026 By OpsMatters In OpsMatters
For most organizations, SaaS sprawl does not begin with a bad technology decision. It starts with a useful tool. Marketing needs a new analytics platform. Sales adopts prospecting software. HR adds an applicant tracking system. Engineering signs up for another monitoring service. Someone discovers an AI tool that saves several hours a week and puts it on a company card. Each purchase makes sense on its own.
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From AI Prototype to Production: The Technical Architecture Enterprises Need

From AI Prototype to Production: The Technical Architecture Enterprises Need

Sep 2, 2026 By OpsMatters In OpsMatters
Building a generative model that spits out flawless answers in a controlled notebook feels like a massive win for any engineering team. But watching that exact same model crash the second it hits real, concurrent user traffic? That is a frustrating reality check. The gap between a slick proof of concept and a mission-critical deployment is surprisingly wide, and it almost always comes down to the underlying infrastructure. If your systems cannot handle the dynamic load, the smartest algorithm in the world will not save you.
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checkly

We Let AI Agents Rewrite a 92M-Message-a-Day Service in Go. Zero Incidents.

Sep 1, 2026 By Edvinas Janusevicius In Checkly
Our Results Daemon processes about 92 million messages a day. We recently rewrote it from Node.js to Go, and we let Claude Code write it. We wanted to know whether we could trust an agentic rewrite for a critical, high-throughput production service rather than a prototype. It shipped with zero incidents, a 70% reduction in running pods, and a lighter database load.
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haproxy

AI in the public sector (infrastructure challenges and solutions)

Sep 1, 2026 By Amina Mujkanovic In HAProxy
The U.S. government has cataloged over 1,700 active AI use cases, and nearly 90% of federal agencies are already using or planning to use AI. The European Commission has disclosed nearly 1,500 AI use cases across EU member states. With over 3,200 combined AI use cases cataloged across the US and EU, public sector IT leaders face an identical roadblock: traditional application delivery controllers were not designed to parse or throttle Layer 7 LLM payloads, leading to backend GPU exhaustion.
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datadog

From traces to experiments: A loop for improving AI agents

Sep 1, 2026 By Datadog In Datadog
Let’s say your team shipped a support agent last quarter. The launch demo went well, stakeholders were pleased, and everyone moved on. A few months later, things start to look off. Summaries of long conversations are truncated, and monitors show latency spikes on tool calls to the billing API. Your team’s first instinct is to ship fixes such as tweaking prompts or upgrading the model.
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cloudzero

AI usage tracking: Monitor spend by team, feature & model

Sep 1, 2026 By Lyne Carolyne In CloudZero
AI usage tracking means measuring who and what consumes AI across your company, by team, feature, and model, then converting the usage into spend and cost per unit of work. Provider consoles stop at totals per API key. Tracking puts names on those totals: which team, which product, which model, and whether any of it was worth the money. In May 2026, CNBC reported that “almost every Fortune 500 is tracking overall AI usage,” quoting ModelOp CTO Jim Olsen. The same reporting carried his warning.
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upsun

The gap between individual AI productivity and team performance

Sep 1, 2026 By Upsun In Upsun
As a product manager at Upsun with a computer engineering background, Kateryna Dvornichenko had spent months researching competing tools in the agentic development space, running tests, comparing features, and building a picture of where the market was heading. She realized the tools were impressive, but something kept standing out. "Collaboration was not the strong point of any of them," she says. "Everyone stays on their own machine with their own setup.".
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AI can write database code fast. Here's how to keep it safe before production.

Sep 1, 2026 By Redgate Software In Redgate
AI can write database schema changes in seconds, but nothing should reach production until it's validated, tested, and approved. In this discussion, Ken Muse (GitHub), Steve Jones (Redgate), and Huxley Kendall (Redgate) show how a governed pipeline keeps AI-generated database changes safe without slowing teams down.
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How to set up CircleCI with Cursor Origin

Sep 1, 2026 By CircleCI In CircleCI
CircleCI now integrates with Cursor Origin, bringing scalable CI/CD to Origin-hosted repositories. In this demo, see how to connect an Origin repository to CircleCI, configure your pipeline triggers, run a build, and report CI status back to your Origin pull request. Already using CircleCI? Your existing.circleci/config.yml works as-is, with no Origin-specific CI syntax or separate config to maintain.
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How to Use Claude Code with CircleCI to Fix Failed Builds

Sep 1, 2026 By CircleCI In CircleCI
Give Claude Code direct access to CircleCI and let it diagnose failed builds, fix issues, and keep iterating until your pipeline is green. In this tutorial, we walk through how to connect Claude Code to CircleCI using the CircleCI CLI. You’ll see how Claude can read pipeline results, identify test failures, make fixes, trigger new builds, and monitor CircleCI without leaving the terminal.
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From Attention to Action: How Digital Systems Shape Demand

From Attention to Action: How Digital Systems Shape Demand

Sep 1, 2026 By OpsMatters In OpsMatters
Between the moment someone types a query and the moment they act on the result, a sequence of independent systems runs: query rewriting, intent classification, retrieval, an auction, a click-through prediction, a page render measured in hundreds of milliseconds, and a routing decision about where the resulting tap goes. None of those systems is designed to persuade. They are designed to estimate, price, and allocate.
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The End of Browsing: How AI Is Rewriting Digital Discovery

The End of Browsing: How AI Is Rewriting Digital Discovery

Sep 1, 2026 By OpsMatters In OpsMatters
Sometime in 2025, a quiet threshold was crossed: the majority of Google searches in the United States began ending without a single click. Data from SparkToro and Similarweb puts roughly 58.5% of US searches as resolving on the results page itself, and for news queries the zero-click rate climbed from 56% to 69% in a single year. The search box still works the way it always has. What changed is that we've stopped leaving it.
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Why More Technology Is Becoming a Service Instead of a Product

Why More Technology Is Becoming a Service Instead of a Product

Sep 1, 2026 By OpsMatters In OpsMatters
A growing number of technology purchases no longer end at checkout. A phone gains new AI features months after launch, a vehicle receives software updates from the cloud, and a security camera may lose important functions if its online service disappears. The physical product still matters, but increasingly it is only the visible edge of a much larger system.
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