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Turning Churn Into A Growth Engine

Jul 6, 2026 By N-able In N-able

An MSP facing churn asked how to reach out to a list of 500 local businesses, but the advice was that mass outreach is activity, not strategy, and the real need is rebuilding a growth engine. The episode outlines six points.

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Governance while scaling AI in IT operations

Jul 6, 2026 By Ivanti In Ivanti

Ivanti is a leading enterprise software company that offers a powerful, cloud-based IT and security platform. Our solutions are designed to scale with your business, helping IT and Security teams boost operational efficiency, cut costs and stay ahead of security threats. The Ivanti Neurons platform is cloud-native, providing a unified and reusable foundation for consistent visibility, scalability, and secure delivery. Trusted by over 34,000 customers, including 85 of the Fortune 100, Ivanti empowers organizations to tackle challenges with end-to-end solutions.

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Shipped: Give your Explorer filters & groupings room to scale

Jul 6, 2026 By Kaitlin Woo In CloudZero

The controls at the top of Explorer are great for a simple question. But as your query grows with more group-bys or a stack of filters, those controls start eating into the vertical space you actually want for your data. Now you have the option to move filters and groupings into a dedicated left side panel, so a complex query has room to scale cleanly. Set it once and CloudZero keeps it that way.

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GPT-4 API cost 2026: pricing breakdown and how to estimate it

Jul 6, 2026 By Lyne Carolyne In CloudZero

GPT-4 API pricing spans $0.10 to $30.00 per million input tokens across the model family. GPT-4.1 is the current recommended production model at $2.00 input / $8.00 output per million tokens. Legacy GPT-4 still runs at $30.00/$60.00 per million tokens -- 15x more expensive for no meaningful quality gain. For finance and engineering leaders accountable for AI spend, choosing the right GPT-4 variant is the single biggest cost lever on your bill.

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CloudZero

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ActiveMQ Backup and Disaster Recovery: Complete DR Guide

Jul 6, 2026 By meshIQ In meshIQ

A message broker's backup and disaster recovery plan is the last line of defense against scenarios that HA cannot address: a full datacenter outage, catastrophic hardware failure that destroys both primary and secondary nodes, accidental message deletion, or KahaDB corruption that prevents the broker from starting.

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meshIQ

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ActiveMQ JVM Memory & GC Tuning: Heap Sizing, G1GC, ZGC Guide

Jul 6, 2026 By meshIQ In meshIQ

The JVM is the runtime foundation of every ActiveMQ deployment. Message throughput, delivery latency, producer flow control triggers, OOM crashes, and GC-induced delivery pauses all trace back to JVM memory configuration. Yet ActiveMQ ships with a 512MB heap and no GC logging, appropriate for a developer laptop, not for an enterprise message broker handling millions of messages a day.

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One SSL certificate on multiple servers

Jul 6, 2026 By Todd H. Gardner In CertKit

Every certificate renewal automation tool has to answer one architecture question before it does anything else: where does the private key get generated? A reader who used to be “the certificate guy” at his organization emailed me this week to ask about exactly that: It’s the right instinct. It’s also how most automation tools work. Certbot generates the key on the server, builds a certificate signing request, and the private key never leaves the machine.

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From Prototype to Production With AWS AgentCore

Jul 6, 2026 By Moses Mendoza In Honeycomb

"Hello world, this is your agent speaking!" The agent loop! The LLM is calling tools, the answers are sensible, and the sky's the limit. Now, as you look forward to production, you look for a composable toolset, something that can grow with your use case and system needs. That's what we created with Honeycomb Canvas: a collaborative investigation space where AI agents help you understand, fix, and learn about your system.

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Q&A: How Elastic and Anyshift are bringing AI-powered context to incident response

Jul 6, 2026 By Sunnie Weber In Elastic

Incident response often depends on connecting two kinds of context: what changed in the environment and what the logs say happened next. Through a new integration with Elastic, Anyshift’s AI agent, Annie, can read from a customer’s Elasticsearch deployment to search logs, surface error and warning spikes, and correlate log evidence with infrastructure change history.

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