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How to Choose Managed IT Services in Addison, IL: A Buyer's Guide for Local Businesses

If your servers go down during a shipping window or a ransomware email slips past an unpatched laptop, the cost lands on your business within hours - not next quarter. For the manufacturers, warehouses, logistics operators, and professional-services firms packed into Addison's roughly 21 million square feet of industrial and commercial space, that risk is the reason managed IT services have moved from "nice to have" to baseline infrastructure. The hard part isn't deciding whether to outsource technology operations. It's choosing the right provider.

The Modern B2B Outbound Lead Generation Playbook: Building a Predictable Sales Pipeline

If you're relying on referrals, inbound inquiries, or the occasional marketing campaign to fill your sales pipeline, there is less chance of growth. While those channels are relevant, they rarely provide the consistency that B2B companies need to forecast revenue and scale with confidence. Here comes B2B outbound lead generation. Outbound is all about identifying the right prospects, starting meaningful conversations, and creating a repeatable process that delivers qualified opportunities.

Aiven for Valkey Dev Tier is Live #aiven #valkey #developer

You're gonna want a cache. Aiven for Valkey's Dev Tier gets you 2 CPUs and 4 GB RAM on a single node, with automated backups, full monitoring (metrics + logs), and basic support included. JSON, Bloom filters, and Search come pre-enabled. AIVEN DATA PLATFORM The Aiven Platform is more than a collection of open source services for streaming, storing and analyzing data. The platform ensures that all services run reliably and securely in the clouds of your choice, are observable, and can easily be integrated with each other and with external 3rd party tools.

How AI-First Operations Unlocks Compounding Engineering Productivity

Engineering teams have plenty of ideas, but they’re often short on time to act on them. As software systems grow more complex, an increasing share of engineering capacity is consumed by non-building activities: investigating alerts, coordinating fixes, and managing operational incidents. Every hour spent diagnosing failures is an hour not spent shipping features or experimenting with new product ideas. Over time, that lost capacity compounds.

Overview of AI Evaluation (The Context Window #05)

Can you actually trust an AI agent? In this pre-recorded episode of The Context Window, Nicole van der Hoeven sits down with Yas Ekinci, an engineer on the Grafana AI team, to talk about evals — how Grafana measures the quality and reliability of the AI it ships. They get into the difference between online and offline evals, why reviewing AI-generated code has become the real bottleneck, the "final answer problem" of plausible-but-wrong outputs, and o11y-bench, Grafana's open benchmark for observability agents. Along the way.

The debugging crisis nobody's talking about: AI, abstraction, and the skills gap

Here's a scenario that's playing out in engineering teams across the industry right now. A developer uses AI to rapidly prototype a microservice. The code works. They deploy it to production. Six months later, something breaks. The system is under load, a database connection pools, and the service starts failing in subtle ways. The engineer pulls up the code, but here's the problem, they didn't write it. An AI assistant did. They don't understand the flow deeply. They don't know where to look first.

Where did all my Claude Code tokens go?

Most teams judge their AI coding agent on two things: the monthly bill and a feeling. The bill tells you what you spent and the feeling tells you whether it seems to be helping, but neither one tells you what the agent actually did. As these tools move into the critical path of how software ships, that gap is starting to matter. I wanted to replace the feeling with something I could measure and understand what shapes of work affects this bill, so I decided to run an experiment on myself.

How AI is changing platform engineering

AI is changing software development fast. But what does that actually mean for platform engineering teams? In this conversation, Civo's John Dietz and M R Rishi dig into what they're seeing on the ground, the 10x effect of AI on app count, what it means for platform team workloads, the debugging skills that are quietly being lost, and whether Kubernetes itself might eventually become just another abstraction.

Azure FinOps with AI: What's New in Turbo360 v5.2

Turbo360 v5.2 is the biggest AI update we've shipped. Every module now has AI built in - not just to surface data, but to explain it, guide you through it, and help non-experts take action without needing to call in a specialist. In this video, Mike Stephenson walks through every new feature in v5.2, from AI agents that explain cost drivers and rightsizing recommendations, to a brand new Savings Tracker that gives you a better way to prove FinOps impact to management.