Systems | Development | Analytics | API | Testing

7 Ways Power Cables Affect Data Center Performance and Uptime

Data centers are the backbone of the digital economy. Every second of downtime can cost a business thousands of dollars - and in some cases, damage its reputation beyond repair. While most conversations around uptime focus on servers, cooling systems, and redundant networks, the role of power cables is often overlooked. Yet these humble components sit at the heart of every data center's reliability.

The Impact of Network Latency on Cloud Load Testing Accuracy: Rethinking Performance Data in 2026

Teams often assume that cloud load test results reflect how their applications will perform under real-world pressure. Yet, network latency is the silent variable that can quietly undermine these results. While organizations invest heavily in simulating user traffic, they often overlook the impact of latency – a factor that can significantly alter outcomes. Latency is ever-present in cloud testing, but rarely receives the attention it deserves.

How durable sessions unify human-to-human and human-to-agent messages

AI chats are often a rather solitary experience: just you and ChatGPT, sitting there together, solving a problem. But so many of the tasks that we perform day to day are ones that benefit from, or often even require, collaboration with other people such as colleagues, family members, or friends. So, if AI agents are helpful, and other people are helpful, then how can we provide a space for multiple people to collaborate with each other and with AI agents?

The Perforce Delphix DevOps Data Platform Explained in Under 3 Minutes

Software teams move fast — until they hit a data bottleneck. Meet the Delphix DevOps Data Platform from Perforce. Delphix automates the delivery of compliant, production-quality, and AI-ready data so teams can validate and release software at AI speed. With Delphix, you can: Provision and refresh virtual datasets in minutes, not days or weeks. Automatically discover and mask sensitive data while preserving relationships across systems.

Reliable Pipelines, Predictable Bills: Why Settle for One Without the Other

Somewhere along the way, data teams accepted a trade-off: pipelines that just work, or bills that you can actually forecast, pick one. So you live with the silent failures, the schema changes that break dashboards overnight, and the month-end invoice that never quite matches the data you moved. Not because it's acceptable, but because it's familiar. In this session, we're challenging that trade-off head-on. We'll break down where pipelines fail quietly and where costs inflate invisibly and show you, live, what it looks like when your pipeline gives you full visibility into every sync, every record, and every dollar.

AI Agents Deployed, but what about cost optimization?

AI agents are no longer a pilot-stage bet. As of 2026, 80% of enterprises have at least one production AI agent deployed. The global AI agents market has crossed $10.91 billion and is sprinting toward $52.62 billion by 2030. The cost-per-task economics are staggering: a human-handled customer support ticket costs $4.18 on average. An AI agent resolves the same ticket for $0.46. That is a 9x cost reduction, right there.

Is AI making your teams better, or just busier?

AI adoption programs tend to end in the same place. Tools are accessible, usage is up, and there's a dedicated Slack channel for wins. Six months later, nothing about how the team works has fundamentally changed. People are doing the same things – just slightly faster. And it’s easy for programs to stall when you’re measuring the wrong thing. Adoption (whether people have access and whether they're using the tools) is visible and easy to report.