Operations | Monitoring | ITSM | DevOps | Cloud

Splunk Enterprise customers want access to the latest Splunk capabilities as quickly as possible. Occasionally, new experiences arrive first for Splunk Cloud, leaving self-managed customers without a clear timeline. Cloud Connect is a creative way Splunk is solving that problem. Cloud Connect gives Splunk Enterprise customers a standard admin path to access curated Splunk-managed services.

This is the second post in our DRIVE Deep Dive series. Over the coming weeks we're examining each pillar of the DRIVE framework in turn, and mapping DRIVE against the frameworks engineering leaders already run on, including DORA and SPACE. For the complete model, download the full DRIVE framework. Our last post covered Delivery. Up next: Initiatives. --- AI has removed the last real constraint on producing code, and organizations are shipping more of it than ever.

The GitHub Copilot cost runs from $0 for the Free tier to $10/month for Pro, $39/month for Pro+, and $100/month for Max. Teams pay $19/user/month for Business and $39/user/month for Enterprise. The twist: on June 1, 2026 GitHub swapped fixed premium requests for usage-based AI Credits, so what those flat fees actually buy now depends on how hard you push the AI. The sticker price is the easy part. The part that ambushes finance is everything stacked on top of it.

Deterministic processes carry one guarantee: the same input will produce the same output. That guarantee built the entire observability stack. AI broke that contract by reasoning in terms of probability. The same input can now produce different outputs, whether from AI-generated code that carries assumptions invisible in staging, or from distributed systems where timing creates failures that no pre-captured telemetry can anticipate.

Every IT leader is under pressure to show AI results. Budgets are approved, pilots are launched, and vendors promise transformation within a quarter. Some teams are already running AI agents in production, resolving tickets and answering employees without human intervention. Others are still stuck in proof-of-concept purgatory, six months into a rollout with nothing to show a board. The thing is, AI doesn't fix what's broken in an IT operation, it multiplies what's already there.

AI agents are changing how software gets built, but the infrastructure around them hasn’t caught up. Agents burn through tokens on noise. They take actions they shouldn’t. Context evaporates between releases. And most delivery pipelines were never designed for the pace and volume of agentic development.

Every developer knows the moment: CI goes red, and you face a choice. Open the browser and click through the web UI to the run, the workflow, the job, the step, the log line. Or stay in the terminal, where the fix is going to happen anyway. The new CircleCI CLI exists so you can stay. It’s 1.0, it’s in beta, and it’s a ground-up rewrite in Go, not an iteration on the CLI we’ve shipped for years.

Your monitoring stack never sleeps. Datadog fires a spike, ServiceNow spins up a ticket, your RMM flags a failed backup, and every one of those signals competes for attention across email, dashboards, and chat channels. For IT Ops teams running on-call rotations, the volume itself becomes the problem. Alert fatigue sets in, critical notifications blend into the noise, and the one incident that matters at 3 a.m. gets buried under a hundred that don’t. The cost is real.

One of the primary reasons organizations adopt Grafana Cloud is to create a single pane of glass across the data they collect from self-hosted systems, cloud providers, and third-party platforms. Bringing those signals together enables richer correlations, reduces tool sprawl, and makes it easier for teams to understand what's happening across their environment. But as observability grows and becomes more centralized, access management becomes more important.

A platform is an environment that allows software to run smoothly across the infrastructure, runtime, and application layers. The key word there is “smoothly”: a good platform connects those layers so well that you don’t notice it. That’s what Ubuntu Server has become: the essential layer between bare metal and the apps running on top, continuously optimized across resource management, networking, and security. Ubuntu 26.04 LTS represents over 12 years of that work coming together.