Operations | Monitoring | ITSM | DevOps | Cloud

Most large enterprises elect a hybrid approach to SAP operations, but this is a more recent trend. And, as SAP operations professionals, we are still learning about the impacts of this choice and approach, even though it’s often the most sensible and pragmatic. Years ago, everything ran on-premises.

Avantra 21 introduced the concept of Automation workflows. By Avantra 23, compatibility with Ansible was added. Along the way, Avantra became the tool SAP teams reached for when they wanted system copies, refreshes, and backup orchestration to just run — predictably, on a schedule, without a senior engineer babysitting them. So, automation isn’t new to Avantra users. Avantra made automation for SAP practical to deploy, predictable in operation, and easier to maintain.

Many teams use Notion as the central hub for documentation, runbooks, incident response, and operational planning. When an outage occurs, the last thing you want is for responders to jump between multiple tools searching for information about the health of critical vendors and dependencies. That’s why we’re excited to introduce the StatusGator Notion integration.

Distributed systems don't just fail. They adapt. Services in Tencent Cloud environments are tightly interconnected. Compute, load balancing, databases, and networking layers continuously respond to each other based on changing conditions. Under normal load, this coordination stays in the background. As pressure builds, the behavior shifts. The system does not degrade in a straight line. Instead, it starts adjusting itself.

Operational visibility is becoming increasingly important as infrastructure teams are asked to support AI initiatives, automation goals, cost accountability, modernization efforts, and growing operational complexity at the same time. Most are expected to do it without expanding headcount, introducing additional risk, or rebuilding the environment from scratch. Those expectations are changing the role of infrastructure operations.

Engineering teams are shipping more AI-generated code than ever, but at what cost? Learn how to build a telemetry pipeline to monitor Claude Code usage and costs directly in SquaredUp. It is estimated that 85-90% of engineering teams are now using AI coding assistants such as Claude, Codex and Cursor. This is not just for small-scale pilot projects— around 40% of all code now being shipped is AI-generated, and in start-ups the figure is around 95%. This can result in incredible productivity gains.

The quick download: Most observability strategies overlook the internet layer that underpins every user’s digital experience, leaving it almost entirely unmonitored. Most IT teams monitor servers, networks, and applications, yet the infrastructure layer that carries traffic to users remains largely unmonitored.

Modern IT environments generate huge volumes of telemetry across infrastructure, applications, cloud services, and networks. Teams now have more data than ever, but that does not automatically lead to better decisions. In many organizations, the real problem is no longer visibility alone. It is the ability to identify which signals matter, understand what they mean, and respond before users or business services are affected.

Sentry Snapshots diffs screenshots on every commit and blocks the PR if there are any visual changes so you can confirm they’re intentional. Users don’t interact with code, they interact with something they can see and touch. Snapshots gives you a lightweight way to test it. It’s easier than ever to change code. It’s also easier than ever to trade quality for speed. Modern codebases need guardrails to ensure correctness.