Operations | Monitoring | ITSM | DevOps | Cloud

In large tech organizations, keeping track of every laptop, desktop, and endpoint is one of the IT department’s toughest challenges. Each device needs to be accounted for, properly assigned, and compliant with the organization’s policies, all while teams, offices, and contractors constantly change.

The data is there, but it’s scattered across domains, formats, and vendors. Teams are often left piecing together an incomplete story of what went wrong, long after the damage has been done. Now, a new open standard is changing that. OpenTelemetry (OTel) is fast becoming the connective tissue of modern observability—an open-source framework designed to make telemetry data (metrics, logs, and traces) universally accessible.

Deploying web apps can feel overwhelming. Multiple moving parts, including frameworks, hosting, databases, and automation tools make having a smooth, automated workflow seem impossible. But having an automated workflow is worth the effort; you can focus on building features and improving your app instead of worrying about manual deployments or server management.

OpenTofu has emerged as the true open successor to Terraform, restoring transparency and community ownership after Terraform’s shift to a restrictive BSL license. With features like OCI registries, encryption at rest, and a public RFC process, it’s already outpacing Terraform’s innovation.

Enterprises rely on regular patching to secure systems and maintain compliance. Unpatched vulnerabilities expose networks to data breaches and downtime. Implementing structured Windows patch management ensures that every device, server, and virtual endpoint stays protected and up to date. With distributed teams and hybrid IT setups, managing updates manually creates risk. Automated processes improve consistency, visibility, and control while cutting down manual workload.

You want fewer incidents, happier users, and one policy to rule them all—without living in twelve dashboards. Cisco Security Cloud brings the controls together; C1 Managed Services keeps them humming so your team can stop firefighting and start delivering.

One of the best parts of my job is helping Cycle users explore self-hosting options on the platform. This time, I had the pleasure of working with Dgraph (now a part of Hypermode). If you haven't heard of it, Dgraph is a distributed, horizontally scalable graph database that gives you a native graph storage/compute engine with distributed ACID transactions (via Raft and snapshot isolation) and first-class GraphQL.

In 2026, application performance isn’t just a technical metric—it’s a business-critical factor. As organizations move deeper into cloud-native architectures, distributed systems, and AI-driven workflows, ensuring speed, reliability, and uptime has become non-negotiable. According to Gartner, by 2026 more than 70% of new APM implementations will be cloud-native, and businesses that leverage advanced observability platforms are expected to reduce downtime by up to 60%.

Whether it’s a stalled Log Reader Agent, a conflicting insert on the subscriber, or a failed cleanup job bloating the distribution database, Redgate Monitor now brings SQL Server replication issues to light early, before performance or reliability are affected. In many SQL Server environments, replication remains essential for offloading reporting and analytics workloads, or for maintaining local and synchronized data copies across regions.

This is the next installment of the series on building a database and an application called dbRosetta using AI/LLM. Part 1 introduces the concept. THE AI PICKED DATABASE FIRST! Look, I talk databases at this thing a lot, so it probably knows my own preference, but when I asked it, it chose to build a database separate from the code. Let’s get into it.