Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Author: Alexander Ivanyuk, Senior Director, Technology AI is moving fast, and with that speed comes a new set of terms that many business readers are now hearing for the first time: RAG and MCP. They may sound technical, but the ideas behind them are actually practical. They describe how modern AI systems get better information, connect to business tools, and, in some cases, go beyond answering questions to carrying out work.

Your database crashes at 2 PM, but your last backup ran at midnight. That’s 14 hours of lost transactions, customer records, and operational data. The gap between your last usable backup and the moment disaster strikes is exactly what the recovery point objective (RPO) defines. Most organizations don’t think seriously about it until they’re already staring at the damage. RPO in disaster recovery planning determines whether you lose five minutes of data or five days of it.

MSPs managing hundreds or thousands of endpoints cannot afford remote support that lives in a separate tool, on a separate license, with a separate login and a separate workflow. Every extra console adds friction between monitoring, troubleshooting, patching, and security response. That is exactly why AI remote desktop matters now: not as a buzzword, but as a way to shorten the path from issue detection to issue resolution while keeping technicians in one operational environment.

Most OpenShift Virtualization projects start with a simple goal: move virtual machines off a traditional hypervisor and onto a Kubernetes-based platform without forcing every workload to be rewritten. That is a practical goal. Many organizations have VM estates that will not become containers any time soon, and OpenShift Virtualization gives infrastructure teams a way to run those VMs next to containerized applications on the same operational platform.

Something significant is happening across enterprise IT right now — and I do not think it has been fully reckoned with yet. More than 5,000 organizations are actively evaluating or executing a migration away from VMware. The Broadcom acquisition changed the economics of VMware dramatically and abruptly. Licensing costs surged. Bundling decisions eliminated flexibility.

Manufacturers face a trio of converging challenges: Cyberthreats are escalating, regulations are tightening, and operational environments are becoming more complex. The traditional approach to operational technology (OT) security is no longer working. Manufacturers need to respond by moving toward platform-based cybersecurity to reduce risk and improve resilience. An ARC Advisory Group report published in April 2026 provides details.

Managing a growing list of vendors can add complexity across an organization. Adding a new partner may require navigating additional administrative processes and internal alignment. As a result, third-party DevOps backup often ends up lower on the priority list until one serious data deletion, prolonged recovery, or failed restore turns it from a “nice to have” into an executive-level decision.

Amazon Simple Storage Service (S3) is a popular cloud storage service part of the Amazon Web Services (AWS). Amazon S3 cloud storage provides high reliability, flexibility, scalability and accessibility. The number of objects and the amount of data stored in Amazon S3 is unlimited. S3 cloud storage is attractive for business because you pay only for what you use. However, terminology and methodology may lead to misunderstanding and difficulties for new Amazon S3 users. Where is S3 data stored?

The initial ESXi configuration after installation is an important step in making sure the host is functional, that is ready to serve as a standalone host or as part of a vCenter cluster. In the previous post, we explained the interactive ESXi installation step by step. Once the installation is done, you need to complete some initial ESXi configuration in the Direct Console User Interface (DCUI) and embedded VMware Host Client.