Operations | Monitoring | ITSM | DevOps | Cloud

As organizations increasingly adopt multi-cloud strategies, identifying areas to reduce cloud spend has become highly complex and time consuming. While there are many reasons that organizations choose to run their infrastructure in a multi-cloud environment, many do so to comply with regional data requirements, take advantage of best-of-breed offerings, or avoid vendor lock-in.

When developing software, the longer you intend to keep a system around, the more important it becomes to prioritize its code quality. But as more organizations move toward microservice architectures and adopt agentic AI and LLMs into their development workflows, many engineering teams have increased their emphasis on accelerating developer velocity, often at the expense of code quality. This can often result in code that fails to meet standards for performance, reliability, and security.

Kubernetes v1.34, which is scheduled for release August 27, 2025, focuses on improved scheduler visibility, deeper life cycle observability, and enhanced resource management. As always, the list of changes and improvements in the official changelog is extensive, and cluster operators may be wondering which changes are most important. If you're operating a monitoring platform or depend on deep Kubernetes observability, here's how a number of new features will affect your workflows.

In the early stages of building a system, a few well-placed dashboards and monitors can provide sufficient visibility into service health and performance. However, as infrastructure scales and teams grow, so does the complexity of the monitoring landscape. In organizations where individual teams manage their own services but rely on a central platform or observability team for tooling and guidance, this complexity can quickly multiply.

As modern infrastructure becomes increasingly distributed across on-premises data centers, multi-cloud environments, ISPs, and remote offices, understanding how traffic flows across your network is critical to delivering reliable performance and great user experiences. But pinpointing the source of network slowdowns remains one of the most persistent challenges for operations, network, and IT teams.