Operations | Monitoring | ITSM | DevOps | Cloud

OpenTelemetry (OTel) is transforming observability by standardizing and unifying how telemetry data such as metrics, logs, and traces are collected from distributed systems. However, while it unlocks new opportunities for monitoring and troubleshooting, adopting and operating OpenTelemetry comes with real-world challenges. Here’s what you need to know about these limitations, and how Site24x7 provides a holistic, simplified observability solution for your organization.

In a webinar hosted by CloudZero on Oct. 30, 2025, Larry Advey, Director of Cloud Platform and FinOps and a respected voice in the FinOps community, joined Umesh Rao to deliver a practical session on cloud cost allocation. The session, titled Three Allocation Mistakes Most FinOps Teams Make, unpacked hard-earned lessons and offered a guided tour of CloudZero’s new Dimension Studio.

Imagine you have an API service composed of multiple microservices. Traffic fluctuates — sometimes light, sometimes spiking. Without Fargate, you’d have to manage EC2 instances, autoscaling, patching, and more. With Fargate, you define each microservice as a task, setting the CPU/memory, container image, network rules, and AWS schedules, and then run them as needed. The result: faster deployment, lower ops overhead, and smooth scaling.

As AI workloads and cloud-native applications expand, organizations are generating more log data than ever. Each service, container, and model inference produces continuous telemetry that must be stored, secured, and analyzed. As telemetry grows more complex, teams must balance full visibility with new retention and residency needs.

Testing ecosystems contain massive amounts of data, including outlined test scenarios, prerequisite configurations, and the tests themselves. As a result, these ecosystems are prone to data sprawl. This makes it difficult to prevent configuration drift and quickly spin up new tests, especially at the frequency needed to support a fast-growing application. Teams can handle these challenges by treating their tests as part of their application infrastructure.

Across the IT and observability landscape, enterprise leaders are facing a troubling pattern. A trusted vendor announces a “modernization initiative,” often following a major acquisition or a shift in ownership. Overnight, pricing structures change, license models disappear, and long-time customers are pressured into multi-year bundles under the banner of innovation. What’s being framed as progress often feels more like pressure.

What approaches exist, and how to use automation to benefit the overall business processes.

Your users are complaining about slow application performance. Your monitoring dashboard shows all devices are green, routers operational, switches functioning, and bandwidth utilization is normal. Yet something is clearly wrong. The problem isn't your equipment; it's the path between your users and their destinations. This is where network path monitoring comes in.

Harness now supports the Model Context Protocol (MCP) for Feature Management and Experimentation (FME), enabling developers to interact with feature flags directly from AI-powered IDEs like Claude Code and Windsurf. The FME MCP tools make it easier to explore, understand, and manage feature flags through natural language, streamlining delivery and release workflows without leaving your development environment.

GCP Cloud Monitoring probe let you transform your existing GCP metrics into automated pass/fail validation for chaos experiments, eliminating subjective observation in favor of objective measurement. With flexible authentication options (workload identity or service account keys) and PromQL query support, you can validate infrastructure performance against defined thresholds during controlled failure scenarios.