Operations | Monitoring | ITSM | DevOps | Cloud

Sponsored Post

The Product Manager's Nightmare: Seeing Features Too Late

Sarah stared at her laptop screen in disbelief. The feature her team had been building for three weeks was finally deployed to staging, and it looked nothing like what she had envisioned. The user interface was cramped, the workflow felt clunky, and the color scheme clashed with their brand guidelines. "Can we change the button placement?" she asked during the demo. "That'll require refactoring the entire component structure," replied the lead developer. "It's probably a two-day task now." What should have been a simple adjustment had become a major undertaking.

Store and search logs at petabyte scale in your own infrastructure with Datadog BYOC Logs

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.

The Right Way to Deliver Infrastructure: Every Deploy Comes with Guardrails

In fast-moving organizations, developers are expected to ship quickly. Infrastructure shouldn’t be a blocker, but it can’t become a liability either. One unchecked terraform apply, a missing tag, or a misconfigured instance can turn into a surprise bill, a failed audit, or even a production outage. The most reliable way to manage infrastructure at speed is to make governance part of the delivery process.

Validating chaos experiments with GCP Cloud Monitoring probes

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.

Streamline feature management with Harness MCP and Claude Code

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.

The one where we scaled

From 3 people in 2020 to 93 in 2025—incident.io has come a long way, and we’re just getting started. Whether you’ve been here since the early days or just joined, this is what it looks like to build something great *together*. If you're after:️️ Great people Real impact (across the globe, not just in Greece) A place where growth is the default And teammates who’ll always be there for you... We’re hiring! (And we're going to need a bigger couch…)

Puppet Edge Across Lifecycle: Day 0, Day 1, and Day 2

Puppet Edge extends your Puppet automation to now include all your network devices, providing a centralized platform to manage your entire infrastructure, enabling teams to work together efficiently. Automate tasks, manage configurations, and ensure compliance across all your devices from one place. This video discusses how to use Puppet Edge for Day 0 planning and provisioning, Day 1 device configuration, and Day 2 ongoing operations, streamlining your workflows, and reducing manual errors.