Operations | Monitoring | ITSM | DevOps | Cloud

It’s 2026, and developers have more tools at their disposal than at any point in the industry’s history: CI/CD platforms are richer; observability stacks are deeper; security, data, and AI tooling have exploded into crowded, competitive ecosystems. And yet, delivery is still slow, incidents are still noisy, workflows are still brittle. The problem is no longer tool scarcity or feature depth. It’s integration debt.

Today, we’re launching a new approach to running disaster recovery tests, validating failover processes, and ensuring compliance with regulations such as DORA. With Disaster Recovery Testing, you can run zone, region, and datacenter-scale experiments across your entire Gremlin organization simultaneously. ‍

Over the past couple of weeks, as snowstorms and extreme cold swept across much of the Northeast, something interesting started happening on our end at OnPage. Our phones lit up. Not from healthcare teams or IT operations/tech teams, which is where many people expect us to be used, but from HVAC companies, contractors, and property management firms scrambling to prepare for what they knew was coming.

This guide shows you how to implement OpenTelemetry’s auto-instrumentation for complete distributed tracing across your microservices, from initial setup through production optimization and troubleshooting.

OpenTelemetry instrumentation is the foundation of modern microservices observability, but getting it right in production requires more than just enabling auto-instrumentation. This guide covers production-tested OpenTelemetry best practices that help engineering teams achieve reliable distributed tracing, control observability costs, and extract maximum value from their telemetry data.

Modern IT service management platforms excel at structuring work: tickets, workflows, approvals, SLAs, and reporting. But when a major incident occurs, success depends on more than clean processes – it depends on how fast the right people are reached and respond. This is where EasyVista Service Manager (EVSM) and SIGNL4 work exceptionally well together.

There is often a temptation to stretch on-call shifts to a month or longer, especially when incident volume is low. The logic seems sound. If the phone rarely rings, it feels unnecessary to hand off on-call duties every week. But looking strictly at incident volume often misses the human side of the equation. Being on-call isn’t just about answering pages. It is also a state of mind. Even when it is quiet, simply being on-call could create fatigue of its own.

Choosing an on-call rotation is about finding a rhythm that balances your team’s well-being and your system’s reliability. The right on-call rotation helps prevent burnout and makes on-call duties sustainable over the long run. This guide walks you through different on-call rotation patterns, from daily rotation to after-hours rotations. We’ll look at why you might choose a particular rotation and the challenges that often come with it.

Organizations are increasingly using agentic AI applications powered by large language models (LLMs) to automate analysis, decision-making, and operational workflows. As these AI agents take on more responsibility, they gain access to internal tools and services and can interact with them in unintended ways.