Operations | Monitoring | ITSM | DevOps | Cloud

How to perform HTTP checks in Grafana Cloud Synthetic Monitoring

Your users should not be the first to know when your application goes down. When HTTP endpoints fail or respond sluggishly, users experience timeouts, connection errors, and degraded performance — often without clear indication of the root cause. This is where HTTP checks in Grafana Cloud Synthetic Monitoring come in, allowing you to proactively monitor your endpoints, verify they're online, measure response times, and ensure they're returning the correct status codes.

Building the Next Phase of Harness's AI Engineering Organization in India

Over the past year, Harness’s India organization has entered a new phase of growth – one defined not just by scale, but by increasing technical depth and impact. What began as steady expansion has turned into real momentum across engineering, product, and operations. Today, 480 people work in India, contributing across every major product area. In 2025 alone, the team in India grew by more than 75%, and now each core Harness product offering has a strong engineering presence in the region.

To Do What? Why Great CX Starts with Great Agents

If your CX strategy starts with technology instead of people, you’re doing it backwards. Too many organizations invest in customer-facing platforms—chatbots, analytics dashboards, “AI-driven experience suites”—without first asking the fundamental question: “To do what?” That single question should be the first slide in every CX roadmap.

Do You Need a Service Mesh? Understanding the Role of CNI vs. Service Mesh

The world of Kubernetes networking can sometimes be confusing. What’s a CNI? A service mesh? Do I need one? Both? And how do they interact in my cluster? The questions can go on and on. Even for seasoned platform engineers, making sense of where these two components overlap and where the boundaries of responsibility end can be challenging. Seemingly bewildering obstacles can stand in the way of getting the most out of their complementary features.

Top Synthetic Monitoring Solutions for Enterprise DevOps Teams

Legacy monitoring creates dangerous visibility gaps in the accelerated enterprise DevOps landscape, where release cycles count in hours, not weeks. For teams managing hundreds of microservices, complex cloud-native architectures, and global user bases, basic synthetic monitoring tools simply cannot scale. The top synthetic monitoring solutions for enterprise DevOps must function not as mere observability tools, but as proactive, integrated safety nets engineered for scale, security, and precision.

Why Use a Purpose-Built Time Series Database

A time series database has a straightforward definition: it’s a database purpose-built for efficiently ingesting, storing, and querying time series data. Time series data is any data with a timestamp, collected regularly or periodically, that you’ll often visualize on graphs where the X-axis is time. This definition doesn’t quite tell you what sets it apart from other types of databases, though.

Building and deploying the Symfony ChatGPT app with Upsun

This blog post is based on a live presentation by Guillaume at a SymfonyCon 2023 on deploying applications with the Upsun platform-as-a-service. We utilized AI tools for transcription and to enhance the structure and clarity of the content. If you still use File Transfer Protocol (FTP) for deployment, this post is for you.

Document Automation Best Practices for DevOps Reporting and Compliance

DevOps has streamlined how teams build, test, and deploy software, but reporting and compliance often remain outside the automated pipeline. Release summaries, test reports, and audit records are still frequently created manually, pulled from scattered tools, and updated only when needed. This slows delivery and increases the risk of inconsistency, especially as systems and compliance requirements grow more complex. To scale DevOps sustainably, documentation can no longer be treated as an afterthought-it needs to become a reliable, automated output of the pipeline itself.

Measuring Workplace Efficiency in Hybrid and Shared Environments

The way work gets done has changed faster than most organizations ever expected. Teams now move fluidly between home offices, shared desks, and collaboration hubs, making traditional productivity benchmarks feel increasingly disconnected from reality. In this new landscape, workplace efficiency is no longer about visibility or hours logged-it's about understanding how effectively people use time, space, and resources across flexible environments. Measuring performance in hybrid and shared workplaces demands a smarter lens, one that captures outcomes, adaptability, and real contribution rather than outdated notions of presence.

Why Dechecker AI Checker Matters When Executives Review High-Stakes Content

Executives rarely question whether AI was used. They question whether a document feels owned. In board decks, internal reports, or external statements, language signals responsibility long before facts are debated. Dechecker exists in that narrow space where leadership judgment meets written expression.