Operations | Monitoring | ITSM | DevOps | Cloud

There are many vendors, Honeycomb included, where actions on the application can emit a web request that goes to another service for coordination or tracking purposes. Many vendors have pre-built integrations, but some have a fallback that says “Custom Webhook” or similar. If you’re looking to create a full picture of your request flow, you would want these other services to show up in your trace waterfall.

Automating SDLC Governance is one of our key use cases. Kosli gathers all of the evidence your engineering teams need for change management and audit by recording every step in their SDLC, from commit to production, across all of their CI/CD tools. But robust SDLC governance doesn’t just depend on gathering all the necessary data - it also depends on controlling who can add to that data. And that’s exactly what our new access control feature solves.

This is the fourth blog in our Azure Monitoring series, and this time, we’re digging into cost efficiency. Azure makes it easy to scale, but just as easy to overspend. Idle VMs, forgotten disks, and silent data transfer fees add up fast. The result is budget overruns that catch teams off guard and force reactive cuts. This blog breaks down the Azure metrics that actually help you reduce waste, improve visibility, and keep cloud spend aligned with business priorities. Missed our earlier posts?

This is the ninth post in our Azure Monitoring series, and it’s all about taking control of your cloud costs without losing visibility. We’ll unpack why Azure bills tend to spiral, where native tools fall short, and what it really takes to cut spend while keeping performance on point. You’ll walk away with practical ways to spot waste early, act fast, and stay ahead of surprise invoices. Missed the earlier posts? You can catch up anytime.

In today’s era of AI-powered transformation, the excitement around automation is palpable. Technology leaders race to deploy AI agents, build self-healing systems, and create digital environments that seem almost magical in their seamlessness. But amid all the buzz about automation and efficiency, it’s crucial we don’t lose sight of the most powerful force behind any successful transformation: people.

Managed Service Providers (MSPs) are under intense pressure: 24/7 uptime, seamless client experiences, and proactive service models are table stakes. But many are still operating with fragmented, manual-heavy toolsets designed for a simpler era.

It’s been a year since we launched Grafana Alloy, our OpenTelemetry Collector distribution with built-in Prometheus pipelines and support for metrics, logs, traces, and profiles. OpenTelemetry is quickly becoming an industry standard for telemetry collection, processing, and delivery, and we’re committed to making Alloy the best possible collector for telemetry data, whether you’re using it with Grafana Cloud or not.

Moving your existing Grafana instance to Grafana Cloud just got dramatically simpler. Today, we’re excited to announce the general availability of the Grafana Cloud Migration Assistant, a powerful yet intuitive tool designed to streamline your migration journey. Traditionally, migrating from Grafana OSS or Grafana Enterprise to Grafana Cloud required technical expertise with Grafana’s HTTP API or command-line tools like Grizzly.

Imagine IT systems that fix themselves, customer service platforms that auto-resolve tickets, and organizations that detect and block fraud in milliseconds. This is not science fiction—it is the real-world impact of AI vs. Gen AI. While traditional AI drives automation and intelligent decision-making, Generative AI takes it further, writing reports, generating code, and crafting marketing campaigns in seconds. Together, they are transforming how industries operate in 2025.

When your MongoDB database slows down, it affects your entire application stack. Performance issues can range from minor inconveniences to major outages, making a solid understanding of MongoDB metrics essential for any DevOps engineer. This guide covers the key performance metrics you need to monitor in MongoDB, how to interpret what you're seeing, and practical steps to resolve common issues.