Operations | Monitoring | ITSM | DevOps | Cloud

Setting Up an MQTT Data Pipeline with InfluxDB

In this blog, we’re going to take a look at how you can set up a fully-functioning, robust data pipeline to centralize your data into an InfluxDB instance by collecting and sending messages with the MQTT protocol. We’ll start with a brief overview of the technologies and protocols used in the pipeline, then dive into how you can connect, configure, and test them to ensure your data pipeline is fully functional. It’s going to be a long post, so let’s jump right in.

Autonomous AI for Cloud-Native Cost Optimization: Balancing FinOps and Performance SLAs

Platform Engineering leaders are caught between two competing imperatives. You’re under pressure to flatten cloud spend but your team is still provisioning defensively because nobody wants to be the person who causes a production incident. You try to optimize, but six months later, when someone pulls a report, nothing has changed.

Every team should be A/B testing

Technical teams want to know the newest, most cutting-edge tools they can implement to give themselves a competitive advantage, whether it’s the latest developer framework or modern CI/CD practices that boost velocity. But there’s one tool from all the way back in the 1920s that can improve any organization, no matter its scale: the randomized, controlled trial—or simply put, experiments.

Network Instability: What It Is, What Causes It, and How to Fix It

Network outages are easy. Something goes down, alarms fire, you fix it, life moves on. Everyone understands a full outage. It's clean, binary, and at least somewhat predictable. Network instability is the opposite of all that. Nothing fully breaks. Nothing fully works. The ping responds. The connection shows active. And yet users are complaining about choppy calls, sluggish apps, and sessions dropping for no apparent reason. You run a speed test, and it's fine.

How to set up rolling deployments with CircleCI

A rolling deployment updates running application instances in batches, replacing old instances with new ones while the application keeps serving traffic. The concept applies to any system that can run multiple instances of an application, but Kubernetes has it built in as the default deployment strategy. Kubernetes terminates an old pod only after its replacement passes the configured readiness check, so no requests land on an unready instance.

Choosing GPU cloud platforms for developers

For developers building AI applications, training models, or running inference pipelines, the GPU cloud market in 2026 has never offered more choice - or more complexity. Picking the wrong platform means overpaying, dealing with availability problems, or battling infrastructure that slows you down rather than accelerating your work.

Your AI Agents Are Autonomous. But Are They Accountable?

Why accountability, not capability, is the real bottleneck for enterprise agentic AI, and what security leaders need to do about it before regulators force the issue. Every enterprise is building AI agents. Marketing has one summarizing campaign performance. Engineering has one triaging incidents. Customer support has one resolving tickets. Finance has one processing invoices.

How to Source the Right Solutions for Your Business

When it comes to being in business, you always need to make sure that you're making the right decisions that facilitate growth and success. A huge part of this will mean creating a strong supply chain and finding the right vendors and solutions to put in place. Let's take a look at how you can approach this.

6 Ways Ops Teams Can Align AI With Business Impact

AI adoption is at an all-time high, withover 70 percent of organizations are using AI in at least one core function. Despite the high rate of AI adoption, many operational teams continue to have difficulty answering the question 'Is AI actually benefiting our business?' The challenge lies in the gap between AI systems and actual business results. Bridging the gap requires aligning operational AI with revenues, customers, and growth metrics. Here are actionable steps to transform AI from a technical tool into a measurable business contributor.