Operations | Monitoring | ITSM | DevOps | Cloud

Flyway provides a lot of flexibility for releasing database changes in a safe and repeatable manner. Earlier this year, we added the ability to automate state-based deployments. This means the structure of the database is defined in version control and Flyway handles updating a target database to match it. The Flyway comparison engine does all the hard work of identifying what’s different and creating a script that will run on the target database to alter it so it matches the latest state.

In this guide, you will build and deploy a serverless data processing workflow using AWS Step Functions and AWS Lambda. This approach enables you to orchestrate discrete processing tasks in a scalable and cost-efficient way, leveraging the event-driven architecture that AWS offers. You will begin by creating individual Lambda functions that handle specific tasks in your data pipeline.

The world of cloud costs is always evolving, and AI spend is quickly becoming one of the most unpredictable and confusing cost drivers. As more organizations integrate generative AI into their products, FinOps teams are struggling to account for — and control — these new, often mind-boggling cost streams. In fact, 44% of engineering professionals say improving AI explainability is a top priority in AI budgeting, according to CloudZero’s State Of AI Costs In 2025 report.

Cloud costs are no longer just an engineering problem or a finance problem. It’s now an everyone problem. That was the central message from the FinOps Training At Scale webinar that took place on Sept. 25, 2025, where CloudZero’s Larry Advey (a.k.a. “Fred FinOps”) and Director of Tech Enablement Umesh Rao walked through the realities of building FinOps practices that work in the real world.

Most organizations think of monitoring as a checkbox: set it up once, confirm that it runs, and move on. If the tool says the website is “up,” then the job is done, right? Not quite. The truth is that where you run synthetic monitoring tests from can be just as important as the tests themselves. Synthetic monitoring works by simulating user actions from pre-defined probes or agents. Those probes might live in a cloud data center, a mobile network, or even inside a corporate office.

These days, maintaining uptime of your servers and other infrastructure elements remains as critical as ever—but it’s not enough. Quite simply, even the best server reliability metrics won’t mean a thing if the user experience is poor. What truly matters is understanding the service levels your users experience, whether they’re accessing apps through a web browser or interacting with API-based services.

A little while ago, I wrote a piece with the provocative title, "The End of the Network Engineer as We Know It?" It struck a chord because it articulated a shift many of us feel in our bones: the ground is moving beneath our feet. The traditional, well-defined corporate network has dissolved into a sprawling, borderless ecosystem of public clouds, SaaS platforms, and the vast, untamed internet. The old role, focused on the care and feeding of devices within our four walls, is no longer sufficient.

The launch of Puppet Edge this week could not have been more timely. Within a day of its general availability, Cisco disclosed a vulnerability in its IOS and IOS XE software, followed almost immediately by an Event Response detailing two additional critical-severity CVEs affecting its firewalls.

As organizations navigate increasingly complex tech environments, unified observability practices have become essential. That was one of the main takeaways from Grafana Labs Co-founder Anthony Woods’ recent appearance on “Tech Keys by by Mercari India,” a podcast hosted by Vaibhav Khurana, Head of Platform Engineering at Mercari India.

I recently joined the Developer Advocacy team here at Grafana Labs, and have been exploring ways to accelerate my Grafana learning journey. Like many others in the Grafana community, my introduction to the open source project happened when I needed a way to easily visualize data that resided in external databases, mostly using SQL queries.