Netdata introduces its latest feature, the Alerts Configuration Manager, transforming the way users configure and manage alerts in their Netdata environment. This powerful tool integrates directly into the Netdata Dashboard, offering a streamlined and intuitive interface for both novice and experienced users.

Are you looking for Kubernetes monitoring tools? Then you have come to the right place. Kubernetes has grown to become the container orchestration platform of choice. It simplifies managing your containerized workloads. You get the power of automating deployments, scaling resources, and keeping your applications running smoothly. But with great power comes added responsibility. And like any complex system, Kubernetes needs monitoring.

Serverless architectures such as AWS Lambda have created new challenges in debugging code. Without a solid logging framework in place, you could waste precious hours tracking down simple defects in your functions. A strategic logging framework can be a powerful way to track down and resolve bugs. Let’s walk through how to get the most out of logging Lambda functions.

Tucker Callaway (CEO, Mezmo) and Kevin Petrie (Vice President of Research, Eckerson Group) had a conversation centered around enterprises taking control of their data and the growing need for consolidated collection and management of telemetry data. They discuss how enterprises can optimize telemetry pipelines, take charge of their data, and enhance their observability and security game.

Backstage by Spotify is an open-source platform for building IDPs (internal developer portals). IDPs provide standardization and visibility for engineering teams and managers, as the single source of truth for status, ownership, and metrics on software projects. Teams often try Backstage when they have aspirations of “building anything and everything,” but run into problems when supporting “anything and everything” becomes a full-time job for multiple front and back-end engineers.

Monitoring your machine's internal temperatures is important for maintaining system health, optimizing performance, and ensuring the longevity of your computer hardware. It allows you to take proactive measures to prevent potential damage caused by overheating and helps in diagnosing and addressing cooling-related issues effectively. In this article we'll detail how to use the Telegraf agent to collect temperature readings from a Mac computer, that you can forward to a datasource.

Practical IT Service Management (ITSM) can be challenging when considering the growth of users and services to support. Additionally, ongoing trends in distributed enterprises with remote workforces, hybrid cloud, and cost-based pressures force companies to do more with less. Atop the usual demands, ITSM teams increasingly expect integrations with observability and security, giving IT support teams a single pane of glass across their roles and responsibilities.

How much do Synthetics matter to your team? I think they matter a whole lot. Back when I was a freelance developer, I doubled my annual income with synthetics. Working mainly in database optimizations, I would finish out a contract and leave a synthetic monitor running at a very low frequency on their service. When I saw a pattern of slower performance, I knew it was time to hit the team lead-up to ask if I could help.

As we close out another year, we want to take this moment to thank you, our customers, for your continued support. Whether you have been with us from the start or are just discovering our brand, we appreciate your business. This year's theme is IT resilience, which refers to the ability of an organization to withstand, adapt, and recover from disruptions or attacks with minimal or no impact.

As the demand for AI-based solutions continues to rise, there’s a growing need to build machine learning pipelines quickly without sacrificing quality or reliability. However, since data scientists, software engineers, and operations engineers use specialized tools specific to their fields, synchronizing their workflows to create optimized ML pipelines is challenging.