For IT teams seeking speed and agility, agentless monitoring offers a lightweight approach. This is particularly useful for Microsoft servers like Windows Nano Server, where resources may be constrained, or in environments where gaining approval for agent installations could be a hurdle. An agentless Microsoft monitoring tool is ideal if: However, there are limitations.

The SRE Report is now seven years old. I’ve had the honor and privilege of authoring it for the last five years. This 2025 version included working with some amazing individuals like Kurt Andersen and Denton Chikura. My heartfelt thanks go to them for shouldering the weight of what is both a labor of love and an often daunting, procrastination-inducing marathon of analysis.

Google Cloud Run is a fully managed platform that enables you to deploy and scale container-based serverless workloads. Cloud Run is built on top of Knative, an open source platform that extends Kubernetes with serverless capabilities like dynamic auto-scaling, routing, and event-driven functions. By using Cloud Run, developers can simply write and package their code as container images and deploy to Cloud Run—all without worrying about managing or maintaining any underlying infrastructure.

In Part 1 of this series, we looked at key Cloud Run metrics you can monitor to ensure the reliability and performance of your serverless containerized workloads. We’ll now explore how you can access those metrics within Cloud Run and Google’s dedicated observability tool, Cloud Monitoring. We’ll also look at several ways you can view and explore logs and traces in the Cloud Run UI and Google Cloud CLI.

In part 1 of this series, we introduced the key Cloud Run metrics you should be monitoring to ensure that your serverless containerized applications are reliable and can maintain optimal performance. In part 2, we walked through a couple of Google Cloud’s built-in monitoring tools that you can use to view those key metrics and check on the health, status, and performance of your serverless containers.

Docker has transformed how we deploy, manage, and scale applications. As applications grow in complexity, the need for effective orchestration increases. This is where Docker Swarm comes into play. Docker’s native clustering and orchestration tool simplifies the management of multi-container applications. Together, Docker and Docker Swarm form a powerful combination for building and scaling modern, distributed systems.

ClickHouse is known for its fast performance and ability to handle large amounts of data, making it a popular choice for running analytical queries. However, it can face challenges when dealing with high cardinality data, which refers to columns with a large number of unique values. This can affect query performance and storage efficiency if not managed properly. In this blog, we will explain what high cardinality means in simple terms and share practical ways to handle it in ClickHouse.

Splunk is a powerful tool for data analysis and monitoring, but its high costs and complex implementation can be challenging for many organizations. Here are 13 proven Splunk alternatives that provide robust monitoring capabilities, comprehensive data analysis, and more cost-effective solutions for organizations of all sizes.

Here’s the deal: the Internet is flooded with articles telling you to “do this” or “try that.” This isn’t one of those. Instead, we’re bringing you a fair market analysis straight from our team of network experts, who collectively have over 30 years of experience in network monitoring.

The way we manage, qualify, and utilize our data is constantly tested. With the amount of information we have at our disposal, managing and ensuring data quality has become a strategic lever for companies striving for excellence. How can we ensure our data management is flawless and the data quality on which we base our decisions is optimal? This is where data observability becomes an essential component.