Operations | Monitoring | ITSM | DevOps | Cloud

As cyber threats grow in sophistication and frequency, organizations worldwide are grappling with the challenge of safeguarding their systems and data while maintaining operational continuity. Cyber resilience, the ability to prepare for, respond to, and recover from cyber incidents, is no longer just a competitive advantage…it’s a critical necessity.

Containers are a big deal today. They are software units that contain all the code, runtime, and dependencies required to run a distributed application. Thus, containers help engineers test and run apps without compatibility issues on any device and platform. Organizations can use containers to reduce engineering costs, speed up deployments, develop and test AI models, and automate more processes. You probably want those benefits as well.

A patch management process lays out the steps associated with updating software and hardware. The typical patch management procedure includes things like prioritizing important patches, testing them, and eventually deploying them on an automated schedule — but with so many tools for managing patching in so many different kinds of setups, no two IT teams’ patch management processes look alike. What does your patch management process look like?

Incident response has always been a vital function within IT and the organizations it supports. However, as technology landscapes become increasingly hybrid and IT environments grow more complex, the need for a fast, efficient, and adaptive incident response system has never been greater. Teams in this environment face many challenges, starting with overwhelming event noise. When systems generate too many alerts, critical warnings can get lost in the chaos, leading to missed issues and delayed responses.

Smooth and efficient software deployment is critical to delivering high-quality applications that meet user expectations. Still, many software failures can be traced back to deployment issues. A well-structured deployment strategy can help DevOps & SREs teams prevent these errors, ensure system reliability, and enhance user satisfaction. This guide explores software deployment best practices, from planning and execution to post-deployment monitoring and incident management.

So, you’ve got a PostgreSQL database packed with juicy data, and you want to turn those raw numbers into slick, interactive Grafana dashboards? Good call! Grafana’s PostgreSQL datasource is like the secret handshake that lets you visualize your data in style—no extra ETL magic required. In this guide, we’ll walk through getting PostgreSQL and Grafana to play nice, covering everything from connection settings to query tuning.

Logs are crucial for understanding what's happening in your system, but they can often be hard to make sense of. Log parsing is the key to turning raw, unstructured data into something useful. In this blog, we'll explore the basics of log parsing, its importance, and how it helps you extract valuable insights from your logs without all the clutter.

Most developers are familiar with Opentelemetry core components—Traces, Metrics, and Logs. But there’s one part of the OpenTelemetry ecosystem that doesn’t always get the spotlight: processors. These behind-the-scenes operators shape your data pipeline, helping you filter, enrich, and fine-tune telemetry data before it reaches your backend systems. Processors play a key role in making sure your data is cleaner, more useful, and just the way you need it.

HAProxy 3.1 makes significant gains in performance and usability, with better capabilities for troubleshooting. In this blog post, we list all of the new features and changes. All these improvements (and more) will be incorporated into HAProxy Enterprise 3.1, releasing Spring 2025. Watch our webinar HAProxy 3.1: Feature Roundup and listen to our experts as we examine new features and updates and participate in the live Q&A.