We all use computers — some of us are on our laptops all day, every day. But how do our personal or work computers connect to the internet, share files, send emails, and complete other tasks? That’s the role of servers.

In part 1, we looked at how the design plan of traditional monitoring technologies depended heavily on properties of the systems that were intended to monitor and then showed how those properties began to be undermined by an increase in complexity, an increase which can ultimately be captured by the concept of entropy. In this part, we will explore how increased entropy forces us to rethink what is required for monitoring.

In the business world, shadow IT is a controversial topic. Gartner defines Shadow IT as any IT devices, software and services that are used outside or beyond the ownership or control of IT departments/ organizations. This includes: In a standard work environment, the IT department would be responsible for providing whatever IT solutions and work tools were needed across all business functions.

The RED method is a streamlined approach for monitoring microservices and other request-driven applications, focusing on three critical metrics: Rate, Errors, and Duration. Originating from the principles established by Google's "Four Golden Signals," the RED monitoring framework offers a pragmatic and user-centric perspective on service performance.

In a world where artificial intelligence (AI) seems is leaping forward and is growing at a CAGR of almost 40%, questions about governance and ethics with the use of AI are surfacing. As humans continue to develop AI systems, it is crucial to establish proper guidelines to ensure powerful technologies like generative AI and adaptive AI are used in a responsible manner.

Pi-hole is a fantastic open-source DNS-based ad blocker that enhances your online experience by blocking unwanted ads and trackers network-wide. Monitoring the performance and status of your Pi-hole setup is essential to ensure its effectiveness. Next, we'll explore how to use a Prometheus exporter to expose metrics from Pi-hole and have the OpenTelemetry collector scrape the metrics and send them to Splunk Observability Cloud.

ChatGPT and other LLMs have become so accessible that even our grandmas know about AI. But what’s really happening beyond the hype? Recently, I sat down with IT and security leaders Cory Minton and Kirsty Paine to share the inside scoop on how we’re thinking about AI here at Splunk. Watch the replay of our conversation here.

Cloud-based services have changed how individuals and businesses get things done. That doesn’t mean it’s all positive — there are some tradeoffs and compromises that come with cloud services and the internet. One major tradeoff is speed. For instance, if your website fails to load within three seconds, 40% of your visitors will abandon your site. That’s a serious dent for anyone doing business online. The culprit here is latency.

Cyber-Physical Systems refer to a system that models, automates and controls the mechanism of a physical system in a digital environment. This is an area of significant growth: the global market for Cyber-Physical Systems (CPS) is expected to grow from around $87 billion in 2022 to over $137 billion by the year 2028 at a CAGR of 7.9%. So, what exactly are cyber-physical systems? Let’s take a look.

Traditional monitoring methods become inefficient as organizations shift from legacy software systems to complex cloud-native architectures. This transition renders these methods less effective, as they no longer provide the critical insights needed. In response, observability engineering has emerged as an important discipline, offering a more comprehensive understanding of modern software systems. This article will take you through the definition, importance, and processes of observability engineering.