Operations | Monitoring | ITSM | DevOps | Cloud

Apache Tomcat servers are useful because they provide a robust and flexible environment for running Java-based web applications, ensuring high performance and scalability. They are essential to monitor because regular monitoring helps in identifying performance bottlenecks, security vulnerabilities, and potential failures, ensuring the reliability and efficiency of web applications.

Welcome to the debut of Tales from the Trenches, a ‘boots on the ground’ series written by Richard Ashbee, a seasoned pre-sales engineer and consultant with over 15 years of experience in the telecommunications industry. Read on for practical insights straight from the frontline!

In the last few years, there has been a remarkable expansion in the benefits Artificial Intelligence (AI) offers. AI’s influence is pervasive everywhere, from voice-activated virtual assistants like Siri, Google Assistant, and Alexa to recommendation systems such as those employed by Netflix, Amazon, and Instagram and phone cameras that can provide real-time translation of text, signs, and menus. Nearly 77 percent of devices today use AI technology in one form or another.

Generative AI and large language models (LLM) are fundamentally changing the way we interact with data, especially in the realm of Kubernetes and observability. These technologies are reshaping our field, and there is a lot to understand and unpack so organizations like yours can make sense of it all. What data is important, and what isn’t? How can LLMs make my day-to-day easier, and what do I need to do to ensure I don’t get overwhelmed?

Yesterday, we kicked off Spotlight Week with a brand new look for Spectate. Today, we're excited to announce that our Infrastructure Monitoring feature is now in general availability!

At the most abstract level, a data pipeline is a series of steps for processing data, where the type of data being processed determines the types and order of the steps. In other words, a data pipeline is an algorithm, and standard data types can be processed in a standard way, just as solving an algebra problem follows a standard order of operations.

In the wide world of observability, you have many options for visualizing metrics collected by Amazon CloudWatch. And because of that, you’re often left making lots of decisions — about cost, configurations, flexibility, and more. At Grafana Labs, we stick to our “big tent” philosophy, which means we don’t force you into a decision or even tell you that you have to bring your CloudWatch metrics to Grafana Cloud.

Artificial intelligence (AI) is seemingly everywhere in today’s tech landscape. The hype cycle is in full flow, especially regarding the use of large language models (LLM) for generative AI like OpenAI ChatGPT, Google Gemini and Anthropic Claude. Indeed, many tech companies are determined to add LLM into products where it sometimes seems tacked on.

When writing a custom check plugin for Icinga 2, there are situations where in addition to observing the current state of a system, taking the past into account as well can be helpful. A common case for this is when the data source provides counter values, i.e. values that increase over time and you are less interested in the current value but more in how it changes.

Website uptime is an important factor for businesses in various industries. This article explains the concept of website uptime, what it means, how it is calculated, and why businesses need to keep a high level of uptime.