Operations | Monitoring | ITSM | DevOps | Cloud

What's New in Flowmon ADS 12.5?

In this webinar, we’ll introduce the new features, including: AI-Powered Threat Briefings – A new dashboard that correlates global threat intelligence with your network’s current and historical data. Enhanced Event Visualization – Dive into a redesigned event detail streamlining user experience Expert-level recommendations - Guided next steps for each detection, helping analysts of all skill levels validate and resolve incidents with confidence.

Get Kafka-Nated - Episode 1: Apache Kafka's Evolution: 14 Years of Streaming

Grab your cup and prepare to get Kafka-Nated! In this series we’ll be digging into everything from Apache Kafka, from the pre history of Kafka to the latest Kafka Improvement Proposal (KIP). We’ll be joined by a range of guests who have been at the forefront of Kafka for many years. And to ensure you don’t kip (I know - we’re sorry) we’re offering every attendee a free coffee voucher. What We’ll Cover in Episode 1.

From Detection to Resolution: How Selector + Itential Deliver AI-Driven Observability and Automated Recovery

Every second counts when it comes to detecting, diagnosing, and resolving network incidents, yet many teams still find themselves stuck in reactive mode, drowning in alerts, manually writing scripts, and managing tickets across disconnected systems. This is where Selector and Itential come in. Together, Selector and Itential deliver a powerful, enterprise-ready solution that closes the loop between detection and action.

Myth #5 of Kubernetes Resource Optimization: Spark Dynamic Allocation

In this blog series we’re examining the Five Myths of Kubernetes Resource Optimization. The fifth and final myth in this series relates to another common assumption of many Kubernetes users: Dynamic Allocation for Apache Spark applications automatically prevents Spark from overprovisioning resources while improving workload utilization levels.

Can AI/ML Guide Observability? Tech Talk #6

This talk will examine the application of Artificial Intelligence and Machine Learning in observability. It will cover how AI/ML is being used to monitor systems, detect anomalies, and extract insights from telemetry data. The session will provide information on integrating AI/ML into observability pipelines, improving analytical capabilities, and system performance.

How to Handle the NumberFormatException in Java

The NumberFormatException is one of the most common runtime exceptions you'll encounter in Java. It's an unchecked exception that occurs when you try to convert a string to a numeric value, but the string format isn't compatible with the target number type. Simply put, if you attempt to parse "hello" as an integer or "12.5" as an integer, Java throws a NumberFormatException because these strings can't be converted to the expected numeric format.