Operations | Monitoring | ITSM | DevOps | Cloud

In the context of application performance monitoring (APM) and observability, traces and spans are fundamental concepts that help users to track and understand the flow of requests and operations within a system. They are essential in assisting users to identify bottlenecks, troubleshoot issues, and optimize application performance.

“Necessity is the mother of invention,” so here is a quick backstory to understand what brought AIOps into the ITSM landscape In the fast-paced world of Information Technology Service Management (ITSM), staying ahead of challenges and effectively managing complex systems is crucial. As organizations embrace digital transformation and adopt cutting-edge technologies, the volume of data and incidents generated becomes overwhelming for IT teams to handle manually.

Mastering Git can sometimes feel like trying to untangle a bunch of super tangled – and wired (old school, I know) – headphones, not sure exactly where to pull or loop or flip next. Here are 10 Git tutorial videos that’ll help you level up your Git game. These videos are the perfect combination of fast and helpful.

For today’s IT and security professionals, threats come in many forms – from external actors attempting to breach your network defenses, to internal threats like rogue employees or insecure configurations. These threats, if left undetected, can lead to serious consequences such as data loss, system downtime, and reputational damage. However, detecting these threats can be challenging, due to the sheer volume and complexity of data generated by today’s IT systems.

Microsoft’s Azure Data Lake Storage (ADLS) has been a vital component for organizations aiming to build scalable and secure data lakes. As technology evolves, transitioning from Azure Data Lake Storage Gen1 to Gen2 has become increasingly important. This article aims to guide readers through the essential considerations, detailed processes, and best practices involved in making this shift.

For most organizations, having a stable and reliable IT infrastructure is essential for success. But managing multiple servers, databases, and applications can often be difficult and time-consuming. Container orchestration is a standard solution for handling this complexity. Docker Swarm has gained popularity as a container orchestration solution because of its simplicity and scalability.

As the size and complexity of database estates increases, with more workloads and data being hosted on more platforms, both on-premises and in the cloud, so the appeal of third-party database monitoring tools has also grown. Their ability to provide a holistic view of an entire estate and monitor multiple databases and platforms from a single dashboard has been shown to save DBAs and IT teams many hours of time when compared to home-grown solutions.

The Internet of Things (IoT) - is a number of physical devices connected to one network that enables the system to interact with the external world. A great deal of the work surrounding IoT is monitoring, as it’s impossible to react without knowing the situation. For example, we might build a greenhouse system for agriculture that can maintain optimal conditions for growing crops. For this purpose, we need to have sensors picking up information about the temperature and humidity.

Often it can be a challenge to collect data into a monitoring environment that does not natively support that data source. Bindplane can help solve this problem. As the Bindplane Agent is based on OpenTelemetry (and is also as freeform as possible), one can bring in data from disparate sources that are not easily supported by the Splunk Universal Forwarder.

As a leader in Security Analytics, we at Elastic are often asked for our recommendations for architectures for long-term data analysis. And more often than not, the concept of Limitless Data is a novel idea. Other security analytics vendors, struggling to support long-term data retention and analysis, are perpetuating a myth that organizations have no option but to deploy a slow and unwieldy data lake (or swamp) to store data for long periods of time. Let’s bust this myth.