The latest News and Information on DevOps, CI/CD, Automation and related technologies.
Use Netdata to effectively monitor and troubleshoot the performance of NVMe (Non-Volatile Memory express) disks in your infrastructure. Preempt disk failures and take action to ensure your systems run without a glitch.
Monitoring HTTP sessions offers a potentially powerful way to gain visibility into your web servers, but in practice, doing so can be complex and resource-intensive. Extended Berkeley Packet Filter (eBPF) technology allows you to overcome these challenges, giving you a simple and efficient way to process application-layer traffic for your troubleshooting needs.
RAN has incrementally evolved with every generation of mobile telecommunications, thus enabling faster data transfers between user devices and core networks. The amount of data has increased more than ever with an increase in the number of interlinked devices. With existing network architectures, challenges lie in handling increasing workloads with the ability to process, analyse and transfer data faster. The 5G ecosystem requires virtual implementations of RAN.
How can you tell if your systems are reliable when under load? A common answer is to open your observability dashboards, wait for a high-traffic event (like Black Friday), and cross your fingers. While this approach is certainly effective, it's far from ideal. Without proactive reliability and load testing, we have no idea if a system will hold up to real-world usage patterns, which could mean a production outage at the worst possible time.
A single-line diagram (also known as an SLD or one-line diagram) is a simplified representation of an electrical system. Symbols and lines are used to represent the nodes and connections in the system, and electrical characteristics may be included as well. In a data center, a single-line diagram is used to visualize the power distribution system to improve planning and troubleshooting, ensure redundancy, and reduce potential outages.
In 2021, we partnered with AWS to develop the Datadog Lambda extension which provides a simple, cost-effective way for teams to collect traces, logs, custom metrics, and enhanced metrics from Lambda functions and submit them to Datadog.