Learn about OpenTelemetry Metrics, types of instruments, and best practices for effective application performance monitoring and observability.

Explore practical methods for monitoring ephemeral storage metrics in Kubernetes to ensure efficient resource management and improve overall performance.

Time series databases are designed to store and analyze data collected at specified points in time. They’re essential for applications that handle huge amounts of continuously generated data, such as Internet of Things (IoT) devices, system monitors, and financial systems. InfluxDB, an open source time series database known for its outstanding performance and scalability, has gained popularity due to its capacity to manage large amounts of time-stamped data.

PostgreSQL PostgreSQL is a powerful open-source relational database management system (RDBMS) and is one of the most popular relational databases with over 1.5 billion users. It’s renowned for its reliability, robustness, and comprehensive capabilities. It is capable of managing a broad variety of workloads, from small single-machine applications to large-scale enterprise databases.

OpenTelemetry is a Cloud Native Computing Foundation(CNCF) project aimed at standardizing the way we instrument applications for generating telemetry data(logs, metrics, and traces). However, OpenTelemetry does not provide storage and visualization for the collected telemetry data. For OpenTelemetry visualization, you need to use a backend that can ingest the collected data and provide a web UI to visualize it.

The cloud offers many benefits, including scalability, cost savings, and operational efficiency. But here’s the deal. Organizing, monitoring, and controlling a cloud environment can become complex as workloads, applications, services, and underlying infrastructure grow. Businesses can better control and monitor their cloud infrastructure services, resources, and data using cloud management software.