Network Monitoring

Track mission-critical systems and devices to gain better insights into network performance. Identify and resolve issues like speed degradations and connectivity failures before they impact users.

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Why a purpose-built time series database?

Time series data are measurements or events that are tracked, monitored, downsampled, and aggregated over time. This could be server metrics, application performance monitoring, network data, sensor data, events, clicks, trades in a market, and many other types of analytics data.

Why InfluxDB for network monitoring?

Networks play a fundamental role in the adoption and growth of Internet applications. Penetrating enterprises, homes, factories, and even cities, networks sustain modern society. While assuring responsive and performant networks in today’s hybrid, distributed and containerized application environments occurs behind the scenes in intangible clouds and diagrams abstractions, network glitches are more visible and unforgiving than ever.

Network availability, responsiveness, and bandwidth consumption are the three pillars that separate unmonitored from the monitored networks — and if you feed this data into a centralized time series platform you will be able to have a holistic view of your network performance monitoring.

Network availability refers to host reachability. If the network is unavailable, there could be something related to the endpoint health or network path (such as a load balancer’s sessions limit or expired SSL) preventing traffic from reaching the host.

Network responsiveness is the combination of latency and packet loss. Latency refers to the time it takes for traffic to cross the network to a target, and packet loss determines the error rate experienced. Latency and packet loss render the network suitable for all or some more sensitive applications. For instance, high latency will completely undermine unified communications (voice & video) services.

Network bandwidth consumption tracks metrics from the network interface providing important information about bandwidth load at the interface, which can be used to set up alerts before the interface is completely saturated. Adding to the network interface metrics data from network traffic analysis appliances allows for identification of bandwidth consumption struggles, providing precious insights about sessions and IPs/protocol/port troublemakers that are causing saturation, as well as identifying resource misuse and potential Denial of Service (DoS) attacks.