Kubernetes Monitoring

Real-time visibility into your entire container-based environment to unify all your metrics and events for faster root-cause analysis.
Application performance monitoring with InfluxDB

Why monitor Kubernetes?

Kubernetes provides built-in fault tolerance, automating the maintenance of a desired cluster state. However, visibility into nodes, containers, workloads, Kubernetes objects and events is still paramount because monitoring is what makes automation reliable.

Why InfluxDB for Kubernetes monitoring?

Application environments are in constant innovation for agility, cost-effectiveness, security or regulatory reasons. InfluxDB can monitor private and public cloud infrastructures (e.g., PaaS, SaaS, website), multi-tier and containerized applications environments, with flexibility for deployment variances, custom instrumentations, and composable indicators for business uniqueness. InfluxDB helps to identify and resolve problems before they affect critical business processes.
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Get broad insight and act in time

Monitor all Prometheus metrics, application events, K8s annotations, and logs from one pane. A comprehensive view of infrastructure, Kubernetes container orchestration and application performance is fundamental to keep services running without degradations or escalating issues that could lead to outages.
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Optimize to be competitive at lower cost

InfluxDB is a performant store for time series data both numeric and non-numeric. Avoiding the need for expensive hardware and storage, and also, to install and maintain multiple monitoring platforms. InfluxDB real-time stream analytics, highly efficient compression and compaction, allow data to be ingested and stored cost-effectively.

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HA and Scalability

InfluxDB’s purpose-built design for time series allows for very high volume storage of monitoring records while providing horizontal scalability and high availability with clustering. This makes it an ideal solution for long-term storage of Kubernetes monitoring data for historic records or modeling purposes.

InfluxData support for Kubernetes monitoring

InfluxData’s open, agile and extensible monitoring platform keeps your organization ahead of the game as you track SLIs, achieve SLOs and comply with SLAs for containerized application environments. Besides a purpose-built time series database (InfluxDB), InfluxData platform also counts with Telegraf — an open source, plugin-based agent (200+ plugins) that collects metrics and events, from Kubernetes APIs, nodes, pods, master node and Prometheus /metric endpoints. Telegraf can be deployed as a DaemonSet in every node, as an application sidecar in pods, or as a central collector.

Telegraf deployed as DaemonSet agent

Telegraf can be installed as a DaemonSet in every Kubernetes node. Telegraf can directly collect monitoring data from the nodes, containers, pods, and applications via push or pull mechanisms.

Telegraf deployed as a sidecar agent

Telegraf can be installed as an application sidecar in Kubernetes pod deployments. As a sidecar, IT can disseminate a metrics monitoring culture while limiting the impact of application metrics exposure on the overall cluster scraping.

Telegraf deployed as central agent with Kubernetes service discovery

Telegraf supports Kubernetes service discovery by watching Prometheus annotations on pods, thus finding out which applications expose /metrics endpoints. As a central agent, Telegraf can scrape all /metrics endpoints exposed and send collective metrics more efficiently to InfluxDB.

Native Kubernetes Operators

InfluxDB Kubernetes Operator allows for InfluxDB to be deployed as a Kubernetes object. It is built using the Operator SDK, which is part of the Operator Framework and manages one or more InfluxDB instances deployed on Kubernetes. A common use case is to facilitate backup/restore operations.

Architecture of the TICK stack including InfluxDB and Kapacitor

Specific Telegraf components

Community integrations

  • Telegraf, InfluxDB, and Grafana Kubernetes apps – Kubernetes apps are prepackaged applications that can be deployed to Google Kubernetes Engine in minutes. The Telegraf InfluxDB and Grafana package (for metrics collection, storage, & visualization) is popular for application performance monitoring, infrastructure monitoring, and even gathering and displaying real-time analytics within your applications.

Featured customers

GravitationalGravitational

“It’s a unique product that provides features like clustering, commercial support, and data retention that matter a lot to us. That’s why we picked InfluxData and that’s why several years ago, we rolled out our first integration with InfluxDB for the Kubernetes clusters that we deploy.”

Sasha Klizhentas, CTO, Gravitational

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GravitationalGravitational

“It’s a unique product that provides features like clustering, commercial support, and data retention that matter a lot to us. That’s why we picked InfluxData and that’s why several years ago, we rolled out our first integration with InfluxDB for the Kubernetes clusters that we deploy.”

Sasha Klizhentas, CTO, Gravitational

Read case study

AporetoAporeto

“Before InfluxDB, we were like a lot of organizations where we didn’t have the visibility into what was going on in our K8s and Docker environments. Now with InfluxDB we are able to get insights in real time and act on.”

Bernard Van De Walle, engineer, Aporeto

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AporetoAporeto

“Before InfluxDB, we were like a lot of organizations where we didn’t have the visibility into what was going on in our K8s and Docker environments. Now with InfluxDB we are able to get insights in real time and act on.”

Bernard Van De Walle, engineer, Aporeto

Read case study

InfluxDB for Kubernetes monitoring

InfluxData has added Kubernetes-specific capabilities to make it easier for its users to work with Kubernetes:

  • Helm Charts for faster node deployment – kube-influxdb is a collection of Helm Charts for the InfluxData TICK Stack to monitor Kubernetes with InfluxData.
  • Native Kubernetes Operators – A Kubernetes Operator manages InfluxDB instances deployed as a Kubernetes object.
  • High availability (HA) and scalability of monitored data – Large volume of Kubernetes metrics and events can be preserved in InfluxDB storage clusters allowing long-term policy retention together with high data granularity and high series cardinality.
  • Integration with Prometheus monitoring – Kubernetes native monitoring is based on Prometheus format. InfluxDB integration with Kubernetes Prometheus monitoring is supported in two ways:
    1. Remote Write API: Prometheus can write samples that it ingests to InfluxDB in a standardized format.
    2. Remote Read API: Prometheus can read (back) sample data from InfluxDB in a standardized format.

What’s next?

Webinar

How InfluxData makes Kubernetes an even better Master of its components through monitoring

shows how to use InfluxData to help Kubernetes orchestrate the scaling out of applications by monitoring all components of the underlying infrastructure.

Webinar

Kapacitor: Service Discovery, pull and Kubernetes

shows how Kapacitor’s Service discovery and scraping code will allow any service discovery target that works with Prometheus to work with Kapacitor.

Performance Monitoring

InfluxDays London 2019 presentation that shows best practices to monitor Kubernetes with Telegraf in DaemonSet, application sidecar and central collector deployment options.
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