Logs & Metrics

Elasticsearch comes with multiple query languages, only one of which makes sense to use for time-series data as ours: ES|QL. It’s obviously modeled after Splunk’s SPL, is easy to read, understand, and write - helped by fantastic autocomplete in the web UI. This article explains some important ES|QL concepts by showing you how to create a chart that visualizes your home’s energy consumption.

This article describes how to send Home Assistant metrics to Elasticsearch for long-term storage and visualization. It focuses on the integration between the two products and on how to configure Elasticsearch. This post is part of my series on home automation, networking & self-hosting that shows how to install, configure, and run a home server & network with dockerized or virtualized services.

This is a deliberately simplistic dockerized Elasticsearch & Kibana setup focused on long-term stability and minimal maintenance requirements. To forego the need to deal with a private CA and certificates, Elasticsearch TLS is not used. Instead, authenticated HTTPS access is provided via Caddy.

This article explains how to set up VictoriaMetrics in a Docker container with automatic HTTPS via Caddy. It also shows how to forward Home Assistant data to VictoriaMetrics for long-term storage and how to query the data from Grafana. This post is part of my series on home automation, networking & self-hosting that shows how to install, configure, and run a home server & network with dockerized or virtualized services.

This article introduces newbies to writing search queries in LogQL. It should help you get started with building Grafana dashboards based on log data in Loki. It would have helped me immensely building my first Grafana dashboard.

This article, effectively part 2 of my Grafana setup guide, explains how to set up Prometheus, Node Exporter, and cAdvisor with automatic HTTPS certificates (via Caddy) and OAuth single sign-on (via Authelia). This post is part of my series on home automation, networking & self-hosting that shows how to install, configure, and run a home server & network with dockerized or virtualized services.

This article explains how to set up Grafana, Loki, and Promtail with automatic HTTPS certificates (via Caddy) and OAuth single sign-on (via Authelia). This post is part of my series on home automation, networking & self-hosting that shows how to install, configure, and run a home server & network with dockerized or virtualized services.

This article is based on my Splunk .conf 2015 session and is the second in a mini-series on Splunk data model acceleration. Make sure to read parts 1 and 2 first.

This article is based on my Splunk .conf 2015 session and is the second in a mini-series on Splunk data model acceleration. Make sure to read part 1 first. Under the Hood HPAS Population The high-performance analytics store (HPAS) is populated by scheduled searches that run every 5 minutes. The HPAS spans a user-defined time range. Old events are purged automatically by a maintenance process that runs every 30 minutes.

This article is based on my Splunk .conf 2015 session and is the first in a mini-series on Splunk data model acceleration. Why Accelerate? Have you ever seen this? Splunk is great and very fast with needle in a haystack searches, e.g. find a specific keyword in millions of events. It is not so fast with searches that perform calculations on millions of events, e.g. the sum or average of fields.

Splunk’s Universal Forward has the neat capability of executing arbitrary scripts while capturing their output and sending that to Splunk. This feature allows you to turn any executable, batch file or PowerShell script into a Splunk data source, making the data collection options basically limitless. This post explains a few tricks that are difficult to find otherwise.

You have probably heard of Splunk, but can you describe what it does to a colleague in a few sentences? That is not easy. Splunk does not belong in any traditional category but stands apart from the crowd. That makes it interesting, but also the explaining harder. Here is my attempt.

This is a collection of useful tips and resources for developing Splunk apps. For an explanation of the available app types please see my earlier article on the topic. Splunk Search References and Guides Splunk publishes two excellent resources for learning and working with its search processing language (SPL):

When you start with developing apps for Splunk the first big question you hit is a bit unexpected: which technology do you work with, which app type do you choose?