High-Availability
How vmstorage Handles Query Requests From vmselect
When vmselect asks vmstorage for data, there’s actually quite a bit happening behind the scenes. This article breaks down the process of how vmstorage locates and retrieves your metrics, from finding the right TSIDs to sending back the actual data points.
How vmstorage's IndexDB Works
IndexDB acts as vmstorage’s memory - it remembers which numbers (TSIDs) belong to which metrics, making sure your queries get answered fast. This article walks through how this system works, from the way it organizes data to how it keeps track of millions of timeseries.
How vmstorage Processes Data: Retention, Merging, Deduplication,...
vmstorage takes data from vminsert through a concurrency limiter, creates TSIDs for each row, and puts them in memory buffers. Every few seconds, it moves data to storage parts on disk. The system merges parts, removes duplicates, and cleans old data. This turns raw metrics into data users can search.
How vmstorage Handles Data Ingestion From vminsert
This article explains how vmstorage processes incoming metrics, assigns unique IDs to timeseries, and organizes everything into different types of storage parts. The whole system is pretty clever - it uses in-memory buffers for speed, smart compression to save space, and has various watchdogs keeping an eye on things like disk space and data retention.
When Metrics Meet vminsert: A Data-Delivery Story
vminsert acts as a gateway for incoming monitoring data. It receives data in different formats, processes it by parsing and adjusting labels, then uses memory buffers to send this data to storage nodes. It’s smart enough to always send the same type of data to the same storage node and can redirect data if a node isn’t working properly.
How vmagent Collects and Ships Metrics Fast with Aggregation, Deduplication, and More
VictoriaMetrics agent, or vmagent, is a lightweight tool designed to gather metrics from a number of different sources. Once it pulls in all those metrics, vmagent lets you ‘design’ them (through ‘relabeling’) or filter them down (doing things like reducing cardinality, stream aggregation, deduplication, and so on) before shipping them off to wherever you want to store them.
How to Choose a Scalable Open Source Time Series Database: The Cost of Scale
When looking for a most scalable open source time series database, what are the criteria to care about? Read this blog to get our recommendations.
vmagent High-Availability Examples
Three examples of vmagent high-availability setup for pull and push models