Operations | Monitoring | ITSM | DevOps | Cloud

Root Cause Analysis Workflows Using InfluxDB

Summary When production incidents strike, distributed systems can mask issues under a collection of fragmented logs. But all your services share a universal metric: time. That’s good news, because root cause analysis (RCA) is inherently a time series problem. InfluxDB is your central telemetry hub, allowing you to reconstruct operational failures using a reliable, four-step workflow: Table of Contents It’s 2:00 AM, and your monitoring system fires a critical alert.

Observability is a data problem

TL;DR Metrics, logs, and traces each have a different shape, so each needs a different backend. Aiven for Metrics handles metrics and alerting, Aiven for OpenSearch handles keyword search across logs, and Aiven for ClickHouse handles analysis of high-volume, high-cardinality events. All three are upstream open source engines on the same Aiven platform, so you can start with one and add the others as your needs change.

How a Solutions Architect Brought Multi-Cloud Migration to OpenSearch | Tony Piazza

Aiven Senior Solutions Architect Tony Piazza joined the company in March. Within months he had merged five PRs adding Google Cloud support and Terraform-based provisioning to the OpenSearch Migration Assistant, a tool that previously only worked on AWS. Tony talks with Jay Miller about: Why he went from consulting to open source contribution. How a consultant’s habit of finding project risks early shaped the work. His first conference keynote at OpenSearchCon. What contributing as a vendor-neutral company looks like. Where he’s contributing next, including ML Commons, Data Prepper and the docs.

Define user actions on your web app with visual labeling in Product Analytics

Adding or renaming a product event has traditionally meant creating an engineering ticket. Datadog Product Analytics uses the same SDKs and configuration as Real User Monitoring (RUM), and those SDKs autocapture actions such as clicks and taps. But an automatically generated action name describes the element rather than the user intent behind it.

Modernize Your Data Historian with InfluxDB

In this video, Dev Advocate Cole Bowden walks you through where traditional data historians fail, and why a dedicated time series database like InfluxDB can streamline your operations. With an AI-powered demo showcasing an automative plant's data, you'll see the value of InfluxDB and where it can power insights that Data Historians can't handle on their own.

Solving AI Latency and Cost Problems with Valkey - Aiven Webinar

LLM providers charge you for caching, and they do it on their terms. You can run it yourself for a fraction of the cost. In this Aiven webinar, Jay Miller (Staff Developer Advocate) shows how to use semantic caching and semantic routing on Valkey to cut prompt costs + latency. You'll see a working demo, "Template Scout", that searches GitHub for deployable repos and picks the cheapest model that can answer each question.

Q3 2026 Recap: Up to 4x Faster Single-Series Queries, Distributed Compaction, and Telegraf Controller High Availability

Q3 was a packed quarter, with releases across InfluxDB, Telegraf, and Amazon Timestream for InfluxDB that help deployments and fleets grow without slowing down. InfluxDB 3.11 brought performance improvements for heavier, more complex workloads to GA in InfluxDB 3 Enterprise. InfluxDB 3.12 followed with roughly 3x faster bulk imports, distributed compaction in beta, per-database schema enforcement, and generally available role-based access control.

PostgreSQL MCP: Manage Postgres From Your AI Assistant

TL;DR Most of the time we understand the tasks we're working on, but inevitably something comes up that we don't know much about, and we need just enough skill to cope. That used to mean reading paper documentation, then searching vendor sites and the web. Now it tends to mean a dialog with an LLM that has already ingested the documentation we don't have time to find and read. That's only half the problem, though.

Why Automotive Manufacturers Are Augmenting Data Historians, Not Replacing Them

Summary Automotive manufacturers face rising costs and scaling limits with per-tag-priced data historians as sensor counts and sampling rates grow. Instead of rip-and-replace, manufacturers are augmenting traditional data historians by routing new telemetry to InfluxDB (via Telegraf or Litmus or consolidating siloed historians, while the historian continues handling SCADA and regulatory data. Table of Contents.