Operations | Monitoring | ITSM | DevOps | Cloud

Scaling Technical Research: Integrating Proxies into Your Data Operations (DataOps) Pipeline

In the world of Big Data, success depends on more than just algorithms. The quality of the incoming data stream is crucial. When a company scales its technical research, it inevitably encounters barriers such as CAPTCHAs, geoblocks, and anti-fraud systems.

Introducing Aiven for DataHub: Managed context for humans and AI

Discover Aiven for DataHub: a fully managed, open-source data catalog that gives your teams and AI agents the context they need to find and understand data. According to an MIT study, 95% of AI projects fail to deliver value. I've been thinking about why that number is so stubbornly high, and I've come to believe the answer isn't about models,compute or even data quality in the traditional sense -It's about context.

Get Kafka-Nated S2E4: Debugging the Kafka-Iceberg Connector

In this episode of Get Kafka-Nated, host Hugh is joined by Anatolii Popov, Senior Software Engineer at Aiven, to dive into one of the most talked-about integrations in the modern data stack: Kafka to Apache Iceberg. Anatolii was accepted to speak at Iceberg Summit 2026 on debugging the Kafka Connect Iceberg Connector, and in this session we’ll cover the talk he would have given, including common failure modes, debugging locally, catalog complexities, and where the integration is heading next.

Top 5 Must-Have Integrations for Your Zendesk Suite in 2026

Modern customer support demands more than a basic ticketing system - it requires strategic zendesk integrations that connect your support team with AI automation, real-time analytics, quality control, multilingual content, and unified customer data. In 2026, businesses that fail to build this integrated ecosystem will struggle to meet rising customer expectations for speed, personalization, and seamless self service across channels.

How a single space broke OpenSearch backups - and how Aiven fixed it for our customers

One space character, one broken backup. See how Aiven’s engineering team traced an OpenSearch k-NN bug to its source and implemented a lasting fix. Backing up your OpenSearch indexes via the Snapshot process is vital for disaster recovery, allowing you to restore the indexed data, cluster configuration and state if something goes wrong.

Introducing Aiven Apps: Applications next to your data, where they belong

Unify your code and data. Aiven Apps lets teams deliver real-time applications faster, without building new platforms. No lock-in. No custom pipelines. No egress surprises. We are excited to announce the Limited Availability (LA) launch of Aiven Apps! For over a decade, Aiven has simplified how you store and stream data with an open-source foundation. Over that same time, data volumes have exploded, and so has the friction caused by the distance between where your data is stored and where your code runs.

Telegraf Overview - InfluxData's Metric Collection Agent

Telegraf is InfluxData’s open source agent for collecting metrics, and it’s used everywhere. In this quick overview, Product Manager Scott Anderson shares what makes it stand out, from more than 5 billion downloads to a huge plugin ecosystem with 400+ integrations. It’s also built by a strong community, with over 1,300 contributors and thousands of GitHub stars. That momentum is a big part of why Telegraf keeps growing.

New Plugins, Faster Writes, and Easier Configuration: What's New with the InfluxDB 3 Processing Engine

The Processing Engine is one of the most powerful features in InfluxDB 3. It lets you run Python code at the database—transforming data on ingest, running scheduled jobs, or serving HTTP requests—without spinning up external services or building middleware. You define the logic, attach it to a trigger, and the database handles the rest. Since launching the Processing Engine, we’ve been building out both the engine itself and the ecosystem of plugins that run on it.

From Data to Dollars: How AI-Driven Hyper-Personalization Is Reshaping Retail Revenue

Every retailer knows that personalization drives revenue. The evidence has been consistent for years: personalized experiences convert better, retain customers longer, and generate higher average order values. What has changed is the scale and sophistication at which personalization is now possible - and the gap it creates between brands that embrace AI-driven approaches and those still relying on manual rules and static segments.