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I’ve been active in technical communities like PyData and codebar across the UK for nearly a decade now and owe much of my career to meeting and learning from cool people at events. Now, as someone with a professional interest in community organising, I spend a lot of my time looking for events to sponsor or speak at. But whilst finding technical events and communities can be tricky, I think I’ve found a solution using Kafka that might be useful for you too.

You've felt it. You're deep in a flow state with Claude or Cursor, building the next great thing, and then you hit the wall. Time to leave your editor, open a browser, click through a console, copy a connection string, paste it back, and pray you didn't fumble a character. The vibe is gone. What if your AI agent could just... do it? Deploy the database. Create the Kafka topic. Ship the app. All without you ever leaving the conversation. Today, that's real.

Aiven for Valkey includes the Valkey Search module setup and ready to go. Here's what that looks like in practice: a small online shop adding real search on top of the cache it's already running. Needle & Yarn sells the yarn you crochet with (skeins) and the design patterns you crochet from. Like a lot of e-commerce backends, it already runs Valkey as a product cache, with each product stored as a Hash for hot-path performance.

In this article we’ll show how we built an image search demo in Aiven Apps. The demo uses the CLIP Large Multimodal Model (LMM) to turn a user’s text prompts into a vector that can be compared with the precomputed vectors for a corpus of images, allowing the user to find images based on their text. While in this example the LMM input (the text prompt) is coming from the user, the principle is the same as for an internally generated query.

Every time your app asks the database 'does this row exist,' it pays the cost of a database query to get back 'no'.

OpenSearch isn't just a search engine anymore. Recent releases moved it into AI infrastructure: agentic memory built in, Better Binary Quantization (BBQ) compressing vectors 32x, token-usage tracking, and a one-command Observability Stack. A stack for building practical AI applications, not just indexing. The catch is that production-sized OpenSearch clusters aren't where you want to prototype.

We recently announced the Limited Availability (LA) launch of Aiven Apps, which lets teams define, run, and scale production-ready, real-time applications using container and Compose-based workflows they already know. It provides a managed, stateless runtime that runs directly inside your data perimeter, letting you deploy applications alongside open-source data services like PostgreSQL and Apache Kafka.

Many businesses see emissions reduction as a cost sink: assigning people, maintaining compliance, the hard labor of calculating carbon signatures. That view is out of date – and a new partnership between Aiven and data provider OxygenIT demonstrates why. Our premise: your carbon footprint isn't just about understanding emissions; it's about understanding your business. Today, we're announcing a new service that helps with both.

In the high-stakes world of Online Travel Agencies (OTAs) like Expedia, Hopper, Priceline, and Airbnb, seconds matter. A traveler searching for a "beachfront stay in Hawaii" isn't just looking for a room — they are reacting to weather changes, fluctuating flight prices, and social media trends. Traditional travel platforms often rely on stale data: yesterday's search history or last week's preferences. To truly compete, travel platforms must pivot to Real-Time Context Engineering.

Luckily, in Kafka cache invalidation is not an issue, but we still need to name things. Let me tell you a story about naming things in Kafka.