Operations | Monitoring | ITSM | DevOps | Cloud

env zero Launches EZ Control, the Autonomous Cloud Control Plane for the AI Era

Industry-Leading Asset Coverage Spanning Nearly 2,300 Resource Types Across AWS, Azure, Google Cloud and Kubernetes, Structured into a Real-Time Ontology That EZ Control Uses to Enforce Security, Cost, Availability, Maintenance and Performance Policies Continuously.

Database change management on Databricks: migrations, environments, and AI-generated change

You wouldn’t ship untested SQL Server database changes – Why is Databricks different? Databricks is where the data estate is growing, and increasingly where AI workloads run and generate change. But schema change there still happens the hard way: views and stored procedures managed through manually versioned scripts, drift between workspaces discovered when a deployment fails, and no reliable record of what changed, when, where, or why. As AI raises the volume and speed of schema change, these gaps widen.

This AI agent finds your app's bottlenecks and suggests the fix

Most teams collect the profiles and traffic data that explain a slowdown. Almost nobody has time to read it before users notice. In this Product Highlights conversation, Sylvain Guittard, Senior Director of Product at Upsun who leads the team behind the Upsun console and CLI, breaks down the Upsun Cloud Performance Agent, the first background agent running on Upsun Cloud. His take: "We monitor everything, we feed that into an agent, and the agent will be capable of finding what the bottlenecks are in your application. And on top of it, it gives you a patch, or a way to fix it." We get into.

Watch this AI agent find and fix performance bottlenecks

Anyone can claim an AI agent will fix your performance problems. This demo shows exactly what it looks at and what it hands back. In this Product Highlights conversation, Sylvain Guittard, Senior Director of Product at Upsun who leads the team behind the Upsun console and CLI, runs the Upsun Cloud Performance Agent live on a demo project. His take: "You have a patch that is already available, and a recommendation, so you can see if it fits or not to your context." We get into.

Realtime transaction fraud detection - with an LLM?

Conversational AI with a chatbot is great for drafting emails or debugging code, but it’s less ideal for real-time application middleware. If you’re trying to inspect a financial transaction for potential fraud in the middle of a checkout loop, you don’t need an LLM to write you an essay about why a credit card transaction looks suspicious – you just need a probability score, and you need it as fast as possible.

Right-size your analytics stack with Aiven for ClickHouse

TL;DR If most of your Snowflake or Databricks spend goes to dashboards and reports, you are paying for a platform built for much bigger problems. Aiven for ClickHouse runs those workloads on a fixed plan, so adding dashboard users does not add to your compute bill. Native integrations with PostgreSQL and Apache Kafka also replace most of the ingestion and orchestration tools around your current platform. Move one dashboard at a time, and keep Snowflake or Databricks for work such as model training.

Bring Your Own Key: Encryption sovereignty without the headache

Let's start with an uncomfortable question that tends to surface exactly once, usually in front of an auditor, a customer's security team, or your own CISO: who can actually decrypt your data right now? For most managed databases and message queues, the honest answer is "the provider, technically, if they really wanted to." That's not a scandal. It's just how managed encryption-at-rest normally works: the provider generates the key, holds the key, rotates the key, and you trust them not to misuse it.

Build The Future: Building a Startup Inside a Scaleup

TL;DR Stan's experience ranges from raising millions for his own startups to working across programming, marketing, and PR. Here is how that versatile founder mindset fuels his Product Director role at Aiven today. Stan has had a lot of ownership from day one, in the most literal sense. Aiven headhunted him to build a new product from the ground up. "My onboarding was thirty minutes with my boss, who gave me a handful of really good and original ideas, he says. "After that, I had to figure it out.

How Etsy gets its mobile apps ready for peak traffic

Most advice about surviving a traffic spike is about capacity. Scale the fleet, warm the caches, load test the checkout path. All of it assumes you can fix whatever breaks the moment you find it. Mobile apps don’t work that way. I spent an hour on a workshop with Jay Henry, a senior engineering manager at Etsy who owns engineering strategy across three teams covering CI, build, test, release, observe, and SRE. Jay’s take: a web team having a bad day can revert in minutes.