Operations | Monitoring | ITSM | DevOps | Cloud

Previously, we showed you how to securely pull Docker images from Cloudsmith to Kubernetes using OIDC with a CronJob-based approach. We concluded the post discussing credential provider plugins from Kubernetes 1.20 and an enhancement in Kubernetes 1.33 that offers a new approach for external registries like Cloudsmith. We have now built a credential provider that takes advantage of this new capability. This article explores what this means for the future of pulling images from Cloudsmith on Kubernetes.

Aiven is proud to introduce our new pricing plans for Aiven for ClickHouse! Depending on your chosen region and plan, you can now double your compute power for the same price. On the other hand, if reducing costs is your priority, it's now possible to lower your total cost by up to 30% for the same compute power, depending on how you use the service. But how did we achieve this? This article explains how, and why Aiven’s nodes are the best for your ClickHouse workloads.

Diskless topics are proposed in KIP-1150, which is currently under community review. The examples in this article use "Inkless", Aiven's implementation of KIP-1150 that lets you run it in production. I joined Aiven as a Developer Advocate in May, shortly after the Kafka Improvement Proposal KIP-1150: Diskless Topics was announced, which reduces the total cost of ownership of Kafka by up to 80%!

You asked, and we listened! We’re thrilled to announce the release of the VictoriaLogs Cluster version – one of the most requested and anticipated updates from our user community. This marks a significant leap forward for VictoriaLogs, empowering users to handle log volumes and ingestion rates far beyond the limits of a single node.

Global demand for data center capacity is skyrocketing. From 2023 to 2030, power consumption across data centers is expected to grow by up to 22% annually, driven primarily by generative AI (GenAI) workloads. By 2030, AI workloads are predicted to account for 70% of total demand. This demand doesn’t just mean more hardware; it necessitates high-density computing environments to support training large language models like GPT and real-time inference systems.

If you’ve ever had a user complain that their video call was choppy or their VoIP call had weird delays, even though the Internet speed looked fine, you’ve probably run into Internet jitter. It’s one of those issues that doesn’t always show up on a speed test, but it can absolutely wreck real-time communication. And if you’re managing networks across remote offices, home setups, or hybrid work environments, you’ll want to keep an eye on it.

There’s no doubt that managing networks today is a whole different ballgame than it used to be. Complexity is growing, environments are more fragmented, and user expectations have never been higher. One of the biggest challenges for network operations teams? Visibility—or the lack of it. Network operations used to be much simpler. Traffic flowed through your own data center, and you had the visibility and control needed to manage performance and troubleshoot issues.

Whether you’re dealing with IT issues, customer questions, or just trying to keep track of who’s supposed to fix what and when, ticketing tools are the unsung heroes of organized chaos. They help teams stay on top of requests, assign responsibility, (no more “I thought you were going to handle it”) and actually close the loop on problems instead of letting them collect dust in someone’s inbox.

Data plays a critical role in shaping operational decisions. From sensor streams in factories to API response times in cloud environments, organizations rely on time-stamped metrics to understand what’s happening and determine what to do next. But when that data is inaccurate or incomplete, systems make the wrong call. Teams waste time chasing false alerts, miss critical anomalies, and make high-stakes decisions based on flawed assumptions.