Operations | Monitoring | ITSM | DevOps | Cloud

Flavors of PostgreSQL: Choosing the Right Database for Your Next Build

In this deep dive, we’ll explore the modern PostgreSQL landscape—from core extensions to cloud-native forks—and help you confidently choose the right implementation based on your technical and business needs. AIVEN DATA PLATFORM The Aiven Platform is more than a collection of open source services for streaming, storing and analyzing data. The platform ensures that all services run reliably and securely in the clouds of your choice, are observable, and can easily be integrated with each other and with external 3rd party tools.

Visualize Google Cloud BigQuery data in Grafana: the latest updates, key features, and more

Here at Grafana Labs, our commitment to our “big tent” philosophy runs deep. We prioritize interoperability and flexibility within our observability solutions, and believe you should be able to connect to and visualize data from a wide range of sources, including both open source and commercial technologies. Our rich ecosystem of Grafana data sources directly reflects these values — and today, we’re excited to share a recent milestone related to that ecosystem.

How InfluxDB 3 Enterprise Delivers 10-Millisecond Queries Over Historical Time Series Data

Time series data, such as IoT sensor readings or stock market ticks, flow in fast, often at a rate of millions of points per second. Querying this data, especially years of historical records, can be slow and painful if using a nonspecialized database rather than a time series database like InfluxDB.

Beyond Storage: How Time Series Databases Are Becoming Intelligent Data Engines

Data isn’t just a record of what happened—it shapes what happens next. Across industries, connected devices continuously stream time-stamped data that reflects the current state of machines, environments, and systems. This steady flow gives businesses a live view of their operations and the opportunity to catch issues early, adjust quickly, and operate more efficiently.

Top tips: Dismantling data silos in your organization

Top Tips is a weekly column where we highlight what’s trending in the tech world and list practical ways to explore these trends. This week, we're going over how you can eliminate data silos in your organization to enable smoother data flows. The free flow of data is one of the clearest signs of organizational health. When data is locked away—isolated in disparate systems that don’t communicate with each other—you’re dealing with a data silo.

Myth #3 of Kubernetes Resource Optimization: Instance Rightsizing

In this blog series we are examining the Five Myths of Kubernetes Resource Optimization. So far we’ve looked at Myth 1: Observability and Monitoring and Myth 2: Cluster Autoscaling. Stay tuned for the entire series! The third myth addresses another common assumption of many Kubernetes practitioners: Choosing the right instances will eliminate waste in a cluster.

The 3 Es of Diskless Kafka BYOC

Diskless Kafka splits storage from compute, delegating replication to cheap object storage and turning Apache Kafka Brokers into a stateless compute layer. It’s 100% Kafka, and 80% cheaper. But in the cloud, a cheaper underlying technology does not always mean you pay less. The cost varies significantly depending on the deployment model - SaaS or BYOC. In this article, we will learn why.

Apache Spark security: start with a solid foundation

Everyone agrees security matters – yet when it comes to big data analytics with Apache Spark, it’s not just another checkbox. Spark’s open source Java architecture introduces special security concerns that, if neglected, can quietly reveal sensitive information and interrupt vital functions.

Moving from Relational to Time Series Databases

I’ve been building apps with SQL Server for years. Everything worked well until I started dealing with sensor data, stock trade volume, and IoT telemetry. As the volume of time-stamped records grew into the millions, I saw relational databases struggling with workloads they weren’t designed for. That’s when I explored time series databases. The performance improvements were significant, but what surprised me was the mental shift required.