Operations | Monitoring | ITSM | DevOps | Cloud

Unveiling Azure's Hidden Costs: What You Need to Know

So, you’re new to the cloud or just starting off with Azure. You’re probably starting your first project and using the Azure Calculator to help estimate your monthly run rate. The problem is that Azure, like all clouds, has hidden costs. So why does the cloud have hidden costs? Well, while we call them hidden costs, it’s really more a matter of unexpected costs or unknown costs.

ClickHouse Pricing Made Simple. Choose Aiven.

Aiven for ClickHouse has become a favorite on the platform thanks to its blazing-fast analytical querying, built specifically to handle the unique challenges of OLAP workloads. It excels at crunching massive datasets in real-time, making it a favorite for demanding applications like log analytics, web analytics, and ad tech. At Aiven, we understand the power that ClickHouse can unlock for businesses of any size.

Learn to Forecast Time Series Data Using ML & InfluxDB

Forecasting is all about predicting the future—in data science, it is one of the key skills in dealing with time series data, such as stock price prediction, sales forecasting, logistics planning, etc. In this tutorial, we’ll learn how to forecast the notorious weather pattern of London, UK, using the following free and open source technologies.

16 Ways Tiered Storage Makes Apache Kafka Simpler, Better, and Cheaper

Tiered Storage for Apache Kafka is a simple idea that goes a longway. At its bare bones, it basically means: store most of the Kafka broker’s data in another server, e.g AWS S3. On the surface, it sounds insignificant—like a minor architectural tweak with minimal impact.

CLI Operations for InfluxDB 3 Core and Enterprise

This blog covers the nitty-gritty of essential command-line tools and workflows to effectively manage and interact with your InfluxDB 3 Core and Enterprise instances. Whether you’re starting or stopping the server with configurations like memory, file, or object store, this guide will walk you through the process. We’ll also look at creating and writing data into databases using authentication tokens, exploring direct line protocol input versus file-based approaches for tasks like testing.

How AI Can Misinterpret Data and Lead to Errors

While AI systems can analyze vast amounts of data quickly, they may also misinterpret that data and lead to significant errors. Understanding how AI misjudgments occur will improve algorithms and ensure they provide accurate results. From biases in data to linguistic ambiguities, various factors can contribute to an AI's misinterpretation of information. Look closely at how these systems work and reveal why you should address these issues right below.

How AI is Transforming the Way We Analyze Data

In 1956, when IBM's engineers unveiled the first hard disk drive, it stored only five megabytes-an amount dwarfed today by a single high-quality photo on your smartphone. But that wasn't the fascinating part; it was the vision. They anticipated a future where data would not only be stored but also analyzed on an unprecedented scale. Fast forward to the 21st century, and data is growing exponentially. Every second, trillions of bytes are created, tracked, and stored across the globe. But storing it isn't the challenge anymore; making sense of it is.

You Can Solve the Overprovisioning Problem

If you're like most companies running large-scale, data-intensive workloads in the cloud, you’ve realized that you have significant quantities of waste in your environment. Smart organizations implement a host of FinOps and other activities to address this waste and the cost it incurs: … and the list goes on. These are infrastructure-level optimizations.

You Can Solve the Overprovisioning Problem

If you're like most companies running large-scale, data- intensive workloads in the cloud, you’ve realized that you have significant quantities of waste in your environment. Smart organizations implement a host of FinOps and other activities to address this waste and the cost it incurs: … and the list goes on. These are infrastructure-level optimizations.