Operations | Monitoring | ITSM | DevOps | Cloud

The big data landscape is always changing to solve existing problems and continues to push the boundaries of performance and scale. Data lakehouses are a new architectural pattern that is rapidly gaining popularity by solving a variety of problems seen with previous solutions like data warehouses and data lakes. In this article, you will learn the following.

Various economic pressures on businesses have created a focus on new and innovative ways to manage operational costs. At the same time, businesses are looking at using IT to help manage overall business costs and increase income—for example, by supporting remote working, and in many cases, enabling e-commerce to replace closed retail outlets. Management of infrastructure to minimize downtime has two major benefits: reductions in support and maintenance costs and improvements in service levels.

Grafana is an open-source web application for visualizing data. You can query your data, create visuals, and receive alerts to better understand what you have. Some people think of Grafana as a Kubernetes-only tool, but in reality, it’s simply a data visualization tool that became popular within the Kubernetes ecosystem, especially when combined with Prometheus. In this post, I’ll focus on a very specific part of Grafana: the dashboards.

In the era of big data, choosing the right data storage solution is crucial for organizations to harness the power of their data. Understanding the differences and benefits of data lakes and data warehouses can help businesses make informed decisions on which option best suits their needs. In this blog post, we will explore data lakes and data warehouses, their architecture, and their key features, enabling you to make the right choice for your organization.

Any existing InfluxDB user will notice that InfluxDB underwent a transformation with the release of InfluxDB 3.0. InfluxDB v3 provides 45x better write throughput and has 5-25x faster queries compared to previous versions of InfluxDB.