Operations | Monitoring | ITSM | DevOps | Cloud

The amount of data organizations handle has created the need for faster data access and processing. Data Denormalization is a widely used technique to improve database query performance. This article discusses data normalization, its importance, how it differs from data normalization and denormalization techniques. Importantly, I’ll also look at the pros and cons of this approach.

What’s the right way to manage growing volumes of enterprise data, while providing the consistency, data quality and governance required for analytics at scale? Is centralizing data management in a data lake the right approach? Or is a distributed data mesh architecture right for your organization? When it comes down to it, most organizations seeking these solutions are looking for a way to analyze data without having to move or transform it via complex extract, transform and load (ETL) pipelines.

If the past year has taught us anything, it’s that the more things change, the more things stay the same. The whiplash and pivot from the go-go economy post-pandemic to a belt-tightening macroeconomic environment induced by higher inflation and interest rates has been seen before, but rarely this quickly. Technology leaders have always had to do more with less, but this slowdown may be unpredictable, longer, and more pronounced than expected.

Google Cloud Operations is a powerful integrated monitoring, logging, and trace managed service for applications and systems running on Google Cloud and beyond. As part of our partnership with Google, we help extend Cloud Operations with BindPlane OP and OpenTelemetry monitoring for a complete monitoring solution. With BindPlane OP, Google Cloud Operations becomes a single pane of glass for monitoring all aspects of your data center, no matter if it’s on prem or running in the cloud.

Prometheus is the de facto open-source solution for collecting and monitoring metrics data. Its straightforward architecture, operational reliability, minimal upfront cost, and versatility in integrating with cloud-native systems make it the preferred choice for many. Getting started is as simple as configuring the Prometheus server and setting simple parameters such as the scrape intervals and targets, cadence, and setting the job name based on the function of the server.