Operations | Monitoring | ITSM | DevOps | Cloud

Last week, I saw a user asking for help on Slack: Note: The screenshot was taken in the UTC+8 timezone, so the high churn rate at 8:00 AM occurs at 0:00 AM UTC.

As part of our big tent philosophy here at Grafana Labs, we believe you should be able to access and derive meaningful insights from your data, regardless of where that data lives. One of the ways we stay true to that philosophy is through our Grafana Enterprise data sources.

Ensuring all operations are normal and all data is guarded in the firm’s IT structure is vital. Regularly checking out various aspects that indicate the performance of the database makes it easier for management to identify issues that may have gone out of hand through database monitoring.

Users should maintain data consistency to ensure accurate database testing and analysis, especially when generating data in dependent columns. For example, they can use formulas, data generators, or post-scripts to fill in columns based on other columns in the table. However, post-scripts may be complicated and affect database performance. In the article, we’ll explore how to generate values for the referenced columns using dbForge Data Generator for SQL Server.

Manual updating of Salesforce records is far from optimal. If you have ever worked with this CRM, you should know it requires you to find the exact record you want to edit, and only then you’ll be able to change data in its fields. This is fine when you work with separate records, but what if you need to mass update records in Salesforce? If done manually, such an update might eventually lead to errors and consume time.

.NET 9 will be released this November, featuring versatile performance and security upgrades, C# syntax enhancements, and new LINQ methods along with the.NET Aspite stack for cloud-native development, ML.NET for extended AI capabilities, and an array of other handy updates. However, while we are still one month away from the official.NET 9 launch, its Preview version is already here, giving developers an early look at the latest advancements. Keep reading to explore the upcoming improvements in detail.

Big data storage tools like BigQuery, Hadoop, and Cassandra are used to manage large volumes of structured and unstructured data generated by modern applications. Unlike traditional databases, these tools provide scalable and distributed infrastructure that efficiently stores, processes, and analyzes petabytes of data across clusters.

With an expanding community of users and an array of data management features under the hood, PostgreSQL has outperformed less popular databases in 2024 and is expected to become a huge trend in the upcoming year. For those who know their way around other RDBMSs, this database management system is quite easy to master, even though it has a more complex architecture.

I don’t understand why pure open-source licenses, such as Apache2, MIT or BSD, should be replaced with a source available license in order to increase profits from enterprise support contracts. That’s why we at VictoriaMetrics aren’t going to change the Apache2 license for our products. Our main goal is to provide good products to users, and to help users use these products in the most efficient way.