Dynatrace

MAY 28, 2024

Logs provide answers, but monitoring is a challenge Manual tagging is error-prone Making sure your required logs are monitored is a task distributed between the data owner and the monitoring administrator. Often, it comes down to provisioning YAML configuration files and listing the files or log sources required for monitoring. This manual, error-prone approach can lead to monitoring gaps, which become critical when a host or service has an outage or incident.

Analytics 195

Analytics Infrastructure Database Monitoring 195

DZone

MAY 28, 2024

An encrypted home directory is typically used to protect a user's personal data by encrypting the contents of their home directory. This directory is only decrypted and mounted when the user logs in, providing an extra layer of security.

147

147

Percona

MAY 28, 2024

Running and managing MongoDB clusters in Kubernetes is made easy with the Percona Operator for MongoDB. Some aspects are just easy to grasp as they are well defined in the operator custom resources and documentation, but some are often considered to be a hidden craft.

Servers 96

Servers Network Cloud Software 96

DZone

MAY 28, 2024

With the complexity of modern software applications, one of the biggest challenges for developers is simply understanding how applications behave. Understanding the behavior of your app is key to maintaining its stability, performance, and security. This is a big reason why we do application logging : to capture and record events through an application’s lifecycle so that we can gain valuable insights into our application.

Software 130

Software Software Systems Performance 130

Percona

MAY 28, 2024

In this blog post, we are going to implement the concept of sharding in a Valkey setup. This is a built-in feature and can be implemented by enabling clustering in the Valkey configuration.Sharding, in general, helps in distributing/scaling application writes over multiple nodes. In a similar fashion, it works in Valkey.

Servers 87

Servers Development Software Software 87

DZone

MAY 28, 2024

At a high level, bad data is data that doesn’t conform to what is expected. For example, an email address without the “ @ ”, or a credit card expiry where the MM/YY format is swapped to YY/MM. “Bad” can also include malformed and corrupted data, such that it’s completely indecipherable and effectively garbage. In any case, bad data can cause serious issues and outages for all downstream data users, such as data analysts, scientists, engineers, and ML and AI practitioners.

Engineering 130

Engineering 130