Modern enterprises are more dependent than ever on data. That's why it's more important than ever for organizations to ensure that their data is accurate, reliable, and easily accessible. Data observability is a modern method that helps achieve this. It involves real-time monitoring of data to detect unusual patterns. By doing so, it ensures data quality and reliability, which boosts operational efficiency and governance.

Integrating MQ monitoring into a newly modernized mainframe environment isn’t something you can just wing. We’ve worked on projects where it seemed straightforward at first—just plug in some monitoring tools and you’re good to go, right? Not quite. The reality is, if you don’t approach this with a plan, you’ll find yourself tangled in a web of configuration headaches and performance hiccups.

Most load balancers only check a client certificate when the client first connects. However, this can be problematic if a client stays connected for an extended period of time. Staying connected would allow clients to continually send and receive data. Imagine you have an employee whose certificate and key were stolen by an adversary. If you are using TLS client authentication, that adversary can connect to your infrastructure and maintain illegal access.

Data quality testing is a subset of data observability. It is the process of evaluating data to ensure it meets the necessary standards of accuracy, consistency, completeness, and reliability before it is used in business operations or analytics. This involves validating data against predefined rules and criteria, such as checking for duplicates, verifying data formats, ensuring data integrity across systems, and confirming that all required fields are populated.

In 2024, an interconnected network is a must-have. Here’s how to get one and supercharge your business operations. Globally distributed networks, remote workforces, multicloud architectures – all of these setups have something important in common (besides the fact they’re the norm now). They all leverage multiples to maximize business benefits. Multiple locations, multiple endpoint types, multiple cloud providers.

Creating a positive user experience is always one of the most important goals our teams focus on. Whether it’s administrators working behind the scenes on the platform, or users looking to uncover cost savings opportunities in Explorer, or engineers working with our APIs, we always strive to provide a frictionless experience making sure each person has the right information to achieve their goals in our platform.

AWS MediaTailor provides a wealth of information via metrics, but one key feature that is very difficult to track is the Transcoding performance. What is transcoding and why is performance important?

This month I continued adding features to OnlineOrNot's status page functionality, while also taking the time to fix bugs, and add an integration for Pingdom.

As the Managed Service Provider (MSP) landscape continues to evolve, developing a robust MSP monitoring strategy is essential for MSPs wanting to stay ahead in an increasingly complex digital environment.Rapid advancements in technology, coupled with the growing complexity of IT environments, necessitates a shift in how MSPs approach monitoring. The fiercely competitive MSP market and external pressures on costs such as cloud pricing mean that customer expectations are high but profit margins slim.

Designed in the early 1990s Python was built to emphasize code readability and on the principle that there should be one way to do things. Python is one of the most popular programming languages and is utilized for a range of purposes including machine learning, web applications, and data analysis.