The control plane and the data plane are two key components of a network, each facilitating the flow of network packets, and each with its own set of functions and responsibilities. Understanding the differences between these two planes helps you design and optimize networks for improved performance, scalability, and security. This article will explore the control and data planes, including their functionalities, fundamental differences and use cases.

Data has become an essential asset for businesses, driving innovation, improving decision-making, and shaping the future. But how does one effectively manage this valuable resource? This is where Data Lifecycle Management (DLM) comes in — a comprehensive approach to managing data throughout its lifecycle. This blog post will guide you through the ins and outs of DLM, its key stages, benefits, and the tools and technologies that enable successful implementation. Let's dive in!

When working with sensitive data, there’s no skimping on security. Keeping data protected and private is paramount at Cribl, which is why we prioritized building a robust framework for Role-Based Access Control (RBAC), and with this latest release, we created an authorization system across the entire Cribl suite. WOOHOO!!

In today’s rapidly evolving digital landscape, organizations heavily rely on their applications and systems to deliver optimal performance. As such, driving down the key metric of Mean Time to Resolution (MTTR) is clearly one of the biggest challenges facing observability practitioners today.

Imagine your company relies on inaccurate data to drive its strategies, only to realize too late that the information needed to be revised. The consequences could be devastating — missed opportunities, incorrect forecasts, and damaged customer relationships. But by monitoring data, you can understand your company's digital ecosystem comprehensively, make informed decisions, optimize processes, and mitigate risks effectively.

Government and education leaders estimate that data volume at their organizations will increase by 59% over the next three years. Although having more information than you need is (arguably) better than not having it when you need it, the sheer volume of data can make it challenging for teams to pinpoint exactly what data will bring value to their mission goals.

With thousands of logs generated every minute from your infrastructure, applications, services, and devices, retaining this copious amount of data for active search and analysis can be cost-prohibitive. Because log volumes continue to grow rapidly as operations scale, it’s common for organizations to implement log management strategies and store only a limited number to minimize costs.

Digital Experience Monitoring (DEM) is a practice that involves monitoring and analyzing the end-to-end digital experience of users interacting with websites, applications, and other digital services. By examining performance, availability, and usability from the end user’s perspective, DEM provides insights into the performance, availability, and usability of these services from the perspective of the end user.

Organizations use the cloud for scalable computing and storage solutions to meet their changing business needs. However, another deployment model is quickly growing in popularity: edge computing. In fact, Gartner estimates that 75% of enterprise-generated data will originate and be processed at the edge by 2025.

As companies embrace containers, microservices, and complex architectural components, systems have grown more and more distributed and unpredictable, increasing the unknown unknowns. How can organizations remain efficient and effective in this type of intricate environment? With observability-driven development.