The more customers I talk to, the more I see a trend toward wanting a low-cost vendor-agnostic data lake. Customers want the freedom to store their data long-term and typically look to object stores from AWS, Azure, and Google Cloud. To optimize for data access, users will partition their data into directories to optimize for use cases such as Cribl Replay and Cribl Search. Only relevant files will be accessed for rehydration or search by partitioning data.

The Cribl Syslog source is our most commonly used input type. Cribl Stream can act as your edge and/or central syslog server, giving you more capability while easing management tasks. In this blog post we’ll go over a brief history of syslog. Then we’ll dive into best practices for standing up Cribl Stream as a syslog server, tuning the server, and other tips for running a high performance syslog platform.

In today’s digital era, data has become an integral part of every organization. The exponential growth of data continues to accelerate, with projections indicating a compound annual growth rate of 28% for data creation. While this surge in data presents vast opportunities, it also brings substantial challenges in terms of management and value extraction. This is where the concept of a data engine comes in. It serves as the core of your data infrastructure, functioning like a central nervous system.

Cloud migration has become a crucial strategy for businesses aiming to capitalize on scalability, flexibility, and cost-saving opportunities. As organizations transition from traditional data centers to cloud infrastructure, these companies can access advanced cloud services, enhance operational efficiency, and ensure seamless data and application management. However, cloud migration challenges can be difficult to solve.

We’re already halfway through 2024, and thus far, it’s been an eventful year: Swifties won the Super Bowl, CriblCon happened at not the real Caesar’s Palace, and we witnessed both a solar eclipse and a Drake diss track. Whether you’re a long-time Cribl customer or are new to our Community, we want to make sure you’re always informed of what’s the latest and greatest with Cribl’s suite of products.

We’ve all been there, cursing the “network” when a service fails to load as expected. Even with my 1.5Gbps fiber connection, there are many reasons why the “network” can be blamed. And, yes, I intentionally put the word network in quotes because the network is more than the speed of the network link.

In modern network systems, managing data flow efficiently is critical, especially when dealing with high volumes of log data. One common challenge for IT teams is the bottleneck caused by Syslog TCP pinning, where a limited number of persistent TCP connections lead to throughput inefficiencies. This blog explores the concept of TCP pinning in depth, discussing its implications on network performance and detailing strategies to alleviate these bottlenecks through innovative load balancing techniques.

We know endpoints can be endless and that you need an efficient, simple way to collect data from all of them— no matter the size of your environment. This is why, in the 4.7 release, our engineering team has worked hard to expand Cribl Edge’s scalability to support 250,000 Edge nodes!!!

Data storage has come a long way. It’s impossible to imagine having to search racks of tape reels for specific datasets, and the same is happening for archival storage. This type of storage is very low cost, but the tradeoff is the data isn’t readily available, often requiring 24 hours or more to convert, thaw, and be in a usable format. But what if you could have your cake and eat it, too? Low-cost archival storage AND instant access to your data?

Would that make a difference? Of course it would!