Preventing data loss for data in motion is a challenge that LogStream Persistent Queues (PQ) can help prevent when the downstream Destination is unreachable. In this blog post, we’ll talk about how to configure and calculate PQ sizing to avoid disruption while the Destination is unreachable for few minutes or a few hours. The example follows a real-world architecture, in which we have.

It is commonly believed that once data is collected and ingested into a system of analysis, the most difficult part of obtaining the data is complete. However, in many cases, this is just the first step for the infrastructure and security operations teams expected to derive insights.

Shortly before the December holidays, a vulnerability in the ubiquitous Log4J library arrived like the Grinch, Scrooge, and Krampus rolled into one monstrous bundle of Christmas misery. Log4J maintainers went to work patching the exploit, and security teams scrambled to protect millions of exposed applications before they got owned. At Cribl, we put together multiple resources to help security teams detect and prevent the Log4J vulnerability using LogStream.

Here at Cribl, we have a cloud offering of our LogStream product. In building and supporting our cloud product, we have a service-based architecture. And we want to be able to gather metrics from our services, in order to monitor those services and make sure we meet our SLAs.

While I write this blog post, I reflect on the years of being a system administrator and the task of ensuring that no sensitive data made its way past me. What a daunting task right? The idea that sensitive data can make its way through our systems and other tools and reports is terrifying! Not to mention the potential financial/contractual problems this can cause.

Over the last year, we’ve seen tremendous growth in both demand and usage for LogStream Cloud. It is exciting to be able to speed up time to value, reduce the total cost of ownership, and deliver LogStream to customers in a way that best fits their organizational needs. We here at Cribl have been working with our cloud customers to better understand how to optimize LogStream Cloud pricing to provide the best possible ROI.

We see unfriendly customer practices all around in the SIEM space. For example, some major SIEM vendors use an Events Per Second (EPS) license model to monetize access to their tools. Typically, these vendors will drop data above the EPS license or stop data ingestion to incentive license compliance if you run over your EPS license. These license controls disrupt operations and risk enterprise security posture, which can cause chaos.

The recent Apache Log4j vulnerability CVE-2021-44228 dubbed Log4Shell is a big deal. By now there is no shortage of blogs, other write-ups, and analysis about why this vulnerability is an urgent issue and why there is a very good chance it applies to your environment. Here are some of the articles that dive into the gory details on this CVE.

If you read my last blog post, you’re already ahead of the game. You know that in May of 2021, the Biden Administration announced Executive Order (EO) 14028: Improving the Nation’s Cybersecurity, which mandates each federal agency to adapt to today’s continuously changing threat environment. Well, folks, the saga continues.

We’ve all been there. That harrowing moment at the restaurant when the waiter comes to the table and asks that fateful question: “Are you ready to order?” I don’t know about you, but I am almost never ready. Do I want chicken or steak? I’ve eaten a lot of meat this week… Should I opt for fish or a vegetarian option instead? Oh, God. I forgot to check the reviews online. What do other people like the best? Cue heart palpitations.