Whether you capture them for application security and compliance, production monitoring, performance monitoring, or troubleshooting, logs contain valuable information about the health of your apps. But it all comes down to what and how you log, which is where log management tools come into play.

Delivering value to customers quickly and efficiently is critical to the success of modern businesses. Understanding the process and timeframe during which an organization generates new ideas and then designs, develops and deploys them is vital to success. At the recent Illuminate User Conference, Drew Horn, Director of Business Development, held a discussion with Clara Ko, Director of Engineering at Sauce Labs, and Bryan Veselka, Director and Product Owner for Cloud and Automation at Vizient.

If you’re like most organizations, you’re leveraging Jenkins for all sorts of things. Deployment pipelines, automated API tests, even glorified CRON jobs just to name a few.

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.

Recently, I wrote an article titled Life Cycle Monitoring: Why an Ounce of Prevention Is Worth a Pound of a Cure. The great Benjamin Franklin coined the term. In the article, I highlighted the value, efficiency, and logic of putting more time into a proper capacity planning and optimization process for all types of IT environments. Most IT professionals would tell you the first thing that comes to their mind when asked how they use log management tools is troubleshooting.

When your Elasticsearch cluster ingests data, it needs to understand how the data is constructed. To do this, your Elasticsearch cluster undergoes a process called mapping. Mapping involves defining the type for each field in a given document. For example, a number or a string of text. But how do you know the health of the mapping process? And why do you need to monitor it? This is where mapping statistics come in. Mapping statistics give you an overall view of the mapping process.

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.

Chris Steffen is a research director for information security at Enterprise Management Associates. EMA is a leading analyst and consulting firm that prides itself on going beyond the surface to provide deep insights about the IT industry. I'm Liesse from LogDNA. Before we dive in, I just wanted to take a moment to thank all of you for tuning in to season one of DevOps State of Mind.

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.

Legacy logging solutions simply couldn’t keep up with the complex, hyperconverged regional infrastructure at Civo, a Kubernetes service provider that enables users to launch k8s clusters within 90 seconds. “With our infrastructure and application deployment getting more complex and more distributed, we needed our logging solution and our entire observability stack to scale up with our needs,” said Anaïs Urlichs, Site Reliability Engineer at Civo.