Although AWS Lambda is a blessing from the infrastructure perspective, while using it, we still have to face perhaps the least-wanted part of software development: debugging. In order to fix issues, we need to know what is causing them. In AWS Lambda that can be a curse. But we have a solution that could save you dozens of hours of time. TL;DR: Dashbird offers a shortcut to everything presented in this article.

Three years ago, when we released Embedded Views into beta, we were excited to enable customers to share log lines in a customized way outside of our web application. However, it's become clear that the vast majority of our users prefer having the full functionality of our web application when exploring their logs rather than using an Embedded View.

This post’s mission is to answer what seems to be a simple question: “What is log analysis?” It doesn’t seem too hard to answer, right? Obviously from the name log analysis is the process of analyzing log entries. Case closed? Can we finish the post here? Well, not so fast.

If you’re a product on the web, you have less than a second to impress your customers. Web application performance is crucial to the success of online products. Using a Content Delivery Network (CDN) like Cloudflare can provide just the edge you need.

Let’s say you get an alert that one or more queries is slow. Or that your users complain, whichever comes first 🙂 We’ve all been there… How do you find the root cause for this slowness and then fix it? In this article, I’ll go through my usual thought process: first, I’d try to find which queries are slow. Then, I’d dig deeper: Let’s take a specific example and run through each step.

A couple of days ago, Elastic announced that it will change the licensing of Elasticsearch and Kibana as of the 7.11 release to a proprietary dual license (under the SSPL license) and away from the open-source Apache-2.0 license. This move has caused extensive turmoil and frustration in the open-source community, especially with organizations that rely on Elasticsearch. Let me start with the end in mind.

As the Trump Administration comes to a close, there is no better time than the present to reexamine the Department of Defense Digital Modernization Strategy and its potential sustainment beyond January 2021.

Centralized Log Management offers the visibility you need to optimize your cloud usage to keep infrastructure costs down. Cloud-first infrastructures are the future of modern business operations. As organizations like Google and Twitter announce long-term plans for enabling a remote workforce, maintaining a competitive business model includes scaled cloud services adoption. While the cloud offers scalability that can save money with pay-as-you-need services, managing the costs is challenging.

Network security has changed a lot over the years, it had to. From wide open infrastructures to tightly controlled environments, the standard practices of network security have grown more and more sophisticated. This post will take us back in time to look at the journey that a typical network has been on over the past 15+ years. From a wide open, “chewy” network, all the way to zero trust networking. Let’s get started.

In a previous post, we explored the basic concepts behind using Grok patterns with Logstash to parse files. We saw how versatile this combo is and how it can be adapted to process almost anything we want to throw at it. But the first few times you use something, it can be hard to figure out how to configure for your specific use case.