Logz.io is excited to announce the 2020 Cloud Observability Webinar Series focused on DevOps, Open Source, and Observability! It’s certainly harder to attend interesting events in person these days. However, learning the same content you would at meetups and conferences for delivery of more reliable, performant, and secure services shouldn’t have to be. This series will offer a webinar every Wednesday until the end of June.

In this challenging global environment, we realize many of our customers will work from home for the next several weeks. Thankfully, Logz.io is designed to support distributed teams and work environments, and we wanted to highlight some of the ways you can use the platform both for remote monitoring and to collaborate better with your teams over the course of the COVID-19 pandemic.

Most software architects and developers know that they need to monitor their systems. What often prevents them from implementing an effective monitoring solution is the plethora of choices they face. To set up a monitoring solution, you first have to decide what you want to monitor and how you want to monitor it. Then you have to settle for a collection and storage method. Next, you have to implement the interesting metrics in your system and start collecting them.

What is YAML? YAML is a readable data serialization language used frequently in configuration files for software; it stands for “Ain’t Markup Language.” This article will show you samples of YAML files (written .yml or .yaml) for the ELK Stack and other programs commonly used by DevOps team. And while some people love yaml and some hate it, it’s not going away.

Threat intelligence feeds are a critical part of modern cybersecurity. Widely available online, these feeds record and track IP addresses and URLs that are associated with phishing scams, malware, bots, trojans, adware, spyware, ransomware and more. Open source threat intelligence feeds can be extremely valuable—if you use the right ones. While these collections are plentiful, there are some that are better than others.

First things first, why would you want to collect logs from Palo Alto and send them to a Cloud SIEM? There are many reasons. At its core, having a centralized location with a consistent user experience for managing alerts, notifications, and information coming from the technologies securing your environment can provide value in a lot of ways. In this blog, we’ll discuss how to collect, parse, and analyze Palo Alto logs in Logz.io Cloud SIEM, and how it can help secure your cloud workloads.

Kubernetes is the world’s leading container orchestration platform. Its cloud agnostic status enables you to manage your workloads with ease, whether they reside in the cloud or on-premises. It has reduced the necessity of being locked into services provided by a cloud provider as well as the need for an entire operations team to manage large workloads on-premises on virtualization platforms.

Software monitoring allows developers and IT professionals to observe events occurring within a monitored system. The data gathered by monitoring processes offers visibility into how the monitored entity is behaving and provides warning signs indicating that some aspect of the system deserves greater attention. More and more software is migrating to the cloud, and monolithic software is being decomposed into microservices to create distributed applications.

As the team responsible for building dormakaba’s first cloud-access control solution, Exivo, the Cloud Development team at dormakaba AS EMEA needed a logging solution that with scalable logging throughout their global environment, handle a huge amount of throughput, be piped through an API, and remain highly secure so it could be implemented on the doors and entry systems the company produces. Logz.io was the perfect fit for these requirements.

Kinesis is a managed, high-performance and large-capacity service for real time processing of (live) streaming data. Prominent users include Netflix, Comcast and Major League Baseball. Its design to let it grab data from multiple sources at the same time and to scale processing within EC2 instances.