In the world of IT, availability can mean a lot of things. Your website is available if it is up, responding in a timely manner, sending the correct headers, and serving a valid certificate. Your network is available if the correct hosts are online, responding to ICMP pings, and responding to TCP requests on specific ports. Your API endpoint is available if it returns the correct values when sent specific requests.

Sumo Logic is taking the next step towards Moderate authorization under the Federal Risk and Authorization Management Program (FedRAMP). Today Sumo moved from “Ready” to “In Process” on the FedRAMP Marketplace, an important step toward expanding our ability to serve U.S. governmental agencies. Sumo Logic expects to achieve FedRAMP-Moderate Authorization quickly while working closely with the Federal Trade Commission (FTC) as our agency partner.

Having visibility into your Java application is crucial for understanding how it works right now, how it worked some time in the past and increasing your understanding of how it might work in the future. More often than not, analyzing logs is the fastest way to detect what went wrong, thus making logging in Java critical to ensuring the performance and health of your app, as well as minimizing and reducing any downtime.

Untangling a chaotic mess can be daunting. And that’s exactly the problem Alain Adler, the Head of Engineering at BetterHelp, faced.

Continuous Integration and Continuous Delivery (CI/CD) delivers services fast, effectively, and accurately. In doing so, CI/CD pipelines have become the mainstay of effective DevOps. But this process needs accurate, timely, contextual data if it’s to operate effectively. This critical data comes in the form of logs and this article will guide you through optimizing logs for CI/CD.

Microservice architecture is widely popular. The ease of building and maintaining apps, scaling CI/CD pipelines, as well as the flexibility it offers when it comes to pivoting technologies are some of the main reasons companies like Uber and Netflix are all in on this approach. As the amount of services in a microservice architecture rises, complexity naturally also rises.

The modern enterprise has expanded its reach by using the power of cloud computing. However, with that power comes complexity in leveraging the multiple platforms needed to provide rich functionality. To achieve a seamless integration that involves multiple cloud infrastructures you need insightful and actionable data. You also need the right team to bring the clouds together in a seamless, effective, and efficient manner.

Isn’t all logging pretty much the same? Logs appear by default, like magic, without any further intervention by teams other than simply starting a system… right? While logging may seem like simple magic, there’s a lot to consider. Logs don’t just automatically appear for all levels of your architecture, and any logs that do automatically appear probably don’t have all of the details that you need to successfully understand what a system is doing.

After my last blog around sending Github Data to Splunk via Webhooks, I received a healthy amount of feedback that I want to address here. I learned that (unsurprisingly) a lot of customers are curious about, or dependant on, other cloud platforms out there. In fact, I heard directly from some customers who specifically cannot use any other cloud platforms than one in particular that was not highlighted in my last blog.