Today we released version 1.5.0 of Loki! This release comes with some really exciting news and a little bit of caution if you operate Loki installations.

DevOps monitoring didn’t simply become part of the collective engineering consciousness. It was built, brick by brick, by practices that have continued to grow and flourish with each new technological innovation. Have you ever been forced to sit back in your chair, your phone buzzing incessantly, SSH windows and half-written commands dashing across your screen, and admit that you’re completely stumped? Nothing is behaving as it should and your investigations have been utterly fruitless.

Application performance monitoring (APM) and logging both provide critical insight into your ecosystem. When paired together with context, they can provide vital clues on how to resolve problems with your applications. As the log data you analyze becomes more complex, navigating to the relevant pieces can be tricky using traditional tools. With Elastic Observability (powered by the Elastic Stack), correlating logs with APM is as simple as a few clicks in Kibana.

Today we are officially releasing Graylog v3.3 This release includes enhancements to search, events, and alerts that introduce greater efficiencies to your daily log management efforts and strengthen your audit and compliance capabilities. Please read on for detailed descriptions of each feature.

IDG’s recent “State of the CIO” survey across IT leaders has revealed the impact of COVID-19 on IT organizations and the sudden and unforeseen shifts of their initial 2020 plans.

Computing environments are constantly changing. Back when an on-premises server hosted your work, your infrastructure and applications were easy to track. Now that you’re developing in the cloud, things are more challenging. You’re learning that each team within your organization uses a different monitoring tool. At this point, you may be wondering if it’s time to build your own monitoring solution with open source tools at its core that everyone can use.

Here at Sumo Logic, we share a lot of thoughts about managing data at scale, and the innovative ways we help customers address their unique use cases. It’s not just about analysis of logs. In this article, I will talk about another important observability signal: distributed traces. I will share a few observations about how we at Sumo think about the future of adoption of distributed traces, a very important concept, taking from our own experience.

Everyone at Splunk is very proud of the amazing things that our customers and partners do with their data. It is always extra special when one of those organisations is really doing good and looking after us all in our daily lives. I’m delighted to share one of those stories from the Derbyshire Fire & Rescue Service (DFRS) who is using Splunk as its data-driven SIEM.

One of the great things about developing for Splunk Security Essentials is that most of the features and capabilities are requested from customers and the security community. In this latest release (3.1), we added a feature that has been requested frequently: the ability to filter the ATT&CK Matrix for Cloud and SaaS Techniques. The MITRE ATT&CK Framework consists of multiple matrices such as Enterprise, Mobile, and ICS.

We're excited to announce that the Splunk Machine Learning Toolkit (MLTK) version 5.2 is available for download today on Splunkbase! Earlier this month, I discussed how the release of version 5.2 will make machine learning more accessible to more users. Splunk’s MLTK lets our customers apply machine learning to the data they're already capturing in Splunk, develop models, and operationalize these algorithms to glean new insights and make more informed decisions.