One of the key performance indicators of any system, application, product, or process is how certain parameters or data points perform over time. What if you want to monitor hits on an API endpoint or database latency in seconds? A single data point captured in the present moment won’t tell you much by itself. However, tracking that same trend over time will tell you much more, including the impact of change on a particular metric.

Boston and Tel Aviv–July 19, 2018–Logz.io, the leading provider of AI-powered log analysis, announces the release of its intelligent log analysis platform on Amazon Web Services (AWS) Marketplace. The Logz.io platform is the first and only ELK solution offered on the AWS Marketplace, giving AWS customers worldwide access to powerful capabilities for extracting actionable insights from machine data.

Kubernetes is developing so rapidly, that it has become challenging to stay up to date with the latest changes (Heapster has been deprecated!). The ecosystem around Kubernetes has exploded with new integrations developed by the community, and the field of logging and monitoring is one such example.

Request tracing is the ultimate insight tool. Request tracing tracks operations inside and across different systems. Practically speaking, this allows engineers to see the how long an operation took in a web server, database, application code, or entirely different systems, all presented along a timeline. Request tracing is especially valuable in distributed systems where a single transaction (such as “create an account”) spans multiple systems.

Elasticsearch 6.3 included some major new features, including rollups and Java 10 support, but one of the most intriguing additions in this version is SQL support.

As an open-source system for automating deployment, scaling, and management of containerized applications, Kubernetes has grown immensely in popularity. Increasingly, we are also beginning to come across platforms offering Kubernetes as both a hosted and managed service.

Companies today can’t afford to have an application succumb to a spike in traffic or fail due to an overload of user requests. Two of the key benefits of cloud computing today are elasticity and scalability, both of which help ensure an application’s optimal performance.

We all like a pretty dashboard. For us data nerds, there’s something extremely enticing about the colors and graphs depicting our environment in real-time. But while Kibana and Grafana bask in glory, there is a lot of heavy lifting being done behind the scenes to actually collect the data.

With millions of downloads for its various components since first being introduced, the ELK Stack is the world’s most popular log management platform. In contrast, Splunk — the historical leader in the space — self-reports 15,000 customers total. But what exactly is ELK, and why is the software stack seeing such widespread interest and adoption? Let’s take a deeper dive.

Kibana 6.3 was released a few weeks ago, together with new versions of Elasticsearch, Logstash and Beats, and despite the fact that this was not a major release, the new capabilities included in this version definitely deserve a close look.