A new year with a new look and many more...
Simplified analysis. Enhanced visualizations, alerting capabilities, advanced data forwarding, and more. Great news! We have published a new update with many exciting new features and optimizations.
The latest News and Information on Log Management, Log Analytics and related technologies.
Simplified analysis. Enhanced visualizations, alerting capabilities, advanced data forwarding, and more. Great news! We have published a new update with many exciting new features and optimizations.
You can now use the Cloud Logging datasource plugin to view your logs in Grafana.
Graphite provides time-series metrics in an open-source database. With Graphite dashboards, you can see key performance indicators (KPIs) as well as other metrics visually. Dashboards typically display data as graphs, charts, and tables and can be customized to meet the specific needs of an organization. Using dashboards, organizations can monitor and analyze various aspects of their performance, such as system utilization, application performance, and resource utilization, using web interfaces.
When you’re adding or subtracting fractions, you need to make sure that they have a common denominator, a number that allows you to compare values. In the same way, your IT environment needs a common “language” for your event log data. Your environment consists of various devices running different operating systems, software, and firmware.
The ability to continue business operations for the foreseeable future is a key metric from a financial standpoint. But from a risk management perspective, all dimensions of an organization’s strategic and operational framework must be analyzed in order to… The last part relates to business resilience — and it’s what we’re going to explore here. (This article was written by Joseph Nduhiu. See more of Joseph’s contributions to Splunk Learn.)
Today, businesses are generating more data than ever before. However, with this data explosion comes a new set of challenges, including increased complexity, higher costs, and difficulty extracting value. With this in mind, how can organizations effectively manage this data to extract value and solve the challenges of the modern data stack?