The latest News and Information on Log Management, Log Analytics and related technologies.
This post is part of a blog series highlighting how we embrace the solutions and features of the Elastic Stack to support our business and drive customer success. The Elastic InfoSec Security Engineering team is responsible for deploying and managing InfoSec's infrastructure and tools. At Elastic, speed, scale, and relevance is our DNA and leveraging the power of the Elastic Stack is the heart of InfoSec.
LogQL, the Loki query language, is heavily inspired by Prometheus PromQL. However, when it comes to filtering logs and finding the needle in the haystack, the query language is very specific to Loki. In this article we’ll give you all the tips to create fast filter queries that can filter terabytes of data in seconds. In Loki there are three types of filters that you can use.
When approached by stakeholders in their organization, few security teams can confidently demonstrate that logging and alerting capabilities are working as expected. Organizations have become more distributed and reliant on cloud offerings for use cases such as identity and access management, user productivity, and file storage. Meanwhile, adversaries have extended their operational capabilities in cloud environments.
Monitoring and analytics have been an issue for Serverless systems since they were invented. While it’s easy to attach an agent like NewRelic or DataDog to a server or container, function monitoring requires a different approach. Serverless applications, where logic is distributed over a large number of functions, attaching agents or wrappers leads to cost increase and development overhead.
