Elastic announced new features and enhancements across its Elastic Observability solution, enabling customers to gain deeper and more frictionless visibility at all levels of applications, services, and infrastructure.

Innovations across the Elastic Observability solution include:

Providing effortless, deep visibility for cloud-native production environments with zero instrumentation and low overhead, with always-on Universal Profiling

Elastic’s new Universal Profiling capability, now in private beta, provides visibility into how application code and infrastructure are performing at all times in production, across a wide range of languages, in both containerized and non-containerized environments.

Modern cloud-native environments are increasingly complex, creating infrastructure and application blind spots for DevOps and SRE teams. Engineering teams typically use profiling to spot performance bottlenecks and troubleshoot issues faster. However, most profiling solutions have significant drawbacks limiting adoption in production environments:

- Significant cost and performance overhead due to code instrumentation
- Disruptive service restarts
- Inability to get visibility into third-party libraries

Universal Profiling is lightweight and requires zero instrumentation. Enabled by eBPF-based technology, it overcomes the limitations of other profiling solutions by requiring no changes to the application code, making it easier to quickly identify performance bottlenecks, improve time to resolve problems, and reduce cloud costs.

The low overhead of Universal Profiling, less than 1% CPU overhead, makes it possible to deploy in production environments to deliver deep and broad visibility into infrastructure and cloud-native application performance at scale.

For a production application running across a few hundred servers, early results show code optimization savings of 10% to 20% of CPU resources, resulting in cost savings and a reduction of CO2 emissions per year.

Introducing new capabilities to cloud- and developer-first synthetic monitoring

Synthetic monitoring enables teams to proactively simulate user interactions in applications to quickly detect user-facing availability and performance issues and optimize the end-user experience.

Designed to reduce manual and repetitive tasks for development and operations teams, Elastic is introducing the beta of the following innovative synthetic monitoring capabilities available within the current Uptime application for Elastic Cloud customers:

- A cloud-based global testing infrastructure that enables the ability to schedule tests from an expanding global network of synthetic monitors for better visibility into regional variances in user experience.

- Automated creation of synthetic monitors during functional testing when code is released to production. Creating, editing, and deleting synthetic monitors entirely in code reduces the inefficiency of duplicating functional tests.

- Deploying monitoring scripts via CI/CD pipelines to ensure tests and applications are aligned.

- Running synthetics agent locally, making it easier to create and debug monitoring scripts.

- A point-and-click script recorder, enabling non-technical users to quickly create a user journey through an application and turn that into a synthetic monitor. The recorder speeds up the process of creating monitoring scripts for developers by providing a framework that can be edited locally.

Additionally, a new and intuitive user interface to simplify workflows and make it easier to identify and quickly troubleshoot problems in production is currently under development and planned for future availability.

“The capabilities announced today provide deep, frictionless observability into application and infrastructure performance that enable customers to gain even greater value from their data,” said Sajai Krishnan, GM, Observability, Elastic. “Elastic’s continued focus on innovation extends to Universal Profiling, which helps customers understand their application’s CPU consumption hotspots, provides opportunities to optimize applications for real savings in production, plus a reduced carbon footprint.”