Cloud Native ComputingDevelopersDevOpsNewsObservability /Monitoring

Chronosphere’s New Release Adds Query Accelerator, Collections And Workspaces

0

Chronosphere has launched a new release of its cloud native observability platform that includes new capabilities designed to improve cloud native engineering team efficiency by streamlining workflows and speeding up mean time to detection and remediation (MTTD) (MTTR).

The Chronosphere platform takes a new approach to cloud native observability with a reimagined user workflow tailored to the unique ways engineering and DevOps teams work in today’s cloud native environment. Chronosphere’s platform gives customers the tools they need to organize their teams, users, and observability data in order to speed up MTTD and MTTR making engineers’ lives easier and increasing overall productivity.

The new release will be available to all Chronosphere customers and includes the following new capabilities:

Collections and Workspaces – A streamlined workflow that presents the right data in the right context so teams can troubleshoot faster. Too often issue resolution takes too long and relies on institutional knowledge and power users. With Workspaces, users have a global view of all data but can easily zoom in on the data most relevant to the services for which they are responsible.

Query Accelerator – Automatically and continuously scans for slow dashboard queries and augments them with their faster alternative. This capability eliminates the need for engineers to be proficient at writing “good queries.” They can create a query that returns the data they need, and Query Accelerator will ensure that it performs optimally on every dashboard where it is used.

Quotas – Provides teams with an easy way to allocate licensed data capacity amongst teams and services. Quotas gives engineering team leaders a deeper understanding of their data — from its usage to the impact of changes — helping them make better decisions on what data to protect or sacrifice.

Trace metrics – Customers can leverage trace data to define metrics and alerts. This gives users the ability to quickly jump from a trace metric alert to the associated trace data — a powerful tool in the triage process to find where a new error or latency exists, ultimately speeding up remediation times and improving system efficiency.

Don't miss out great stories, subscribe to our newsletter.

Mirantis Discovers Kubernetes Networking Bug

Previous article

Pepperdata Introduces Autonomous Solution For Optimizing Kubernetes Clusters In Public Clouds

Next article
Login/Sign up