Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Chronosphere Launches New Release of Its Cloud Native Observability Platform

Chronosphere, the only cloud native observability platform that puts engineering organizations back in control by taming rampant data growth and cloud native complexity, announced it 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).

Companies are aggressively adopting cloud native workflows, infrastructure and applications, creating explosive data growth that makes observability challenging at best and impossible at worst. In fact, according to an upcoming report from Chronosphere, 87% of companies agree that using cloud native architectures has increased the complexity of discovering and troubleshooting incidents.

Recommended AI: Eric Tippetts Announces Version 3.0 of Innovative Network Marketing App

The majority of observability tools available today do not support cloud native organizations or those on the path to a cloud native future, and were not designed to fit into the evolving workflows of modern engineering teams.  An upcoming report from Chronosphere found that engineers waste more than 10 hours on average per week trying to triage and understand incidents when they could be contributing more time to achieving key business outcomes. 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.

Related Posts
1 of 40,672

“Great observability is not about having more data — its about having the right data, in the right context at the right time.” said Martin Mao, Co-founder and CEO of Chronosphere. “The new release of Chronosphere was designed to work alongside engineers, enabling them to prioritize the data that is most important to them. All of the capabilities built into our platform, from trace metrics to collections and workspace dashboards, lead back to our mission of increasing the productivity of engineering teams and in turn, reducing burnout ”

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.

Recommended AI: Understanding the Role of AI in Gaming

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.