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Chronosphere Launches New Release of Cloud Native Observability Platform

Chronosphere 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.

"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.

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Chronosphere Launches New Release of Cloud Native Observability Platform

Chronosphere 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.

"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.

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Payment system failures are putting $44.4 billion in US retail and hospitality sales at risk each year, underscoring how quickly disruption can derail day-to-day trading, according to research conducted by Dynatrace ... The findings show that payment failures are no longer isolated incidents, but part of a recurring operational challenge that disrupts service, damages customer trust, and negatively impacts revenue ...

For years, the success of DevOps has been measured by how much manual work teams can automate ... I believe that in 2026, the definition of DevOps success is going to expand significantly. The era of automation is giving way to the era of intelligent delivery, in which AI doesn't just accelerate pipelines, it understands them. With open observability connecting signals end-to-end across those tools, teams can build closed-loop systems that don't just move faster, but learn, adapt, and take action autonomously with confidence ...

The conversation around AI in the enterprise has officially shifted from "if" to "how fast." But according to the State of Network Operations 2026 report from Broadcom, most organizations are unknowingly building their AI strategies on sand. The data is clear: CIOs and network teams are putting the cart before the horse. AI cannot improve what the network cannot see, predict issues without historical context, automate processes that aren't standardized, or recommend fixes when the underlying telemetry is incomplete. If AI is the brain, then network observability is the nervous system that makes intelligent action possible ...

SolarWinds data shows that one in three DBAs are contemplating leaving their positions — a striking indicator of workforce pressure in this role. This is likely due to the technical and interpersonal frustrations plaguing today's DBAs. Hybrid IT environments provide widespread organizational benefits but also present growing complexity. Simultaneously, AI presents a paradox of benefits and pain points ...

Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

In MEAN TIME TO INSIGHT Episode 20, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA presents his 2026 NetOps predictions ... 

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment ...

My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

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