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Datadog Releases IT Event Management

Datadog announced the general availability of IT Event Management to its suite of AIOps capabilities.

With Event Management, Datadog intelligently consolidates, correlates and enriches all alert events and important signals from Datadog and existing third-party observability tools into one consistent view. This process reduces alert fatigue so teams can focus their time and resources on remediating issues.

Datadog's AIOps capabilities enable teams to proactively identify underlying causes, reduce noise with intelligent event correlation and take action sooner. By integrating Datadog's IT service management offerings into a customer's existing ecosystems, Event Management enhances responders' ability to triage quickly with intelligent correlation, deduplication and enrichment of events with observability context across all services and applications. This gives operations teams a complete picture of underlying causes so they can respond to and remediate issues.

"The volume of incoming alerts and events can quickly become untenable as systems grow in scale and complexity, making it increasingly difficult for teams to prioritize which issues require immediate attention and to summarize and route them to the necessary teams," said Michael Whetten, VP of Product at Datadog. "Event Management addresses this challenge by automatically reducing the massive volume of events and alerts into actionable signals that can generate tickets, call an incident or trigger an automated remediation through our Workflows product. With the release of Event Management, Datadog now offers a robust AIOps solution that helps operations teams automate remediation, intelligently and proactively prevent outages, and reduce the impact of an incident."

With the addition of Event Management, Datadog's AIOps capabilities help organizations to:

- Unify Alert Data: Aggregate alerts and change events from third-party tools and Datadog into one case view to break down tool sprawl and simplify investigations.

- Enrich Events with Context: Automatically enrich ingested events with business-specific data from a configuration management database or operational spreadsheet, and normalize events with consistent tagging or create new tags for enhanced AIOps best practices.

- Correlate Events Intelligently: Enable teams to focus on what's really important with intelligent correlation powered by AI that helps relieve alert fatigue and reduce duplicative efforts.

- Accelerate Remediation: Automate triage workflows and reduce investigation time by escalating and prioritizing cases, creating tickets in the preferred IT Service Management tool or automating notifications to triage alongside observability context for accelerated discovery.

Event Management is now generally available.

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Datadog Releases IT Event Management

Datadog announced the general availability of IT Event Management to its suite of AIOps capabilities.

With Event Management, Datadog intelligently consolidates, correlates and enriches all alert events and important signals from Datadog and existing third-party observability tools into one consistent view. This process reduces alert fatigue so teams can focus their time and resources on remediating issues.

Datadog's AIOps capabilities enable teams to proactively identify underlying causes, reduce noise with intelligent event correlation and take action sooner. By integrating Datadog's IT service management offerings into a customer's existing ecosystems, Event Management enhances responders' ability to triage quickly with intelligent correlation, deduplication and enrichment of events with observability context across all services and applications. This gives operations teams a complete picture of underlying causes so they can respond to and remediate issues.

"The volume of incoming alerts and events can quickly become untenable as systems grow in scale and complexity, making it increasingly difficult for teams to prioritize which issues require immediate attention and to summarize and route them to the necessary teams," said Michael Whetten, VP of Product at Datadog. "Event Management addresses this challenge by automatically reducing the massive volume of events and alerts into actionable signals that can generate tickets, call an incident or trigger an automated remediation through our Workflows product. With the release of Event Management, Datadog now offers a robust AIOps solution that helps operations teams automate remediation, intelligently and proactively prevent outages, and reduce the impact of an incident."

With the addition of Event Management, Datadog's AIOps capabilities help organizations to:

- Unify Alert Data: Aggregate alerts and change events from third-party tools and Datadog into one case view to break down tool sprawl and simplify investigations.

- Enrich Events with Context: Automatically enrich ingested events with business-specific data from a configuration management database or operational spreadsheet, and normalize events with consistent tagging or create new tags for enhanced AIOps best practices.

- Correlate Events Intelligently: Enable teams to focus on what's really important with intelligent correlation powered by AI that helps relieve alert fatigue and reduce duplicative efforts.

- Accelerate Remediation: Automate triage workflows and reduce investigation time by escalating and prioritizing cases, creating tickets in the preferred IT Service Management tool or automating notifications to triage alongside observability context for accelerated discovery.

Event Management is now generally available.

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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...