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Datadog Launches Workflow Automation

Datadog announced the general availability of Workflow Automation.

The new product enables teams to automate end-to-end remediation processes—with out-of-the-box actions and pre-built templates—across all systems, apps and services to help identify, investigate and resolve service disruptions and security threats faster.

Workflow Automation combines alerts and remediation in a single, streamlined solution. Datadog provides developers and security engineers end-to-end visibility across the tech stack so that teams are alerted to disruptions as they arise. Now, with Workflow Automation, teams can use context-rich alerts to automate entire remediation processes across their tools and services in response to disruptions directly in Datadog's unified platform. By giving teams the ability to both observe the entire tech stack in a single platform and also remediate any issues directly in the same place, Workflow Automation helps organizations maintain the availability of their systems.

"Manual processes and context switching are often the root cause of long stretches of IT downtime. This impacts both a company's bottom line and its reputation with end users," said Michael Gerstenhaber, VP of Product at Datadog. "Workflow Automation provides the automation and context that DevOps, SRE and security teams need in order to remediate issues quickly. Automation that seamlessly connects observability information with remediation allows engineers to proactively respond to insights before they turn into issues that would otherwise affect their businesses."

Workflow Automation enables organizations to:

- Trigger Responses Instantly: Users can automatically trigger responses from observability alerts, security signals and dashboards. These response workflows can be enriched with real-time observability data, such as logs and metrics, that guide automated decision-making. This allows teams to identify, investigate and resolve service disruptions and security threats quickly while proactively maintaining the health of systems.

- Automate Complex Processes: Over 300 out-of-the-box actions and more than 40 pre-built templates enable users to easily automate routine response tasks and complex end-to-end processes to save engineers time, eliminate human error and reduce overhead.

- Safeguard Automation: Teams can create interactive, human-in-the-loop workflows, and safeguard these workflows with granular role-based access control (RBAC) while keeping track of executions with detailed workflow auditing.

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Datadog Launches Workflow Automation

Datadog announced the general availability of Workflow Automation.

The new product enables teams to automate end-to-end remediation processes—with out-of-the-box actions and pre-built templates—across all systems, apps and services to help identify, investigate and resolve service disruptions and security threats faster.

Workflow Automation combines alerts and remediation in a single, streamlined solution. Datadog provides developers and security engineers end-to-end visibility across the tech stack so that teams are alerted to disruptions as they arise. Now, with Workflow Automation, teams can use context-rich alerts to automate entire remediation processes across their tools and services in response to disruptions directly in Datadog's unified platform. By giving teams the ability to both observe the entire tech stack in a single platform and also remediate any issues directly in the same place, Workflow Automation helps organizations maintain the availability of their systems.

"Manual processes and context switching are often the root cause of long stretches of IT downtime. This impacts both a company's bottom line and its reputation with end users," said Michael Gerstenhaber, VP of Product at Datadog. "Workflow Automation provides the automation and context that DevOps, SRE and security teams need in order to remediate issues quickly. Automation that seamlessly connects observability information with remediation allows engineers to proactively respond to insights before they turn into issues that would otherwise affect their businesses."

Workflow Automation enables organizations to:

- Trigger Responses Instantly: Users can automatically trigger responses from observability alerts, security signals and dashboards. These response workflows can be enriched with real-time observability data, such as logs and metrics, that guide automated decision-making. This allows teams to identify, investigate and resolve service disruptions and security threats quickly while proactively maintaining the health of systems.

- Automate Complex Processes: Over 300 out-of-the-box actions and more than 40 pre-built templates enable users to easily automate routine response tasks and complex end-to-end processes to save engineers time, eliminate human error and reduce overhead.

- Safeguard Automation: Teams can create interactive, human-in-the-loop workflows, and safeguard these workflows with granular role-based access control (RBAC) while keeping track of executions with detailed workflow auditing.

The Latest

For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

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 ...