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Datadog Expands Log Management Offering

Datadog announced new capabilities in its log management suite, which are designed to help organizations optimize logging costs at scale and meet the stringent data retention, auditability and data residency requirements of regulated industries.

Datadog launched Flex Logs in 2023, which has since become one of its fastest-growing products. Flex Logs decouples the costs of log storage from the costs of querying. It provides both short- and long-term log retention for a nominal monthly fee without sacrificing visibility, enabling streamlined correlation between all of an organization’s logs, metrics and traces.

To help companies meet data residency regulations, policies and preferences—while further optimizing cost and efficiency—Datadog has launched new log management capabilities that build on the foundation set by Flex Logs. Datadog’s latest enhancements enable organizations to support modern SIEM and security workflows while maintaining full visibility, cost consciousness and operational efficiency:

  • Archive Search queries logs from customer-owned cold storage without requiring re-indexing. Archived logs can be searched the same way as logs under retention in the Log Explorer without introducing new tools or extra training. Datadog keeps the user experience consistent, regardless of the age of logs.
  • Flex Frozen is a new storage tier extending log retention to over seven years, eliminating the need for managing and securing external archives. Built for audit-heavy, compliance-driven environments, Flex Frozen simplifies data retention by keeping logs inside Datadog in order to reduce overhead, simplify reporting and analytics, and improve accessibility.
  • CloudPrem enables enterprises to deploy Datadog’s indexing and search capabilities within their own infrastructure. Whether it’s due to regional data residency laws or internal compliance mandates, customers can now keep their logs local—while continuing to use the Datadog UI and workflows they trust.

“As compliance standards grow more complex and global data regulations tighten, organizations face mounting pressure to retain log data longer, search it faster and keep it where it belongs,” said Michael Whetten, VP of Product at Datadog. “With today’s launches, Datadog makes it easier to manage logs, control their costs and stay compliant without sacrificing performance, accessibility or the user experience.”

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Datadog Expands Log Management Offering

Datadog announced new capabilities in its log management suite, which are designed to help organizations optimize logging costs at scale and meet the stringent data retention, auditability and data residency requirements of regulated industries.

Datadog launched Flex Logs in 2023, which has since become one of its fastest-growing products. Flex Logs decouples the costs of log storage from the costs of querying. It provides both short- and long-term log retention for a nominal monthly fee without sacrificing visibility, enabling streamlined correlation between all of an organization’s logs, metrics and traces.

To help companies meet data residency regulations, policies and preferences—while further optimizing cost and efficiency—Datadog has launched new log management capabilities that build on the foundation set by Flex Logs. Datadog’s latest enhancements enable organizations to support modern SIEM and security workflows while maintaining full visibility, cost consciousness and operational efficiency:

  • Archive Search queries logs from customer-owned cold storage without requiring re-indexing. Archived logs can be searched the same way as logs under retention in the Log Explorer without introducing new tools or extra training. Datadog keeps the user experience consistent, regardless of the age of logs.
  • Flex Frozen is a new storage tier extending log retention to over seven years, eliminating the need for managing and securing external archives. Built for audit-heavy, compliance-driven environments, Flex Frozen simplifies data retention by keeping logs inside Datadog in order to reduce overhead, simplify reporting and analytics, and improve accessibility.
  • CloudPrem enables enterprises to deploy Datadog’s indexing and search capabilities within their own infrastructure. Whether it’s due to regional data residency laws or internal compliance mandates, customers can now keep their logs local—while continuing to use the Datadog UI and workflows they trust.

“As compliance standards grow more complex and global data regulations tighten, organizations face mounting pressure to retain log data longer, search it faster and keep it where it belongs,” said Michael Whetten, VP of Product at Datadog. “With today’s launches, Datadog makes it easier to manage logs, control their costs and stay compliant without sacrificing performance, accessibility or the user experience.”

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Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...