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Datadog Introduces Online Archives

Datadog announced the release of Online Archives, an always-on log warehousing solution that provides 15 months or more of extremely cost-effective storage and live query capabilities.

Security, compliance and engineering teams often require access to data over an extended period of time. For example, it can take weeks, if not months, for a security breach to be detected. Legal compliance reviews and audit processes may require log information stretching back more than a year, and engineering teams conducting post-mortem analysis or troubleshooting support issues may need to look back at log data from many months prior to the incident itself. Yet, to date, many organizations have not been able to interact with their data for more than a few weeks because of the prohibitive cost and complexity of doing so.

With Online Archives, organizations will now be able to retain and search all of their log data for 15 months, for the same price as it currently costs to index data for one month. With the option of Indexing and Online Archives, teams will be able to continue using indexes for real-time log streaming and alerting scenarios and use Online Archives for situations requiring historical investigation and analysis, like security audits. Online Archives also enables organizations to analyze extra high-cardinality trends over long time periods and correlate system forensics from metrics with application and user behavior from log data.

“As Datadog continues to expand its log management support for larger customers, the complexity of their needs is increasing as well. With Online Archives, we saw the opportunity to develop a solution that would break down silos even during their most complex investigations,” said Michael Whetten, Director of Product Management, Datadog. “Online Archives provides a truly collaborative historical investigation and analysis platform for our customers that’s responsive enough for interactive investigations, without sacrificing their budget.”

Online Archives delivers:

- Long-term archival with live query capabilities: access and search all of your log data for 15 months or more

- Historical investigations: easily view log data in context, correlated with historic metrics and trace data

- Variable query capacity: scale your query capacity up or down to reflect the urgency of your searches or dynamically allocate higher-access priority to some teams

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Datadog Introduces Online Archives

Datadog announced the release of Online Archives, an always-on log warehousing solution that provides 15 months or more of extremely cost-effective storage and live query capabilities.

Security, compliance and engineering teams often require access to data over an extended period of time. For example, it can take weeks, if not months, for a security breach to be detected. Legal compliance reviews and audit processes may require log information stretching back more than a year, and engineering teams conducting post-mortem analysis or troubleshooting support issues may need to look back at log data from many months prior to the incident itself. Yet, to date, many organizations have not been able to interact with their data for more than a few weeks because of the prohibitive cost and complexity of doing so.

With Online Archives, organizations will now be able to retain and search all of their log data for 15 months, for the same price as it currently costs to index data for one month. With the option of Indexing and Online Archives, teams will be able to continue using indexes for real-time log streaming and alerting scenarios and use Online Archives for situations requiring historical investigation and analysis, like security audits. Online Archives also enables organizations to analyze extra high-cardinality trends over long time periods and correlate system forensics from metrics with application and user behavior from log data.

“As Datadog continues to expand its log management support for larger customers, the complexity of their needs is increasing as well. With Online Archives, we saw the opportunity to develop a solution that would break down silos even during their most complex investigations,” said Michael Whetten, Director of Product Management, Datadog. “Online Archives provides a truly collaborative historical investigation and analysis platform for our customers that’s responsive enough for interactive investigations, without sacrificing their budget.”

Online Archives delivers:

- Long-term archival with live query capabilities: access and search all of your log data for 15 months or more

- Historical investigations: easily view log data in context, correlated with historic metrics and trace data

- Variable query capacity: scale your query capacity up or down to reflect the urgency of your searches or dynamically allocate higher-access priority to some teams

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In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...