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LogDNA Introduces Variable Retention

LogDNA announced early access for Variable Retention.

This new capability allows companies to better control spend by storing different types or sources of logs for different lengths of time.

Modern infrastructure and applications generate massive amounts of data—sometimes petabytes worth of log data in a single day. Many teams need access to this data to gain critical insights into their services, but logging can get expensive, fast, and companies are forced to make difficult trade-offs that reduce observability and heighten risk. As a result, teams may not have the granular log data needed to form a complete picture during an incident or troubleshooting workflow. Variable Retention gives users the flexibility to save logs within the platform only for the amount of time that they're relevant, ensuring teams get access to the data they need, when they need it, while keeping costs in check.

“Different organizational and business functions need varying amounts and periods of data, but cost concerns drive sacrifices on what to keep and force dollar-driven decisions that diminish the value of all that data,” said Tucker Callaway, CEO, LogDNA. “Variable Retention gives LogDNA users control, removing friction that impacts how autonomous teams use log and other machine data to be more efficient and secure. Now, teams don’t have to choose between a reasonable logging bill and comprehensive observability data.”

Within the LogDNA user interface, customers select a subset of logs to store for different retention periods based on their needs—for instance, 30 days for security logs but only seven days for quality assurance and testing logs. When these rules are in place, users can monitor how their logging volume is distributed across different tiers in their usage dashboard to ensure the appropriate logs are being put in their respective retention tiers.

This new capability is one of many built by LogDNA to give users more control over how teams can route and store their log data. Earlier this year, the company released Spike Protection to give organizations more control over fluctuations of log data. And the recently announced LogDNA Streaming enables enterprises to ingest all of their log data to a single platform, and then route it for any enterprise use case.

Available retention tiers are three days, seven days, 14 days, and 30 days. LogDNA customers on an enterprise plan can sign up for the private beta program.

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LogDNA Introduces Variable Retention

LogDNA announced early access for Variable Retention.

This new capability allows companies to better control spend by storing different types or sources of logs for different lengths of time.

Modern infrastructure and applications generate massive amounts of data—sometimes petabytes worth of log data in a single day. Many teams need access to this data to gain critical insights into their services, but logging can get expensive, fast, and companies are forced to make difficult trade-offs that reduce observability and heighten risk. As a result, teams may not have the granular log data needed to form a complete picture during an incident or troubleshooting workflow. Variable Retention gives users the flexibility to save logs within the platform only for the amount of time that they're relevant, ensuring teams get access to the data they need, when they need it, while keeping costs in check.

“Different organizational and business functions need varying amounts and periods of data, but cost concerns drive sacrifices on what to keep and force dollar-driven decisions that diminish the value of all that data,” said Tucker Callaway, CEO, LogDNA. “Variable Retention gives LogDNA users control, removing friction that impacts how autonomous teams use log and other machine data to be more efficient and secure. Now, teams don’t have to choose between a reasonable logging bill and comprehensive observability data.”

Within the LogDNA user interface, customers select a subset of logs to store for different retention periods based on their needs—for instance, 30 days for security logs but only seven days for quality assurance and testing logs. When these rules are in place, users can monitor how their logging volume is distributed across different tiers in their usage dashboard to ensure the appropriate logs are being put in their respective retention tiers.

This new capability is one of many built by LogDNA to give users more control over how teams can route and store their log data. Earlier this year, the company released Spike Protection to give organizations more control over fluctuations of log data. And the recently announced LogDNA Streaming enables enterprises to ingest all of their log data to a single platform, and then route it for any enterprise use case.

Available retention tiers are three days, seven days, 14 days, and 30 days. LogDNA customers on an enterprise plan can sign up for the private beta program.

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Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

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Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...