LogDNA Adds Usage Quota Tools to Help Control Costs

LogDNA announced today it will enable IT teams to apply usage quotas to help rein in log management costs.

Tucker Callaway, CEO, LogDNA, said as applications become more complex – thanks, in part, to the rise of microservices – the amount of log data that a DevOps team can collect has significantly increased. IT teams can now assign DevOps teams both hard and soft quotas to limit the amount of log data collected during a specific time period, Callaway said.

IT teams can set a daily or monthly hard limit on the volume of logs stored or, alternatively, they can also set soft daily or monthly quotas that can apply throttling logic to ensure mission-critical log data will continue flowing through LogDNA as usage volume approaches the limit threshold. It will then be up to each IT team to determine, based on the tasks at hand, whether to enable a DevOps team to exceed those thresholds, Callaway said.

IT teams can also make use of soft limits to reallocate storage resources from one DevOps teams to another based on how much log data might be generated in a specific time period, Callaway noted.

LogDNA will notify team members any time a quota is hit, or when an exclusion rule is triggered because a quota has been reached. Those alerts can also be integrated with email systems or the Slack messaging platform. Logs that are not retained are not counted toward the monthly bill, but are displayed and will trigger other relevant alerts.

In the wake of the economic downturn brought on by the COVID-19 pandemic, IT organizations are, generally, more sensitive to costs. At the same time, many of them are encouraging developers to assume more responsibility for application life cycle management as they embrace DevOps best practices. The usage quotas are intended to enable IT teams to strike a better balance between what can be two competing agendas, Callaway said. IT leaders are not necessarily trying to discourage DevOps teams from collecting log data as much as they are trying to make sure costs are predictable, Callaway added.

Log data, of course, is one of the core elements of any observability strategy. While observability has always been a core DevOps principle, the number of organizations that have been able to meaningfully achieve it has been limited. However, as organizations start to deploy microservices with multiple dependencies, the need to provide context when troubleshooting those applications has become more acute.

It’s not clear to what degree more granular control over log data might sway an IT organization toward one platform versus another. However, when it comes time to justify a choice to senior IT and business leaders, it’s always a good idea to address, at some point, how one decision versus another might have a more positive impact on the bottom line.