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The main reason we emphasized storage is because we built it with scaling that in mind, that's all. We've also built it with live tail in mind too. It's an okay

by leeab 11y ago

The main reason we emphasized storage is because we built it with scaling that in mind, that's all. We've also built it with live tail in mind too. It's an okay differentiator since we believe we can handle the volume with our infrastructure. We also followed up with UI/UX which at the end of the day should make us a platform you can goto, get what you need and go back to work. Give us a try, even if you don't think you'll use the GBs. We have alerting, field parsing and live tail. Analytics is the only piece we don't have today, but we're working towards it.

chrissnell 11y ago
I understand. For me, though, scaling is just a small piece of the puzzle and not really a differentiator. To give you an idea of our size, we run about ~500 instances in a private cloud hosted on about 45 dedicated servers at Rackspace. We use OpenStack for stateful services and data storage and we use Kubernetes/Docker/CoreOS for 12FA/microservices. We have many dozens of apps and even with all of that, we're still only pushing about 4-5 GB of logs each day. The number one most important problem we're trying to solve is the actual parsing of logs during ingestion. We need logs from commonly-used apps & frameworks to be automatically identified and parsed and we need an easy way to set up a custom parser for internal logs that doesn't require crazy hand-written regex. How does LogDNA handle parsing? What apps/frameworks are supported?
- leeab 11y ago
  We automatically detect common formats using regex during ingestion. Many are based on logstash patterns and we have several of our own (including one that just tries to strip out timestamp + log level). If you use a common format, we can usually add it. If you have a custom format that your app defines, we don't have a way for you to add it yet but it'll likely be a regex as you said. (We can always help you create it if you don't want to).
sz4kerto 11y ago
Give me syslog target, and I'm all yours :)

by leeab 11y ago

chrissnell 11y ago

I understand. For me, though, scaling is just a small piece of the puzzle and not really a differentiator. To give you an idea of our size, we run about ~500 instances in a private cloud hosted on about 45 dedicated servers at Rackspace. We use OpenStack for stateful services and data storage and we use Kubernetes/Docker/CoreOS for 12FA/microservices. We have many dozens of apps and even with all of that, we're still only pushing about 4-5 GB of logs each day. The number one most important problem we're trying to solve is the actual parsing of logs during ingestion. We need logs from commonly-used apps & frameworks to be automatically identified and parsed and we need an easy way to set up a custom parser for internal logs that doesn't require crazy hand-written regex. How does LogDNA handle parsing? What apps/frameworks are supported?

leeab 11y ago
We automatically detect common formats using regex during ingestion. Many are based on logstash patterns and we have several of our own (including one that just tries to strip out timestamp + log level). If you use a common format, we can usually add it. If you have a custom format that your app defines, we don't have a way for you to add it yet but it'll likely be a regex as you said. (We can always help you create it if you don't want to).

sz4kerto 11y ago

Give me syslog target, and I'm all yours :)