On the internet, nothing necessarily stays easy, simple, and reliable forever – but we’re trying to keep it that way for your logs. When our customers use Kubernetes, they want to remain focused on the real challenges of scaling, and avoid infrastructure headaches, so that they can adapt to the unexpected easily and with a minimum of toil. That’s why we continue to invest in the LogDNA Agent. It’s built to handle file logging in even the most intensive Kubernetes deployments.

LogDNA is adding the ability to store and view raw lines, allowing customers to debug with logs in their unaltered form. If you’ve ever looked at your logs and noticed that the timestamp was different than what you expected, it is usually due to a long latency between the event and processing time of the logs. Depending on the size of the latency, we may update the log timestamp to order them accurately and to provide a cleaner and more intuitive search experience.

The Extract and Aggregate fields feature allows users to custom parse historical logs (post ingestion) and get an aggregated count on those newly parsed fields. Enterprise SREs work with large systems that consist of internally built components and external products. Debugging with logs from external products can be extremely challenging.

LogDNA is releasing Custom Webhooks, enabling customers to easily integrate LogDNA alerts with 3rd-party services. Custom Webhooks allows you to configure a webhook’s header and body and add specific LogDNA tokens to your alerts going through that webhook.

In the olden days, we used to have to get logs by putting our agent on one machine at a time, like hitching a horse to a horse-drawn carriage. But now, we’ve got Kubernetes. It’s like a horse factory, and we’ve got more horses than we know what to do with. In this wild west of containerization, we could quickly end up underneath more logs than our old-timey agent could keep track of! But now there’s a new sheriff in town.

AWS has a lot of services, and they all generate logs. A lot of logs. We’ve worked hard to make sure you can capture logs from every source and service on AWS, and today we’re happy to announce the final piece of our AWS logging puzzle: LogDNA’s S3 Collector integration. It’s an easy-to-use Lambda function that lets you ingest any AWS logs that get dumped to S3 – like logs from CloudFront and ELB.

It’s the start of a new year and the time is right to assess what we’ve accomplished and where we’re going. First, I think we should celebrate the incredible year LogDNA just completed. I’m so proud of what our LogDNA team accomplished. Not only because it’s quite impressive, which it is, but also because it lays the groundwork for what’s to come in 2020.

SRE and Security teams rely heavily on alerts to know whether their systems are experiencing issues and to prevent any future outages. At LogDNA, customers can set alerts that trigger when specific logs match (presence alerts) or set an alert to go off if there are expected lines that haven’t come through (absence alerts). These alerts can be set up with various channels so you can be alerted in the product of your choice (Slack, Email, PagerDuty, etc).

LogDNA is known and loved by developers for our lightning fast live tail and search. With some users ingesting over a petabyte of data per day, our users want to be able to visualize their data and put it to use. You told us what analytics you value most and we’ve taken the first step to providing them within the LogDNA product. The first is having highly interactive graphs. Graphs allow you to analyze patterns and trends by navigating through your data over a period of time.

IBM recently announced an expanded Cloud Paks offering with LogDNA. With this offering, developers and engineering teams can easily aggregate and search huge volumes of data from any source to gain real-time insights on their applications. LogDNA is now offered by IBM and deployable on-premise or multi-cloud with all IBM Cloud Paks including Cloud Pak for Applications, Cloud Pak for Data, Cloud Pak for Integration, Cloud Pak for Multi-cloud Management, and Cloud Pak for Automation.