LogDNA today announced a new offering that enables developers to troubleshoot coding bugs and quickly fix development errors in applications, potentially saving businesses millions of dollars in development hours, downtime and associated revenue loss. IBM Log Analysis with LogDNA integrates LogDNA services to allow developers to aggregate all their log data across applications in the IBM Cloud.
Organizations that handle logging at scale eventually run into the same problem: too many events are being generated, and logging components can’t keep up. Even with persistent queues and other mitigating features enabled, there’s simply not enough of a buffer between log generators and log ingesters to handle the volume of log lines coming in.
I hosted a webinar where I covered why logging is important, how to choose a logging provider. And then shared our experience of setting up logging on Kubernetes containers, the Kubernetes logging framework and the logging best practices we’ve implemented internally and supported our customers who run Kubernetes in production.
We’re excited to announce that LogDNA’s built-in log parser offers custom parsing, now available in beta. This means you can now use our step-by-step wizard to wrangle non-standard log formats and run custom transformations on your logs, allowing you to easily search and graph log lines that were previously off limits. The best part is, it’s a simple three step process: search, extract, validate… done!
One of the greatest threats to a log management solution is load. As log volume increases, the ability for a solution to process each event decreases. Given enough load, this will result in dropped messages and data loss.
We’re excited to announce the general availability of our new On-Prem, Self-Hosted, and Multi-Cloud logging platforms. Our customers will have the capability to log data in their infrastructure of choice. Whether across multiple public/private clouds or within a customer’s own data center, logs can be viewed through a unified interface while addressing any data locality and performance requirements.
Recently, we held a webinar where Chris Nguyen, our CEO and Co-Founder and Norman Hsieh, our Head of Business Development talked about the ever increasing production of data, the shift from monitoring to observability, and the evolution of production infrastructure into multi-cloud. LogDNA is uniquely positioned to have enabled thousands of customers to gain deep insights into their evolving DevOps infrastructure.
As any business running microservices, containerized applications, networking devices, or multiple servers knows, it’s important to get a centralized log management system that fits your company’s unique needs. The best log management solution should empower your business to gain insights, resolve production issues quickly, streamline your DevOps and IT teams, and allow you to work more efficiently.
What is log monitoring and log analysis? Both are crucial parts of log management and related in many capacities, but by definition, the two actually have different core meanings.
