Operations | Monitoring | ITSM | DevOps | Cloud

K-NN (k-nearest neighbors) is a widely used machine learning (ML) recommendation algorithm, it is used to locate nearby documents based on vector dimensions. The algorithm can be and has been applied to numerous different use cases including image recognition, fraud detection, image recognition, and ‘other songs you might like’ feature in a music application. KNN uses proximity to provide classifications and predictions regarding the grouping of an individual data point.

The business of observability is all about data: what you’re observing in the data, how you’re visualizing it, what it indicates about the state of your environment, and how to address issues that may occur. Creating your own perspective for observability, and understanding what you’re seeing, can be difficult.

The more customers I talk to, the more I see a trend toward wanting a low-cost vendor-agnostic data lake. Customers want the freedom to store their data long-term and typically look to object stores from AWS, Azure, and Google Cloud. To optimize for data access, users will partition their data into directories to optimize for use cases such as Cribl Replay and Cribl Search. Only relevant files will be accessed for rehydration or search by partitioning data.

In most situations, you will have several sources of telemetry data that you want to send to multiple destinations, such as storage locations and observability tools. In turn, the data that you are sending needs to be optimized for its specific destination. If your data contains Personally Identifying Information (PII) for example, this data will need to be redacted or encrypted before reaching its destination.

With observIQ’s contributions to OpenTelemetry, you can now use free, open-source tools to easily aggregate data across your entire infrastructure to any or multiple analysis tools. The easiest way to use the latest OpenTelemetry tools is with observIQ’s distribution of the OpenTelemetry collector. You can find it here. In this blog, we cover how to use OpenTelemetry to monitor SNMP.

Federal agencies are adopting a more modern, digital-centered approach in everything they do. That’s good progress, but it’s also exposing some critical problems in the modernization journey.

The Cribl Syslog source is our most commonly used input type. Cribl Stream can act as your edge and/or central syslog server, giving you more capability while easing management tasks. In this blog post we’ll go over a brief history of syslog. Then we’ll dive into best practices for standing up Cribl Stream as a syslog server, tuning the server, and other tips for running a high performance syslog platform.

With the development and increased usage of cloud-native technologies, containers, and microservices-based architectures, log monitoring has become a fundamental component of effective management for organizations. Logs offer users insights into occurring issues and assist them in understanding how their software performs over time, where it excels, and where it fails.