August 2021 Summaries

The text provides a comprehensive tutorial on using Axiom’s serverless log management solution to monitor and analyze Kubernetes environments, specifically focusing on IBM Kubernetes Service. It guides users through setting up an IBM Kubernetes Cluster, configuring log ingestion into Axiom, and utilizing various data aggregation methods such as count, sum, distinct, and histogram to extract insights from Kubernetes logs. The tutorial also covers setting up alerts for changes in pod states using Axiom Notifiers, allowing notifications via Email, Slack, PagerDuty, or Webhook. Additionally, it highlights the flexibility of configuring monitors to trigger based on specific conditions and encourages engagement with the Axiom community for further support.

Axiom's live streaming feature allows users to easily view, filter, and extract logs from various data sources in real time, enhancing the ability to diagnose and evaluate system performance. By creating datasets and ingest tokens, users can import events into Axiom using APIs, data shippers, or Elasticsearch Bulk API. The tutorial guides users through setting up filters and exploring operators to refine log searches, enabling the extraction of specific data insights based on field criteria. Users can manipulate the stream's display settings, such as text size and field visibility, and save their searches for future use. The stream feature offers both a live mode, which continuously updates with new events, and a time range mode for viewing specific intervals, providing flexibility in monitoring and analyzing data.