April 2021 Summaries

Ted Gould, the first employee of Axiom and a Principal Engineer, shares insights into his professional journey and personal interests. He joined Axiom after his previous project ended, enticed by the opportunity to work from home (WFH), which he values greatly if understood correctly by the organization. During the pandemic, he navigated the challenges of WFH alongside his family, requiring adjustments to maintain the focus needed for his engineering role. Outside of work, Ted is an avid lover of nature, with aspirations to visit all U.S. National Parks, and enjoys spending Saturdays engaged in sports activities with his sons. Since relocating to Texas, he has developed a passion for Texas BBQ, particularly perfecting his brisket smoking skills, while also exploring local BBQ restaurants.

The tutorial by Tola Ore-Aruwaji, a Developer Relations Engineer, guides users through the process of integrating log data from Microsoft Azure Kubernetes Service (AKS) into Axiom for enhanced monitoring and analysis. It outlines the setup of a new AKS deployment, or the use of an existing one, to log data directly to Axiom, highlighting the benefits of extended data retention and comprehensive monitoring capabilities. The tutorial provides detailed instructions on creating a Kubernetes cluster in Azure, configuring a resource group, and setting up Axiom datasets and ingest tokens for authentication. It further explains how to use Filebeats for forwarding logs from Kubernetes clusters and how to apply configuration files using Azure command-line tools. Once set up, users can stream, query, and visualize their logs on Axiom, leveraging the Axiom Data Explorer and Axiom Processing Language (APL) for insights and alert configurations. The tutorial also encourages readers to explore further resources and support for any pricing or technical queries.

The article by Tola Ore-Aruwaji, a Developer Relations Engineer, provides a detailed exploration of using aggregations with queries on the Axiom platform to extract insights and visualize data. Aggregations, which are functions run across filtered data, help group and analyze various data types, including log events and metrics. Key aggregations discussed include count, sum, distinct, average, minimum, topK, histogram, and percentile, each serving to generate visualizations and tables that facilitate data comprehension. The article further explains how aggregations can be paired with "Group By" clauses to segment data for deeper insights and with the "Against" option to compare current data against previous time periods, enhancing anomaly detection and performance analysis. The author encourages readers to explore these aggregation techniques to maximize data querying potential on Axiom, highlighting the visual and analytical advantages they offer.