Observability is a buzzword in the enterprise software industry. Conceptually, Observability is not new. This concept has been borrowed from the world of Engineering and Control Systems. Observability, by definition, is the ability to measure the internal state of a Software System based on the previous output obtained from it. Observability demystified Observability assumes greater significance in the backdrop of the adoption of decoupled system architecture like Microservices. It is imperative to deploy state of the art instrumentation to gauge the properties of an application and its performance as elaborate distributed systems evolve across the delivery pipeline and into production. Technical Set-up 1. Prerequisites (a) Adobe I/O Integration Project linked to Adobe Experience Platform (b) Installation of ELK stack 2. Architecture Elastic stack, aka ELK, is a conglomerate of three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a “stash” like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch. Image for post 3. Implementation In line with the aforesaid solution architecture, implementation has been illustrated with sample code snippet/configuration in the following subsections; (a) Import Observability Insights Observability Insights from Adobe Experience Platform shall be imported in the Elasticsearch platform through Logstash event processing pipeline. Logstash event processing pipeline shall import, mutate/transform, and index the data in the Elasticsearch index.
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