We are in the final stretch for the 2020 version of the Elastic Advent Calendar! This is the last weekly wrap up, the next one will be a recap of the full 25 days. This week we have some great insights into preparing interviews, monitoring tekton tasks and pipelines, text analysis for korean language, searchable snapshots, OpenTelemetry, Data visualisation and log correlation with APM.
Let’s dive into Week 3
Dec 15 [english] — Preparing for an Elasticsearch Interview, by Aravind Putrevu
Elasticsearch is the most popularly used data store for building a Search Engine, Centralized Logging, Observability, or Threat Hunting use cases.
That also means Elasticsearch is omnipresent in many organizations.
In this post, we’ll see what are some important topics that you need to prepare for an Elasticsearch interview.
Dec 16 [french/english] — Monitorer les tâches et pipelines Tekton avec Elastic Observability | Monitoring Tekton Tasks and Pipelines with Elastic Observability, by Maxime Gréau
Do you know that Elastic performed 21 releases in 2020?
Each time a release is promoted, this is 500+ artifacts published to multiple public places (bucket, Docker registries, Maven Central, Rubygems, and so on) and available on Cloud at the same time. This complex process became a non-event thanks to our Unified Release workflow based on Tekton Tasks and Pipelines and monitored with Elastic Observability.
This blog post shows how to run your first Tekton Task, and then how to install and use the Elastic Observability Solution to monitor many Tasks and Pipelines deployed within a cluster.
Dec 17 [korean] — 한글 형태소 분석기 파헤치기, by Jongmin Kim
Elasticsearch 에서는 Elastic 에서 공식으로 제공하는 한글 형태소 분석기인 nori 를 사용할 수 있습니다. 한글은 띄어쓰기가 없는 복합어가 대다수이기 때문에 의도하지 않은 대로 분석이 되는 경우가 많아 nori 를 사용하기 위해서는 목적에 맞는 사용자 사전을 등록해야 할 때가 많습니다.
Dec 18 [english] — Set up searchable snapshots in ECK, by Idan Moyal
Searchable snapshots, recently released as BETA in Elasticsearch 7.10, let you reduce your operating costs by using snapshots for resiliency rather than maintaining replica shards within a cluster.
In this blog we’ll demonstrate how to create a hot-cold topology using Elastic Cloud on Kubernetes (ECK). For the cold tier we will mount a snapshot using the new searchable snapshots API. The demonstration is carried out on Google Kubernetes Engine (GKE) and can easily be adjusted to other Kubernetes environments.
Dec 19 [english] — OpenTelemetry in Go Applications using Elastic APM, by Ricardo Ferreira
Distributed tracing technologies allow developers to virtually glue together disparate services to build a cohesive transaction that can be observed by folks in the operations team. This is super important because the distributed nature of modern cloud-native applications makes it hard for teams responsible for maintaining these applications up-and-running to rapidly perform RCA (Root Cause Analysis) of issues when they happen.
Though tracing technologies are not necessarily new only in recent years it gained enough traction to become one of the three main pillars of an observability strategy—notably logs, metrics, and distributed tracing.
To speed up developer adoption, multiple standards such as OpenTracing and OpenCensus have been created throughout the years. However, it didn’t make any sense to have multiple standards since this creates more harm than good. For this reason the standard OpenTelemetry was created out of the existing ones to be an observability framework for cloud-native software.
Practitioners in the field of data visualizations often talk about 2 types of visualizations: exploratory vs explanatory. To quote Google definitions (the most authoritative source, of course), “Exploratory data visualizations (EDVs) are the type of visualizations you assemble when you do not have a clue about what information lies within your data.”
Elastic stack is a great tool for such exploration since because of the flexible ways you can combine search, filtering, and aggregations to understand your data. In addition, you don’t need to go through a costly process of defining a schema before you can start exploring.
Dec 21 [english] — When neither logging nor code tracing is enough: Log Correlation with APM, by Emanuil Tolev
Application Performance Monitoring and logging both provide critical insight into your ecosystem. When paired together for context, they can provide vital clues on how to resolve problems with your applications. This post assumes you’re familiar with what an APM (also known as “code tracing”) system does, what log monitoring is, and the benefits of both. Elastic offers free solutions for both as part of Elastic Observability.
Not long now
Only 4 more posts of handy howto’s and tips from the engineers behind the projects, and that’ll be our 2020 series over! Make sure you subscribe to the Advent category on Discuss for the latest posts, and follow @elastic for tweets when new posts are published.