It’s one thing to ship the logs into the stack. Configuring the various integrations and pipelines in Logstash can be complicated and extremely frustrating, and configuration errors can bring down your entire logging pipeline. Most likely, you will be pulling data from multiple and distributed sources. The logs could be coming in from a local instance, AWS, Docker or Kubernetes. You could be ingesting database logs, web server logs, or application logs. This pipeline will greatly depend on the type of logs you want to ingest, the volume of log data, and the type of data source from which you are pulling the logs. Once you’ve troubleshooted those issues, you need to establish a pipeline into the stack. (For more, see my prior post on troubleshooting five common ELK Stack glitches.) Kibana not connecting with Elasticsearch, Kibana not being able to fetch mapping, and Logstash not running or not shipping data are all-too-frequent occurrences. Depending on whether you decided to install the stack on a local, cloud, or hybrid infrastructure, you may encounter various configuration and networking issues. However, connecting the dots when your logs aren’t showing up is not always error-free. Getting up and running with your first instances of Elasticsearch, Logstash, Kibana and Beats (usually Filebeat or Metricbeat, or Fluentd for Kubernetes log collection) is pretty straightforward, and there is plenty of documentation available if you encounter issues during installation (see our Elasticsearch tutorial, Logstash tutorial, and Kibana tutorial for help). Also, these recommendations are based on the assertion that you are starting from scratch and require a scalable, highly available, and at least medium-sized ELK deployment. These variables reflect what a production deployment of ELK needs to include based on the extensive experience of both our customers and ourselves while working with ELK. This article will break down the variables that need to be added into the equation. When contemplating whether to invest the valuable resources at your disposal in doing ELK on your own, you must ask yourself if you have the resources to pull it off. Jumping to the conclusion of this article, it all boils down to time and money. But before you go ahead and install Elasticsearch, Logstash, Kibana and the different Beats, there is one crucial question that you need to answer: Are you going to run the stack on your own, or are you going to opt for a cloud-hosted solution? The platform’s open source foundation, scalability, speed, and high availability, as well as the huge and ever-growing community of users, are all excellent reasons for this decision. The ELK Stack is now the world’s most popular log management platform, with millions of downloads per month. So, you’ve decided to go with ELK to centralize, manage, and analyze your logs.
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