Logstash is a tool to collect, process, and forward events and log messages and this Logstash tutorial will get you started quickly. It was created by Jordan Sissel who, with a background in operations and system administration, found himself constantly managing huge volumes of log data that really needed a centralized system to aggregate and manage them. Logstash was born under this premise and in 2013 Sissel teamed up with Elasticsearch.
Let’s face it, nothing is perfect. The better we architect our systems, though, the more near-perfect they become. But even so, someday, something is likely to go wrong, despite our best effort. Part of preparing for the unexpected is regularly backing up our data to help us recover from eventual failures and this tutorial explains how to use the Elasticsearch Snapshot feature to automatically backup important data.
Searches are integral parts of any application. Performing searches on terabytes and petabytes of data can be challenging when speed, performance, and high availability are core requirements. This blog post will pit Solr vs Elasticsearch, two of the most popular open source search engines whose fortunes over the years have gone in different directions. Both of them are built on top of Apache Lucene, so the features they support are very similar.
Reliable systems are vital to meeting customer expectations. Downtime not only hurts a company’s bottom line but can be detrimental to reputation. Our goal at Gremlin is to help enterprises build more reliable systems using Chaos Engineering. Whether your infrastructure is deployed on bare metal in a corporate-owned data center or as Kubernetes-orchestrated microservices in a public cloud, chaos experiments can help you find system weaknesses early, before they affect customers.
In administrating all technology and application requirements within an organization, IT operations management (ITOM) is pretty complex, and tends to send IT admins scrambling for authentic and actionable insights across the internet. We’re taking matters into our own hands and launching our very own podcast series to provide you valuable information on ITOM, which you can choose to listen to at your leisure or on the go!
In classic Puppet deployment architecture, compile masters are widely used when the number of managed nodes goes up. Multiple compile masters sit behind a load balancer to take care of the additional workloads. It is not rare to see Puppet adopters launching the compile masters in the public cloud, such as Amazon Web Service (AWS) and Google Cloud Platform.
