Search is a common requirement for applications of all varieties. Elasticsearch was built to make it easy to include search functionality in projects built in any language. From that foundation, the rest of the Elastic Stack has been built, expanding to many more use cases in the proces. In this episode Philipp Krenn describes the various pieces of the stack, how they fit together, and how you can use them in your infrastructure to store, search, and analyze your data.

Your data platform needs to be scalable, fault tolerant, and performant, which means that you need the same from your cloud provider. Linode has been powering production systems for over 17 years, and now they’ve launched a fully managed Kubernetes platform. With the combined power of the Kubernetes engine for flexible and scalable deployments, and features like dedicated CPU instances, GPU instances, and object storage you’ve got everything you need to build a bulletproof data pipeline. If you go to dataengineeringpodcast.com/linode today you’ll even get a $60 credit to use on building your own cluster, or object storage, or reliable backups, or… And while you’re there don’t forget to thank them for being a long-time supporter of the Data Engineering Podcast!

Datadog is a SaaS-based monitoring and analytics platform for cloud-scale infrastructure, applications, logs, and more. Datadog delivers complete visibility into the performance of modern applications in one place through its fully unified platform—which improves cross-team collaboration, accelerates development cycles, and reduces operational and development costs.