Philipp is part of the infrastructure team and a Developer Advocate at Elastic, spreading the love and knowledge of full-text search, analytics, and real-time data. He is a frequent speaker at conferences and meetups about all things search & analytics, databases, cloud computing, and devops.
Elasticsearch is a distributed, RESTful search and analytics engine built on top of Apache Lucene. After the initial release in 2010 it has become the most widely used full-text search engine, but it is not stopping there.
The revolution happened and now it is time for evolution. We dive into the following questions:
How did numbers and metrics become first class data in a search engine?
How do shard allocations (which were hard to debug even for us) work and how can you find out what is going wrong with them?
How can you search efficiently across clusters and why did it take two implementations to get this right?
What are current problems and their solution around resiliency and strictness?
Why are types finally disappearing and how are we avoid upgrade pains as much as possible?
How can upgrades be improved so that nobody is stuck on old or even ancient versions?
Attendees learn both about new and upcoming features as well as the motivation and engineering challenges behi
How to use the Elastic Stack (previously called ELK Stack) to monitor logs is widely known. But it can also give you a complete picture of your MongoDB installation:
* System metrics: Keep track of network traffic and system load.
* Logs: Collect and parse MongoDB logs.
* MongoDB metrics: Gather the most relevant attributes with the dedicated Metricbeat module.
* Queries: Monitor your queries on the wire with Packetbeat.
And we will do all of that together since it is so easy and quick to set up.