Finding a home (and career) in the open source community

Open source software development can have a reputation for abrasive behavior. The search community is a clear counterexample for me, with a culture that emphasizes respect and acceptance. This culture played an important part in my own path to open source development. A little over six years ago, I was a wide-eyed software engineer settling into my first full-time job.


Ingram Micro chooses Elastic to bolster search, sales on ecommerce site

Ingram Micro is a Fortune 100 company with $50 billion plus in revenue and operating in 56 countries. As the global leader in delivering technology and supply chain services to businesses, Ingram Micro touches about 80% of all high tech products sold around the world. Andre Dykhno, Head of Product for Global ecommerce, says ecommerce has been a large contributing factor to Ingram Micro’s modern day successes.

Virtual Meetup: Running Elasticsearch on Kubernetes

Elasticsearch is the world's most popular open source search engine. Kubernetes (k8s) is the popular container orchestration engine giving developers the flexibility to run all sorts of workloads easily. Elastic launched Elasticsearch k8s operator sometime ago. With this, one can not only run Elasticsearch on k8s but also can launch other Elastic Stack projects like APM Server, help run rolling upgrades, manage data etc. This talk is a demo of all latest features.

Virtual Meetup: Search, Full Text Search and Elasticsearch

This talk starts with the significance of search problem and its origin in history how it has been an integral part of our daily lives. Also, basics of full text search will be discussed along with the anatomy of a full text search engine by taking Elastic Search as an example. Speaker: Muhammad Junaid Muzammil is a Software Engineer with over 9 years of professional experience, along with over 4 years of experience working with Elasticsearch. He is also an Elastic Certified Engineer and one of our active Elastic user group organizers, based in Pakistan, Karachi.

Searching Zendesk: Elastic Workplace Search for customer service organizations

We’re excited to announce that Zendesk is now available as a pre-built content source, along with a host of others, as part of the Workplace Search application. With more than 130,000 customers in 30 countries, Zendesk has become one of the de facto customer service platforms in the world. Each day, millions of users interact with support agents via the cloud-based tool regardless of the support channel they choose.


Feature importance for data frame analytics with Elastic machine learning

With Elasticsearch machine learning one can build regression and classification models for data analysis and inference. Accurate prediction models are often too complex to understand simply by looking at their definition. Using feature importance, introduced in Elastic Stack 7.6, we can now interpret and validate such models.


Elastic App Search: A free product for building great search experiences

Wherever people encounter a search bar — whether on Google, phone apps, or while shopping online — they're conditioned to expect search experiences that deliver fast and relevant results. With this ever-evolving expectation in mind, millions of developers and organizations have chosen Elasticsearch for building powerful content discovery experiences over the years, to the great delight of their audience and user base.

While You Work from Home, Double Down on Elasticsearch Security

As engineers, you and I have a responsibility to protect both our customers’ and our respective companies’ data. But unlike our office networks that adhere to strict security protocols and a well-defined perimeter, our home networks usually fall short. And now that most of us are at home waiting out the COVID-19 pandemic, it’s time to revisit of logging in and Elasticsearch security during while you work from home.

blue medora

Elasticsearch Query Performance | Metrics to Watch

If you’re using the Elasticsearch query functionality, for mainly front-facing client search, there are 3 important metrics to monitor performance. Your cluster can be putting up with any number of queries at a time. The volume of queries over time will align roughly to the load of requests laying a potential burden. Unexpected peaks and valley in a time series of query load could be signs of a problem or potential optimization opportunities.