In the world of IT, availability can mean a lot of things. Your website is available if it is up, responding in a timely manner, sending the correct headers, and serving a valid certificate. Your network is available if the correct hosts are online, responding to ICMP pings, and responding to TCP requests on specific ports. Your API endpoint is available if it returns the correct values when sent specific requests.

Welcome to another blog in our series on cost management and optimisation in Elasticsearch Service. In previous installments, we looked at hot-warm architecture and index lifecycle management as ways of managing the costs associated with data retention and at managing replicas as a means of optimising the structure of your Elasticsearch Service deployment. Be sure to check out the other blogs in the series for additional tips to help you as you build out your deployment.

As well as being a search engine, Elasticsearch is also a powerful analytics engine. However, in order to take full advantage of the near real-time analytics capabilities of Elasticsearch, it is often useful to add structure to your data as it is ingested into Elasticsearch. The reasons for this are explained very well in our schema on write vs. schema on read blog post, and for the remainder of this blog series, when I talk about structuring data, I am referring to schema on write.

This post is a brief summary of a presentation I gave recently where I deploy Elastic App Search, show off the ease of setup, data indexing, and relevance tuning, and take look at a few of the many refined APIs. It’s also written up in a codelab with step-by-step instructions for building a movies search engine app using Python Flask. The app will work on desktop or mobile and is a fast, simple, and reliable way to query the information.

This is part of our series on cost management and optimization in Elasticsearch Service. If you’re new to the cloud, be sure to think about these topics as you build out your deployment. If you are yet to start, you can test out the content here by signing up to a 14-day free trial of Elasticsearch Service on Elastic Cloud.

The issue of unsecured databases is growing. In 2019, 17 percent of all data breaches were caused by human error — twice as many as just a year before. And the IBM/Ponemon 2019 report found that the estimated probability of a company having repeated data breaches within two years grew by 31 percent between 2014 and 2019. Why is this happening?

"Upgrade" can be a four-letter word for admins, so at Elastic, we try to make the upgrade process as simple as possible. Why? Because we pack a ton of goodness into each release, but you can only take advantage of that goodness by being on the latest version of the Elastic Stack. This is also why we make the latest version available on Elastic Cloud the same day that we release.