Operations | Monitoring | ITSM | DevOps | Cloud

Think about your last online order. If you’re a frequent online shopper and have created profiles for sites you visit often (*raises hand*), then you’re probably familiar with customized recommendations. Based on your purchase history, location, and other factors, the website may suggest other items you might be interested in buying. And if you’re on the site long enough, chatbots may appear asking if you have questions or need assistance locating something.

Machine learning — the practice of writing algorithms that improve automatically through experience — has become a buzzword nowadays that connotes to something otherworldly and on the bleeding edge of technology. I’m here to tell you while that may be true, getting started with machine learning doesn’t have to be hard!

Editor’s note: This post is a collaboration between Tim Tully, Splunk CTO, and Spiros Xanthos, Splunk’s vice president of product management for observability and IT Ops and previously the founder and CEO of Omnition. My love for the open-source software movement began with Linux in the ’90s and grew during my time at Yahoo! in the early days of Hadoop.

We recently announced the general availability of our Elasticsearch Service API. APIs help to automate tasks such as creating and scaling deployments, integrating with existing workflows, and testing. The Elasticsearch Service API supports the Open API Specification, which allows you to use tools like Swagger to generate software development kits (SDKs) in any programming language. You can import the API spec onto Postman and create a Postman Collection to create a test suite.

Android Enterprise is Google’s unified management platform for Android OS devices. It has been around since Android 6 but is just recently gaining traction as Android 10 fades out the old device admin management methods.

When you build your application on top of Lambda, AWS automatically scales the number of “workers” (think containers) running your code based on traffic. And by default, your functions are deployed to three Availability Zones (AZs). This gives you a lot of scalability and redundancy out of the box. When it comes to API functions, every user request is processed by a separate worker. So the API-level concurrency is now handled by the platform.

When working with IoT (internet of things) devices one of the key issues is to keep track of the health of all installations. Most of the time, especially with smaller devices, the applications (firmwares) are flashed for a single time during setup and stay untouched at their location of action for a long while.

Open source contributions are foundational to Elastic — from Elasticsearch’s Apache Lucene core to the addition of open source Logstash and Kibana to form the Elastic Stack you’ve come to know and love. Over the years, the Elastic community has created over 90 Beats, shared use case tutorials like those from Volvo, T-Mobile, and Microsoft, and presented at hundreds upon hundreds of meetups.

Mattermost and Jitsi—open source, self-hosted alternatives to Slack and Zoom—now integrate! With the Mattermost Jitsi plugin, Mattermost users can now instantly launch secure Jitsi voice, video and screen-sharing calls, either on-prem with the self-hosted Jitsi software or via the cloud with Jitsi Meet.