Operations | Monitoring | ITSM | DevOps | Cloud

Hiya! With Elastic’s expansion of our Elasticsearch Service Cloud offering and automated onboarding, we’ve expanded the Elastic Stack audience from full ops teams to data engineers, security teams, and consultants. As an Elastic support rep, I’ve enjoyed interacting with more user backgrounds and with even wider use cases.

Alibaba Cloud is an important partner to us here at Elastic. We officially started our collaboration and strategic partnership with Alibaba Cloud back in 2017, when we announced the Alibaba Cloud Elasticsearch service. Since then, we’ve seen rapid adoption and growth of the service, which now supports more than 10 petabytes of data.

Docker is a power tool for deploying applications or services, and there are numerous Docker orchestration tools available that can help to simplify the management of the deployed containers. But what if you are wanting to deploy a small number of services and not wanting to undertake setting up and managing another application stack just to run a handful of containers. I will cover how I deployed a handful of services on a single Docker host.

Customers interact with your business multiple times before reaching any goal. These repeated digital interactions are what make up the customer journey. Your customers’ overall experience across the different channels as they engage with your organization (websites, social media, email, etc.) make up the customer experience. Customer journey analytics refers to the process of analyzing the experience of customers across multiple touchpoints in the customer journey.

Leading retailers have an ambitious vision for what data and connectivity can do in the physical shopping space, and brick-and-mortar retail is already rapidly transforming the shopping experience with technologies such as IoT, VR, AI and cloud computing.

Security analysts have long been challenged to keep up with growing volumes of increasingly sophisticated cyberattacks, but their struggles have recently grown more acute. Only 46% of security operations leaders are satisfied with their team’s ability to detect threats, and 82% of decision-makers report that their responses to threats are mostly or completely reactive — a shortcoming they’d like to overcome.

A common challenge in data engineering is to combine traditional data warehousing and BI reporting with experiment-driven machine learning projects. Many data scientists tend to work more with Python and ML frameworks rather than SQL. Therefore, their data needs are often different from those of data analysts. In this article, we’ll explore why having a data lake often provides tremendous help for data science use cases.