Artificial Intelligence for IT Operations (or AIOps for short) continues to be a hot topic among developers, SREs, and DevOps professionals. The case for AIOps is especially crucial given the expansive nature of today’s observability efforts across hybrid and multi-cloud environments. As with most observability platforms, it all starts with your telemetry data: metrics, logs, traces, and events.
As a DevOps engineer or SRE, you are often faced with investigating complex problems — mysterious application performance issues that happen intermittently or to only certain portions of your application traffic — that impact your end users and potentially your company’s financial targets. Sifting through hundreds or even thousands of transactions and spans can be a lot of tedious, manual, and time consuming investigative work.
Microsoft Azure’s recently launched new Azure Virtual Machines (VMs) feature the Ampere Altra Arm-based processor. These new VMs are engineered to efficiently run horizontally scalable workloads such as web servers, application servers, and open source databases. They deliver excellent price-performance and represent an important addition to Microsoft Azure's portfolio of instance types.
In Enterprise Search 8.4, hybrid ranking for vector similarity is now available from the main querying endpoint, commonly known as the _search Elasticsearch endpoint. Introduced as a standalone query endpoint in 8.0, vector querying functionality (specifically, kNN vector similarity) greatly simplifies and accelerates the process of crafting and issuing queries that leverage the native vector querying capabilities of Elasticsearch along with the tried-and-tested traditional scoring algorithms.
Your search application is more powerful than you realize. With these features, you can harness search data to build a better customer experience. What’s the top thing customers want when purchasing online? It’s ease. Experiencing friction for even a fraction of a second may send a shopper to a competitor’s site. It may also mean they don’t return to your site the next time they’re looking to purchase.
For online storefronts, there’s a fine line between a converted sale and a lost opportunity. The slightest overlooked detail on an ecommerce site can lead to customers quickly clicking elsewhere. The key to retaining site visitors and driving clicks that lead to sales lies in the technology behind the customer experience — specifically, search.
When it comes to delivering exceptional results to customers, having an understanding of all the tools at your disposal will give you a leg up. Especially in these uncertain economic times, this is even more important as companies look to gain any advantage possible. Being able to convert browsers into buyers and customers for life by providing the best customer experience will truly usher in this advantage.
Elastic App Search allows developers to bring the power of Elasticsearch to mobile apps in a pretuned search experience. When parsing body text, the App Search crawler extracts all the content from the specified website and spreads it in fields depending on the HTML tags it finds. Text within title tags are assumed as title field, anchor tags are parsed as links, and body is parsed as one giant field with everything else.
Insights from the 2022 Results That Matter study Correlating data across multiple silos and applications to derive meaningful and actionable insights is an ongoing struggle. These challenges are only set to increase as high-speed connectivity becomes more ubiquitous and enables data-heavy, digital experiences.
The Elastic Enterprise Search team is working on an exciting new project: Elastic Enterprise Search Connectors framework. It appeared in version 8.2 as a Technical Preview, and it has been significantly expanded in 8.3. Elastic Enterprise Search, and specifically Workplace Search, is a solution that helps harness the power of Elasticsearch to search over company documents.
