We love to write and ship code to help developers bring their ideas and projects to life. That’s why we’re constantly working on improving our product to meet developers where they are, to ensure their happiness, and accelerate Time to Awesome. This week, we are covering a featured product release that we think will save you time and effort when onboarding to time series and InfluxDB.

InfluxDB is an open-source time series database. Built to handle enormous volumes of time-stamped data produced from IoT devices to enterprise applications. As data sources for InfluxDB can exist in many different situations and scenarios, providing different ways to get data into InfluxDB is essential. The InfluxDB client libraries are language-specific packages that integrate with the InfluxDB v2 API. These libraries give users a powerful method of sending, querying, and managing InfluxDB.

Dataflow is a fully managed stream and batch processing service from Google Cloud that offers fast and simplified development for data-processing pipelines written using Apache Beam. Dataflow’s serverless approach removes the need to provision or manage the servers that run your applications, letting you focus on programming instead of managing server clusters. Dataflow also has a number of features that enable you to connect to different services.

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.

This article was originally published in The New Stack and is reposted here with permission. You may be familiar with live examples of machine learning (ML) and deep learning (DL) technologies, like face recognition, optical character recognition OCR, the Python language translator, and natural language search (NLS). But now, DL and ML are working toward predicting things like the stock market, weather and credit fraud with astounding accuracy.

This article was written by Shane from Infosys. Infosys is a global IT Leader, headquartered in India, with over 200,000 employees and a focus on digital transformation, AI/ML, and Analytics. Our organization faces challenges when working with data to assist with proactive anomaly detection, triaging incidents to accommodate for data and volume growth, and maintaining high availability and SLA’s for a near 100% uptime.