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Co-authors: Ping Yan and Yuly Tenorio Background on Session Hijacking All communication on the internet happens over a set of standards called TCP/IP (Transmission Control Protocol/Internet Protocol). They are the World Wide Web’s core communication system that enables Internet-connected devices to communicate simultaneously with each other. This system lays the groundwork over which higher level protocols… Continue reading How Salesforce Helps Protect You From Session Hijacking Threats

Real-time Predictions in a Multitenant Environment Introduction The Einstein Vision and Language Platform Team at Salesforce enables data management, training, and prediction for deep learning-based Vision and Language use cases. Consumers of the platform can use our API gateway to upload datasets, train those datasets, and ultimately use the models generated out of training to… Continue reading Realtime Predictions in a Multitenant Environment

Heroku CI and GitHub Checks Integration Before we dive into the crux of this article, let’s first get an understanding of what GitHub Checks is and how it will be useful for you when you use any external Continuous Integration (CI) tool like CircleCI, Heroku CI, or any local tool. The Checks functionality enables integrations… Continue reading Heroku CI and Github Checks Integration

Automate Shadow DOM with WebDriver & Playwright Locate elements in Shadow DOM of Web Components directly through CSS query engine. This document shows how to use the simpler CSS/xPaths that calls through document.querySelector to locate elements within #shadow-root of your Web Components or Salesforce LWC Applications. This solution can be extended to LitElements, Lighting Fast Templates… Continue reading Automation made easy for Web Components #shadow-roots

Salesforce uses machine learning to improve every aspect of its product suite. With the help of Salesforce Einstein, companies are improving productivity and accelerating key decision-making. Data is a critical component of all machine learning applications and Salesforce is no exception. In this post I will share some unique challenges Salesforce has in the realm… Continue reading ML Lake: Building Salesforce’s Data Platform for Machine Learning

The Salesforce Unified Intelligence Platform (UIP) team is building a shared, central, internal data intelligence platform. Designed to drive business insights, UIP helps improve user experience, product quality, and operations. At Salesforce, Trust is our number one company value and building in robust security is a key component of our platform development. In this blog,… Continue reading Building a Secured Data Intelligence Platform

AsyncAPI is gaining traction in the ecosystem of API tools. It solves an important problem: it provides a convenient way of describing the interface of event-driven systems independently of the underlying technology. With AsyncAPI, evented systems can be treated as any other API product: a productizable and reusable, self-describing building block encapsulating some set of… Continue reading AsyncAPI and OpenAPI: an API Modeling Approach

At Salesforce, we have thousands of customers using a variety of products. Some of our products are enhanced with machine learning (ML) capabilities. With just a few clicks, customers can get insights about their data. Behind the scenes, it’s the Einstein Platform that builds hundreds of thousands of models, unique for each customer and product,… Continue reading Flow Scheduling for the Einstein ML Platform

Journey to a Million Models The AIOps team in Salesforce started developing an anomaly detection system using the large amount of telemetry data collected from thousands of servers. The goal of this project was to enable proactive incident detection and bring down the mean time to detect (MTTD) and mean time to remediate (MTTR) Simple problem, right?… Continue reading Journey to a million models