Metadata Archives - gettectonic.com

15Jun

The AI Tech Stack

The AI tech stack integrates various tools, libraries, and solutions to enable applications with generative AI capabilities, such as image and text generation. Key components of the AI stack include programming languages, model providers, large language model (LLM) frameworks, vector databases, operational databases, monitoring and evaluation tools, and deployment solutions. The infrastructure of the AI tech stack leverages both parametric knowledge from foundational models and non-parametric knowledge from information sources (PDFs, databases, search engines) to perform generative AI functions like text and image generation, text summarization, and LLM-powered chat interfaces. This insight explores each component of the AI tech stack, aiming to provide a comprehensive understanding of the current state of generative AI applications, including the tools and technologies used to develop them. For those with a technical background, this Tectonic insight includes familiar tools and introduces new players within the AI ecosystem. For those without a technical background, the article serves as a guide to understanding the AI stack, emphasizing its importance across business roles and departments. Content Overview: The AI layer is a vital part of the modern application tech stack, integrating across various layers to enhance software applications. This layer brings intelligence to the stack through capabilities such as data visualization, generative AI (image and text generation), predictive analysis (behavior and trends), and process automation and optimization. In the backend layer, responsible for orchestrating user requests, the AI layer introduces techniques like semantic routing, which allocates user requests based on the meaning and intent of the tasks, leveraging LLMs. As the AI layer becomes more effective, it also reduces the roles and responsibilities of the application and data layers, potentially blurring the boundaries between them. Nevertheless, the AI stack is becoming a cornerstone of software development. Components of the AI Stack in the Generative AI Landscape: The emphasis on model providers over specific models highlights the importance of a provider’s ability to update models, offer support, and engage with the community, making switching models as simple as changing a name in the code. Programming Languages Programming languages are crucial in shaping the AI stack, influencing the selection of other components and ultimately determining the development of AI applications. The choice of a programming language is especially important for modern AI applications, where security, latency, and maintainability are critical factors. Among the options for AI application development, Python, JavaScript, and TypeScript (a superset of JavaScript) are the primary choices. Python holds a significant market share among data scientists, machine learning, and AI engineers, largely due to its extensive library support, including TensorFlow, PyTorch, and Scikit-learn. Python’s readable syntax and flexibility, accommodating both simple scripts and full applications with an object-oriented approach, contribute to its popularity. According to the February 2024 update on the PYPL (PopularitY of Programming Language) Index, Python leads with a 28.11% share, reflecting a growth trend of +0.6% over the previous year. The PYPL Index tracks the popularity of programming languages based on the frequency of tutorial searches on Google, indicating broader usage and interest. JavaScript, with an 8.57% share in the PYPL Index, has traditionally dominated web application development and is now increasingly used in the AI domain. This is facilitated by libraries and frameworks that integrate AI functionalities into web environments, enabling web developers to leverage AI infrastructure directly. Notable AI frameworks like LlamaIndex and LangChain offer implementations in both Python and JavaScript/TypeScript. The GitHub 2023 State of Open Source report highlights JavaScript’s dominance among developers, with Python showing a 22.5% year-over-year increase in usage on the platform. This growth reflects Python’s versatility in applications ranging from web development to data-driven systems and machine learning. The programming language component of the AI stack is more established and predictable compared to other components, with Python and JavaScript/TypeScript solidifying their positions among software engineers, web developers, data scientists, and AI engineers. Model Providers Model providers are a pivotal component of the AI stack, offering access to powerful large language models (LLMs) and other AI models. These providers, ranging from small organizations to large corporations, make available various types of models, including embedding models, fine-tuned models, and foundational models, for integration into generative AI applications. The AI landscape features a wide array of models that support capabilities like predictive analytics, image generation, and text completion. These models can be broadly classified into closed-source and open-source categories. Closed-Source Models have privatized internal configurations, architectures, and algorithms, which are not shared with the model consumers. Key information about the training processes and data is withheld, limiting the extent to which users can modify the model’s behavior. Access to these models is typically provided through an API or a web interface. Examples of closed-source models include: Open-Source Models offer a different approach, with varying levels of openness regarding their internal architecture, training data, weights, and parameters. These models foster collaboration and transparency in the AI community. The levels of open-source models include: Open-source models democratize access to advanced AI technology, reducing the entry barriers for developers to experiment with niche use cases. Examples of open-source models include: Open-Source vs. Closed-Source Large Language Models (LLMs) AI engineers and machine learning practitioners often face the critical decision of whether to use open- or closed-source LLMs in their AI stacks. This choice significantly impacts the development process, scalability, ethical considerations, and the application’s utility and commercial flexibility. Key Considerations for Selecting LLMs and Their Providers Resource Availability The decision between open- and closed-source models often hinges on the availability of compute resources and team expertise. Closed-source model providers simplify the development, training, and management of LLMs, albeit at the cost of potentially using consumer data for training or relinquishing control of private data access. Utilizing closed-source models allows teams to focus on other aspects of the stack, such as user interface design and data integrity. In contrast, open-source models offer more control and privacy but require significant resources to fine-tune, maintain, and deploy. Project Requirements The scale and technical requirements of a project are crucial in deciding whether to use open-

June 15, 2024in Generative AI

AI Agents

Lessons Learned in the First Year of Developing AI Agents In the first year of working on AI agents, valuable insights emerged from direct collaboration with engineers and UX designers, as they iterated on the overall product experience. The objective was to create a platform for customers to use standard data analysis agents and build custom agents tailored to specific tasks and data structures relevant to their business. This platform integrates connectors to databases like Snowflake and BigQuery with built-in security, supports RAG over a metadata layer describing database contents, and facilitates data analysis through SQL, Python, and data visualization tools. Feedback on the effectiveness of these developments came from both internal evaluations and customer insights. Users from Fortune 500 companies utilize these agents daily to analyze their internal data. Key Insights on AI Agents Additional Insights Further insights on code and infrastructure include: These lessons underscore the importance of focusing on reasoning, iterative improvements to the agent-computer interface, understanding model limitations, and building robust supporting infrastructure to enhance AI agent performance and user satisfaction. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

June 4, 2024in Salesforce Einstein

14May

Zero Copy from Salesforce

When was the last time you relocated? Remember the hassle of packing up all your stuff, loading it onto a truck, and unpacking everything at your new digs, hoping it all survived the journey? Now, imagine if your furniture and possessions could simply teleport to your new location in perfect condition. While this may not be possible (yet) in the physical world, the concept of zero copy integration offers a similar seamless experience for handling customer data. Zero Copy from Salesforce. Zero copy integration, also known as zero ETL (extract-transform-load), allows data to be shared among multiple data stores without the need for actual movement or duplication. This is particularly advantageous for companies utilizing cloud data warehouses like Snowflake or Google BigQuery. Some companies hesitate to adopt a customer data platform (CDP) due to concerns about duplicating data. However, with zero copy integration, users can leverage the benefits of a CDP—such as data harmonization, identity management, built-in analytics, and activation—without the drawbacks of physical data movement. Some functions related to data have advanced with astonishing speed: generation, dissemination, storage, even security (and yes, that one still has many challenges). But there are others still mired in the stone age—call it the 80s—of the digital era. For example, think copies. How many business professionals still make multiple copies of sensitive data, just as it’s been done for the last four decades? What does this endless duplication do for regulatory risk, security threats and privacy liabilities? This is a symptom of a larger problem: Far from the data-centric universe we all envisioned, we’re beholden instead to the apps used to create, store, and distribute data. There’s an app for everything, but also a database for every app, leading to dozens of data silos undergoing hundreds of integrations, increasing fragmentation, complexity, and costs. The basic idea, according to Dan DeMers, Cinchy’s CEO, is that the framework aims to remove application data silos by using access-based data collaboration versus standard API-base data integration that involves copying data and branding it with complex app-specific coding. This would be done by access controls set in the data layer. It would also involve: What is Zero Copy Integration? Zero copy integration enables access to data stored in multiple databases simultaneously without the need to move, copy, or reformat the data. This approach not only facilitates faster and easier access to data but also reduces costs and minimizes the risk of errors associated with data movement or transformation. Comparing Traditional Methods with Zero Copy Integration: Traditional Methods: Zero Copy Integration: How It Works: From CDP to Data Warehouse In this scenario, data is accessed from the CDP and shared with the data warehouse, a process known as data sharing. The steps typically involve: How It Works: From Data Warehouse to CDP Conversely, in this scenario, data is accessed from the data warehouse and integrated into the CDP, a process referred to as data federation. The steps typically involve: Real-World Application: How Buyers Edge Utilizes Zero Copy Technology Buyers Edge, a leading procurement optimization company in the food service industry, leverages zero copy technology to access purchase data stored in a data warehouse while building a unified customer profile in a CDP. This allows them to provide better customer insights to their sales and marketing teams. By eliminating the need for data movement, duplication, or reformatting, zero copy technology streamlines data access, harmonizes data for insights and analytics, and provides a real-time holistic view of customers. As data volumes continue to grow exponentially, technologies like zero copy integration will play a crucial role in simplifying data management and facilitating seamless access to valuable insights. Whether it’s optimizing business processes or enhancing customer experiences, zero copy integration empowers organizations to navigate the data landscape with agility and efficiency. Be a zero copy hero and unlock the full potential of your data management strategy. “In today’s digital landscape, companies struggle with islands of data spread across various systems. With this global ecosystem of partners, companies can access all of their data, no matter where it resides, and unlock the power of all of that data within Salesforce — creating more personalized customer interactions and establishing a foundation for trusted AI, in less time and at lower cost.” Brian Millham, President and Chief Operating Officer at Salesforce The Zero Copy Partner Network features initial partners Amazon Web Services (AWS), Databricks, Google Cloud, and Snowflake, and adds Microsoft, all committed to zero copy integrations with Salesforce that give customers a secure and cost-effective way to connect and take action on all of their data New zero copy support for data warehouses and data lakehouses built on open table formats, like Apache Iceberg, with Salesforce Data Cloud, removes the need to copy or move data, so customers can unlock their data, powering Customer 360 experiences with AI, automation, and analytics The network includes Salesforce ISV partners, building new Zero Copy Data Kits to bring valuable new datasets to Salesforce Data Cloud, and Salesforce SI partners including Accenture, Cognizant, Deloitte Digital, and PwC, helping customers with zero copy Salesforce Data Cloud implementations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

May 14, 2024in Salesforce, Salesforce Data Cloud, Snowflake

21Apr

Harnessing Zero Copy Integration

Streamlining Data Management: Harnessing Zero Copy Integration for Efficient Customer Insights Zero copy integration offers a revolutionary approach to accessing and utilizing customer data without the need for burdensome data transfers. By seamlessly linking disparate databases, this innovative technique eliminates the complexities associated with moving, copying, or reformatting data. Let’s explore how zero copy integration can optimize data management processes and enhance the efficiency of customer data platforms (CDPs) alongside traditional data warehouses. Understanding Zero Copy Integration: Zero copy integration, also known as zero ETL (extract-transform-load), facilitates the sharing of data across multiple databases without physically relocating it. This method enables real-time access to data, significantly reducing costs and mitigating the risks of errors inherent in data movement processes. Unlike traditional data replication methods, zero copy integration ensures that data remains in its original location, eliminating the need for redundant storage and synchronization efforts. Good technology standards can actually bring order to the chaos and allow products from different companies to work together, fostering healthy competition and enhancing productivity. That is precisely what Zero-Copy Integration does. Zero-Copy Integration is a framework that eliminates the need for data copies and integration, making it easier to work with applications, analytics, artificial intelligence, and machine learning. Canada’s Digital Governance Council recently announced that Zero-Copy Integration has been published for open access by the public, setting a new standard for data collaboration. Moreover, Zero-Copy Integration prioritizes data-centricity and active metadata over complex code and solution modularity over monolithic design. It also facilitates data governance through data products and federated stewardship, eliminating the need for centralized teams. In addition to boosting the development and deployment of new technologies, Zero-Copy Integration also addresses the growing number of data privacy regulations. By putting data at the center of the process, Zero-Copy Integration ensures greater collaboration and control, positively affecting industries like healthcare, research, banking, and public services. Benefits of Zero-Data Integration Proponents of zero-copy integration and dataware say the framework will lower data storage costs, improve performance of IT teams, improve privacy and security of data, and drive innovation in systems for public health, social research, open banking and sustainability through innovations in: Comparing Traditional vs. Zero Copy Integration: Aspect Traditional Zero Copy Replication Requires copying data to target Data remains in original location Updates Data accuracy dependent on synchronization Real-time access to data Cost Involves data movement expenses No additional data movement costs Regulatory Compliance Complex governance due to data duplication Simplified compliance with source data only Errors Data movement introduces potential errors Minimized risk of errors with no data movement Maintenance Increases complexity with copying and synchronization Streamlined management with no data relocation Implementing Zero Copy Integration: The implementation of zero copy integration varies depending on the platform and direction of data access. Let’s explore how it works in scenarios involving Salesforce Data Cloud and Snowflake data warehouse: Case Study: Buyers Edge’s Zero Copy Success Story: Buyers Edge, a procurement optimization company, leveraged zero copy integration to unify customer profiles in a CDP while accessing purchase data from their data warehouse. By seamlessly integrating Salesforce Data Cloud with their warehouse, Buyers Edge enhanced predictive modeling capabilities, resulting in tailored sales and marketing strategies. Zero copy integration revolutionizes data management practices by enabling seamless data access and eliminating the need for data duplication or relocation. As businesses navigate the evolving data landscape, leveraging zero copy integration can streamline operations, enhance insights, and empower organizations to unlock the full potential of their data assets. MILESTONES / TIMELINE Second half 2023 – Internationalization February 21, 2023 – Information Session (watch above ☝ or via YouTube) February 15, 2023 – ‘Zero-copy’ applications published by DCA February 08, 2023 – Published by Digital Governance Council (Press release) December 15, 2022 – Approved by Standards Council of Canada June-Nov 2022 – Public consultation period Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

April 21, 2024in Salesforce, Salesforce Data Cloud, Salesforce Einstein, Snowflake

09Apr

What is Salesforce Einstein 1?

The bold new future of enterprise AI requires a new type of platform. What is Salesforce Einstein 1? One platform that can handle terabytes of disconnected data, gives you the freedom to choose your AI models, and connects directly into the flow of work, all while maintaining customer trust. The Einstein 1 Platform unifies your data, AI, CRM, development, and security into a single, comprehensive platform. It empowers IT, admins, and developers with an extensible AI platform, facilitating fast development of generative apps and automation. What is Salesforce Einstein 1 Einstein 1 has a mixture of artificial intelligence tools on the platform, and it kind of mirrors the way the core Salesforce platform is built, standardized and custom. We have out of the box AI features such as sales email generation in Sales Cloud, and service replies in Service Cloud. What is Einstein One? Einstein One seamlessly integrates our robust data platform with Data Cloud, offering a comprehensive AI and data-driven solution within our CRM service. As the leading comprehensive AI for CRM, Salesforce Einstein transforms the Customer Success Platform by incorporating a suite of integrated AI technologies, making it more intelligent and accessible to innovators worldwide. Introducing the Einstein One Platform The future of enterprise AI demands a groundbreaking platform capable of managing terabytes of diverse data, providing the flexibility to select AI models, and seamlessly integrating into daily workflows while maintaining customer trust. The Einstein One Platform consolidates data, AI, CRM, development, and security into a singular, comprehensive platform. It empowers IT, administrators, and developers with an extensible AI platform, facilitating rapid development of generative apps and automation. Salesforce has made significant investments in enhancing the Einstein One platform by introducing two prompt engineering features – a testing center and prompt engineering suggestions, demonstrating the company’s commitment to advancing AI capabilities. Data-driven and AI-driven customer experiences are vital in constructing Data Cloud. Salesforce’s predictive AI, Einstein, has been operational since 2016, conducting over a trillion predictions per week. The company continuously evolves its capabilities, introducing generative AI products like Einstein GPT, discussed at Dreamforce [2023]. ‘Customer 360′ now represents Salesforce customers’ ability to transform into customer-centric entities, delivering integrated and cohesive experiences across sales, marketing, service, and commerce. Leveraging Data Cloud, structured and unstructured engagement data comes alive, offering a personalized perspective of customer interactions. Einstein is accessible through various Salesforce products, including Sales Cloud, Service Cloud, Marketing Cloud, Salesforce Platform, Analytics Cloud, and Community Cloud. What is the Einstein One platform? Salesforce’s Einstein One is a transformative platform that securely integrates data, connects multiple Salesforce products, and empowers customer-centric businesses to create AI-driven apps, revolutionizing CRM interactions. What applications are connected with the Einstein One platform? Einstein Trust Layer: Ensuring the security of generative AI applications within Salesforce, this application acts as a safeguard for data, preventing unauthorized access. Data Cloud: Unifying structured and unstructured data, Data Cloud completes the customer 360 profile, integrating seamlessly with the Einstein One platform and making data actionable. Einstein Copilot: A built-in conversational assistant, Einstein Copilot enables users to ask questions in Natural Language and receive intelligent answers, actions, and more. Copilot Studio: An essential component of Einstein One, Copilot Studio manages Einstein One and Einstein Copilot, allowing businesses to control user access and use generative AI in their workspace. Prompt Builder, Skill Builder, Model Builder: Tools within Copilot Studio, these components empower businesses to create trusted AI prompts, add skills to user access, and choose AI models. What is Data Cloud for Einstein One? Data Cloud, combined with the Einstein Trust Layer, provides secure access to a unified data repository, forming a reliable resource for complete customer profiles and supporting AI assistants. Data Cloud facilitates valuable visualizations through reports, dashboards, and tools like Tableau, offering insights to enhance understanding of customers and business operations. What will Einstein One do for businesses? Einstein One aims to: Increase productivity Reduce operational costs Enhance the delivery of exceptional customer experiences The debut of Einstein One marks a significant stride for Salesforce and businesses, offering a secure path to boost productivity through AI technologies, ensuring continuous access to cutting-edge technologies for businesses. Where can generative AI impact businesses today? Generative AI has the potential to impact businesses by enhancing repetitive processes, making them faster. Exploring text-based processes, such as repetitive emails or form filling, is a great starting point for businesses looking to enhance capabilities. What can generative AI do for sales, service, field service teams? Generative AI can positively impact teams by automating processes, offering intelligent insights, and improving overall efficiency. Specific use cases for generative AI in sales, service, and field service teams can be explored through Salesforce’s 101 video series. What does Einstein One Tableau do? Einstein One Data Cloud, formerly known as Genie, serves as a metadata management tool connecting data from various sources. It makes data usable for AI and analysis, integrating with Einstein One, Tableau, and Salesforce’s CRM applications. Is Salesforce Einstein the same as Tableau? Formerly known as Einstein Analytics, Tableau CRM is Salesforce’s premium analytic platform, offering a powerful way to explore data, especially for current Salesforce users. Salesforce has renamed Einstein Analytics to Tableau CRM, reflecting its commitment to empowering users to make better decisions faster. In essence, the Einstein One platform combines Salesforce Data Cloud, Einstein Copilot, and the Einstein Trust Layer, providing a comprehensive solution for secure and connected data, facilitating generative AI on a comprehensive platform. Salesforce’s Einstein One Platform & the Data-Driven Revolution This innovation has the potential to revolutionize the way businesses interact with their customers. In this insight, we delve deeper into this transformative development, offering valuable insights, considerations for implementation, and the indispensable expertise of Tectonic as a data-oriented technology partner. Salesforce Data Cloud and Einstein AI are now seamlessly integrated into the Einstein One Platform. This integration empowers companies to effortlessly connect their diverse data sources, enabling the creation of AI-driven applications with minimal coding effort. Moreover, it forges a cohesive view of your data across

April 9, 2024in Artificial Intelligence, Data, Einstein 1 Platform, Einstein Insights, Enterprise, Generative AI, Google, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Salesforce Sales Cloud, Technology

31Mar

Legacy Salesforce URL Redirection Retires

Legacy Salesforce URL Redirection Retires – Salesforce Announcement Security Notification At Salesforce, we understand that the confidentiality, integrity, and availability of your data is vital to your business, and we take the protection of your data very seriously. We’re writing to remind you that redirections for some of your Salesforce orgs’ URLs stop in the Winter ’25 release, starting in August 2024 for sandboxes and in September 2024 for production orgs. We highly encourage you to test for this change and update all references to your previous URLs before those redirections stop. Security Notification Why the Change? To comply with the latest browser and security standards, Salesforce recently required that customers deploy enhanced domains. This feature updated the hostname formats for the domains that serve Salesforce orgs. To reduce the impact of this change, your previous hostnames are redirected by default. However, to meet Salesforce security standards, some of the previous domains will be retired in 2024. The corresponding redirections stop in the Winter ’25 release. Why the Change? Actions Required Review the affected hostnames and how you can disable the redirections for testing. For details, see Prepare for the End of Redirections for Non-Enhanced Domains in Salesforce Help. Additional Resources Salesforce Enhanced Domains FAQSalesforce Help: Prepare for the End of Redirections for Non-Enhanced DomainsSalesforce Help: Log My Domain Hostname RedirectionsSalesforce Help: Enhanced Domains TimelineTo ask questions about enhanced domains, visit our monitored My Domain and Enhanced Domains group in the Trailblazer Community.We appreciate your trust in us as we continue to make your success and security our top priorities. Additional Resources Legacy Salesforce URL Redirection Retires Prepare for the End of Redirections for Non-Enhanced Domains After enhanced domains are deployed, your previous non-enhanced hostnames are redirected. Those redirections stop in Winter ’25, starting in August 2024 for sandboxes.. Review the affected hostnames and how you can disable the redirections to test before Salesforce disables them. REQUIRED EDITIONS Available in: both Salesforce Classic (not available in all orgs) and Lightning Experience Available in: Group, Essentials, Professional, Enterprise, Performance, Unlimited, and Developer Editions After enhanced domains are deployed, Salesforce redirects two categories of non-enhanced hostnames. To see if redirections are in place for a previous My Domain, check the Redirections section of the My Domain Setup page. NOTE My Domain URL redirections help prevent disruption, but they’re not intended as a permanent solution. Not all services work well with redirections, and a redirection adds a step to the process of loading the final web page. When you deploy enhanced domains, we highly recommend that you disable redirections during testing and update all references to your old URLs. Track the Source of Redirections You can search the metadata for your org to determine where the impacted URLs are used in Salesforce, but discovering all the other places that your URLs are used can be more complex. For example, site URLs and content URLs can be used on your website, social media pages, marketing materials, and templates such as email signatures and automated responses. To help you identify these locations outside of Salesforce, the Hostname Redirects log includes the referrer and origin sent with each request that Salesforce redirects. For more information, see Log My Domain Hostname Redirections. Notify Users During Redirections To help your users update outdated links and bookmarks, display a brief message during the redirection that provides the current URL. See Manage My Domain Redirections. Previous *.force.com Site Hostnames When you enable and deploy enhanced domains, the hostname formats change for your Experience Cloud sites and Salesforce Sites. To minimize potential disruption, the *.force.com hostnames that Salesforce hosted for your sites are redirected to your current site hostnames. Those redirections remain in place until Winter ’25 or until you disable these redirections. To disable these redirections for testing purposes, use an option in the Redirections section of the My Domain page and test. For more information, see Disable Redirections for Your Previous Force.com Site URLs. For the replacement format for each of these hostnames, see My Domain URL Format Changes When You Enable Enhanced Domains. To better understand the purpose of each hostname type and whether it applies to you, see My Domain Hostnames. Here are the *.force.com site hostnames for a production org that are temporarily redirected after you enable and deploy enhanced domains. Here are the .*force.com site hostnames for a sandbox that are temporarily redirected after you enable and deploy enhanced domains. Other Non-Enhanced My Domain Hostnames When you enable and deploy enhanced domains, your other previous non-enhanced My Domain hostnames are redirected. Those redirections remain in place until Winter ’25 or until you disable these redirections. For the type and the replacement format for each of these hostnames, see My Domain URL Format Changes When You Enable Enhanced Domains. To better understand the purpose of each hostname type and whether it applies to you, see My Domain Hostnames. NOTE If you deploy another My Domain change after you enable and deploy enhanced domains, these hostnames are no longer redirected. For more information, see Understand Redirections for Previous My Domain Hostnames. To disable the redirections of these non-enhanced My Domain hostnames for testing purposes, you can temporarily disable your previous My Domain. For more information, see Disable or Remove Your Previous My Domain. Here are the non-enhanced hostnames for a production org that are temporarily redirected after you enable and deploy enhanced domains. Here are the non-enhanced hostnames for a sandbox that are temporarily redirected after you enable and deploy enhanced domains. 1 If your installed package is unmanaged, the package name is c. Instanced URLs Without My Domain If your org was created before October 2020, you didn’t get a My Domain by default. In that case, your users accessed Salesforce with these hostnames that contained your instance name but not your My Domain name. These hostnames are redirected if the Instanced URL setting in the Redirections section on the My Domain Setup page is set to Redirect to the same page within the domain

March 31, 2024in Hyperforce, Salesforce, Salesforce Experience Cloud

16Jan

Salesforce Developer Toolkit

Have you ever been overwhelmed by a complex project with numerous tasks and deadlines? I felt the same until I discovered Salesforce tools. One afternoon, a colleague introduced me to these tools, and everything changed. Suddenly, I could manage my work more effectively, collaborate better with my team, and consistently deliver outstanding results. Salesforce tools completely transformed the way I work. They showed me that with the right technology, teams don’t just meet expectations—they exceed them, driving better business performance. Let’s explore how Salesforce tools can lead to better development outcomes and help you stay ahead of the competition. Key Takeaways Understanding Salesforce Development Tools Diving into Salesforce development tools reveals how essential they are for boosting productivity and streamlining processes. Each tool plays a unique role in making Salesforce adaptable for developers. For instance, using the Salesforce Developer Edition allows me to test apps without real data, helping me create better solutions. Scratch Orgs provide a space to develop apps for specific needs, offering flexibility in my work. The Salesforce CLI simplifies managing and integrating different tools, enhancing my overall development workflow. By learning and mastering these tools, I’ve significantly improved my technical skills, gaining confidence to tackle various projects knowing I have the right tool for each task. Key Benefits of Using Salesforce Tools Salesforce tools have revolutionized how we work and engage with clients. One of the standout benefits is the clear visibility into customer data. This makes our interactions more personalized and effective, as everyone on the team has access to the necessary customer information. Team collaboration also becomes more seamless. Sharing vital information removes delays, streamlining the development process and ensuring we all work towards the same goals. Automation is another game-changer. It reduces manual tasks, allowing us to focus on high-value activities. Companies that embrace these tools often see improved sales and overall business performance. Salesforce Tools for Better Development The right tools can transform your development process. Salesforce tools enhance every aspect, from understanding customer needs to improving team collaboration. By making both teams and customers more visible, these tools lead to better strategies and outcomes. Improved Customer Visibility Customer insight is crucial to business success. Salesforce tools provide immediate access to customer data, enabling us to tailor services to meet their needs. I can now predict trends and respond quickly, enhancing the customer experience. This visibility also allows businesses to adjust plans rapidly, leading to faster improvements. Enhanced Collaboration Across Teams Collaboration is key to success. Salesforce tools enable seamless communication and information sharing across teams, reducing errors and making development smoother. As teams work more efficiently together, productivity rises, and customer satisfaction improves. These tools have fundamentally changed how my team operates, driving us toward our goals. Getting Started with Salesforce Tools When I began exploring Salesforce tools, I realized how crucial it was to understand the setup process. It’s not just about choosing the right tool—it’s about selecting one that aligns with your business needs. I spent considerable time researching and selecting the best tools for my organization, which resulted in smoother operations. Setting up accounts in an organized manner also prevented potential issues down the line. Training was equally important. I provided my team with comprehensive resources and hands-on experience with Salesforce tools. This approach ensured everyone was prepared to use the tools effectively and enhance our productivity. Salesforce Developer Toolkit For a Salesforce developer, the Salesforce Developer Toolkit is essential to improving workflow and productivity. Using the right tools significantly enhances both efficiency and output quality. Essential Tools for Every Salesforce Developer The toolkit includes indispensable tools like the Developer Console and Salesforce Extensions for Visual Studio Code. These make coding easier and allow for better testing and debugging. The Ant Migration Tool is invaluable for transferring project components, tracking changes, and deploying updates seamlessly. Streamlining Development Processes with Salesforce By utilizing the Salesforce Developer Toolkit, I’ve accelerated development processes. Integrated environments and robust command-line interfaces make app deployment faster. These tools enhance my coding efficiency, allowing me to deliver exceptional Salesforce apps to clients with speed and precision. Top Salesforce Tools to Consider When starting with Salesforce, it’s essential to identify the tools that best meet your needs. Salesforce Lightning, Salesforce CLI, and Workbench stand out for their powerful features and benefits. Salesforce Lightning Salesforce Lightning simplifies app development with its intuitive interface. Its drag-and-drop functionality enables quick assembly of components, allowing me to focus on adding value rather than technical complexities. Salesforce CLI For developers who prefer command-line interfaces, Salesforce CLI is an excellent choice. It automates tasks, improves workflow efficiency, and reduces errors, ultimately enhancing productivity. Workbench and the Ant Migration Tool Workbench is a versatile tool for managing data and running SOQL queries, making it a favorite among developers. The Ant Migration Tool ensures smooth metadata transfers between Salesforce environments, ensuring seamless development. Optimizing Salesforce Development Processes Optimizing development in Salesforce involves improving efficiency and productivity. Automated testing, for instance, simplifies repetitive tasks, allowing developers to focus on more complex challenges. Using scratch orgs for feature branches is another winning strategy. It enables developers to work on new features without affecting the main codebase—a must in fast-paced environments. Agile methodologies also transform development processes. Iterative practices ensure that workflows stay up-to-date with evolving requirements, and continuous feedback drives consistent improvement. Integrating Third-Party Tools with Salesforce When enhancing my Salesforce setup, I often consider third-party integrations. Salesforce AppExchange offers a variety of apps that can be tailored to fit specific business needs. This flexibility is invaluable. Salesforce API integration makes it easy to connect Salesforce with other apps, allowing for better data management and automation. By leveraging these integrations, I’ve enhanced workflows and improved efficiency across the board. Best Practices for Enhancing Salesforce Development Maximizing Salesforce development success depends on following best practices, such as leveraging automation and community resources. Automating Routine Tasks with Salesforce Tools Automation is central to my daily routine. Tools like Process Builder and Workflow automate repetitive tasks, saving time

January 16, 2024in Data, Salesforce, Technology

salesforce marketing cloud interaction studio

03Aug

Marketing Cloud and Einstein

AI has emerged as an effective solution to tackle the challenges arising from the sheer volume and rapidity of data in the marketing landscape. This article delves into some cutting-edge functionalities presented by Einstein within the Salesforce Marketing Cloud, showcasing how these features empower marketers to enhance performance and streamline their workflows. Einstein for Marketing Cloud uses Salesforce’s AI to help you best evaluate and implement your marketing activities. Use valuable insights on audiences, send time, engagement frequency, and your content to best target your customers. Deliver information to your customers when they need it and how they need it. Einstein in Marketing Cloud offers a range of opportunities for you to analyze, automate, and optimize your content. Use the apps throughout Marketing Cloud platforms to gain insight and better target your audiences. Salesforce Einstein for Marketing Cloud In the dynamic realm of marketing and sales, the pursuit of refining strategies is perpetual. Einstein Social Insights Within the Marketing Cloud’s Social Studio feature, marketers can publish content, engage in conversations, and analyze social data. Einstein augments this platform, introducing AI-powered capabilities: These advanced features empower marketers to optimize social strategy, fostering brand loyalty. For instance: Einstein Vision for Social With over 3 billion images uploaded to social platforms daily, Einstein Vision for Social equips marketers to analyze and derive insights from images. Marketers can train Social Studio to recognize images related to their brand, including products, logos, scenes, and food. This enriched data allows for a deeper understanding of brand followers, facilitating engagement and measurement of marketing efforts. Lookalikes Einstein lookalikes leverage lookalike modeling, identifying common traits among current customers to target new customers with similar characteristics. This tool streamlines the process, allowing marketers to create rich audiences and segments for modeling purposes using first, second, and third-party data in Audience Studio. Einstein Journey Insights In today’s consumer-centric world, Einstein Journey Insights helps marketers comprehend customer journeys by tracking interactions across touchpoints like web browsing and email. Advanced attribution modeling enhances engagements and event sequences, leading to specific goals such as purchases or product reviews. Interactive reports and visualizations enable marketers to optimize campaigns by comparing planned journeys with organic consumer journeys. Einstein Content Tagging Personalized and engaging messages demand an organized library of content. Einstein Content Tagging and image recognition technology automatically add and update content tags and metadata, helping marketers manage their assets efficiently. Smart Orchestration Einstein Send Time Optimization determines the best time to send an email or push notification. Einstein Engagement Frequency evaluates your contacts and identifies the optimal number of email messages or push notifications to send. Marketing Cloud Intelligence As marketing budgets increase, the need for ROI and superior customer experiences rises. Marketing Cloud Intelligence delivers AI-generated insights through automated regression modeling and statistical analysis. Einstein Marketing Insights sifts through data to identify high and low performers, enabling marketers to make informed decisions swiftly and optimize strategies for better results. The Einstein features in Salesforce Marketing Cloud present myriad opportunities for marketers to optimize their performance and work more efficiently. By harnessing these AI-powered capabilities, marketers can make informed decisions rapidly, fostering better brand engagement and higher ROIs. Tectonic is ready to assist you in deploying Einstein for Marketing Cloud. Contact us today. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

August 3, 2023in Data, Einstein Insights, Marketing Automation, Salesforce, Salesforce Einstein, Salesforce Marketing Cloud, Technology

15Jul

Salesforce Analytics Acronyms

Here is a helpful list of analytics acronyms you may encounter when discussing Salesforce. Salesforce Analytics Acronyms Acronym Meaning Definition AWS Amazon Web Services AWS offers “reliable, scalable, and inexpensive cloud computing services…the world’s most comprehensive and broadly adopted cloud, offering over 200 fully featured services from data centers globally.” (source)Multiple Salesforce products use AWS; however, it’s prominent in the analytics arena, where organizations rely on AWS to:”Extract, prepare, and analyze Salesforce.com data using Amazon AppFlow, AWS Glue DataBrew, and Amazon Athena.” (source) BYOAI Bring Your Own AI ‘Bring your own AI (model)’ is Salesforce’s way to meet their customers where they’re at. With Data Cloud, Salesforce not only supports Einstein (their own LLM), but also other ones like Sagemaker, Vertex AI, etc. BYOM Bring Your Own Model ‘Bring your own AI (model)’ is Salesforce’s way to meet their customers where they’re at. With Data Cloud, Salesforce not only supports Einstein (their own LLM), but also other ones like Sagemaker, Vertex AI, etc. CRMA CRM Analytics This is the analytics/business intelligence (BI) solution on the Salesforce platform, integrating Salesforce data with external data and provides the ability to analyze large datasets while performing predictive analytics. (Previously known as Wave/Einstein Analytics/Tableau CRM). EA Einstein Analytics The former name for CRM Analytics (also formerly Tableau CRM). You may still come across EA in outdated documentation. GPT Generative Pre-trained Transformer GPT is a technology concept, although it’s often mistaken for a product name (with the rise of the wildly popular ChatGPT). LLM Large Language Model An AI model that has been trained using lots of data. Salesforce has their own LLM that outperformed expectations during testing. Salesforce’s LLM leverages Data Cloud, or can be plugged into a different data lake. Organizations can also opt to their own LLM alongside their Salesforce data. NBA Einstein Next Best Action An AI-driven Salesforce product that makes recommendations to users when they are working with records in Salesforce. It appears within a Lightning component that’s typically placed on the record page sidebar. The user can choose to Accept or Reject the recommendation. NLP Natural Language Processing “Artificial intelligence that focuses on how computers can understand, interpret, and generate human language. NLP allows customers to interact with systems using normal human language rather than complex commands.” (source) SAQL Structured Query Language “Use SAQL to access data in Tableau CRM dataset. Tableau CRM uses SAQL behind the scenes in lenses, dashboards, and explorer to gather data for visualizations.” (source) TCRM Tableau CRM Tableau CRM is a self-service data visualization and business intelligence (BI) platform that integrates Salesforce data with external data. Formerly known as Einstein Analytics, and now CRM Analytics, this product boasts some of the most powerful data analysis capabilities in the market. XMD Extended Metadata “Enables you to customize the formatting of dataset fields and their values in Analytics dashboards and lenses.” (source) Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

July 15, 2023in Salesforce

16Jun

Codescan Salesforce

Codescan Salesforce by AutoRABIT is a static code analysis solution that provides visibility into code health from the first line written through final deployment into production. Reliable code analysis directly on the AutoRABIT DevSecOps platform drives Salesforce development quality, speed, and security. The quick code scan tool is free of charge at this time. Code Scanning Definition Code scanning is the process of examining code to identify bugs, errors, and security flaws. Any issues found are displayed, enabling you to address them quickly and enhance the security of your application. What is the CodeScan tool for Salesforce? CodeScan Shield is the leading end-to-end static code analysis solution for code security and quality. Lightning ready and exclusively for the Salesforce platform, CodeScan increases productivity, quality, and security for all Salesforce DevOps teams. What does static code analysis do? Static analysis is a method of debugging that is done by automatically examining the source code without having to execute the program. This provides developers with an understanding of their code base and helps ensure that it is compliant, safe, and secure. The most comprehensive code analysis tool supporting SF languages and metadata. Track and control your SF code quality with CodeScan. Robust Analysis for High-Quality Code and Intuitive Governance Total visibility over the health of your environment reduces costs and increases time to market. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

June 16, 2023in Salesforce

25May

Salesforce Revenue Cloud Integration

Integrating Revenue Management with Salesforce Revenue Cloud If your organization utilizes both Revenue Management and Salesforce Revenue Cloud Integration, you can seamlessly integrate them using the Revenue Cloud Connector feature available in Feature Console. Enabling this feature configures your org with a standardized integration, allowing Revenue Management to effectively recognize revenue and costs against Salesforce orders. Key Integration Capabilities By enabling the Revenue Cloud Connector feature, you benefit from: Hierarchical Structure of Recognition Settings The integration creates recognition settings records for Salesforce objects organized in the following hierarchical structure: Level 2 Objects: Level 3 Objects: Level 4 Objects: Recognition Transactions The resulting recognition transactions encompass transaction lines generated from: Additional Considerations Revenue Contracts for Revenue Cloud For organizations creating revenue contracts for Salesforce orders, enabling the “Revenue Contracts for Revenue Cloud” feature is recommended. This feature streamlines the creation of revenue contracts via engagements linked to orders: For comprehensive details regarding fields, recognition settings, and templates established upon feature activation, refer to “Metadata Changes when Enabling Revenue Cloud Connector.” Instructions for enabling the feature are available under “Enabling Revenue Cloud Connector.” By leveraging these integrative features, organizations enhance their ability to manage revenue recognition efficiently and maintain compliance with regulatory standards. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

May 25, 2023in Salesforce Revenue Cloud

14May

Salesforce FlowLog

Admins sometimes wonder if their work is being used effectively. Salesforce FlowLog is a great solution. While it’s easy to track whether fields are being filled out or new records are being created, many of the things built—such as background flows that automate processes—are harder to measure. These automations often run behind the scenes, making their impact less visible. Building, testing, and debugging automations can be challenging, even with the improvements in Flow Builder. Sometimes visualizing the process within a flow can be difficult. In screen flows, it’s possible to add interstitial screens to display variable values or messages to track progress. However, in record-triggered flows, which operate invisibly during or before record saving, tracking what’s happening becomes more complex. To address this, some admins use Chatter posts, either on created or updated records or tagged to a special Chatter Group for aggregation: A Chatter Group page showing a post indicating a contact was updated by the Skyvia integration user. Tasks can also be used for tracking, as they are easy to create and relate to updated records: Classic contact page with an image formula displaying the organization’s logo and status. While these methods are useful for debugging, they are not ideal for reporting on flow activity or capturing structured data. Introducing FlowLog To address these limitations, a custom object called “FlowLog” was created specifically for logging flow activities. This object includes fields for the flow name, version, step, and notes. The records are auto-numbered for easy sorting by creation time. Once the FlowLog object was set up, adding a Create Record step in any flow became straightforward: Assignment step setting values for FlowLog record. Easier with a Subflow To simplify the process further, an autolaunched flow was created and named “FlowLog.” This subflow can be included in other flows to log steps along the path or different decision paths: A flow canvas showing the FlowLog subflow used at different decision points. Avoiding Redundancy Rather than recreating the custom object and subflow for each new client, it is more efficient to store and install these elements multiple times. Three main methods to achieve this are: File viewer in VisualStudio Code displaying FlowLog object, fields, and flow definitions. Salesforce FlowLog None of these solutions are groundbreaking, but they offer practical approaches anyone can use. Creating a FlowLog object similar to the one described is encouraged. Sharing a public GitHub repo might seem too straightforward, so exploring and setting up these solutions independently is recommended. Now, equipped with these ideas, it’s time to get hands-on with Salesforce Setup. ⚙️ Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

May 14, 2023in Salesforce

21Oct

SysCloud Backup for Salesforce

Introducing SysCloud Backup for Salesforce. Protect and manage your critical SaaS applications seamlessly: Enhanced Backup Capabilities: Simplify Backups with Sky – Our AI Copilot: Addressing Salesforce’s Native Data Retention Limitations: SysCloud Shared Drives Backup: Effortlessly Protect Your Salesforce Data: Pricing and Compatibility: Superfast SOC-2 Compliant Backups: Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

October 21, 2022in Salesforce

13Jun

Druva – Salesforce Data Backup and Recovery

Introducing Druva: Your Comprehensive Salesforce Data Management Solution. Druva – Salesforce Data Backup and Recovery Druva presents a comprehensive data management solution tailored specifically for Salesforce users. By seamlessly integrating data protection, sandbox seeding, and archiving functionalities, Druva streamlines tedious tasks, ensuring enhanced data security, improved efficiency, and reduced ownership costs. Why Opt for Druva with Salesforce? Where Does Druva Store Backups? Druva securely backs up your data in the cloud hosted by Amazon Web Services (AWS), leveraging AWS’s robustness and stringent security standards to guarantee the safety and confidentiality of your backup data. Key Features of the Druva Platform: Explore Druva with a Free POC: Every Salesforce platform is unique, which is why Druva offers a free Proof of Concept (POC) allowing you to test against your data with full access to their support team, providing confidence in the platform’s capabilities. Druva’s Data Protection Platform: Druva’s Software-as-a-Service (SaaS) platform offers data protection across data centers, cloud applications, and endpoints. Securely backup and recover data with the scalability and simplicity of the public cloud, paying only for what you use, and enhance data governance with search and analytics capabilities to unlock the full potential of your data. FAQs: Druva offers a robust and secure solution for Salesforce data management, ensuring reliable backup, efficient recovery, and streamlined operations. With its user-friendly interface and advanced features, Druva empowers organizations to focus on their core objectives while ensuring the integrity and security of their critical data. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

June 13, 2022in Salesforce

08Feb

Snowpark Container Services

Snowpark Container Services is a fully managed solution designed to simplify deploying, managing, and scaling containerized applications within the Snowflake ecosystem. Key Features Benefits of Snowpark Container Services in Native Apps Integrating Snowpark Container Services into Snowflake Native Apps enables developers to create solutions for various use cases, including: Developers benefit from Snowflake’s Native Apps Framework safeguards, which ensure secure and efficient operations. Development Workflow for Snowpark Container Services Here’s a quick guide to the development cycle for building and deploying containerized services within Snowflake. 1. Develop Code Locally 2. Build and Push an Image 3. Provision Resources 4. Deploy and Test Services Getting Started To build containerized applications with Snowpark Container Services: For a deep dive into architecture and workflows, explore Snowflake’s guides and tutorials on Snowpark Container Services and Native Apps. The Snowflake Native Applications Framework allows developers to package Snowflake features into standalone applications that can be installed across multiple accounts. This framework now supports advanced features for managing resource provisioning and deploying container services. Below is an overview of how to integrate container services into a Native App. Key Components 1. Manifest File The manifest file defines the configuration and setup properties for the application, including: Example Manifest File: Specifying Container Images yaml Copy code manifest_version: 1 version: name: V1 label: “Version One” comment: “The first version of my amazing Snowflake Native App” artifacts: readme: readme.md setup_script: scripts/setup.sql container_services: images: – /provider_db/provider_schema/provider_repo/server:prod – /provider_db/provider_schema/provider_repo/web:1.0 Here: Setting a Web UI as the Landing Page For apps with a web UI, specify a default_web_endpoint field to make the UI the landing page. yaml Copy code default_web_endpoint: service: ux_schema.ux_service endpoint: ui Here, service corresponds to the name defined in the CREATE SERVICE command, and endpoint refers to the service’s endpoint in the specification file. Using Streamlit as a Landing Page Alternatively, you can specify a default_streamlit field to use Streamlit as the landing page. Note: default_web_endpoint and default_streamlit are mutually exclusive—you can only use one. 2. Setup Script The setup script executes during the application installation and upgrade processes. It contains SQL statements for creating: Resource Provisioning for Snowpark Container Services The setup script also includes logic for provisioning resources like compute pools. However, these provisioning procedures are executed post-installation to ensure the consumer has granted the necessary privileges. Managing Compute Pools and Privileges Consumer-Controlled Resource Provisioning A foundational principle of the Snowflake Native Apps Framework is that consumers maintain full control over the resources the application accesses. This includes compute resources. Privileges Required To enable an application to provision resources, specific privileges must be requested in the manifest file: Example Privileges in the Manifest File yaml Copy code privileges: – CREATE COMPUTE POOL description: “Enable application to create its own compute pool(s)” – BIND SERVICE ENDPOINT description: “Enables application to expose service endpoints” Note: These privileges are not granted by default. The installation user may need to request them from another user with the appropriate permissions within the organization. By wrapping container services into a Snowflake Native App, developers can: This approach ensures that both providers and consumers retain control over their resources and data, while maximizing the capabilities of Snowflake Native Apps. Managing Privileges and Deploying Services in Snowflake Native Apps Once a Snowflake Native App is installed, consumers can grant the necessary privileges through various supported mechanisms. Here’s an overview of how to configure privileges, deploy services, and manage app components effectively. Granting Privileges 1. Snowsight UI Configuration Snowflake Native Apps with Snowpark Container Services provide a custom Snowsight configuration UI. When privileges are granted via this UI, it triggers the app’s grant_callback procedure specified in the manifest file. This procedure receives a list of privileges as input, making it ideal for initiating resource provisioning, such as creating compute pools. For containerized apps, this is the recommended approach. Example Manifest Configuration: yaml Copy code manifest_version: 1 configuration: log_level: debug trace_level: always grant_callback: setup.grant_callback 2. Streamlit Integration Using Snowflake’s Permissions SDK, developers can create Streamlit-based pop-ups to request privileges. After privileges are granted through the pop-up, resource provisioning can begin. Specify Streamlit as the landing page in the manifest using the default_streamlit field. This configuration allows Streamlit to invoke the necessary resource provisioning procedures. 3. SQL Worksheet Consumers preferring SQL-based interaction can grant privileges and execute resource provisioning procedures directly through the SQL worksheet. Example Grant Callback Procedure: sql Copy code CREATE OR REPLACE PROCEDURE setup.grant_callback(privileges ARRAY) RETURNS STRING AS $$ BEGIN CREATE COMPUTE POOL IF NOT EXISTS backend_compute_pool MIN_NODES = 1 MAX_NODES = 1 INSTANCE_FAMILY = CPU_X64_XS; CALL services.start_backend(‘backend_compute_pool’); RETURN ‘Callback successful’; END; $$; GRANT USAGE ON PROCEDURE setup.grant_callback(ARRAY) TO APPLICATION ROLE app_public; This procedure creates a compute pool and then calls another procedure to set up services within the pool. Deploying Services Once compute pools are created, the application can deploy one or more services. Scenario 1: The App Has All Required Resources If the app has everything it needs, it can directly execute CREATE SERVICE commands in the grant_callback procedure to set up its services. For services requiring warehouses, the app can request the CREATE WAREHOUSE privilege in the manifest and create warehouses as needed. Scenario 2: The App Needs Additional Consumer Resources If the app requires additional objects (e.g., external access integrations or secrets) from the consumer, references can be used. A reference includes a register_callback procedure that binds the required resources. This procedure can also trigger service creation after the reference is bound. Example Register Callback Procedure: sql Copy code CREATE OR REPLACE PROCEDURE v1.register_single_callback(ref_name STRING, operation STRING, ref_or_alias STRING) RETURNS STRING LANGUAGE SQL AS $$ BEGIN CASE (operation) WHEN ‘ADD’ THEN SELECT SYSTEM$SET_REFERENCE(:ref_name, :ref_or_alias); CASE (:ref_name) WHEN ‘external_access_backend_reference’ THEN CALL services.start_service_with_egress(); WHEN ‘secret_reference’ THEN CALL services.start_service_using_secret(); END CASE; WHEN ‘REMOVE’, ‘CLEAR’ THEN SELECT SYSTEM$REMOVE_REFERENCE(:ref_name); ELSE RETURN ‘Unknown operation: ‘ || operation; END CASE; RETURN ‘Operation ‘ || operation || ‘ succeeds.’; END; $$; This procedure: Packaging Service Specifications Service creation requires specification files, which must be included in the app package (typically alongside the manifest.yml). These files define the service

February 8, 2022in Data, Snowflake

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