We are a family-owned neighborhood breakfast and lunch restaurant located near Los Angeles International Airport (LAX). We take pride in providing friendly and swift service to our local patrons and those who are traveling or are &quot;on the go&quot;. Join us for &quot;Good Food &amp; Good Company

The Coffee Company

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New England Coffee – Count On Every Cup.

Ritesh Agarwal invested in a coffee company on a recent episode of Shark Tank India. He called the pitchers &#x27;baazigar&#x27; and was the only investor who offered them a deal.

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Delivery &amp; Pickup Options - 2242 reviews of The Coffee Company &quot;This place always has a line out the door on the weekends (maybe because of the churches across the street) but it&#x27;s worth it. We usually split a skillet and pancakes or french toast. Soooo yummy.

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At Bones Coffee Company, coffee isn&#x27;t just a drink that wakes you up in the morning; it&#x27;s an experience. One sip and you&#x27;ll discover why our freshly roasted coffee is leagues above the ...

Bones Coffee Company - Say Goodbye to Boring.

More than just great coffee. Explore the menu, sign up for Starbucks® Rewards, manage your gift card and more.

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At Community Coffee, we’ve discovered the recipe for the perfect cup of coffee: rich heritage, premium coffee beans, and dedication to our community.

Community Coffee | #1 Family-Owned Retail Coffee Brand in America

1050 S Coast Hwy, St B Laguna Beach, CA 92651 · Open 5:30am-4pm daily

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Live with a Death Wish. Death Wish Coffee Company delivers a bold, full-bodied yet flavorful brew that will awaken your taste buds, with an extra kick of caffeine to ignite your attitude. Made with Fair Trade and Organic beans.

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CFCF Coffee is a premier coffee &amp; pastry shop serving the Greenwich &amp; Stamford, CT area. For freshly roasted coffee and delicious breakfast options, visit us today!

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Joe Coffee Company is a family-owned coffee shop in New York City dedicated to making flawless coffee served with warm hospitality.

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Estate Coffee Company is a small batch, craft coffee roaster and espresso bar in downtown San Antonio, Texas.

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1951 Coffee Company is a non-profit specialty coffee organization that promotes the well-being of the refugee community in the United States

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Supplying the world’s most iconic foodservice, retail and CPG brands with the most transformative coffee, tea, flavors, extracts, and ingredients products.

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Since 2003 C &amp; P Coffee Company has been building friendships around community and coffee. We proudly serve Lighthouse Roasters fine coffees as well as a rotating selection of beer and wine. We offer locally sourced baked goods including vegan and wheat free options.

C and P Coffee – Great Coffee and so much more – West Seattle

San Antonio&#x27;s First and Favorite Cafe for Specialty Coffee and Friendly Baristas

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A Hamptons classic since 1994 with local family-owned cafe &amp; espresso bar locations in The Hamptons, the North Fork, and beyond! Small-batch hand roasted coffee, freshly baked muffins, homemade hot breakfast &amp; lunch, and so much more. Outdoor seating, kid-friendly, and pet-approved!

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Seven Coffee Roasters is a small-batch and hand roasted purveyor of artisan coffee. Browse our website for the best coffee for sale in Seattle!

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The Bean Coffee Shop in Auburn Alabama serves the finest roasted coffee that supports fair trade from LOTH also serving desserts with an inhouse bakery.

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**Please Note**No Longer Available for &quot;Off Site&quot; Catering · San Antonio, TX, 78209 United States

Theory Coffee Co

Coffeee is on a mission to build a world-class ecosystem with the largest pool of pre-vetted and skilled developers, creating abundant choices for both companies and candidates, to make hiring quick, easy and free of biases.

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E-Commerce is an ever-changing industry due to the nature of innovation that influences it. Each eCommerce trend has to be analyzed in deep and adopted in due if it’s truly going to drive your brand forward. If not, you could be missing out on the . projected 6.54 trillion US dollars in 2022 In the coming years, we must expect to see continued growth with more online brands joining the market. Continuing growth translates to more competition, too. This is why you have to be well versed with the latest that are often a result of advancements in technology and changes in customer interests and behavior. eCommerce trends Why are eCommerce Trends Significant? The eCommerce industry is becoming increasingly competitive. To beat the competition, you must constantly monitor and follow the trends. No matter how young or mature your online store is now if you don’t keep up with the current industry drifts, you will risk falling behind. You must constantly keep looking ahead to ensure future success in the industry. That is why it is important to analyze and adapt eCommerce trends in a timely manner. By doing so, you can drive your eCommerce brand to heights and stay ahead of the competition. Online shopping is one of the most popular online activities, and a rising number of people are turning to it with each year passing by. The increase in online shopping can be attributed to a number of factors, and eCommerce trends arguably are one of the major ones. If you own an eCommerce store, you can’t repeat the old strategies you followed last time to survive in the market. New eCommerce businesses are budding every day with brand new marketing tactics and access to tools which makes selling online easy and effortless. For the same reason, every eCommerce store that wants to survive the fierce competition must work harder. In this era of technological advancements, you are not just expected to sell products online, you must focus on creating experiences. To build a suitable and successful online store, you must adopt the latest eCommerce trends, learn from your mistakes and bring in the changes along the way. Every year, new trends emerge and transform the way eCommerce stores operate. Here, we will discuss the top trends in eCommerce you must follow in 2019 to beat the competition and to grow your brand. Augmented Reality Will Rule Augmented reality shows a computer-generated 3D sensory in the real world. This virtual experience is even better than the real in-person experience as it offers convenience and enhances the shopping experience. Among the emerging technologies, AR is driving the eCommerce industry to a wide horizon and results in increasing overall participation levels. Augmented reality helps in providing users with an in-store shopping experience that makes it easy to choose the right product. It helps your users to deal with the imagination gap and lack of confidence in taking risks while shopping online. For instance, IKEA combines augmented reality to bridge the imagination gap by potentially taking you into a fully 3D world so that you can clearly see how the furniture looks once it is placed in your living space. Not just IKEA, Sephora’s virtual artist app and Kylie Jenner’s app allow you to try out different lip colors, eyeshadow, and cheek colors virtually. AR is a totally new way to shop online by overcoming challenges and experience more of real shopping. Evolving Role of Social Media in Ecommerce Social media has changed the way we live, and that includes the way we shop as well. With the introduction of Instagram checkout and buy button on Facebook, social media is playing a direct role in the eCommerce world. Refer to the example shown below where @colourpopcosmetics allow Instagram checkout making it easy for customers to shop. 2019 is a great opportunity for businesses to start thinking about how to improve their presence on social media. With customers spending more time on platforms like Facebook and Instagram, an eCommerce business can leverage the possibilities of social media to get discussed by the target audience. Additionally, leveraging eCommerce software, brands can link their online shops with social media platforms so that customers can purchase from stores directly through social media platforms. Machine Learning, AI, and Chatbots Soon we will see more eCommerce brands using chatbots to bring in sales and close deals. Businesses can use chatbots to instantly connect with customers and solve their issues on multiple platforms like an online store or social media. These bots use artificial intelligence to understand customer preference and offer a valuable and personalized shopping experience. For instance, Sephora Virtual Artist app offers chatbots not justto answer customer queries, but to offer smart product suggestions as well. With that said, in 2019, you will see more eCommerce software integrating chatbot plugins. Many Facebook-based online stores use chatbots to facilitate transactions or answer FAQs. Machine learning allows Chatbots to get a better understanding of the common questions asked frequently. They can parse user data to customize the support experience to each customer. If you haven’t already, it’s a good time to invest in a chatbot now so that you can drive better engagement, customer support, and sales. Voice Search Will Continue to Grow Voice search has become popular with the invention of personal assistant devices like Alexa and Siri. While just 20% of search queries are made with voice now, it is expected to cross over 50% by 2020. It is a big opportunity for eCommerce as more customers are making more purchases using personal assistance devices. These devices allow you to play music, browse the web, make online purchases, etc. It is rather easy to say instead of taking up your phone and order it yourself. It can even read out the product descriptions on your online store, so it is recommended to optimizeVyour product pages for voice search. “Okay, Google, order a cup of coffee” If you ask why voice search is so important to eCommerce, users don’t remember the products, they remember the brands. You don’t order a coffee, you order Starbucks. Likewise, you buy Elizabeth Arden, Nike Calvin Klein, and Ford. Voice search is still in its infant stage, but it is expected to transform your shopping experience very soon. Product Videos We all have hesitated at least once before hitting the “Buy” button when shopping online. It is because you doubt whether it will be a quality product or if it’s going to be exactly as it is shown. If users are given an opportunity to interact with the product before making a purchase, they are more likely to buy. Online reviews and influence trends aren’t just enough to establish trust among customers. That is when interactive product visualization through detailed pictures and videos help to make a better decision. ASOS add product videos in every product page so that customers can clearly visualize products before purchasing. Most eCommerce brands seek the help of technology and facilitate product visualization through videos. Interactive product visualization is a popular eCommerce trend that is expected to stay in the future. Videos considerably increase the chance that a customer will actually purchase a product from your store. Even eCommerce product videos have evolved so much from a cheesy infomercial to a 360-degree shopping experience. Product demo videos are also an excellent eCommerce tool where you can show how a product works in a single video in an engaging way. For example, Amazon offers product videos for almost every category to give customers a better perception of the products. 2019 Will Transform the Future of eCommerce With the advent of machine learning and AI, eCommerce is making its shift towards personalization and creating a new user experience for customers. What do you think this year will bring to the eCommerce world? If you are an eCommerce brand, these trends will get you more business this year. Choose a trend that suits your niche and put it into action. However, if you are a new business looking to make your mark with your new store, it will be worth to look into these trends and apply it. No matter which eCommerce trend you choose to follow in 2019, do it with the intent of offering an engaging shopping experience to your customers.

5 eCommerce Tech Trends That Will Drive Sales Online in 2019

5 steps to more responsible estimations E There’s no debate about it. From “how long will it take us to build a new product?” to “how much will it cost?”, estimations are part of the daily grind when it comes to . More often than not, the pressures of time, chaos, deadlines, commitments, and management dictate the opportunity and ability to provide an estimate that is honest, credible and accurate. Regardless of these pressures, one who makes an estimate is responsible and accountable for making one that is honest, credible and accurate. stimations are hard . software development The unseen responsibility There’s a pretty good chance that you’ve made a “bad” estimate if you’ve helped develop software. This doesn’t make you a bad person, but it does make you responsible and accountable for understanding what went wrong and being self-aware of the quality of the estimates that were provided. For example, do you often overestimate, underestimate or estimate “just about right”? If so, why is that and how can it be improved? There are also some things that we cannot control such as an estimate that was transformed into a commitment. This is where how we communicate plays an important role because if we clearly understood the purpose and intent of the estimate, the way we communicated the estimate would most likely be quite different than just a number. Our human mind fails us We love “lying” about numbers. It is because of the that is built into our brains. In the context of software estimations, our human minds take mental short cuts which cause our estimates to be driven by emotion more often than credible data. mentioned that “people and organisations do manipulate information for their own uses.” This can be seen in the theatre of politics where people present project deliveries sooner than the project can realistically be delivered by. The reality is that we’re not going to be able to stop the “lies”, whether it was intentional or not, but we do have control over our individual responsibility to detect and provide accurate estimates. cognitive bias Statistics Canada So, what does it mean to detect and provide accurate estimates? 5 Steps To Estimating Responsibly 1. Understand the purpose When providing an estimate, there is a purpose. The purpose is to provide some information to quantify uncertainty so that a decision can be made. In the case of estimates, the decision-making is usually not done by the person who provides the estimate. And the person providing the estimate usually isn’t the person who needs the estimate for a decision. So in order for the provided estimate to be relevant and useful for the decision maker (eg. manager), the purpose needs to be understood. The and necessary context of each estimation. purpose serves as the foundation Knowledge of the purpose enables one to determine the method required to produce the appropriate estimation. In turn, the decision made is impacted by the quality of the estimate. Without an understanding of the purpose, it is easy to become , making it more difficult to select the appropriate estimation method required. As a result, the estimation is no better than a guess. For example, the estimation method and rigour required for identifying a feasible investment amount of a new product is very different to the estimation method and rigour required for additional work that arose from the unknowns of an existing project. The main reason for this is that the risk and size of potential loss is much higher and larger respectively in the former than the latter case. This example also highlights a common misconception between methods and techniques. When it comes to estimations, there are many different techniques (eg. “tools” or technical skills that can be applied to achieve a desired result): distracted by the noise of overwhelming information and uncertainty Analogous Estimation Top down estimation Bottom-up estimation / Work Breakdown Structure (WBS) Three Point Estimation Function Point Delphi / Wideband Delphi Technique On the other hand, a method is a procedure, usually including a logical, systematic or established plan, used to solve a problem. Depending on the problem and level of risk associated, we need to employ different methods fit for the purpose of our estimation. 2. Articulate assumptions When we make estimates, assumptions are made because adequate information is often not available when we want to make a decision. When it comes to software development estimations, here are some common assumptions that we make (perhaps without even realising): The order of work is ideal Engineers/developers understand exactly what needs to be done Engineers/developers know the benefit of the card/work to be delivered No wait times or delays between tasks No rework No hand-offs Showcases and status updates do not go over the allocated time Etc. It is worth noting that the number of assumptions is proportional to our level of uncertainty. Because of this, there is another type of assumption which we don’t often consciously recognise. They are the “ ”. In other words, these are the assumptions that we cannot “imagine”. For example, when we have a validated idea with no requirements, there are significantly more assumptions compared to when there is a detailed design specification of the software. We can see this from the diagram below. unknown unknowns cone of uncertainty Cone of Uncertainty (Barry Boehm 1981, p. 311) Thirty-seven years ago, the was a result of empirical research work by . He found that no matter how hard we try, our estimations made before the requirements are defined will be +/-400%. In the beginning of a software development product, our uncertainty is at it’s highest and the only way to get an estimate to precisely reflect the actual, exact time a project will take is to just do the project. This is still true today, in 2018, and one of the reasons why other methodologies, such as , , , and more, have emerged over the last few decades. cone of uncertainty Barry Boehm Agile Lean Scrum Extreme Programming (XP) We make assumptions based on our experience of what goes on during the software development process and lifecycle. This is acceptable so long as we clearly communicate these assumptions to the managers and our team members so that they have an accurate understanding of what the estimate reflects. By doing this, a shared understanding is created and some discussions could arise to strengthen an estimate. After all, collective than knowledge of a single mind. knowledge is more powerful 3. Assess risk, money and time available Before diving into this one, it’s worth clarifying that I’m referring to the risk, money and time available to complete one or more activities (eg. surveys, prototyping, etc) to collect adequate information for an estimate. referred to such activities as “buying information” to reduce our uncertainty and therefore risk. Given enough time and money, we could provide an almost perfect estimate. Unfortunately, time and money is not unlimited. This combined with the pressures, expectations and commercial viability of developing software, estimations are often made in a hurry without much thought to it’s quality or if the appropriate method was applied. It’s ironic because the intent of estimations is to quantify and reduce our uncertainty about a particular initiative or effort. In other words, estimations help us manage the risk associated with delivering successful software. So why is it not perceived important enough to ensure our estimation method and techniques are robust? Boehm Firstly, quantifying risk is not part of the daily software development practice and therefore it is hard to “imagine” because “reality is based on perception”. Secondly, having the capabilities to produce high-quality estimate in a short timeframe is not perceived as being important but only that an estimate was provided. Although the fast-paced environments of software development could benefit a great deal from quicker and higher quality estimates. The obvious would be more accurate estimates leading to increased confidence. Recall earlier that understanding the purpose was the first suggested step to providing an appropriate estimate. The purpose is also vital for knowing the appropriate estimation method to apply given time available, money and risk factors (eg. How much money is worth investing to reduce our uncertainty around successfully delivering project X? How much confidence do we desire in our estimate given an investment of $3 million into this project?). Awareness about the level of confidence of the estimate provided is also important. 4. Communicate estimates as a range Estimates are often communicated as a date or a single value. Whilst how we ask for the estimate is a contributing factor, we will not focus on the appropriate way to ask for an estimate here. For now, we will focus on how one should present and hence communicate an estimate. When an engineer presents an estimate as a date or single estimate value, may give the impression that the estimate is highly accurate when it likely is not. Single value estimations also makes it easier to be transformed into a promise, whether that was intentional or not. And in doing so, the engineer has taken on the increased risk of delivering by that date or within that exact time. By definition, the engineer has taken it upon them self to provide the information and decide on when the work could be ready for launch, rather than just providing the information. It is the job of the manager to make decisions, as the developer is likely missing some information. Note that there is nothing wrong with an engineer wanting to make a commitment or promise but doing so with an exact date or timeframe is high risk. It means that one must be 99.9% confidence but the chances of this is very slim. An engineer’s main responsibility is to come up with a honest, credible and accurate estimate. To do this, they should provide an estimate as a range with that they are 90% confident about. “A reasonable probability is the only certainty.” Additionally, ranges enable an engineer to share more information such as different ranges with the respective probabilities of delivering within those different time ranges (eg. 90% chance that it can be done in 7–9 days or 95% chance that it can be done in 6–10 days). With this approach, the manager (or the “decider”) can now make truly informed decisions based on the risk that they are willing to take on. Some of the questions might include: Which features should we put into the software product in the first version? What order should we develop the features? When do we need to handle the communications to existing customers about the upcoming changes? As you can see, the manager has lots to coordinate and the better the estimates provided, the better chance of not having a negative ripple effect. 5. Present duration, not the effort required When asking an engineer for an estimate, one often receives an estimate for the effort it will take the engineer to complete the work or task. However, this estimate doesn’t account for the interruptions of an engineer’s other daily activities such as meetings, coffee breaks, ad-hoc defects and/or customer issues, etc. Without these factors, an estimate is meaningless to the manager or stakeholder because it does not reflect the “common conversation”, specifically the day-to-day realities of delivering working software to the customer. It is also not be helpful for the decisions that a product manager needs to make. This might include the following questions: How long before this feature is ready for marketing? How long before the next chunk of product development work can begin? Do I need additional resources to deliver within the expected timeframe? How long before the new customer acquisition strategy needs to be launched? How much could we deliver for the next version of the product? As you can see, all the questions above relate to duration. Stakeholders, investors and managers make decisions based on the duration something takes to complete or execute as well. Hence, communicating estimates that can be understood and utilised to make decisions is crucial. Additionally, clear communication of estimations are directly related to stakeholder, investor and manager expectations. “Since expectations are based on what they understood we said, not what we meant, failing to communicate our meaning clearly is a major risk, particularly if misunderstandings by senior stakeholders lead to unrealistic expectations are that unlikely to be fulfilled!” explains . business Dr Lynda Bourne Measure Probabilistically Over Guessing Badly Uncertainty limits our ability to make accurate estimates. But when estimations are done right, they are useful and valuable. The intent of estimations underpins all software development efforts from the moment an idea is born to when we’re madly pumping out features to satisfy our quickly growing customer base. A careless, ignorant estimate will be the difference between a definite failure and fighting chance to a timely and successful product or project delivery. Honest, credible and accurate estimations are a much harder task than we perceived them to be, especially if you’ve not done them before or never received formal training on how to do estimations correctly, eg. . It is also naive to think that estimates was just sharing an educated guess of numbers or a number from applying a popular technique (eg. or ) — . Estimations frequently get morphed into promises that were not intended and I touched on how it’s a communication problem between the person who needs the information to make a decision and the person who is providing the estimate. Therefore, it’s important for the person providing the estimate to always thoroughly understand the purpose of an estimate before they come up with the estimate. Then they should articulate the assumptions made, balance the money and time available to arrive at a credible estimate, communicate the estimate as a range with probabilities and ensure that the estimate reflects duration rather than the effort required. Using these 5 simple steps, as a guide, will help anyone create an estimate that is useful. calibration training Who knew estimation training was a thing right? planning poker t-shirt sizes which have their issues but will save this for another article; in the mean time, Kiryl offers some great insights on why he stopped using planning poker Quote Daily R There are different estimation methods that are more suitable that others and the most suitable one needs to be applied in order to produce an honest, credible and accurate estimate. emember, those who provide estimates are accountable and responsible for the information they provide as it directly impacts the decision to be made. Don’t use a screwdriver when a hammer is needed;) I’d like to leave you with one last thought. Given the definition of , why do we perceive the activity of estimating as requiring less “know-how”? When it comes to software development, what is the difference between in relation to reducing uncertainty? forecasting estimations and forecasting Learned something? Hold that 👏 to say “thanks!” and help others find this article. Do you want more? Follow me or read more here .

How Not To Lie About Estimates

's debut at CES 2024 with its in-home, smoke-free coffee bean roaster heralds a new era in coffee brewing, blending the sophistication of a café with the comfort of home brewing. Bunafr The device marks the first time consumers can bring the full coffee roasting experience into their homes, merging the allure of a café with the comfort of personal space. Bunafr's vision is ambitious: to transform every kitchen into a personal café. Anjani Annumalla, CEO of Bunafr, emphasizes this during CES: "Our goal is to elevate home-brewed coffee, making it not just comparable, but superior to your favorite coffee shop brew." This commitment to excellence is manifested in their innovative roaster, which is designed to be user-friendly and sophisticated.” At the heart of Bunafr's offering is their Smart Home Coffee Roaster, a testament to technological innovation in coffee making. With the push of a button, users can roast coffee to their exact liking. Bunafr's patent-pending technology is fully automated and tailored to the user's taste profile. It boasts an array of advanced features: Multi-modal heat transfer techn enabling variable batch size roasting in less than 10 minutes First Crack Detection and Multiple Bean Temperature Sensors for precise roasting. Pre-heating and Climate Control Smart roast chamber and patent-pending agitation designRoast Profiles for variable batch size, accommodating different brewing needs. Over a dozen sensors for precision control and repeatability. Offline Mode for traveling and use without WiFi Auto Dispense into storage jars with vacuum seal for convenience. Robust design and materials supporting Back to Back roasting Quick Cool Down of Roasted Beans, preserving flavor and aroma. Real Time Roast Control Technology™, enabling custom profile creation via an app Smart subscription of green coffee beans IoT technology Custom Roasting with an app or optimal roasting with the push of a button Green Subscription Model Bunafr enhances the coffee experience with three curated subscription models. The Single Origin Coffee subscription takes you on a journey to various coffee farms. Each month, a new micro-lot from a single origin partner is delivered, showcasing the diversity in flavors from different regions and countries. From bold tropical fruit notes of Costa Rican  beans to the complex spice of Sumatra, these single origin coffees provide a unique tasting experience. The company also offers the Blend Coffee subscription for coffees  made from single origin beans and Remarkable Coffees subscriptions featuring rare varietals and award-winning micro-lots, such as 90+ scoring geishas and exquisite Yemenese beans, offering a gateway to some of the most interesting and hard-to-find coffee origins and flavors. The freshness of coffee is paramount in Bunafr's philosophy. Studies have shown that green coffee beans maintain their flavor longer at room temperature, whereas roasted beans lose their flavor 63 times faster. Bunafr leverages this fact, enabling consumers to roast beans just before brewing, ensuring peak freshness. Furthermore, Bunafr reimagines the (roasted) coffee supply chain as a “green coffee” supply chain with a strong focus on ethical practices and eliminating unnecessary carbon footprint from every cup. By ensuring farmers receive a larger share of the profits, Bunafr supports sustainable and ethical farming. This model aligns with the fact that, “According to the International Coffee Organisation, coffee prices fluctuate by over annually, and climate change exacerbates this volatility, leading to uncertain incomes for farmers.” [ ] 30% SOURCE The company’s consumer appliance unveiling at CES signifies a shift in lifestyle. It invites coffee enthusiasts to explore the science and art of coffee, from the bean to roast to the cup. With Bunafr, the experience of brewing coffee becomes a journey of personalization, creativity, and enjoyment, merging the best of café culture with the uniqueness of home brewing.

The Future of Coffee at CES: Bunafr Brings Café Quality Coffee to the Home

Scientific American, Volume XXXVI., No. 8, February 24, 1877 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . Caffeone here Caffeone. Caffeone, the aromatic principle of coffee, may be isolated by distilling 5 or 6 lbs. roasted coffee with water, agitating the aqueous distillate with ether, and afterwards evaporating the ether. It is a brown oil, heavier than water, in which it is only very slightly soluble. An almost imponderable quantity of this essential oil will suffice to aromatize a gallon of water. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2006). Scientific American, Volume XXXVI., No. 8, February 24, 1877. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/19406/pg19406-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at www.gutenberg.org https://www.gutenberg.org/policy/license.html

Caffeone, the aromatic principle of coffee.

How we automated SQL Server to Java migration and speeded up 4 times This article is dedicated to SQL Server modernization based on a project carried out by Ispirer for a large company operating in financial consulting. The customer harnessed the power of a SQL Server database to efficiently handle, process, access, and oversee their clients' financial information. The client aimed at migrating SQL Server to a cloud while optimizing system architecture and maintenance costs. Microsoft The Ispirer team offered to transfer business logic to Java because the database is used in OLTP mode. We will carefully analyze the subject and review the client's project, which involves converting SQL Server business rules to Java. Additionally, we will investigate the reasons behind companies opting to migrate SQL code to an application layer. This will involve a comprehensive examination of the entire process. To optimize the costs of cloud infrastructure, the client decided to migrate tables and data to PostgreSQL. Since we specialize in database and application migration, the customer turned to us with the following tasks: Moving 815000 LOC of business logic to the application layer in Java. Migrating 300 GB of data and 3000 tables from Microsoft SQL Server to PostgreSQL. Owing to the substantial scale of the project, the client endeavored to minimize migration expenses by implementing automation. To optimize the efficiency of the Ispirer Toolkit, we determined that its customization should be conducted in advance. This approach enabled us to deliver a tool to the client's team, with a T-SCL to Java conversion rate of approximately 90%. Now let’s dive deeper to the migration of tables and data. From SQL Server to PostgreSQL: migration of data and tables Let's consider the reasons why the customer chose to migrate from an on-premises SQL Server to the cloud. This transition includes a number of undeniable advantages: Cost Savings. One of the primary driving factors behind the migration from SQL Server to PostgreSQL in the cloud is cost savings. The client used to find it expensive to keep SQL Server databases on-site. This was due to the need for special equipment, software licenses, and skilled database administrators.
PostgreSQL, being an open-source database, offers a cost-effective alternative. Customers can save money by using the cloud. They only have to pay for what they use, instead of making big upfront payments. Additionally, they can spend less on operations. Scalability. Cloud computing can scale more easily than on-premises infrastructure to serve greater workloads and more users. For an on-prem system to scale with the needs of a business, organizations had to acquire and install physical servers, software licenses, storage, and network equipment to scale out business services in conventional IT settings.
On the cloud, most of these resources are available instantly within a few clicks and can be auto-scaled up and down depending on the resources needed. PostgreSQL in the cloud provides a high level of scalability, allowing our client to easily adjust resources based on demand. Security. Embracing cloud technology offers notable security advantages thanks to the advanced identity controls, access management, and authentication systems supplied by cloud providers. Often cloud providers have better security standards than in-house IT teams or local systems, making the data environment safer. Strong encryption in the cloud reduces the chance of data breaches. It includes layered security, good key management, and secure access controls, which help businesses control user access effectively. Furthermore, cloud providers rigorously oversee physical access, implementing measures such as anonymity, replication, and encryption to fortify data protection. By 2025, approximately are predicted to transition from physical data centers to cloud services. This shift is driven by the enhanced security benefits provided by the cloud. 80% of businesses Moving from SQL Server to PostgreSQL in the cloud requires careful planning and execution, with specific considerations in mind. Based on the client’s project, our team has highlighted the following steps for modernizing SQL Server: Schema and Data Transformation. Data should be transformed accurately to match PostgreSQL's requirements. This may involve handling nuances like date formats and character encoding. Constraints and Triggers. Understanding the distinctions in the usage of constraints and triggers in the two databases is crucial. It is necessary to make the necessary modifications accordingly. In addition, the functionality of triggers can be moved into the application. However, this task is far from simple, so it’s essential to weigh the pros and cons. Performance Optimization. Optimization of the migration process allows to minimize downtime and data transfer time. It’s important to utilize parallelization, optimize network bandwidth, and invest in powerful hardware for efficient migration Data Validation and Testing. Rigorous validation of the migrated data is required to guarantee data integrity and functionality. Extensive testing ensures that applications work seamlessly with the new PostgreSQL database. Security and Permissions. Security settings, user accounts, and permissions in PostgreSQL should be configured to match the original SQL Server setup, ensuring a seamless transition. Why move Business logic to Application Layer? In the past, our customers used stored procedures for their business logic, thinking it would improve performance. But let’s be honest, SQL language may not be the optimal choice for housing the business logic when compared to the application layer. In fact, SQL only queries or modifies the data in a database. Here many can throw rotten tomatoes at us, because SQL language is good at performing complex joins, filtering, and sorting in order to get exactly the data you need out of a query and nothing more. Then why change anything and bring the business logic to the application level? The question seems logical. Let's answer it in more detail. Below we have outlined 4 main reasons why you should seriously think about transferring business logic to the application. The client’s decision to move business logic to the application layer was driven by the following reasons: Scalability For scalability, storing business logic at the application level is the best option. Why? Because, in general, it’s substantially easier to scale your application server resources than it is to scale your database server resources.
This is almost universally acknowledged. For most web apps, adding more servers is usually easy when there's a lot of traffic to handle. However, the value of extra application servers diminishes unless your database can also scale to accommodate the augmented demand. Scaling a database server is considerably more challenging than simply adding application servers. Maintainability Storing business logic in a database can create maintainability challenges. Modifying stored procedures can disrupt many applications, limit extensibility, and make it challenging to follow the "Don't Repeat Yourself" (DRY) principle. SQL code that exceeds 100 lines often poses complexities and troubleshooting difficulties. Separating business logic into the application tier can facilitate new team members' entry and provides a more intuitive platform for refactoring. Ease of development SQL is a poor choice for encoding the business rules of your system. It's not flexible and we can't depend on it to represent complex models because it can't create proper abstractions. This limitation is the key reason to avoid using it for business logic. It's not about tooling or support, it's about SQL's inability to create a simple and expressive domain model, in contrast to object-oriented and functional design, which offer more opportunities. Reusability In software development, reusing code is an efficient way to save time and costs when adapting existing code for new tasks. Object-Oriented Programming (OOP) is a method that facilitates code recycling, making it suitable for various applications. However, SQL, commonly used in databases, offers limited flexibility for code reuse. Options include using "views" and "stored procedures," though the latter may lead to an abundance of parameters. To ensure the right choice for your project, exploring each method thoroughly is essential. Converting Transact-SQL to Java Converting Transact-SQL to Java involves various essential considerations. The process includes mapping SQL data types to their Java equivalents, ensuring accurate data representation. It also encompasses translating SQL queries into Java code, where Java relies on libraries like JDBC or Hibernate to handle database interactions. Moreover, certain ESQL features lack direct equivalents in Java, potentially giving the impression that automatic conversion is inefficient. During the customization phase of our project, we were able to create a number of conversion solutions that enhanced the automation rate. These solutions, initially believed to be impossible to automate, ultimately proved successful. Let’s delve into the details of some of them. Converting an INSERT statement in combination with a SCOPE_IDENTITY() to get the last identity value inserted into an identity column. Source: ALTER PROCEDURE example1
 AS
 BEGIN
 Declare @idBit int
 Declare @c int
 
 Insert Into tab (c) 
 Values (@c)
 
 Set @idBit = SCOPE_IDENTITY()
 End Target: @Service
 public class Example1 implements IExample1 {
 @Autowired
 private JdbcTemplate jdbcTemplate;
 private static final org.slf4j.Logger LOGGER = org.slf4j.LoggerFactory.getLogger(Example1.class);
 @Override
 public Integer spExample1() throws SQLException, Exception {
 Integer mStatus = 0;
 KeyHolder keyHolder = new GeneratedKeyHolder();
 try {
 Integer idBit = null;
 Integer c = null;
 {
 final Integer tmpC = c;
 jdbcTemplate.update(connection-> {
 PreparedStatement ps = connection.prepareStatement("Insert Into tab(c) \r\n" +
 " Values(?)", new String[] { "" });
 ps.setInt( 1, tmpC);
 return ps;
 }, keyHolder);
 }
 idBit = Tsqlutils.<Integer > strToNum(keyHolder.getKey().toString(), Integer.class);
 return mStatus;
 }
 catch (Exception e) {
 LOGGER.error(String.valueOf(e));
 mStatus = -1;
 return mStatus;
 }
 }
 } Conversion of procedure with multi Result Sets. Source: ALTER PROCEDURE [returnSeveralResultSet]
 @p1 int,
 @p2 varchar(50)
 AS
 Begin

 select cob_ft, lower(buzon) from tab1 
 where cob_id = @p1 and cob_ft = @p2
 
 select dep_ft, lower(fiton) from tab2
 END Target: @Service
 public class Returnseveralresultset implements IReturnseveralresultset {
 @Autowired
 private JdbcTemplate jdbcTemplate;
 private static final org.slf4j.Logger LOGGER = org.slf4j.LoggerFactory.getLogger(Returnseveralresultset.class);
 private Integer errorCode = 0;
 private String sqlState = "";
 @Override
 public Map<String, Object> spReturnseveralresultset(Integer p1,
 String p2) throws Exception {
 Integer mStatus = 0;
 Map<String, Object> outData = new HashMap<>();
 List<SqlRowSet> outRsList = new ArrayList<>();
 SqlRowSet rowSet;

 try {
 rowSet = jdbcTemplate.queryForRowSet("select cob_ft, lower(buzon) from tab1 \r\n" +
 " where cob_id = ? and cob_ft = ?", p1, p2);
 outRsList.add(rowSet);
 rowSet = jdbcTemplate.queryForRowSet("select dep_ft, lower(fiton) from tab2");
 outRsList.add(rowSet);
 return outData;
 }
 catch (Exception e) {
 LOGGER.error(String.valueOf(e));
 mStatus = -1;
 return outData;
 }
 finally {
 outData.put("status", mStatus);
 outData.put("rsList", outRsList);
 }
 }
 } Conversion of DATEDIFF method. Since Java has no direct equivalents, the Ispirer team developed an equivalent to this method that casts String to Timestamp without an explicitly specified format. It makes the code result uncluttered and easier to read. The example below demonstrates how it is used. Source: create procedure datediffFn
 as
 declare @var1 int
 set @var1 = DATEDIFF(dd, '1999-01-01', '2000-02-01')
 set @var1 = DATEDIFF(mm, getdate(), '2000-02-01')
 set @var1 = DATEDIFF(week, '2005-12-31 23:59:59.9999999', '2006-01-01 00:00:00.0000000'); Target: public Integer spDatedifffn() throws Exception {
 Integer mStatus = 0;

 try {
 Integer var1 = null;
 var1 = Tsqlutils.datediff("dd", Tsqlutils.toTimestamp("1999-01-01"), Tsqlutils.toTimestamp("2000-02-01"));
 var1 = Tsqlutils.datediff("mm", new Timestamp(new java.util.Date().getTime()), Tsqlutils.toTimestamp("2000-02-01"));
 var1 = Tsqlutils.datediff("week", Tsqlutils.toTimestamp("2005-12-31 23:59:59.9999999"), Tsqlutils.toTimestamp("2006-01-01 00:00:00.0000000"));
 return mStatus;
 }
 catch (Exception e) {
 LOGGER.error(String.valueOf(e));
 mStatus = -1;
 return mStatus;
 }
 } Conversion of sp_send_dbmail method which sends an e-mail message to the specified recipients. For this purpose, a class called MailService was developed. This method makes it possible to send emails with detailed specifications, including recipients (TO), recipients of a copy (CC), recipients in a blind carbon copy (BCC), the subject of the letter, the main text, attachments, and more. To keep the main code uncluttered, our team placed the method in a separate class. Source: create PROCEDURE spSendDbmail 
 AS 
 BEGIN 
 
 EXEC msdb.dbo.sp_send_dbmail 
 @profile_name = 'New DB Ispirer Profile', 
 @recipients = 'user1@ispirer.com', 
 @body = '<h1>This is actual message embedded in HTML tags</h1>', 
 @subject = 'Automated Success Message' ,
 @file_attachments = 'C:\Temp\Attached.txt',
 @body_format='HTML', 
 @copy_recipients = 'user2@ispirer.com',
 @blind_copy_recipients = 'user3@ispirer.com'; 
 END Target: import java.util.*;
 import com.ispirer.mssql.mail.MailService;
 public class Spsenddbmail {
 private static final org.slf4j.Logger LOGGER = org.slf4j.LoggerFactory.getLogger(Spsenddbmail.class);
 public Integer spSpsenddbmail() throws Exception {
 Integer mStatus = 0;

 try {
 MailService.send("New DB Ispirer Profile", "Automated Success Message", "<h1>This is actual message embedded in HTML tags</h1>", "user1@ispirer.com", "user2@ispirer.com", "user3@ispirer.com", "C:\\Temp\\Attached.txt", "HTML");
 return mStatus;
 }
 catch (Exception e) {
 LOGGER.error(String.valueOf(e));
 mStatus = -1;
 return mStatus;
 }
 }
 } The Ispirer team has developed an XMLUtils class for converting xml Data type and its methods, which are used to get any information from XML data stored in an XML variable. An example implementation of the method: Source: create procedure workWithXml
 AS
 begin
 declare @result bit, @myDoc XML, @myStr varchar(1000), @ProdID INT 
 
 SET @myDoc = '<Root> 
 <ProductDescription ProductID="1" ProductName="Road Bike"> 
 <Features> 
 <Warranty>1 year parts and labor</Warranty> 
 <Maintenance>3 year parts and labor extended maintenance is available</Maintenance> 
 </Features> 
 </ProductDescription> 
 </Root>' 
 
 SET @result = @myDoc.exist('(/Root/ProductDescription/@ProductID)[1]') 

 SET @myStr = cast(@myDoc.query('/Root/ProductDescription/Features') as varchar(max))
 
 SET @ProdID = @myDoc.value('(/Root/ProductDescription/@ProductID)[1]', 'int' ) 

 end; Target: import java.util.*;
 import com.ispirer.mssql.xml.XMLUtils;
 public class Workwithxml {
 private static final org.slf4j.Logger LOGGER = org.slf4j.LoggerFactory.getLogger(Workwithxml.class);
 public Integer spWorkwithxml() throws Exception {
 Integer mStatus = 0;

 try {
 Boolean result = null;
 String myDoc = null;
 String myStr = null;
 Integer prodID = null;
 myDoc = "<Root> " +
 "<ProductDescription ProductID=\"1\" ProductName=\"Road Bike\"> " +
 "<Features> " +
 "<Warranty>1 year parts and labor</Warranty> " +
 "<Maintenance>3 year parts and labor extended maintenance is available</Maintenance> " +
 "</Features> " +
 "</ProductDescription> " +
 " </Root>";
 result = XMLUtils.exist(myDoc, "(/Root/ProductDescription/@ProductID)[1]");
 myStr = XMLUtils.query(myDoc, "/Root/ProductDescription/Features");
 prodID = XMLUtils.<Integer > value(myDoc, "(/Root/ProductDescription/@ProductID)[1]", Integer.class);
 return mStatus;
 }
 catch (Exception e) {
 LOGGER.error(String.valueOf(e));
 mStatus = -1;
 return mStatus;
 }
 }
 } Thanks to our customization efforts, our team has successfully developed a range of techniques to automate the transition from T-SQL to Java. This has significantly slashed the overall migration time for the entire project, allowing us to accelerate migration 4 times compared to potential manual migration. Our Toolkit customization not only expedited the transition but also enhanced the project's overall efficiency, showcasing the valuable impact of our customization initiatives. The methods specified in the examples are provided to the client along with the conversion results. Conclusion In conclusion, transitioning business logic from Transact-SQL to Java is a multifaceted process that requires a comprehensive understanding of both languages and their distinct features. In this article we thoroughly explored the migration of business logic to an app layer, and provided valuable insights for those who are planning such a transition. The case of our client proves that such modernization projects can be automated which significantly saves time and effort during migration. Our client's project serves as a compelling testament to the remarkable potential of automation. It demonstrates that there are modernization facets where automation can successfully streamline processes that may initially appear beyond its capabilities. Ultimately, embracing the migration from is a strategic move for organizations seeking greater flexibility, cross-platform compatibility, and scalability. While it presents its challenges, the benefits in terms of portability, performance, and adaptability to modern software architectures make this transition a worthwhile endeavor for those looking to modernize their database systems and applications. Transact-SQL to Java

Business Logic Migration Made Faster Than Your Coffee Brews

বিজনেস লজিক মাইগ্রেশন আপনার কফি ব্রিজের চেয়ে দ্রুত তৈরি হয়েছে

Die Migration der Geschäftslogik geht schneller als Ihr Kaffee

La migración de la lógica empresarial es más rápida que las preparaciones de café

Migration de logique métier plus rapide que vos préparations de café

बिजनेस लॉजिक माइग्रेशन आपके कॉफ़ी ब्रूज़ की तुलना में तेज़ बना

ビジネス ロジックの移行はコーヒーを淹れるよりも早く完了

커피를 끓이는 것보다 더 빠른 비즈니스 로직 마이그레이션

Migração da lógica de negócios mais rápida do que sua preparação de café

Миграция бизнес-логики выполняется быстрее, чем заваривается кофе

İş Mantığı Geçişi Kahve Demlemekten Daha Hızlı

Quá trình di chuyển logic kinh doanh được thực hiện nhanh hơn việc pha cà phê của bạn

业务逻辑迁移速度比咖啡冲泡还要快

With the cost of a cup of Starbucks and two hours of your time, you can own your own trained open-source large-scale model. The model can be fine-tuned according to different training data directions to enhance various skills, such as medical, , stock trading, and love advice, making your large-scale model more “understanding” of you. Let’s try training an open-source large-scale model empowered by the open-source DolphinScheduler! programming Intro The democratization of ChatGPT The birth of ChatGPT has undoubtedly filled us with anticipation for the future of AI. Its sophisticated expression and powerful language understanding ability have amazed the world. However, because ChatGPT is provided as a Software as a Service (SaaS), issues of personal privacy leaks and corporate data security are concerns for every user and company. More and more open-source large-scale models are emerging, making it possible for individuals and companies to have their own models. However, getting started with, optimizing, and using open-source large-scale models have high barriers to entry, making it difficult for everyone to use them easily. To address this, we use Apache DolphinScheduler, which provides one-click support for training, tuning, and deploying open-source large-scale models. This enables everyone to train their own large-scale models using their data at a very low cost and with technical expertise. Who is it for? — Anyone in front of a screen Our goal is not only for professional AI engineers but for anyone interested in GPT to enjoy the joy of having a model that “understands” them better. We believe that everyone has the right and ability to shape their own AI assistant. The intuitive workflow of Apache DolphinScheduler makes this possible. As a bonus, Apache DolphinScheduler is a big data and AI scheduling tool with over 10,000 stars on GitHub. It is a top-level project under the Apache Software Foundation, meaning you can use it for free and modify the code without worrying about any commercial issues. Whether you are an industry expert looking to train a model with your own data, or an AI enthusiast wanting to understand and explore the training of deep learning models, our workflow will provide convenient services for you. It solves complex pre-processing, model training, and optimization steps, and only requires 1–2 hours of simple operations, plus 20 hours of running time to build a more “understanding” ChatGPT large-scale model. So let’s start this magical journey! Let’s bring the future of AI to everyone. Only three steps to create a ChatGPT that “understands” you better Rent a GPU card at a low cost equivalent to a 3090 level Start DolphinScheduler Click on the training workflow and deployment workflow on the DolphinScheduler page and directly experience your ChatGPT Preparing a Host with a 3090 Graphics Card First, you need a 3090 graphics card. If you have a desktop computer, you can use it directly. If not, there are many hosts for rent with GPU online. Here we use AutoDL as an example to apply. Open , register and log in. After that, you can choose the corresponding server in the computing power market according to steps 1, 2, and 3 shown on the screen. https://www.autodl.com/home Here, it is recommended to choose the RTX 3090 graphics card, which offers a high cost-performance ratio. After testing, it has been found that one to two people can use the RTX 3090 for online tasks. If you want faster training and response speeds, you can opt for a more powerful graphics card. Training once takes approximately 20 hours, while testing requires around 2–3 hours. With a budget of 40 yuan, you can easily get it done. Mirror Click on the community mirror, and then enter the red box below. You can select the image as shown below. Currently, only the V1 version is available. In the future, as new versions are released, you can choose the latest one. WhaleOps/dolphinscheduler-llm/dolphinscheduler-llm-0521 If you need to train the model multiple times, it is recommended to expand the hard disk capacity to around 100GB. After creating it, wait for the progress bar shown in the following image to complete. Start DolphinScheduler In order to deploy and debug your own open-source large-scale model on the interface, you need to start the DolphinScheduler software, and we need to do the following configuration work: To access the server There are two methods available. You can choose the one that suits your preference: Login via JupyterLab (for non-coders): Click on the JupyterLab button shown below. The page will redirect to JupyterLab; from there, you can click “Terminal” to enter. 2. Login via Terminal (for coders): We can obtain the SSH connection command from the button shown in the following image. Then, establish the connection through the terminal. Import the metadata of DolphinScheduler In DolphinScheduler, all metadata is stored in the database, including workflow definitions, environment configurations, tenant information, etc. To make it convenient for users to see these workflows when DolphinScheduler is launched, we can directly import pre-defined workflow metadata by copying it from the screen. Modify the script for importing data into MySQL: Using the terminal, navigate to the following directory: cd apache-dolphinscheduler-3.1.5-bin Execute the command: to open the file.The content of the file is as follows: vim import_ds_metadata.sh import_ds_metadata.sh Set variables Hostname HOST="xxx.xxx.xxx.x" UsernameUSERNAME="root"PasswordPASSWORD="xxxx"PortPORT=3306Database to import intoDATABASE="ds315_llm_test"SQL filenameSQL_FILE="ds315_llm.sql"mysql -h $HOST -P $PORT -u $USERNAME -p$PASSWORD -e "CREATE DATABASE $DATABASE;"mysql -h $HOST -P $PORT -u $USERNAME -p$PASSWORD $DATABASE < $SQL_FILE Replace xxx.xxx.xxx.x and xxxx with the relevant configuration values of a MySQL database on your public network (you can apply for one on Alibaba Cloud, Tencent Cloud, or install one yourself). Then execute: bash import_ds_metadata.sh After execution, if interested, you can check the corresponding metadata in the database (connect to MySQL and view, skipping this step if you are not familiar with the code). Start DolphinScheduler In the server command line, open the following file and modify the configuration to connect DolphinScheduler with the previously imported database: /root/apache-dolphinscheduler-3.1.5-bin/bin/env/dolphinscheduler_env.sh Modify the relevant configuration in the database section, and leave other sections unchanged. Change the values of ‘HOST’ and ‘PASSWORD’ to the configuration values of the imported database, i.e., xxx.xxx.xxx.x and xxxx: export DATABASE=mysqlexport SPRING_PROFILES_ACTIVE=${DATABASE}export SPRING_DATASOURCE_URL="jdbc:mysql://HOST:3306/ds315_llm_test?useUnicode=true&characterEncoding=UTF-8&useSSL=false"export SPRING_DATASOURCE_USERNAME="root"export SPRING_DATASOURCE_PASSWORD="xxxxxx"...... After configuring, execute (also in this directory /root/apache-dolphinscheduler-3.1.5-bin): bash ./bin/dolphinscheduler-daemon.sh start standalone-server Once executed, we can check the logs by using . At this point, DolphinScheduler is officially launched! tail -200f standalone-server/logs/dolphinscheduler-standalone.log After starting the service, we can click on “Custom Services” in the AutoDL console (highlighted in red) to be redirected to a URL: Upon opening the URL, if it shows a 404 error, don’t worry. Just append the suffix /dolphinscheduler/ui to the URL: The AutoDL module opens port 6006. After configuring DolphinScheduler’s port to 6006, you can access it through the provided entry point. However, due to the URL redirection, you may encounter a 404 error. In such cases, you need to complete the URL manually. Login credentials: Username: admin Password: dolphinscheduler123 After logging in, click on “Project Management” to see the predefined project named “vicuna”. Click on “vicuna” to enter the project. Open Source Large Model Training and Deployment Workflow Definition Upon entering the Vicuna project, you will see three workflows: Training, Deploy, and Kill_Service. Let’s explore their uses and how to configure large models and train your data. You can click the run button below to execute corresponding workflows. Training By clicking on the training workflow, you will see two definitions. One is for fine-tuning the model through Lora (mainly using alpaca-lora, ), and the other is to merge the trained model with the base model to get the final model. https://github.com/tloen/alpaca-lora The workflow has the following parameters (pops up after clicking run): base_model: The base model, which can be chosen and downloaded according to your needs. The open-source large models are only for learning and experiential purposes. The current default is TheBloke/vicuna-7B-1.1-HF. data_path: The path of your personalized training data and domain-specific data, defaults to /root/demo-data/llama_data.json. lora_path: The path to save the trained Lora weights, /root/autodl-tmp/vicuna-7b-lora-weight. output_path: The save path of the final model after merging the base model and Lora weights, note it down as it will be needed for deployment. num_epochs: Training parameter, the number of training epochs. It can be set to 1 for testing, usually set to 3~10. cutoff_len: Maximum text length, defaults to 1024. micro_batch_size: Batch size. Deploy The workflow for deploying large models (mainly using FastChat, ). It will first invoke kill_service to kill the deployed model, then sequentially start the controller, add the model, and then open the Gradio web service. https://github.com/lm-sys/FastChat The start parameters are as follows: model: Model path, it can be a Huggingface model ID or the model path trained by us, i.e., the output_path of the training workflow above. The default is TheBloke/vicuna-7B-1.1-HF. If the default is used, it will directly deploy the vicuna-7b model. Kill_service This workflow is used to kill the deployed model and release GPU memory. This workflow has no parameters, and you can run it directly. If you need to stop the deployed service (such as when you need to retrain the model or when there is insufficient GPU memory), you can directly execute the kill_service workflow to kill the deployed service. After going through a few examples, your deployment will be complete. Now let’s take a look at the practical operation: Large Model Operation Example Training a Large Model Start the workflow directly by executing the training workflow and selecting the default parameters. Right-click on the corresponding task to view the logs, as shown below: You can also view the task status and logs in the task instance panel at the bottom left of the sidebar. During the training process, you can monitor the progress by checking the logs, including the current training steps, loss metrics, remaining time, etc. There is a progress bar indicating the current step, where step = (data size * epoch) / batch size. After training is complete, the logs will look like the following: Updating Your Personalized Training Data Our default data is in . The current data source is Huatuo, a medical model finetuned using Chinese medical data. Yes, our example is training a family doctor: /root/demo-data/llama_data.json If you have data in a specific field, you can point to your own data, the data format is as follows: One JSON per line, and the field meaning is: instruction ****: Instruction to give to the model. input: Input. output: Expected model output. For example: {"instruction": "calculation", "input": "1+1 equals?", "output": "2"} Please note that you can merge the instruction and input fields into a single instruction field. The input field can also be left empty. When training, modify the data_path parameter to execute your own data. Note: During the first training execution, the base model will be fetched from the specified location, such as TheBloke/vicuna-7B-1.1-HF. There will be a downloading process, so please wait for the download to complete. The choice of this model is determined by the user, and you can also choose to download other open-source large models (please follow the relevant licenses when using them). Due to network issues, the base model download may fail halfway through the first training execution. In such cases, you can click on the failed task and choose to rerun it to continue the training. The operation is shown below: To stop the training, you can click the stop button, which will release the GPU memory used for training. Deployment Workflow On the workflow definition page, click on the deploy workflow to run it and deploy the model. If you haven’t trained your own model, you can execute the deploy workflow with the default parameters TheBloke/vicuna-7B-1.1-HF to deploy the model, as shown in the image below: vicuna-7b If you have trained a model in the previous step, you can now deploy your model. After deployment, you can experience your own large model. The startup parameters are as follows, where you need to fill in the of the model from the previous step: output_path Next, let’s enter the deployed workflow instance. Click on the workflow instance, and then click on the workflow instance with the “deploy” prefix. Right-click and select “refresh_gradio_web_service” to view the task logs and find the location of our large model link. The operation is shown below: In the logs, you will find a link that can be accessed publicly, such as: Here are two links. The link cannot be accessed because AutoDL only opens port 6006, which is already used for dolphinscheduler. You can directly access the link below it, such as 0.0.0.0:7860 [https://81c9f6ce11eb3c37a4.gradio.live.](https://81c9f6ce11eb3c37a4.gradio.live.) Please note that this link may change each time you deploy, so you need to find it again from the logs. Once you enter the link, you will see the conversation page of your own ChatGPT! Yes! Now you have your own ChatGPT, and its data only serves you! And you only spent less than the cost of a cup of coffee~~ Go ahead and experience your own private ChatGPT! Summary In this data-driven and technology-oriented world, having a dedicated ChatGPT model has immeasurable value. With the advancement of artificial intelligence and deep learning, we are in an era where personalized AI assistants can be shaped. Training and deploying your own ChatGPT model can help us better understand AI and how it is transforming our world. In summary, training and deploying a ChatGPT model on your own can help you protect data security and privacy, meet specific business requirements, save on technology costs, and automate the training process using workflow tools like DolphinScheduler. It also allows you to comply with local laws and regulations. Therefore, training and deploying a ChatGPT model on your own is a worthwhile option to consider. Important Notes: When using ChatGPT through public API services, you may have concerns about data security and privacy. This is a valid concern as your data may be transmitted over the network. By training and deploying the model on your own, you can ensure that your data is stored and processed only on your own device or rented server, ensuring data security and privacy. Data Security and Privacy: For organizations or individuals with specific business requirements, training your own ChatGPT model ensures that the model has the latest and most relevant knowledge related to your business. Regardless of your business domain, a model specifically trained for your business needs will be more valuable than a generic model. Domain-Specific Knowledge: Using OpenAI’s ChatGPT model may incur certain costs. Similarly, if you want to train and deploy the model on your own, you also need to invest resources and incur technology costs. For example, you can experience debugging large models for as low as 40 yuan, but if you plan to run it long-term, it is recommended to purchase an Nvidia RTX 3090 graphics card or rent cloud servers. Therefore, you need to weigh the pros and cons and choose the solution that best suits your specific circumstances. Investment Cost: By using Apache DolphinScheduler’s workflow, you can automate the entire training process, greatly reducing the technical barrier. Even if you don’t have extensive knowledge of algorithms, you can successfully train your own model with the help of such tools. In addition to supporting large model training, DolphinScheduler also supports big data scheduling and machine learning scheduling, helping you and your non-technical staff to easily handle big data processing, data preparation, model training, and model deployment. Moreover, it is open-source and free to use. DolphinScheduler: DolphinScheduler is just a visual AI workflow tool and does not provide any open-source large models. When using and downloading open source large models, you must be aware of the different usage constraints associated with each model and comply with the respective open-source licenses. The examples given in this article are only for personal learning and experience purposes. When using large models, it is important to ensure compliance with open-source model licensing. Additionally, different countries have different strict regulations regarding data storage and processing. When using large models, you must customize and adjust the model to comply with the specific legal regulations and policies of your location. This may include specific filtering of model outputs to comply with local privacy and sensitive information handling regulations. Legal and Regulatory Constraints on Open Source Large Models: Also published . here

How to Train Your Own Private ChatGPT Model for the Cost of a Starbucks Coffee

স্টারবাকস কফির খরচের জন্য কীভাবে আপনার নিজের ব্যক্তিগত চ্যাটজিপিটি মডেলকে প্রশিক্ষণ দেবেন

So trainieren Sie Ihr eigenes privates ChatGPT-Modell zum Preis eines Starbucks-Kaffees

Cómo entrenar su propio modelo de ChatGPT privado para el costo de un café Starbucks

Comment former votre propre modèle ChatGPT privé pour le coût d'un café Starbucks

स्टारबक्स कॉफी की कीमत के लिए अपने निजी चैटजीपीटी मॉडल को कैसे प्रशिक्षित करें

スターバックス コーヒーのコストについて独自のプライベート ChatGPT モデルをトレーニングする方法

스타벅스 커피 비용으로 나만의 비공개 채팅GPT 모델을 훈련하는 방법

Como treinar seu próprio modelo Private ChatGPT para o custo de um café Starbucks

Starbucks Kahvesi Maliyeti Karşılığında Kendi Özel ChatGPT Modelinizi Nasıl Eğitirsiniz?

Cách đào tạo mô hình ChatGPT riêng của bạn với chi phí bằng một ly cà phê Starbucks

如何为星巴克咖啡的成本训练自己的私人聊天 GPT 模型

Like most people I enjoy a morning coffee and on a random day a few years ago I had written this. What’s it about? Could it be about you? This is an unusual non-routine piece,  but consider it a celebration of all you technical professionals, programmers, builders, and creatives adding the important  flavor of new perspectives to make up ‘the whole’. Don’t stop all the amazing things you do. Coffee is The elixir for the daily dead Who rise as skyscrapers and buildings Industrious as explosive sunbeams Power the station, music for the masses Stimulant for an emulant Low dosage all approved Non alcoholic beverage A world of possibilities In a seed Elevated, iconic, historical Textbook for the bookworms Fuel for the station Music for the operator It’s the primal scream Hooked on the fundamentals In a seed The crows have been counting seeds of heaven For a long time Scripting the binary for machine fodder In various strain Employed and deployed In a saloon Minds buzzing in the saloon Since the days of grey Potent powers of the all approved beverages Fueling a movement In space of mind In a sea of a place In time Bill of constitution Beer, coffee, tea Stimulant as an emulant For sunbeams Music for the individual A spice of all nations that Lay awake in the dune Of the rising sun A world of possibilities In a seed of The morning brew A seed in sea Of a place In time In space Of a thought In a day Coffee was a seed Now an empire So says the Script That wrote--Java

The Coffee Poem

Welcome to this series of Q&As I’m publishing with inspirational mentors and community builders in the technology industry! It’s an honor to have had the opportunity to hear from these inspirational leaders who dedicate their time and positive energy to shaping a better future for developers. Over at Twilio, we created the this year to celebrate the most inspirational, motivating mentors who are uplifting developers in 2022 through community, mentorship, or code. Developer Searchlight Handpicked by an esteemed , these honorees are recognized for playing a pivotal role in shaping developer careers in a variety of ways, from virtual community building to school initiatives such as student-run coding contests and educational webinars. panel of expert judges Let’s get to know one of our standout honorees, Bekah Hawrot Weigel! Bekah is the Creator of and a Technical Community Builder at Deepgram, where she uses her experience to support others in the field and fosters inclusivity for developers of all backgrounds. Virtual Coffee Her role in founding the Virtual Coffee online tech community has had a long-lasting impact on those who often feel overlooked, giving them the confidence they need to pursue careers in tech. Who Are You, Where Are You Based, and What Are You Working On Right Now? I’m a mom of 4, a career transitioner, and an unexpected community builder. I spent ten years teaching college English but found the community I always wanted in tech as I worked through a trauma that turned my life upside down. I’m based in the US, and I’m the creator and one of the maintainers of the Virtual Coffee community, as well as the Technical Community Builder for Deepgram. Congratulations on Being Selected as a Twilio Developer Searchlight Honoree. What Does Being a Mentor or Community Builder Mean to You? To be a community builder is to listen to the needs of others, to represent unheard voices, and to empower those around you. Community building requires a person-first approach, an approach that recognizes that everyone is a person with goals and needs and a life outside of only being a user or teammate, or community member. You Are Passionate About Using Tech for Good, Especially With Regard to Mental Wellness and Inclusivity - Tell Me More About How Virtual Coffee Exemplifies This? Our mission is to be a welcoming tech community that allows room for growth and mentorship at all levels and creates meaningful opportunities for learning, leadership, and contribution for everyone. We welcome and support developers at all stages to create a more empathetic tech community. We believe everyone has the ability to teach and learn, and that collaboration of developers at all stages enriches our community, which we exemplify through the participation of our members. We make space for all voices at our twice-weekly meeting and do our best to equip our room leaders, notetakers, and small group leaders with the support they need. We meet people where they are, make space for everyone, and encourage the exchange and exploration of new ideas to create close relationships. This includes putting practices in place to onboard new volunteers, support new speakers and room leaders, and provide mentorship for open-source contributors. What’s Your One Best Piece of Advice for Aspiring or Early-In-Career Developers? Find the right community for you. They’ll support you through the job search, help you grow in ways your team might not be able to, cheer you on when you win, and help you up when you fall and are too tired to get back up on your own. They can be your map, your support system, and most importantly, your friends. Just for Fun: What Was Your First Computer or Your Most Memorable Piece of Tech? I remember playing Reader Rabbit and Mario Teaches Typing as a kid. I was not a fan of computers and I’m sure I only did it to receive some sort of award! Thank you, , for taking the time to share your story. Stay tuned to learn more about the honorees in our series of interviews. You can also read more about the honorees in this , which unpacks how they’re shaping a better future for developers. Bekah Insider article

COFFEEE

coffeee.io

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Since 2021

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COFFEEE

coffeee.io

51-200 employees

Since 2021

COMPANY RANKING

COFFEEE

EVERGREEN INDEX #2745

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