Cloud computing has revolutionized the way businesses operate and manage their data and applications. The three major players in the cloud computing market are Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Each of these cloud platforms offers a range of services and features, making it important to consider your specific needs and requirements before choosing one.

Amazon Web Services (AWS) is the market leader in cloud computing and provides a comprehensive suite of cloud computing services. AWS offers a range of services, including computing, storage, databases, security, analytics, and artificial intelligence. AWS also provides a range of tools for developers and IT professionals, making it easy to build, deploy, and manage applications. With its global infrastructure, AWS offers low latency and high performance, making it a popular choice for businesses of all sizes.

Microsoft Azure is a cloud computing platform that provides a range of services for businesses and developers. Azure offers a range of services, including virtual machines, storage, databases, and security. It also provides a range of tools for developers, including the Azure DevOps suite, which helps streamline development workflows. Azure also integrates well with other Microsoft products, such as Office 365 and Dynamics 365, making it a good choice for businesses that are already using these products.

Google Cloud Platform (GCP) is a cloud computing platform that provides a range of services for businesses and developers. GCP offers a range of services, including virtual machines, storage, databases, security, and artificial intelligence. GCP also provides a range of tools for developers, including the Google Cloud SDK, which makes it easy to build and deploy applications. GCP is also known for its high-performance infrastructure and innovative technologies, making it a popular choice for businesses looking for cutting-edge solutions.

Here is a detailed comparison between AWS, Azure, and GCP

In conclusion, each of these cloud platforms has its strengths and weaknesses, and the best choice for your business will depend on your specific needs and requirements. AWS is a good choice for businesses that are looking for a comprehensive suite of cloud computing services. Azure is a good choice for businesses that are already using other Microsoft products. GCP is a good choice for businesses looking for cutting-edge solutions and innovative technologies. It is important to consider your specific needs and requirements before choosing a cloud platform and to consult with a cloud computing expert if you need additional guidance.

Before we move toward the SWOT Analysis of Visa 2023 let’s understand Visa’s Business. Visa is a popular and widely used form of payment and financial transaction facilitator, operating globally and serving millions of individuals and businesses across the world. Visa was founded in 1958, and since then, has grown to become one of the largest and most recognized payment technology companies in the world.

Visa operates a global payment network that enables electronic transactions to occur between consumers, merchants, financial institutions and governments. This network allows individuals to use Visa cards and digital wallets to make purchases and transfer funds securely and efficiently. Visa also provides financial institutions with the infrastructure and technology to issue and process Visa payments, helping to make these transactions as secure and seamless as possible.

Visa has several types of cards, each designed to meet the unique needs of different customers. Some of the most popular types of Visa cards include Visa debit cards, Visa credit cards, and Visa prepaid cards. Visa debit cards allow customers to make purchases and withdraw cash directly from their checking account, while Visa credit cards offer a line of credit that can be used to make purchases and receive rewards or cash back. Visa prepaid cards, on the other hand, are a type of reloadable card that can be used anywhere Visa is accepted, and they are ideal for those who do not have a traditional bank account or who want to control their spending.

In addition to its payment network, Visa also provides value-added services to enhance the customer experience and make payments more secure and convenient. For example, Visa provides fraud protection services to help prevent unauthorized transactions, and it also offers travel and emergency services to provide assistance and peace of mind when traveling. Visa also offers a range of digital products, including mobile payments, online bill pay, and digital wallets, making it easier for customers to manage their finances and make payments on the go.

Visa is committed to responsible and sustainable business practices, and it works to support financial inclusion and promote economic growth in communities around the world. For example, Visa provides training and support to small businesses, helping them to access the tools and resources they need to grow and succeed. Additionally, Visa has a strong commitment to privacy and security, and it uses advanced technologies and security measures to protect customer information and prevent fraud.

In conclusion, Visa is a global leader in the payment and financial technology industry, offering a wide range of products and services to meet the needs of individuals and businesses across the world. Whether you need to make purchases, transfer funds, or manage your finances, Visa provides a convenient and secure solution to help you achieve your goals.

SWOT Analysis of Visa 2023

SWOT analysis is a strategic tool that helps to identify the Strengths, Weaknesses, Opportunities, and Threats of a business. Below is a SWOT analysis of Visa:

Strengths: SWOT Analysis of Visa 2023

1. Strong brand recognition: Visa is one of the most recognized and trusted brands in the world, and its name alone provides credibility to its customers and partners.
2. Global reach: Visa operates in over 200 countries, providing customers and businesses with a seamless and convenient payment experience.
3. Secure payment network: Visa uses advanced security measures to protect customer information and prevent fraud, ensuring that transactions are safe and secure.
4. Range of products and services: Visa offers a wide range of products and services, including debit and credit cards, digital wallets, and value-added services, to meet the needs of a diverse customer base.
5. Strong partnerships: Visa has strong partnerships with financial institutions, merchants, and governments, which help to expand its reach and enhance its product offerings.

Weaknesses: SWOT Analysis of Visa 2023

1. Dependence on intermediaries: Visa’s success is dependent on the cooperation of financial intermediaries, and disputes with these partners could harm its business.
2. Competition from other payment providers: Visa faces competition from other payment providers, such as Mastercard and PayPal, who are vying for market share.
3. Vulnerability to cyber threats: With the increasing use of digital technology, Visa is vulnerable to cyber threats, which could impact its reputation and financial stability.

Opportunities: SWOT Analysis of Visa 2023

1. Expansion into new markets: Visa has opportunities to expand into new markets, particularly in emerging economies, where the use of electronic payments is growing.
2. Increasing use of digital payments: With the growing trend of digital payments, Visa has opportunities to offer new and innovative products and services to meet customer needs.
3. Partnership opportunities: Visa has opportunities to form partnerships with other companies and organizations to expand its reach and enhance its offerings.

Threats: SWOT Analysis of Visa 2023

1. Regulatory changes: Visa faces the threat of regulatory changes that could impact its business and profitability, particularly in the areas of data privacy and payment processing.
2. Economic uncertainty: Economic uncertainty, such as recessions and market fluctuations, can impact consumer spending and hurt Visa’s revenue.
3. Technological disruption: Visa faces the threat of technological disruption from new and emerging payment technologies, which could impact its market share and profitability.

In conclusion, Visa has a strong brand, global reach, and secure payment network, which provide the foundation for its success. However, it also faces challenges from competition, cyber threats, and regulatory changes. By leveraging its strengths and addressing its weaknesses, Visa has the opportunity to continue to grow and succeed in the dynamic and evolving payment industry.

What are 10 biggest strengths of Visa? SWOT Analysis of Visa 2023

1. Strong brand recognition: Visa is one of the most recognizable and trusted brands in the world, and its name alone provides credibility to its customers and partners.
2. Global reach: Visa operates in over 200 countries, providing customers and businesses with a seamless and convenient payment experience, no matter where they are located.
3. Secure payment network: Visa uses advanced security measures to protect customer information and prevent fraud, ensuring that transactions are safe and secure.
4. Wide range of products and services: Visa offers a wide range of products and services, including debit and credit cards, digital wallets, and value-added services, to meet the needs of a diverse customer base.
5. Strong partnerships: Visa has strong partnerships with financial institutions, merchants, and governments, which help to expand its reach and enhance its product offerings.
6. Innovation: Visa invests heavily in research and development, enabling it to stay at the forefront of payment technology and offer innovative products and services to meet the changing needs of its customers.
7. Financial stability: Visa is a financially stable company with a strong revenue stream, providing stability and reliability to its customers and partners.
8. Customer-focused: Visa is dedicated to providing a seamless and convenient customer experience, and it is constantly working to improve its products and services to meet the evolving needs of its customers.
9. Strong leadership: Visa has a strong and experienced leadership team, which provides direction and guidance for the company, and helps to drive its success.
10. Responsible business practices: Visa is committed to responsible and sustainable business practices, and it works to support financial inclusion and promote economic growth in communities around the world.

What are 10 biggest weaknesses of Visa? SWOT Analysis of Visa 2023

1. Dependence on intermediaries: Visa’s success is dependent on the cooperation of financial intermediaries, and disputes with these partners could harm its business.
2. Competition from other payment providers: Visa faces competition from other payment providers, such as Mastercard and PayPal, which are vying for market share.
3. Vulnerability to cyber threats: With the increasing use of digital technology, Visa is vulnerable to cyber threats, which could impact its reputation and financial stability.
4. Complex business model: Visa’s business model can be complex, making it difficult for some customers to understand and use its products and services.
5. High fees: Visa charges fees for its services, which can be a barrier for some customers, particularly in countries where electronic payments are not yet widespread.
6. Regulatory restrictions: Visa operates in a heavily regulated industry, and changing regulations can impact its business and profitability.
7. Economic uncertainty: Economic uncertainty, such as recessions and market fluctuations, can impact consumer spending and hurt Visa’s revenue.
8. Technological disruption: Visa faces the threat of technological disruption from new and emerging payment technologies, which could impact its market share and profitability.
9. Limited control over user experience: Since Visa’s products and services are offered through financial intermediaries, it has limited control over the user experience, and this can impact customer satisfaction.
10. Reputation risk: Visa’s reputation is critical to its success, and any negative publicity or data breaches could harm its brand and financial performance.

What are 10 biggest opportunities for Visa? SWOT Analysis of Visa 2023

1. Expansion into new markets: Visa has the opportunity to expand its reach into new and emerging markets, where the use of electronic payments is increasing.
2. Digital transformation: The digital transformation of the payments industry presents an opportunity for Visa to grow its market share and improve its products and services.
3. Partnership and acquisition opportunities: Visa can pursue strategic partnerships and acquisitions to expand its product offerings and enhance its competitive position.
4. Expansion of e-commerce: The growth of e-commerce provides an opportunity for Visa to increase its market share and revenue through its payment processing services.
5. Increased demand for mobile payments: The increasing demand for mobile payments presents an opportunity for Visa to offer new and innovative products and services that meet the needs of its customers.
6. The growing use of contactless payments: The growing use of contactless payments presents an opportunity for Visa to expand its product offerings and improve the customer experience.
7. Increased use of online payments: The increased use of online payments presents an opportunity for Visa to grow its market share and revenue through its payment processing services.
8. Expansion into B2B payments: Visa has the opportunity to expand into the business-to-business (B2B) payments market, which is a large and growing market segment.
9. Growing demand for value-added services: The growing demand for value-added services, such as loyalty programs and rewards, presents an opportunity for Visa to enhance its product offerings and increase its revenue.
10. Increased financial inclusion: The goal of increasing financial inclusion around the world presents an opportunity for Visa to support economic growth and improve the lives of people in underserved communities.

Which are 10 biggest threats to visa? SWOT Analysis of Visa 2023

1. Competition from other payment providers: Visa faces intense competition from other payment providers, such as Mastercard, PayPal, and emerging fintech companies, which can impact its market share and profitability.
2. Cybersecurity threats: The increasing use of digital technology in payments presents a threat from cybercrime and hacking, which could harm Visa’s reputation and financial stability.
3. Regulatory changes: The payments industry is heavily regulated, and changes in regulations or government policies could impact Visa’s business and profitability.
4. Technological disruption: Emerging payment technologies, such as blockchain, could disrupt Visa’s business model and impact its market share.
5. Economic uncertainty: Economic recessions and market fluctuations can impact consumer spending, leading to a decrease in revenue for Visa.
6. Dependence on intermediaries: Visa’s success is dependent on the cooperation of financial intermediaries, and disputes with these partners could harm its business.
7. Changing customer behavior: Changing customer behavior, such as the increasing adoption of mobile payments and digital wallets, could impact Visa’s market share and revenue.
8. Reputation risk: Negative publicity or data breaches could harm Visa’s reputation and brand, impacting its financial performance.
9. Increase in fraud and security incidents: The increasing use of electronic payments presents a risk of fraud and security incidents, which could harm customer confidence in Visa and its products and services.
10. Intellectual property disputes: Visa is vulnerable to intellectual property disputes, which could harm its brand and impact its financial performance.

Who are the biggest competitors of Visa? SWOT Analysis of Visa 2023

1. Mastercard: Mastercard is one of Visa’s biggest competitors, offering similar payment processing services and operating in the same markets.
2. PayPal: PayPal is a popular online payment platform that competes with Visa in the digital payments space.
3. American Express: American Express is a well-established player in the payments industry, offering credit cards and payment processing services in markets around the world.
4. Alibaba’s Alipay: Alipay is a popular payment platform in China, offering online and mobile payment services that compete with Visa.
5. Tencent’s WeChat Pay: WeChat Pay is a mobile payment platform in China, offers payment and financial services that compete with Visa.
6. China UnionPay: China UnionPay is a Chinese payment processing company that operates in China and around the world, competing with Visa for market share.
7. Rupay: RuPay is a national payment network established by the National Payments Corporation of India (NPCI) to provide an indigenous payment processing solution for the country. RuPay has been growing rapidly in India, with a large number of financial institutions, merchants, and individuals using the platform for transactions. RuPay has been able to capture a significant market share in India, offering competitive pricing and services that have helped it to gain popularity among Indian customers. With a focus on the domestic market and its growing popularity, RuPay is seen as a major competitor to Visa and other foreign payment processing companies operating in India.
8. JCB: JCB is a Japanese payment processing company that operates in Asia and around the world, competing with Visa for market share.
9. Discover Financial Services: Discover Financial Services is an American payment processing company that offers credit cards and payment processing services in the US and other markets.
10. Stripe: Stripe is a US-based payment processing company that offers online payment services, including payment processing and fraud prevention.
11. Square: Square is a US-based payment processing company that offers mobile payment processing and other financial services, including point-of-sale (POS) systems.
12. Amazon Pay: Amazon Pay is a payment processing platform offered by Amazon, offering online and mobile payment services to customers.
13. Google Pay: Google Pay is a mobile payment platform offered by Google, providing payment processing services for in-app and online purchases.
14. Apple Pay: Apple Pay is a mobile payment platform offered by Apple, providing payment processing services for in-app and online purchases.
15. First Data: First Data is a US-based payment processing company that offers payment processing and other financial services to merchants and businesses.
16. Worldpay: Worldpay is a payment processing company that operates globally, offering payment processing services and solutions for merchants and businesses.
17. Wirecard: Wirecard is a German payment processing company that operates globally, offering payment processing services and solutions for merchants and businesses.
18. FIS: FIS is a US-based payment processing company that offers payment processing and other financial services to merchants and businesses.
19. Global Payments: Global Payments is a US-based payment processing company that operates globally, offering payment processing services and solutions for merchants and businesses.
20. Adyen: Adyen is a Dutch payment processing company that operates globally, offering payment processing services and solutions for merchants and businesses.
21. Paysafe: Paysafe is a payment processing company that operates globally, offering payment processing services and solutions for merchants and businesses.

Who are the biggest customers of Visa? SWOT Analysis of Visa 2023

Visa has a large and diverse customer base that includes financial institutions, merchants, governments, and individuals. Some of its biggest customers include:

1. Banks and financial institutions: Visa partners with banks and financial institutions to offer payment processing services to their customers. These institutions also issue Visa-branded credit and debit cards.
2. Retail merchants: Visa works with retailers to offer payment processing services and to accept Visa cards at their point-of-sale terminals.
3. Government organizations: Visa works with governments to offer payment processing services and to accept Visa cards for government services.
4. Online and mobile merchants: Visa partners with online and mobile merchants to offer payment processing services for e-commerce transactions.
5. Small and medium-sized businesses: Visa works with small and medium-sized businesses to offer payment processing services and to accept Visa cards at their point-of-sale terminals.
6. Travel and entertainment companies: Visa works with travel and entertainment companies to offer payment processing services and to accept Visa cards for travel and entertainment expenses.
7. Individual cardholders: Visa offers credit and debit cards to individuals, who use these cards to make purchases and withdraw cash at ATMs.

Visa’s customer base is global, with operations in over 200 countries and territories worldwide.

Which countries have issued regulatory hurdles to visa? SWOT Analysis of Visa 2023

There have been instances in various countries where regulatory hurdles have been issued to Visa and other payment processing companies. Some of these countries include:

1. Europe: In Europe, there have been regulatory hurdles related to anti-trust concerns, with the European Union (EU) investigating Visa’s practices.
2. United States: In the United States, Visa and other payment processing companies have faced regulatory hurdles related to anti-competitive practices, fraud prevention, and data privacy.
3. Australia: In Australia, Visa and other payment processing companies have faced regulatory hurdles related to anti-competitive practices and the interchange fee system.
4. India: In India, Visa and other payment processing companies have faced regulatory hurdles related to data privacy and data protection, as well as the need for greater transparency in payment processing fees.
5. China: In China, Visa and other foreign payment processing companies have faced regulatory hurdles related to market access and competition, as the country has been promoting the use of its own domestic payment processing companies.

These regulatory hurdles can have an impact on the operations and growth of payment processing companies and may result in fines or restrictions on their activities. Companies like Visa are actively working to address these regulatory challenges and maintain their position as leading payment processing companies.

Also Read:

Solar Industries Limited SWOT Analysis

SWOT Analysis of Apple(AAPL) 2023

SWOT Analysis of Saudi Aramco 2023

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Artificial intelligence is a branch of computer science. It attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can react in a similar way to human intelligence. Regarding the emerging industry of artificial intelligence AI, many people have many misunderstandings. Today, the editor has collected some knowledge about artificial intelligence AI for everyone to popularize science.

Encyclopedia Directory
• What is artificial intelligence
• Seven misunderstandings about artificial intelligence AI
• Artificial intelligence in the future

What is artificial intelligence ?

If you are a business executive (rather than a data scientist or machine learning expert), you may have been exposed to artificial intelligence from mainstream media reports. You may have read related articles in “The Economist” and “Forbes”, or read stories about Tesla’s autonomous driving, or Stephen Hawking’s article about the threat of AI to humans, and even read about artificial intelligence and human intelligence. Caricature. Therefore, if you are an executive who cares about the development of your company, these media reports about AI may raise two annoying questions: First, is the commercial potential of AI true or false? Second, how can AI be applied to my products? The answer to the first question is yes, AI has commercial potential. Today, companies can use AI to change automated operating processes that require human intelligence. AI can increase the workload of human-intensive companies by 100 times while reducing unit economic efficiency by 90%. It takes a little more time to answer the second question. First, we must eliminate the AI myth promoted by mainstream media. Only by eliminating these misunderstandings can you have a framework for how to apply AI to your business.

Seven misunderstandings about artificial intelligence AI

Myth 1: AI is magic

Many mainstream media describe AI as magical as if we only need to applaud senior magicians from big companies such as Google, Facebook, Apple, Amazon, and Microsoft. This description is unhelpful. If we want companies to adopt AI, then we need to make entrepreneurs understand AI. AI is not magic. AI is data, mathematics, model, and iteration. In order for AI to be accepted by enterprises, we need to be more transparent. The following are explanations of 3 key concepts related to AI:

Training data (TD): Training data is the initial data set for machine learning. Training data includes input and pre-answer output, so machine learning models can find patterns for any given output. For example, the input can be a customer support ticket with an email thread between the customer and a corporate support representative (CSR), and the output can be a category label from 1 to 5 based on a company-specific category definition.

Machine Learning (ML): Machine learning is software that can learn patterns from training data and apply these patterns to new input data. For example, when you receive a new customer support ticket with an email thread between the customer and the CSR, the machine learning model can predict its classification and tell you its confidence in the prediction. The main feature of machine learning is that it learns new rather than applying inherent rules. Therefore, it can adjust its rules by digesting new data.

Human-in-the-Loop (HITL): Human-in-the-Loop is the third core element of AI. We cannot expect machine learning models to be absolutely reliable. A good machine learning model may only have 70% accuracy. Therefore, when the confidence of the model is low, people need to use the Human-in-the-Loop workflow.

So, don’t be fooled by the myth that AI is magic. The basic formula for understanding AI is: AI=TD+ML+HITL.

Myth 2: AI is only for the technical elite

Media reports can easily give people the illusion that AI only belongs to the technical elite-big companies such as Amazon, Apple, Facebook, Google, IBM, Microsoft, Salesforce, Tesla, Uber-only they can form a large team of machine learning experts, and receive a billion-dollar investment. This concept is wrong.

Today, you can start applying AI to your business without $100,000. So, if you are one of the 26,000 companies in the U.S. whose revenue is greater than $50 million, you can invest 0.2% of the revenue in AI applications.

Therefore, AI is not exclusive to technical elites. It belongs to every business.

Myth 3: AI is only to solve billion-dollar problems

Mainstream media tend to report on futuristic things, such as self-driving cars or unmanned aircraft used to deliver express delivery. Companies like Google, Tesla, and Uber have invested tens of billions of dollars in order to seize the leading position in the future driverless car market due to the “winner takes all” mentality. These give the impression that AI is only used to solve new problems at the billion-dollar level. But this is another mistake.

AI is also used to solve existing smaller problems, such as million-dollar problems. Let me explain: The core requirement of any company is to understand the customer. This is the case from the agora market in ancient Greece and the personal trading square in ancient Rome. This is also true today, even if business transactions have moved explosively to the Internet. Many companies sit on a treasure trove of unstructured data from customers, which comes from email threads or Twitter comments. AI can be applied to these classifications to support ticket challenges, or to understand the sentiment of tweets.

Therefore, AI can not only be applied to new and exciting problems at the billion-dollar level, such as self-driving cars. AI is also used for existing “uninteresting” small problems, such as better understanding of customers by supporting ticket classification or social media sentiment analysis.

Myth 4: Algorithms are more important than data

Reports on AI in mainstream media tend to believe that machine learning algorithms are the most important element. They seem to equate algorithms with the human brain. They imply that it is the algorithm that makes the magic work, and that more sophisticated algorithms can surpass the human brain. Reports about machines defeating humans in Go and Chess are examples. The media is concerned about “deep neural networks”, “deep learning” and how machines make decisions.

Such reports may give companies the impression that if they want to apply AI, they must first hire machine learning experts to build a perfect algorithm. But if companies do not consider how to obtain higher quality and larger amounts of customized training data for machine learning models to learn, even with perfect algorithms, they may not get the desired results (“We have great algorithms” and “We The model only has an accuracy of 60%.”

Buying commercial machine learning services from companies such as Microsoft, Amazon, and Google without a training data plan or budget is like buying a car and failing to reach the gas station. You just bought a large piece of very expensive metal. The analogy between cars and gasoline is not appropriate, because if you give a machine learning model more training data, the better the model will become. It’s like every time a car runs out of gasoline, the greater the mileage accumulated. So training data is even more important than gasoline. Therefore, the quality and quantity of training data are at least as important as algorithms.

Myth 5: Machines>People

For the past 30 years, the media has always liked to describe AI as a machine that is stronger than humans, such as Schwarzenegger in “Terminator” and Alicia in “Ex Machina” Vikander. It is understandable for the media to do so, because the media wants to establish a simple narrative structure of who will win between the machine and the human. However, this does not match the actual situation.

For example, the recent news that Google’s DeepMind/AlphaGo defeated Li Shishi was simply described by the media as the victory of machines over humans. This is inaccurate, and the real situation is not so simple. A more accurate description should be “the machine unites many people to defeat one person”.

The core reason for eliminating this misunderstanding is that machines and humans have complementary capabilities. Please see the picture above. The machine’s specialty is processing structured calculations, and they will perform well on the task of “finding feature vectors”. Humans’ specialty is to understand meaning and context. They perform well on the task of “finding leopard print dresses”, and it is not so easy for humans to do the task of “finding feature vectors”.

Therefore, the correct framework for enterprises is to realize the complementarity of machines and humans, and AI is the joint work of machines and humans.

Myth 6: AI is the replacement of humans by machines

The mainstream media like to portray the future of dystopia because they think it can attract attention. This may indeed attract readers’ attention, but it does not help to truly understand how machines and humans work together.

For example, let’s go back to the business of enterprise classification to support ticket. In most companies today, this is still a 100% manual process. Therefore, this process is slow and costly, and the number of things that can be done is limited. Suppose you have a model with 70% accuracy after categorizing 10,000 support tickets. The result is wrong 30% of the time, but then Human-in-the-loop can intervene. You can set the acceptable confidence level to 95% and only accept output results with a confidence level of 95% or higher. Then the machine learning model can only do a small part of the work initially, such as 5%-10%. But when the model gets new artificially labeled data, it can learn and improve. Therefore, as time goes by, the model can handle more customer support ticket classification work, and enterprises can also greatly increase the number of classified tickets.

Therefore, the combination of machines and people can increase the workload while maintaining quality and reducing the unit economic benefits of important businesses. This eliminates the AI ​​myth that machines replace humans. The truth is that AI is a machine that strengthens humans.

Myth 7: AI=ML

The last myth about AI in mainstream media is that artificial intelligence and machine learning are treated as the same thing. This may make corporate management think that as long as they buy a commercial machine learning service from Microsoft, Amazon, or Google, they can turn AI into products.

To implement an AI solution, in addition to machine learning, you also need training data, which requires human-in-the-loop. Machine learning without training data is like a car without gasoline. Although it is expensive, it can’t go anywhere. The lack of human-in-the-loop machine learning can also lead to undesirable consequences. You need people to overturn the low-confidence predictions of machine learning models.

Artificial intelligence in the future

There will definitely be a big change in transportation, from the current manual driving to the future unmanned driving. Now in Silicon Valley, the United States can often see those unmanned vehicles put into use, not only unmanned cars, aircraft can also use unmanned technology to soar in the sky, are you hungry, commercial use of small drones Food delivery has already begun. So there will be a big change in traffic. There will certainly be a huge gap in medical treatment. Artificial intelligence will automate diagnosis by automatically browsing the user’s condition. At the same time, wearable medical devices and mobile applications can enable us to go further in the future of artificial intelligence medical treatment. It can also be further improved in terms of wheelchairs and intelligent bones. In terms of security, artificial intelligence must also be an indispensable part of the future. In the future, artificial intelligence will become a very important part of public security, whether it is from the face recognition technology on surveillance or the robot police judge in the future, it will have an important position. At present, face recognition technology has been used in most of cameras, which is of great help to the police in finding suspects. It is believed that artificial intelligence will be of greater help to the police in the future.

Digital technology has become omnipresent. Over the past two decades, we have become more and more dependent on smartphones, tablets, and PC devices. Last year’s epidemic pushed this digital wave to new heights.

Smartphones are a popular communication form worldwide in this century and are likely to remain as such, especially among adolescents. The phone has evolved from basic communicative functions–calls only–to being a computer-replacement device, used for web browsing, games, instant communication on social media platforms, and work-related productivity tools, e.g. word processing. Smartphones undoubtedly keep us connected; however, many individuals are now obsessed with them.

Conventional wisdom says that over-reliance on technology may affect us in a bad way. It may weaken our memory, concentration, and self-control abilities. These are obviously important cognitive abilities. However, this fear may not be based on fact.

Technology changes society

Socrates, the father of philosophy, was deeply worried about the impact of writing technology on society. The oral skill of speech has higher demands on memory function. He was worried that writing will eliminate the need for people to learn and exercise memory.

Plato once quoted Socrates’ famous saying:

When people have mastered the ability to write, forgetfulness will also take root in the depths of the soul; they no longer need to exercise memory, because what they write is enough to remind themselves. As a result, people will no longer rely on the inside, but use external signs to evoke memories.

This passage is very interesting.

Firstly :

It represents an intergenerational discussion among early philosophers about the impact of emerging technologies on the cognitive abilities of future generations. To this day, similar debates still exist. Telephone, radio, and television all have been considered as the “destroyers” of cognitive abilities.

Second interesting reason:

Although Socrates was very worried, modern humans are still able to retrieve information from memory at any time. Technology only reduces the need for certain cognitive functions. But it does not affect our actual execution capabilities.

Cognitive deterioration

Apart from the sensational rhetoric of the mass media, there are also scientific discoveries that prove that technology can make cognitive ability worse. However, after careful analysis of these points of view, we will find that there are two important premise assumptions:

1) it is assumed that this influence has a lasting impact on long-term cognitive ability;

2) it is assumed that digital technology has a significant direct and unlimited impact on cognition. However, neither of these two hypotheses has been supported by any practical research.

We can see that all influential conclusions are only temporary, not long-term. For example,In a study on the dependence of humans on external memory forms, when participants were told that certain information would be stored on a computer and accessible at any time, their ability to remember the content of the information would decrease. At the same time, if they learn that if they forget, the content of the information will be impossible to recover, their memory will quickly improve.
The use of technology does show “signs” of memory decline. But if there is no technology to rely on, the subjects can still revamp their memory’s ability at any time. Therefore, it is too sloppy to say that technology will damage human memory.

In addition, the impact of digital technology on cognition may also depend on the enthusiasm of the individual, not just the cognitive process. In fact, cognitive processes often have completely different modes of operation under the background of different motivations of different individuals. Specifically, the more we can find sufficient internal drive in a certain task, the higher the degree of devotion and concentration. If this is the case, then there will be a different interpretation of the experimental data-at least it does not simply mean that the smartphone will destroy continuous attention, working memory, or functional liquid intelligence.
Motivational factors have a considerable influence on the results of the research. After all, participants often think that the tasks they are required to complete are boring or irrelevant. Since we are accustomed to using digital technology to deal with daily affairs such as dealing with messages, replying to e-mails, and enjoying entertainment, the intervention of digital technology may weaken the incentive effect in experimental tasks.
The important thing is that all of this means that digital technology does not damage cognition-if a task is really important or attractive, people’s ability to perform will not be destroyed by smartphones.

Changes in cognition

In order to use digital technology for training, the internal cognitive process pays less attention to information storage and calculation; on the contrary, the cognitive process is used to converting information into a format that can be transferred to digital devices-such as searching for phrases, and then reloading them and explanation. This kind of cognitive transfer is like people gradually learning to record the results of phased thinking on paper, instead of relying on their own heads to memorize them; or to give a more intuitive example, children break their fingers and make simple calculations.

The main difference between the two is that, compared with analog tools, digital technology can help us transfer complex information sets more efficiently without any loss of accuracy. In this way, we can free ourselves from a few specialized functions and use internal cognitive abilities to handle other core tasks. From a cognitive perspective, digital technology actually allows us to achieve greater achievements than ever before.

Therefore, it is not necessary to regard digital technology as the enemy of our internal cognitive process; on the contrary, it is expanding our working capabilities and expanding our cognitive boundaries.

You could also try boosting your memory based on these principles

Tip 1: Make Time for Meditation
Tip 2: Give your brain a workout
Tip 3: Don’t skip the physical exercise
Tip 4: Get your Zs
Tip 5: Make time for friends
Tip 6: Get Your Vitamin D Levels Tested. Levels shouldn’t be low.
Tip 7: Keep stress in check
Tip 8: Have a hearty laugh
Tip 9: Eat a brain-boosting diet
Tip 10: Identify and treat health problems
Tip 11: Drink less Alcohol

First, the introduction of microservices

1. What are Microservices

In the introduction of microservices, we must first understand what microservices are. As the name suggests, microservices have to be understood from two aspects,what is “micro” and what is “service”. In the narrow sense, the small and famous”2 pizza team” is a good interpretation of this explanation (the 2 pizza team was first proposed by Amazon CEO Bezos, meaning that the design of a single service, all participants from the design, development, testing, operation and maintenance owners add up to only 2 pizzas). The so-called service, must be different from the system, service one or a set of relatively small and independent functional units, is the user can perceive the minimum set of functions.

2. Origin of Microservices

First proposed by Martin Fowler and James Lewis in 2014, microservices architecture style is a way to develop a single application using a set of small services, each running in its own process and communicating using lightweight mechanisms, usually HTTP APIs, that are built on business capabilities and can be deployed independently through automated deployment mechanisms, implemented in different programming languages, and different data storage technologies, with minimal centralized management.

3. Why do you need microservices?

In the traditional IT industry, most of the software is piling up a variety of independent systems, the problem of these systems is summed up as poor scalability, reliability is not high, high maintenance costs. However, since SOA used bus mode in the early days, this bus mode is strongly bound to a certain technology stack, such as: J2EE. This results in many enterprises ‘ legacy systems are difficult to connect, switching time is too long, the cost is too high, the convergence of the stability of the new system also takes some time.In the end, SOA looks beautiful,but it has become an enterprise-class luxury that small and medium-sized companies are afraid of.

3.1 Problems caused by the monolithic architecture

The single architecture works well in the case of a relatively small scale, but with the expansion of the scale of the system, it exposes more and more problems, mainly the following points：

1.Complexity gets higher

For example, some projects have hundreds of thousands of lines of code, the difference between the various modules is more vague, the logic is more confusing, the more code complexity, the more difficult to solve the problem encountered.

2.Technological debt is rising

The company’s personnel flow is a normal thing, some employees before leaving, neglect the quality of the self-control, resulting in leaving a lot of errors, due to the huge amount of project code, a error is difficult to find, which brings great trouble to the new employees, the greater the turnover of personnel left more errors, which is the so-called technical debt more and more.

3.Deployment slows down gradually

This is very well understood, the single architecture module is very large, the amount of code is very large, resulting in the deployment of the project takes more and more time, once some projects start to take 10 minutes, what a terrible thing ah, start a few projects a day will pass, leaving developers very little time to develop.

4.Hindering technological innovation

For example, a previous project was written using struts2, due to the inextricably linked between the various modules, the amount of code, the logic is not clear enough, if you want to use spring mvc to refactor this project will be very difficult, the cost will be very large, so more often companies have to bite the bullet to continue to use the old struts architecture, which hinders the innovation of technology.

5.Cannot scale on demand

For example, the movie module is a CPU-intensive module,and the order module is IO-intensive module, if we want to improve the performance of the order module, such as increasing memory, increasing hard disk, but because all modules are in one architecture, so we have to consider other module factors when expanding the performance of the order module, because we can not expand the performance of a module and damage the performance of other modules, and thus can not scale on demand.

3.2 Differences between Microservices and Monolithic Architectures

Each module of microservices is equivalent to a separate project. The amount of code is significantly reduced, and the problem is relatively easy to solve.

Single architecture All modules share a database, the storage mode is relatively single, microservices each module can use a different storage mode (for example, some use redis, some use mysql, etc.), the database is also a single module corresponding to its own database.

Monolithic architecture All module development uses the same technology, microservices each module can use a different development technology, the development mode is more flexible.

3.3 Microservices and SOA Differences

Microservices, in the essence, are SOA architectures.In a microservice system, there can be services written in Java or services written in Python. They are unified into a system by Restful architectural style.So the microservices themselves have nothing to do with the specific technology implementation, and are highly scalable.

4. The Nature of Microservices

Microservices, the key is not just the microservices themselves,but the system should provide a set of basic architecture, which allows microservices to be deployed, run, and upgraded independently. Not only that, the system architecture also allows microservices and microservices to be structurally “loosely coupled”, and functionally expressed as a unified whole.This so-called“unified whole”shows a unified style of interface, unified rights management, unified security policy, unified on-line process, unified log and audit methods, unified scheduling, unified access entry and so on.

The purpose of microservices is to effectively split applications for agile development and deployment.

Microservices promote the idea that inter-team should be inter-operate, not integrate .inter-operate is to define the boundaries and interfaces of the system. In a team full stack, let the team be autonomous, because if the team is formed in such a way, the cost of communication within the system will be maintained, each subsystem will be more cohesive, each other’s dependent coupling can become weak, cross-system communication costs can be reduced.

5. What kind of project is suitable for microservices

Microservices can be divided according to the independence of the business function itself, if the system provides services that are very low-level, such as: operating system kernel, storage system, network system, database system, etc., such systems are low-level, there is a close relationship between functions and functions, if forced to split into smaller service units, will make the integration workload rise sharply, and this artificial cutting can not bring real isolation on the business, so can not be deployed and run independently, it is not suitable for making microservices.

Whether you can make a microservice depends on four elements：

• Small: microservices are small in size,2 pizza teams.
• Independent:Ability to deploy and run independently.
• Light: Use lightweight communication mechanisms and architectures.
• Loose: Is loosely coupled between services.

6. Microservice Folding and Design

Moving from a monolithic structure to a microservice architecture will continue to encounter the problem of service boundary division: for example, we have a user service to provide the basic information of the user,so should the user’s avatar and picture, etc. be divided into a new service is better or should it be merged into the user service?If the granularity of the service is too coarse, it is back to the old way of monolithic; if it is too fine, the overhead of inter-service calls becomes negligible, and the difficulty of management increases exponentially.So far, there is no standard that can be called service boundary division, which can only be adjusted according to different business systems

The big principle of splitting is that when a business does not depend on or rarely depends on other services,has independent business semantics, provides data for more than 2 other services or clients, then it should be split into a separate service module.

6.1 Microservice Design Principles

Principle of Single Responsibility

It means that each microservice only needs to implement its own business logic on it, such as the order management module, it only needs to process the business logic of the order on it, and the rest does not need to be considered.

Principles of Service Autonomy

It means that each microservice is independent from development, testing, operation and maintenance, etc., including the stored database is also independent, there is a complete process, we can treat it as a project.Do not have to rely on other modules.

Lightweight Communication Principles

The first is that the language of communication is very lightweight, second, the communication mode needs to be cross-language, cross-platform, cross-language is to make each microservice has enough independence, can not be controlled by technology.

Clear principles of interfaces

Since there may be invocation relationships between microservices, in order to try to avoid future adjustments due to changes in the interface of a microservice, it is necessary to take into account all situations at the beginning of the design, so that the interface is as common and flexible as possible, so as to avoid other modules also making adjustments.

7. Microservices Advantages and Disadvantages

7.1 Advantages

Each microservice can run independently in its own process；

A series of independently running microservices work together to build the entire system；

Each service is developed as a separate business, and a microservice generally completes a specific function,such as: order management, user management, etc；

Microservices communicate through lightweight communication mechanisms,such as calls via REST APIs or RPC.

7.2 Advantages

Easy to develop and maintain

Since a single module of microservices is equivalent to a project, the development of this module we only need to care about the logic of this module, the amount of code and logical complexity will be reduced, so that it is easy to develop and maintain.

Faster start-up

This is relative to a single microservice, and the service speed of starting a module is obviously much faster than starting an entire project with a single architecture.

Local modifications are easy to deploy

We found a problem in the development. If it is a single architecture, we need to re-release and start the whole project,which is very time-consuming, but microservices are different. Which module has a bug we only need to solve the bug of that module, after solving the bug, we only need to restart the service of this module, the deployment is relatively simple, do not have to restart the entire project, thus saving time.

The technology stack is not limited

For example, order microservices and movie microservices were originally written in java.Now we want to change the movie microservices to NodeJS technology,which is entirely possible,and because the focus is only on the logic of the movie, the cost of technology replacement will be much less.

Scaling on demand

We said above that monolithic architecture when you want to extend the performance of a module, you have to take into account whether the performance of other modules will be affected. For our microservices, it is not a problem at all.

7.3 Disadvantages

High operation and maintenance requirements

For a single architecture, we only need to maintain this project, but for a microservice architecture, because the project is composed of multiple microservices, each module problem will cause the whole project to run abnormally, it is often not easy to know which module caused the problem, because we can not track the problem step by step through debug, which puts forward high requirements for the operation and maintenance personnel.

Distributed Complexity

For a single architecture, we can not use distributed, but for a microservice architecture, distributed is almost a necessary technology, due to the complexity of distributed itself, resulting in microservice architecture has become complex.

High cost of interface adjustment

For example, user microservices are to be called by order microservices and movie microservices. Once the interface of the user microservices changes greatly, then all the microservices that depend on it have to be adjusted accordingly. Since the microservices may be very large, the cost of adjusting the interface will be significantly increased.

Repetitive work

For a single architecture, if a business is used by multiple modules, we can abstract it into a tool class that is called directly by all modules,but microservices cannot do so, because the tool class of this microservice cannot be called directly by other microservices, so we have to build such a tool class on each microservice, resulting in duplication of code.

8. Microservices Development Framework

At present, the development framework of microservices, the most commonly used are the following four：

Spring Cloud:http://projects.spring.io/spring-cloud (Now very popular microservice architecture）

Dubbo：http://dubbo.io

Dropwizard: http://www.dropwizard.io (Focus on the development of individual microservices）

Consul, etcd&etc.(Modules for microservices）

9. The difference between Sprint cloud and Sprint boot

Spring Boot:

Designed to simplify the creation of product-level Spring applications and services, it simplifies configuration files, uses embedded web servers, contains many out-of-the-box microservices capabilities, and can be deployed jointly with spring cloud.

Spring Cloud：

The Microservice toolkit provides developers with development kits for distributed system configuration management, service discovery, circuit breakers, intelligent routing, micro-agent, control bus and so on.

Second, microservices practice

1. How do clients access these Microservices services?（API Gateway）

The traditional way of development,all services are local, the UI can be called directly, now split into independent services by function, running in a separate Java process that is generally on a separate virtual machine.How does the client UI access his?There are N services in the background,the front desk needs to remember to manage N services,a service offline / update / upgrade, the front desk will be redeployed, which obviously does not serve our split concept, especially when the current desk is a mobile application, usually the pace of business changes is faster.In addition, N small service calls are not a small network overhead.There are also general microservices within the system, usually stateless, and user login information and rights management is best to have a unified local maintenance management (OAuth).

Therefore, generally between the N services in the background and the UI will generally be a proxy or called API Gateway,his role includes

Provide a unified service portal for microservices to be transparent to the foreground

Aggregate back-end services to save traffic and improve performance

Provide security, filtering, flow control and other API management functions

In fact, I understand that this API Gateway can have a lot of generalized implementation, it can be a soft and hard box, it can be a simple MVC framework, or even a Node.The server side of js.Their most important role is to provide an aggregation of background services for the foreground (usually mobile applications), provide a unified service exit, and de-coupling between them, but API Gateway can also become a single point of failure or a performance bottleneck.

2. How do Microservices communicate?(Service calls）

Because all microservices are independent Java processes running on independent virtual machines, so the traffic between services is IPC (inter process communication), there have been many mature programs.Now there are two ways to basically the most versatile.In these ways, you can write a book in terms of expansion, and we are generally familiar with the details, and we do not expand the talk.

REST（JAX-RS，Spring Boot）

RPC（Thrift, Dubbo）

Asynchronous message calls(Kafka, Notify)

General synchronous call is relatively simple, consistency is strong,but easy to call problems, performance experience will be worse, especially when the call level is more.The comparison between RESTful and RPC is also a very interesting topic.General REST based on HTTP, easier to implement, easier to be accepted, the server implementation technology is more flexible,each language can support, at the same time across the client, there are no special requirements for the client, as long as the package of HTTP SDK can be called, so relatively wide use.RPC also has its own advantages, the transport protocol is more efficient,more secure and controllable, especially in a company, if there is a unified development specification and a unified service framework, his development efficiency advantages are more obvious.Look at the actual conditions of their technical accumulation, their own choice.

The asynchronous message mode has a particularly wide range of applications in distributed systems, he can reduce the coupling between the calling services, but also become a buffer between calls, to ensure that the backlog of messages will not flush the callee, while ensuring the caller’s service experience, continue to do their own work, will not be slow down by background performance.However, the cost is to weaken the consistency, the need to accept the final consistency of the data; there is a background service generally to achieve idempotence, because the message is sent for performance considerations will generally be repeated(to ensure that the message is received and received only once is a great test of performance); and finally, the need to introduce an independent broker,if there is no technical accumulation within the company, the broker distributed management is also a great challenge.

3. How do you find so many services?(Service Discovery）

In the microservice architecture, each service generally has multiple copies to do load balancing.A service may go offline at any time,or it may add new service nodes to temporary access pressure.How do services perceive each other?How is the service managed?This is the problem with service discovery.There are generally two types of practices, but also have advantages and disadvantages.Basically, it is through zookeeper and other similar technologies to do distributed management of service registration information.When the service goes live, the service provider registers its service information to ZK(or similar framework) and maintains a long link through a heartbeat, updating the link information in real time.Service callers address through ZK, according to customizable algorithms, find a service, you can also cache the service information locally to improve performance.When the service is offline, ZK will send a notification to the service client.

Client-side: The advantage is that the architecture is simple,the extension is flexible, and only depends on the service registrar.The disadvantage is that the client has to maintain the address of all the calling services, there is technical difficulty, and the general large companies have mature internal framework support,such as Dubbo.

Server side: The advantage is simple,all services are transparent to the front-end caller, and applications deployed on cloud services in small companies are generally used more.

4. What if the service hangs up in Microservices?

The biggest feature of distributed is that the network is unreliable.This risk can be reduced through microservice splitting, but without special guarantees, the outcome is definitely a nightmare.We have just encountered an online failure is a very humble SQL counting function, when the number of visits increases, resulting in high database load, affecting the performance of the application, thus affecting all the foreground applications that call this application service.So when our system is composed of a series of service call chains, we must ensure that any link problem does not affect the overall link.

There are many corresponding means：

1. Retry mechanism
2. Current limiting
3. Fuse mechanism
4. Load Balancing

Downgrade (local caching) these methods are basically clear and generic, not detailed.

For example, Netflix’s Hystrix:https://github.com/Netflix/Hystrix

5. Issues to consider for Microservices

Here’s a very good graph summarizing the issues to consider in microservice architecture, including

API Gateway

Inter-service calls

Service Discovery

Service Fault Tolerance

Service Deployment

Data calls

Third, microservices important components

1. Microservices Basic Capabilities

2. Service Registry

Services need to create a service discovery mechanism to help services perceive each other’s existence.When the service starts, it will register its own service information to the registry and subscribe to the services it needs to consume.

The service registry is the core of service discovery.It holds the network addresses (IPAddress and Port) of each of the available service instances.The service registry must have high availability and real-time updates.The Netflix Eureka mentioned above is a service registry.It provides a REST API for service registration and query service information.The service registers its own IPAddress and Port by using a POST request.Every 30 seconds, a PUT request is sent to refresh the registration information.Log off the service with a DELETE request.The client obtains the available service instance information through a GET request. Netflix achieves high availability is achieved by running multiple instances on Amazon EC2,with each Eureka service having an elastic IP Address.When the Eureka service starts, there is dynamic allocation of DNS servers.The Eureka client obtains the network address (IP Address and Port) of Eureka by querying DNS.In general, the Eureka server address is returned and the client is in the same availability zone. Others that can act as a service registry are：

etcd-highly available, distributed, strongly consistent, key-value, Kubernetes, and Cloud Foundry all use etcd.

consul-a tool for discovering and configuring.It provides an API that allows clients to register and discover services.Consul can perform a service health check to determine the availability of the service.

zookeeper — widely used in distributed applications, high-performance coordination services. Apache Zookeeper was originally a subproject of Hadoop,but is now a top-level project.

2.1 zookeeper service registration and discovery

In simple terms, zookeeper can act as a service Registry, allowing multiple service providers to form a cluster, allowing service consumers to obtain specific service access addresses (ip+ports) through the service registry to access specific service providers.As shown in the following figure：

Specifically, the zookeeper is a distributed file system, whenever a service provider after deployment to their services registered to The zookeeper of a way on the PATH: /{service}/{version}/{ip:port}, such as our HelloWorldService deployed to the two machines, then the zookeeper will create two entries recorded: were/HelloWorldService/1.0.0/100.19.20.01:16888 /HelloWorldService/1.0.0/100.19.20.02:16888。

zookeeper provides a “heartbeat detection” function, it will periodically send a request to each service provider(in fact, a long socket connection is established), if there is no response for a long time, the service center will think that the service provider has“hung up”, and cull it, for example, 100.19.20.02 If the machine is down, then the path on zookeeper will be only/HelloWorldService/1.0.0/100.19.20.01:16888.

The service consumer will listen to the corresponding path (/HelloWorldService/1.0.0), once the data on the path has a task change (increase or decrease), zookeeper will notify the service consumer service provider address list has changed, so as to update.

More importantly, zookeeper’s innate fault-tolerant and disaster-tolerant capabilities (such as leader elections) ensure high availability of the service registry.

3. Load Balancing

In order to ensure high availability, each microservice needs to deploy multiple service instances to provide services.At this point, the client performs load balancing of the service.

3.1 Common Strategies for Load Balancing

3.1.1 Random

The request from the network is randomly assigned to multiple servers in the internal.

3.1.2 Polling

Each request from the network, in turn assigned to the internal server, from 1 to N and then start over.This load balancing algorithm is suitable for servers within the server group have the same configuration and the average service request is relatively balanced.

3.1.3 Weighted Polling

According to the different processing power of the server, assign different weights to each server, so that it can accept the corresponding number of weights of the service request.For example: the weight of the server A is designed to be 1, the weight of B is 3, the weight of C is 6, the server A, B, C will receive 10%, 30%, 60% of the service request.This equalization algorithm can ensure that high-performance servers get more usage, to avoid low-performance servers overloaded.

3.1.4 IP Hash

This way by generating a hash value of the request source IP, and through this hash value to find the correct real server.This means that his corresponding server is always the same for the same host.In this way, you do not need to save any source IP.However, it is important to note that this approach may result in an unbalanced server load.

3.1.5 Minimum number of connections

The time spent on the server for each request of the client may vary greatly. With the lengthening of the working time, if a simple round robin or random balancing algorithm is used, the connection process on each server may vary greatly and does not achieve true load balancing.The minimum number of connections balancing algorithm has a data record for each server that needs to load internally, recording the number of connections currently being processed by the server. When there is a new service connection request, the current request will be assigned to the server with the least number of connections, so that the balance is more in line with the actual situation and the load is more balanced.This equalization algorithm is suitable for long-term processing of request services,such as FTP.

4. Fault tolerance

Fault tolerance, the understanding of the word, is to accommodate the error, do not let the error expand again, let the impact of the error within a fixed boundary,”a thousand miles of embankment destroyed in the nest ” The way we use fault tolerance is to make the nest do not grow large.Then our common downgrades, current limiting, fuses, timeout retry, etc. are fault-tolerant methods.

When calling a service cluster, if a microservice invokes exceptions, such as timeouts, connection exceptions, network exceptions, etc., the service fault tolerance is made according to the fault tolerance policy.Currently supported service fault tolerance policies have fast failure, failure switching.If it fails multiple times in a row, it fuses directly and no longer initiates the call.This prevents a service exception from draining all services that depend on him.

4.1 Fault Tolerance Policy

4.1.1 Fast Failure

The service only initiates a stand-by, and the failure immediately reports an error.Typically used for write operations that are not idempotent

4.1.2 Failover

The service initiates a call, and when a failure occurs, retry the other server.Usually used for read operations, but retry brings a longer delay.The number of retries can usually be set

4.1.3 Failure Security

Fail safe, when the service call has an exception, it is ignored directly.Typically used for operations such as writing logs.

4.1.4 Automatic recovery of failures

When an exception occurs in a service call, a failed request is logged and a regular retransmission is made.Typically used for message notifications.

4.1.5 forking Cluster

Multiple servers are called in parallel, and as long as there is one success, it is returned.Usually used for high real-time read operations.The maximum number of parallelism can be set by forks=n.

4.1.6 Broadcast Calls

The broadcast calls all providers, one by one, and any failure fails.It is typically used to notify all providers of updates to local resource information such as caches or logs.

5. Fusing

Fuse technology can be said to be a kind of”intelligent fault tolerance”, when the call meets the number of failures, the failure ratio will trigger the fuse to open, there is a program to automatically cut off the current RPC call, to prevent further expansion of the error.To achieve a fuse is mainly to consider three modes, off, open, half open.The transition of each state is shown below.

   When we deal with exceptions, we have to decide how to handle them according to the specific business situation. For example, we call the commodity interface, the other party only temporarily does the downgrade process, then as a gateway call, we have to cut to the alternative service to perform or get the bottom data, and give user-friendly tips.There is also a need to distinguish the type of exception, such as the dependent service crashes, which may take a long time to solve.It may also be that the server load is temporarily too high, resulting in a timeout.As a fuse should be able to identify this type of exception, so as to adjust the fuse strategy according to the specific type of error.Added manual settings, in the case of failed service recovery time is uncertain, the administrator can manually force the switch fuse state.Finally, the fuse usage scenario is to call a remote service program or shared resource that may fail.If local private resources are cached locally, the use of fuses increases the overhead of the system.Also note that fuses cannot be used as an exception handling substitute for business logic in your application.

Some exceptions are stubborn, sudden, unpredictable, and difficult to recover, and can also lead to cascading failures (for example, suppose a service cluster load is very high, if a part of the cluster hangs up at this time, but also accounts for a large part of the resources, the entire cluster may suffer).If we continue to retry at this time, the result is mostly a failure.Therefore, at this time our application needs to immediately enter the failure state(fast-fail), and take the appropriate method for recovery.

We can use a state machine to implement CircuitBreaker, which has the following three states：

Closed: Circuit Breaker is closed by default, allowing the operation to be executed.CircuitBreaker internally records the number of recent failures, and if the corresponding operation fails, the number will continue once.CircuitBreaker transitions to the Open state if the number of failures( or the failure rate )reaches a threshold within a certain period of time.In the on state, Circuit Breaker enables a timeout timer that is set to give the cluster the appropriate time to recover from the failure.When the timer time comes, CircuitBreaker will switch to the Half-Open (Half-Open )state.

Open: In this state, the execution of the corresponding operation will fail immediately and an exception will be thrown immediately.

Half-Open:In this state, Circuit Breaker allows a certain number of operations to be performed.If all operations succeed, CircuitBreaker assumes that the failure has been restored,it transitions to a closed state, and resets the number of failures.If any of these operations fail, Circuit Breaker will assume that the fault still exists, so it will switch to the on state and turn the timer on again(giving the system some more time to recover from the failure）

6. Current limiting and downgrading

    Ensure the stability of core services.In order to ensure the stability of the core service, with the increasing number of visits, you need to set a limit threshold for the number of services the system can handle, more than this threshold request is directly rejected.At the same time, in order to ensure the availability of core services, you can downgrade some non-core services,by limiting the maximum number of traffic to the service to limit the flow, through the management console for a single microservice manual downgrade.

7. SLA in Microservices

SLA: Short for Service-LevelAgreement, which means Service level Agreement. A contract between a network service provider and a customer that defines terms such as service type, quality of service, and customer payment.

A typical SLA includes the following items：

1. Minimum bandwidth allocated to customers；
2. Customer Bandwidth Limits；
3. Number of customers who can serve at the same time；
4. Scheduling notifications prior to network changes that may affect user behavior；
5. Dial-in Access Availability；
6. Using Statistics；
7. Minimum network utilization performance supported by the service provider, such as 99.9% active working time or up to 1 minute of downtime per day；
8. Traffic priority for all types of customers；
9. Customer technical support and services；
10. Penalties are specified for service providers that fail to meet SLA requirements.

8. API Gateways

   The gateway here refers to the API gateway, which means that all API calls are unified access to the API gateway layer,and there is a unified access and output of the gateway layer.The basic functions of a gateway are: unified access, security protection, protocol adaptation, traffic control, long-and long-link support, fault tolerance.With the gateway, each API service provider team can focus on their own business logic processing, while the API gateway is more focused on security, traffic, routing and other issues.

9. Multi-level caching

     The simplest cache is to look up the database once and then write the data to the cache, such as redis, and set the expiration time.Because there is expiration, we should pay attention to the penetration rate of the cache.The penetration rate calculation formula,such as query method queryOrder(number of calls 1000/1s)inside the nested query DB method queryProductFromDb(number of calls 300/s), then the penetration rate of redis is 300/1000, in this way of using the cache, it is necessary to pay attention to the penetration rate, the penetration rate is large, indicating that the effect of the cache is not good.Another way to use the cache is to persist the cache,that is, do not set the expiration time, which will face a data update problem.In general, there are two ways, one is to use the timestamp, the query is based on redis by default, each time you set the data into a timestamp, each time you read the data with the current time of the system and the last set of this timestamp to do comparison, such as more than 5 minutes, then check the database again.This can ensure that there is always data in redis, which is generally a fault-tolerant method for DB.The other is to really let redis be used as a DB.The binlog, which subscribes to the database, pushes the data to the cache through the data heterogeneous system,and sets the cache to multi-level.You can use jvmcache as a first-level cache in the application, generally small size, access frequency is more suitable for this jvmcache mode, a set of redis as a second-level remote cache,in addition to the outermost three-level redis as a persistent cache.

10. Timeouts and retry

    Timeout and retry mechanism is also a method of fault tolerance, where RPC calls occur, such as reading redis, db, mq, etc., because the network failure or the dependent service failure, can not return the result for a long time, it will lead to increased threads, increased cpu load, and even lead to an avalanche.So set the timeout for each RPC call.For the case of strong dependence on RPC call resources, there must be a retry mechanism, but the number of retry is recommended 1-2 times, in addition, if there is a retry, then the timeout time should be reduced accordingly, such as retry 1 time, then a total of 2 calls occur.If the timeout is configured for 2s, then the client will have to wait for 4s to return. Therefore, retry + timeout mode, the timeout time should be reduced.Here also talk about a PRC call time is consumed in which links, a normal call statistics of time including: ① call-side RPC framework execution time + ② network transmission time + ③Server-side RPC framework execution time + ④server-side business code time.The caller and the service side have their own performance monitoring,such as the caller tp99 is 500ms, the service side tp99 is 100ms, find the network group colleagues to confirm that the network is no problem.So where is the time spent? There are two reasons, the client caller,and one reason is that TCP retransmission occurs on the network.So pay attention to these two points.

11. Thread pool Isolation

In this aspect of resistance, when Servlet3 is asynchronous, thread isolation has been mentioned. The advantage between thread isolation is to prevent cascading failures or even avalanches.When the gateway calls N more than one interface service, we need to thread isolation for each interface.For example, we have to call orders, goods, users. Then the order of the business can not affect the processing of goods and user requests.If you do not do thread isolation, when the access order service network failure leads to delay, the thread backlog eventually leads to the full-service CPU load.That is, we say that all the services are not available, how many machines will be stuffed with requests at the moment. Then with thread isolation will make our gateway can ensure that local problems will not affect the global.

12. Downgrade and current limiting

 The industry HAS A VERY MATURE APPROACH TO DOWNGRADE CURRENT LIMITING, SUCH AS FAILBACK MECHANISM, CURRENT LIMITING METHOD TOKEN BUCKET, DRAIN BUCKET, SEMAPHORE AND SO ON. Let’s talk about some of our experience here, the downgrade is generally achieved by the unified configuration center downgrade switch, then when there are many interfaces from the same provider, the provider’s system or the machine room network where there is a problem, we have to have a unified downgrade switch, otherwise, it will be an interface to downgrade. That is, to have a large knife on the type of business. There is the downgrade remember violence downgrade, what is the downgrade of violence, such as the forum function down, the results of the user show a large whiteboard, we want to achieve the cache of some data, that is, there is a bottom data.If the distributed current limit is realized, a common back-end storage service, such as redis, is required to read redis configuration information using lua on large nginx nodes.Our current limit is a stand-alone current limit, and did not implement distributed current limit.

13. Gateway Monitoring and Statistics

API gateway is a serial call,then every step of the occurrence of exceptions should be recorded, unified storage in a place such as elasticserach, to facilitate the subsequent analysis of the call exception.Given that the company’s docker applications are all unified distribution, and there are already 3 agents on docker before the distribution, it is no longer allowed to increase.We have implemented an agent program to collect the log output from the server, and then send it to the kafka cluster, and then consume it to the elasticserach, and query it through the web.Now do the tracking function is relatively simple,this piece also needs to continue to be rich.