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Start building some cool sh*t If you’re a developer or entrepreneur, you’re no doubt curious (or possibly sick of hearing) about the that is taking over the internet. wave of Web3 innovation Web3, also referred to as the , is the next era of the internet. It rewires things on both an infrastructural and social level. It provides more autonomy and shared value for all online users - not just internet giants who rule the digital world. decentralized web The space over the past few years has been unimaginable. The decentralised applications (dapps) market is projected to reach while the in decentralised finance has increased , at once point surpassing $100 billion. growth of the dWeb $368.25 billion by 2027, Total Value Locked 7 times year-over-year There are many builders, networks and ecosystems piecing the Web3 puzzle together. These projects are taking on the mammoth challenge of undoing decades of exploitative centralisation and corporatisation. At , we’ve spent years building a new protocol from scratch, powered by a decentralised peer-to-peer network on Ethereum and Polygon, made up of tens of thousands of nodes worldwide. ( Mysterium You can run a node yourself - join the network here. ) It’s infrastructure for this re-imagination of the web - a network powerful enough to act as a building block for developers and entrepreneurs all pioneering a more private and ethical internet. But bringing this new web to life is a collective mission, so we invite you to join us. We have open-sauce ingredients and infrastructure, so you can build new projects and… Bring something new to the Web3 table with Necto Labs 🔺🧬 is a new open-source innovation lab driven by R&D, venture funding and strategic collaborations to build a better web for all. Necto Labs Led by Mysterium, the Lab is dedicating to developers and entrepreneurs who want to build encrypted and uncensorable products and services on the network. $3 million in seed funding And we know that being a developer and being an entrepreneur doesn’t always go hand in hand. That’s why we’ve created a 12-week incubator program that you can also join. Through the program, you get to work with an in-house team of technical mentors, product marketers, UX designers and business development consultants. You can also tap into a network of industry experts and leading organizations, as well as a community of fellow Web3 builders. Every project will , so you can scale your idea beyond the seed stage. automatically be considered for follow-on funding opportunities Whether you have a brand new project that needs a go-to-market plan, or a well-developed idea that needs a workable MVP and paying customers, we’re open to it. You can get crazy creative, so long as there is a meaningful application of the protocol or exit node network, and it contributes to the borderless and accessible web. The Lab is looking for all kinds of ideas. We also encourage teams to build solutions for social impact. We want to make sure resources are being used to solve real-world problems and create shared value for communities in need. Teams can collaborate with any relevant organisation to create tools or services that champion digital rights. Learn more about the seed program in , including technical and commercial criteria. our DOCS (You can also check out the list of ideas for inspo further below.) Throw your ideas at us! Apply for funding here , or register your interest here . Catch you in the Nectosystem 🖖 ‍NEED SOME INSPO? 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Introduction has become a prominent technology in implementing data APIs. It provides a convenient and intuitive approach for querying data. Let’s look at a sample use case using the programming language and see how GraphQL compares to other traditional approaches such as implementing REST-style HTTP APIs. GraphQL Ballerina Use Case: E-commerce Data Query Let’s take a typical e-commerce scenario of processing orders in an online store. The entity-relationship diagram below shows a typical representation that can be used in a relational database. This is of course a simplified representation of a real-life implementation. One approach for exposing such a data set would be to create a service with operations for each database table. This would be similar to the following. getOrder(id): OrderInfo getCustomer(id): CustomerInfo getShipper(id): ShipperInfo In this manner, we do get rather granular access to the data where we can query each table’s records as we need. However, we have to read the full table record at a time. If we have a large number of fields in a table, this may result in a larger message transported to the user, even if most of the fields may not be used by the application. This is an over-fetching scenario, but generally, it’s not a big problem in this type of situation. Now, let’s say the application needs to look up order details as well as the information about the customer. Then it needs to do two separate service operations “getOrder” and “getCustomer”. The following sequence diagram shows this interaction. Note that the service operations are done sequentially since we need the “OrderInfo” to look up the “customerId” to do the “getCustomer” operation. So for the application, this means two network round trips to look up both order and customer information. This becomes worse as we need more information, such as looking up “shipper” information also at once. For applications such as mobile apps where this communication is happening through a high-latency network, such as the Internet, it would hamper the user-experience. So ideally, we need to cut back on the number of service calls we do when a user interacts with an application. In order to reduce the number of service calls, we can have an operation such as “getFullOrderInfo” which will load all the data in connection with an order from the service and send them at once. This would definitely solve our multiple request problem. But, if we just have this single operation, even when we want to look up something like the order date, we will receive lots of unwanted data. This is a potentially problematic over-fetching scenario. If we want to properly fix this situation, we need separate individual operations for all the combinations that are possible, such as “getOrderAndCustomer”, “getOrderAndShipper”, etc. This is obviously not a practical solution for a service developer. If only there is an approach, where the application can dynamically query the service on which parts of the data set is required. This is exactly what GraphQL does. Solution: GraphQL In GraphQL, we can define an object graph in our service, where a client can query the specific fields of an object. These fields can be queried at any nested level. Optionally, we can pass in parameters for these fields as well. A definition of these objects for our use-case can be shown below. type Query {
   order(id: Int): Order
} Order {
   id: Int
   notes: String
   customer: shipper: Shipper
} {
   name: String
   address: } Shipper {
   name: String
   phone: String
} type Customer type Customer Address type The above is actually written in the GraphQL schema format used to define object types. GraphQL “Query” is a special object type, which must exist for the schema. This is basically the root level object that a user will query. So in GraphQL queries, we provide the fields inside the “Query” object to look up the required data. Provided that we have a GraphQL service with the schema above, we would send the following query to get a similar effect to our earlier “getOrder” operation. {
   order( ) {
       notes,
       date
   }
} id: 1 Here, we instruct our service to lookup the “order” field from the root query object and pass in ‘1’ as the value for parameter “id”. This field returns an object type, so we need to list all the fields we require from the object, where we provide “notes” and “date” above. If we need to only look up the date field, our GraphQL query would be the following. {
   order( ) {
       date
   }
} id: 1 We can drill into more fields and get their values as well. The following query, looks up full order information, including the customer and shipper information. {
   orders(id: 2) {
       notes,
       date, {
           name, },
       shipper {
           name,
           phone
       }
   }
} customer address Now that we understand the basics of how GraphQL works, let’s take a look at how to do the actual implementation using some code. We will use for this task. It is a programming language that has GraphQL as part of its built-in language-level services support. Ballerina Implementation: Ballerina GraphQL Services In Ballerina, the GraphQL object structure is modeled using services. A Ballerina GraphQL service contains resource methods that map to the fields of the GraphQL objects and work as resolver functions to provide its data. The GraphQL schema is automatically derived from this service structure and its resources. : GraphQL support is available from Ballerina Swan Lake release and onwards. NOTE The following code shows a simple GraphQL service we can write in Ballerina. import ballerina/graphql; graphql:Service /query on new graphql:Listener(8080) { function name() returns string {
       return ;
   }

} service resource get "Jack" The code above exposes a GraphQL service at the endpoint. Its GraphQL schema is similar to the following. { : String
} type Query name We can send the following GraphQL query to lookup the exposed “name” field in the root query object. { } name Let’s run the Ballerina code above for a sample test run. $ bal run demo.bal
Compiling demo.bal
Running executable
[ballerina/http] started HTTP/WS listener 0.0.0.0:8080 source A GraphQL request can be executed by sending an HTTP request similar to the following. $ curl -X POST -H -d http://localhost:8080/query
{ :{ : }} "Content-type: application/json" '{"query":"{name}"}' "data" "name" "Jack" The resource functions here can be provided with parameters to correlate with the GraphQL field parameters as well. Also, in the case of returning objects in fields, the resource method can return a service object to represent this. Let’s see how we implement our order information query scenario using a Ballerina service. We start with the Ballerina GraphQL service implementation, which represents the GraphQL root “Query” object fields. import ballerina/graphql;

service graphql:Service /query on graphql: {

   resource get 'order( id) 
                          returns Order load ;

} new Listener(8080) function int |error => Order( ) id Here, we have a single resource function “order”, which takes in the “id” parameter and returns an instance of the “Order” service class. The “loadOrder” function and the “Order” service class is implemented in the following way. function loadOrder(int id) returns Order| {
   stream<record{}, error> rs = dbClient->query(`SELECT id, customerId,
                                                 shipperId, date, notes ORDERS WHERE id = `, OrderData);
   var rec = check rs.next();
   check rs.close(); !(rec is ()) {
       return new Order(<OrderData> rec[ ]);
   } {
       return (string `Invalid order: `);
   }
} class Order {

   private OrderData data;

   function init(OrderData data) {
       self.data = data;
   } function notes() returns string {
       return self.data.notes;
   } function date() returns string {
       return self.data.date;
   } function customer() returns Customer| {
       return check loadCustomer(self.data.customerId);
   } function shipper() returns Shipper| {
       return check loadShipper(self.data.shipperId);
   }

} error FROM ${id} if "value" else error ${id} service resource get resource get resource get error resource get error Here, we execute the required SQL query to load the “Order” table data and populate the “Order” object. Note that, we do not also load “customer” and “shipper” information right away, but rather, these are loaded lazily if and when it is required as expressed through the incoming GraphQL query. The “loadCustomer” function shown below is used in the “customer” resource function to load the customer information from the database and populate a “Customer” object. function loadCustomer(int id) returns Customer| {
   stream<record{}, error> rs = dbClient->query(`SELECT id, name, WHERE id = `, CustomerData);
   var rec = check rs.next();
   check rs.close(); !(rec is ()) {
       return new Customer(<CustomerData> rec[ ]);
   } {
       return (string `Invalid customer: `);
   }
} class {

   private CustomerData data;

   function init(CustomerData data) {
       self.data = data;
   } function name() returns string {
       return self.data.name;
   } function address() returns string {
       return self.data.address;
   }

} error address FROM CUSTOMER ${id} if "value" else error ${id} service Customer resource get resource get Similarly, the “shipper” resource function is implemented to query the corresponding GraphQL object field. The full source code for the scenario above can be found . here Let’s do a test run using our full Ballerina service implementation. We are using a MySQL database to provide the data. Let’s create and populate the database first. Navigate to the “ordersvc” directory which contains the Ballerina package and the database script. $ mysql -u root -p < db.sql Let’s execute the default module of our Ballerina package in the following manner. $ bal run .
Compiling laf/ordersvc:0.1.0
Creating balo
        target/balo/laf-ordersvc-any-0.1.0.balo
Running executable
[ballerina/http] started HTTP/WS listener 0.0.0.0:8080 source Let’s send some GraphQL requests to the service. $ curl -X POST -H -d { : { : { : , : , : { : , : }, : { : , : }
        }
    }
}
$ curl -X POST -H -d { : { : { : , : { : , : }
        }
    }
} "Content-type: application/json" '{ "query": "{ order(id: 2) { notes, date, customer { name, address }, shipper { name, phone } } }" }' 'http://localhost:8080/query' "data" "order" "notes" "Street pickup" "date" "2021/01/25" "customer" "name" "Nimal Perera" "address" "No 22, Galle Road, Colombo 02" "shipper" "name" "UPS" "phone" "(408)275-4415" "Content-type: application/json" '{ "query": "{ order(id: 1) { notes, customer { name, address } } }" }' 'http://localhost:8080/query' "data" "order" "notes" "Doorstep delivery" "customer" "name" "Jack Smith" "address" "No 10, N 1st St, San Jose" Ballerina GraphQL services also support GraphQL introspection. For example, the following query can be executed to lookup the types available in the service. $ curl -X POST -H -d { : { : { : [{ : }, { : }, { : }, { : }, { : }, { : }, { : }, { : }, { : }, { : }, { : }]
        }
    }
} "Content-type: application/json" '{ "query": "{ __schema { types { name } } }" }' 'http://localhost:8080/query' "data" "__schema" "types" "name" "Order" "name" "__TypeKind" "name" "__Field" "name" "Query" "name" "__Type" "name" "Customer" "name" "Shipper" "name" "__InputValue" "name" "String" "name" "Int" "name" "__Schema" Summary GraphQL is a technology that makes data querying tasks much more efficient and intuitive for the users. Here, we have looked at how it solves potential problems such as data over-fetching and solves network latency problems that can arise in a services-based solution. Ballerina provides built-in support for implementing GraphQL services in a quick and easy manner, where the user can just concentrate on the business logic. For more information on Ballerina and its GraphQL support, check out the following resources: Ballerina by Example Ballerina API Documentation GraphQL Sample Also published at https://medium.com/ballerina-techblog/graphql-made-easy-with-ballerina-5ca04d9536d0

Querying Data With GraphQL & Ballerina

We have created this blog post for business stakeholders managing the development of a software system or product, those looking to find ways to reduce cost and time to market. This post will be useful for those whose technical background is a bit outdated or isn’t sufficient to make that judgment call. We will look at how to approach architecture planning so that the product is scalable and the money is spent wisely. Also, we will show the example of how CQRS can help in the implementation of client applications and whether microservices is indeed the panacea. Why should business care about software architecture It is impossible to consider any software in isolation from the business context. Software products and systems are built to automate processes, improve customer experience, and assist the business to achieve KPIs. Software architecture is created with the business processes in mind, thus being a prerequisite for seamless product development, scaling, and optimization. Cost Good software architecture makes it cheaper to develop and maintain products due to the creation of reusable elements. Furthermore, it provides a sound basis for communication and straightforward decision making further down the line. Thus, it reduces negotiation times and boosts team effectiveness. In case architecting is ignored, making changes to the product in the later stages of the development process will be much more expensive. Risk mitigation The organization of the system, which business processes it takes part in and how it interacts with other systems and applications is determined by the architecture. Effective architecture identifies design risks and allows timely mitigation. Competitive advantage The effective architecture enables faster time to market. The ability to reduce time to market is vital in the environment of highly competitive markets. A business that is able to meet the needs and demands of the market ahead of others gains a competitive advantage. Adaptable business-model The highly competitive and dynamic environment also dictates that the business is adequately prepared when things change. The ability to transform the business model and introduce changes to the product is contingent on the well-thought-out architecture. The architecture roadmap should be aligned with the product roadmap and strategic plans for the business. Otherwise, strategic adaptability will be lost. Technical solutions Product architecture determines the technical solutions and standards. The choice of programming language, platform, framework, and tools determine the level of current and future cost. Technical solutions also affect the speed at which changes can be introduced to the product. This is critical in a situation when MVP isn’t coping with the influx of users. Two extremes Inevitably a question pertaining to architecture design arises — when should one start considering it, what style and patterns to use, and to what extent should the architecture be thought out? We have come across different points of view. On the one side of the spectrum, there is “minimum viable product does not imply an architecture since it is put together as quickly as possible”, on the other — “microservices should be used from the outset so that scalability and flexibility are at the very core of the product”. These are two extremes, each potentially being quite costly. Below we will look at how to find a middle way. Big Ball of Mud A big ball of mud — a type of system with chaotic architecture — is not uncommon. Such systems take shape over time due to a lack of architecture design and planning. It all starts with a request by a business stakeholder: “we just need to get the first users to sign up, we’ll figure out later what to do with retention and how to improve the product.” Iterative and incremental development is widely used. Generally, MVP is developed without thorough architecture design, and oftentimes even without paying much attention to nonfunctional requirements. This is followed by the series of iterations to incrementally add capabilities. Sometimes this results in technical debt and a system that can hardly function, which requires continuous fixing. We know of many cases when an architectural focus was lacking. Every time that would lead to repercussions costing hefty amounts to correct. For example, a product crashing while not being able to cope with the large user load. Consequently, this leads to the team working long hours trying to put out the fires; the number of churned customers grows. The business fails to take off. In other instances, the entire system may require re-coding. It takes more time and effort than all the preceding development work combined. Worst of all, the users have to learn how to use the system all over again, causing frustration and damaging loyalty on their part. As a result, jeopardizing future sales. Microservices isn’t the magic pill What is microservices There are different approaches to architectural design. Microservices — one of the possible styles of architecture. Microservices are opposed to a monolithic architecture, in which different components are combined into a single indivisible unit. Microservice architecture is created in small, independent, modular services. Each service is responsible for a specific task corresponding to a business capability. Services interact through the API (application program interface) — that is an intermediary that links all the elements together. Each API is programmed to fulfill a specific business goal. Using separate services allows you to use the most appropriate technical stack for each specific task. What to pay attention to Microservices is a rather popular approach to designing system architecture. Moreover, some clines insist on building architecture using microservices from the very outset, not knowing that this might be a very expensive approach. To reap the benefits, one should be able to design microservice in the right way. It isn’t enough to define a few independent modules and say that’s microservices. When designing a microservice architecture, several concerns need to be addressed. For a start, how to trace a sequence of calls to different services that resulted in a mistake? Or how to identify which service is a bottleneck in the work of the entire system? Some of these concerns can be addressed with various degrees of success either by ready-made infrastructure solutions (for example, Elastic for logging) or custom infrastructure services. Another thing to keep in mind is data integrity. Therefore, it is necessary to establish mechanisms for ensuring data integrity in advance. Unfortunately, this is often overlooked, which leads to unpleasant consequences in the form of data loss or desynchronization. Moreover, in the early stages of the design process, segregating the system into independent services is a hard task at hand. The structure of the subject field is vague at this point and the exact functionality isn’t clear. Consequently, inappropriate segregation of services will lead to issues and additional costs when implementing required scenarios of work of the system. In some cases, the system simply will not function adequately. Microservices may cost an arm and a leg Depending on the scale of a system, the costs of deploying infrastructure for several services in several configurations, performance, and scalability checks may cost quite a hefty amount. Smaller projects for sure will cost less but these are expenses that are not necessarily justifiable. More often than not, large investments in the architecture design at the early stages of product development are not justified. When working in a situation of uncertainty it’s hard to tell how many customers will get on board, whether the product will take off, or the business will close down. A well thought out architecture is the foundation of a successful product A competent decomposition and description of the business capability holds a central place in the designing of a microservices architecture. Inadequate decomposition of the system into loosely coupled services may hinder revisions and make it impossible to trace and verify all system behavior scenarios. This will lead to failures in snowballing. To avoid this, a high level of understanding of how the system will work on all the levels, who and how will be using it is required. Therefore, it is critical to start thinking of and put a vision of the architecture at the very early stages of product design. Example Say, we build an e-commerce website. Good user experience is shaped by many things. Not the least by accurate order assembly by the Order Picker at the warehouse, convenient online payment and delivery options available to the customer. For that, a thought out the user interface for warehouse staff is required, as well as integration with payment systems and warehouse logistics system. That is underpinned by a thorough understanding of at least the main business processes. Failure to capture business processes may result in omitting a big part of the requirements. In turn, this will result in an impractical system. Moreover, additional resources will be needed to refine the system. These are the expenses that otherwise could have been avoided. The lack of funds is not uncommon in such situations since the money has been spent on features that were not relevant at the time. Without a thorough understanding of how the system services interact with one another, we may start building the wrong functionality at the wrong time. An example of such functionality maybe a CRM system at a time when the customer does not require a unique functionality and a ready-made solution can be used. And only after having studied and understood the environment, can we justifiably decide on the choice of software architecture and decomposition of the system into loosely coupled services, etc. So, where to start? It is highly recommended to hold a one- or two-day workshop with a customer to not only define architectural solutions but also low-fidelity system design and main use scenarios. In the case of startups, an extremely important step is to fill out a so that all the stakeholders understand the viability of the business idea. One of the artifacts of the workshop would be a document describing non-functional requirements for the system. Business Model Canvas One of the outcomes of the workshop may be the decision to pull the plug on the project: it will help stakeholders see the shortcomings of the business idea without spending time and money on technical implementation. It may sound counterproductive, but even such an outcome can build a better understanding and trust between the client and the technical team. Is the game worth a candle? Absolutely! It costs as little as 2 intensive days of work the team. If this step is left out, the majority of the mistakes in product development will cost considerably more to correct. Over time, a business may change in response to external circumstances. For example, businesses all over the world are facing drastic changes right now. The world, as we know it, will never be the same again due to the pandemic of Covid-19. Businesses should always be ready to adapt and change their business models. As mentioned above, this flexibility is underpinned by an effective architecture and by means of tried and tested practices, such as the CQRS pattern. For instance, using CQRS at the logical level at the beginning of the design process will enable us to physically locate the services as the business and product scale. This, in turn, will enable the reuse of the functionality by splitting it into independent components. At the early stages, it is not that important to have services physically segregate. However, if you attempt to do that early on you may waste resources on monitoring and implementing distributed transactions and other dependencies that are not yet essential at the stage. CQRS at the logical level CQRS definition CQRS (Command-Query Responsibility Segregation) is a popular and widely used software architecture design pattern. It implies that all methods (i.e. certain sets of actions) in a program can be of two types: either requests that do not alter the state of the program or commands that alter the state of the program. In other words, queries can only read data, while commands update data. What we did In this , we had a task to develop a system for a client managing a fleet of sea vessels. The software was to help our client to optimize and manage the automation of business processes. The client was very specific about the strict timelines and restricted budget so we had to find a way to deliver the system fast and in a cost-efficient manner. We opted for the approach of implementing CQRS at the level of logical architecture. project By observing the basic principles of SOLID, namely Dependency Inversion and Dependency Injection, and correct Inversion of Control Containers, all the commands and queries become easily manageable elements which can be reassembled elsewhere in the system. The diagram depicts 3 parts of the system that can work similarly to the Model: Interaction of the Admin Office Desktop App with the Model Interaction of the Ship Desktop Mechanic App with the Model Interaction of the SyncService with the Model We noticed that the users, who use the Admin Office Desktop App in the office, more often read data from the vessels rather than make any data entries. And the users who are on board the vessels in the offline zone, on the contrary, more often submit data rather than read. Why does it matter? It matters because whilst the architecture, as it is at this stage, is the foundation for further scalability of the system, it certainly has a greater potential to make further development, scalability, and maintenance of the system cheaper and trouble-free. If need be, it would be significantly easier to single out query contexts and build services with the DB optimized to enable reads, as well as to single out command contexts into separate services. Examples of segregation The following are a few examples of the main # C classes that you can use in your projects. {
      IQueryHandler<TQuery, TResult> CreateQueryHandler<TQuery, TResult>();
 
      IAsyncQueryHandler<TQuery, TResult> CreateAsyncQueryHandler<TQuery,
TResult>();
      ICommandHandler<TCommand> CreateCommandHandler<TCommand>();
 
      IAsyncCommandHandler<TCommand> CreateAsyncCommandHandler<TCommand>();
    } < >
    { Execute(TCommand command);
    } < , >
    {
        TResult Execute(TQuery query);
    } : { readonly IResolutionRoot _resolutionRoot; NinjectFactory(IResolutionRoot resolutionRoot)
        {
            _resolutionRoot = resolutionRoot;
        } IAsyncCommandHandler<TCommand> CreateAsyncCommandHandler<TCommand>()
        { _resolutionRoot.Get<IAsyncCommandHandler<TCommand>>();
        } IAsyncQueryHandler<TQuery, TResult> CreateAsyncQueryHandler<TQuery, TResult>()
        { _resolutionRoot.Get<IAsyncQueryHandler<TQuery, TResult>>();
        } ICommandHandler<TCommand> CreateCommandHandler<TCommand>()
        { _resolutionRoot.Get<ICommandHandler<TCommand>>();
        } IQueryHandler<TQuery, TResult> CreateQueryHandler<TQuery, TResult>()
        { _resolutionRoot.Get<IQueryHandler<TQuery, TResult>>();
        }
    } /// <summary> ///   Universal factory for creating queries. ///   To be implemented in Composition Root (web api project,  website main prototype, etc) /// </summary> public interface IHandlersFactory /// <summary> ///   Basic interface for the command /// </summary> public interface ICommandHandler TCommand void /// <summary> ///   Basic interface for the query /// </summary> public interface IQueryHandler TQuery TResult /// <summary> ///  Factory Ninject to create standardised commands and queries /// </summary> public class NinjectFactory IHandlersFactory private public public return public return public return public return Examples of Binding of queries with Ninject override Load()
        { Bind<IQueryHandler<GetCertificateByIdQuery, Certificate>>(). <GetCertificateByIdQueryHandler>();
            Bind<IQueryHandler<GetCertificatesQuery, <Certificate>>>(). <GetCertificatesQueryHandler>();
            Bind<IQueryHandler<GetCertificateByShipQuery, <Certificate>>>(). <GetCertificateByShipQueryHandler>();
…………. public void // queries To List To List To After the injection of IHandlerFactory into the class, you can use your commands and queries as follows. Query example:
Ship ship = mHandlersFactory.CreateQueryHandler<GetShipByIdQuery, Ship> . );

Command example:
mHandlersFactory.CreateCommandHandler<DeleteReportCommand> . ); () Execute( GetShipByIdQuery( ) new id () Execute( DeleteReportCommand( ) new report By all means, all architectural decisions must be based on and developed according to the requirements and situation. No need to design the architecture for the entire product or system outright. The following questions will guide you through the decision making process. Why is the structure of the software product like this? Why is this particular implementation being used here? How will a new implementation fit into the overall structure of the system? How will the non-functional requirements of the entire system be met? It is also very important to allocate the Bounded Context in the system. This practice helps to depict the customer’s business structure, find a common language with a client, and manage the regression in the product. But we’ll cover this in the next article. Benefits of CQRS The basic architecture of the application was built in compliance with various principles and design patterns: MVVM, SOLID, CQRS, etc. This allowed reusing functionality in separate client applications. With that, the implementation did not take much time and was cost-effective. By the time the development was to commence the team had already developed classes and the same level of understanding of the application architecture. In subsequent refinements, it fully paid off: about 40% of functionality could simply be flexibly reused. With this approach, the customer significantly reduced the cost of implementing functions by roughly 30–40%. In conclusion The Agile approach to development is mistakenly interpreted as “you don’t need to design anything in advance, just build, release and get the feedback. Should we need to improve the operational speed of the product or add new capabilities more rapidly, we’ll just throw microservices in. At every corner, they saw how effective and versatile microservices are.” uch a thoughtless approach, generally, results in a poor product and wasted cash. On the other hand, it is practically impossible to come up with a fully-fledged design right off the bat. A balanced approach is the best. S Firstly, having a vision for the product architecture provides a sound basis for current and future decisions. As a result, this will have a huge impact on the cost of the development as the product matures. Secondly, documenting the adopted architectural decisions will allow for the understanding of certain decisions further down the line. Thirdly, regular checks of the environment in which the product operates, allows to reduce the risks of failures and justifies the decisions regarding refinements or change. Thus, giving some thought to what a product’s architecture will look like and using competent practices when writing code provides a solid foundation for scaling a product in the future.

Microservices and CQRS: Why Business Should Care

Starting an can be both fun and a nightmare. Here’s my story to inspire and to learn from. AI business When I first started , I thought the hardest part would be putting together a talented team, breaking into the market, and finding some solid long-term leads. Label Your Data Little did I know, however, that the biggest challenge I would face was an unprecedented pandemic, followed by a devastating war in my country, a massive power outage for five months, and now a stormy crisis gripping the IT industry. It feels like one headache after another… But when it comes to challenges, I always say, “Bring it on!” Here’s how I kept pushing through and making sure my company comes out on top. My CEO Journey That Could Have Been Yours To me, no crisis lasts forever, and every difficulty can be overcome. Our data labeling company is 3 years old now, and we are currently entering our third crisis. But let’s take it one crisis at a time and really dive into the nitty-gritty details. Starting the Company Amidst the Pandemic Label Your Data started with a conference in San Francisco, which I visited back in February 2020. At that time already, I saw people wearing masks at the airports and temperature measurement control everywhere. Those were the clear precursors of the future global, lingering pandemic. But despite of that, we flew back home to Ukraine very inspired and with hundreds of collected leads. Soon after, the pandemic hit, and most businesses were forced to adapt to a new remote way of operating. Speaking of COVID-19, my team didn’t perceive it as a crisis. Instead, we saw it as the circumstance in which our company was born, and we forged ahead with our beliefs. In our first year, we took on this massive project of fitting 100 people into our office space. We launched it within a month during a total lockdown. Of course, it wasn’t all smooth sailing. I had to deal with all kinds of challenges, like figuring out how to get everyone to work without public transport (we paid for taxis) and implementing strict hygiene standards to keep our team safe. Plus, we were measuring the temperatures of the entire personnel every hour like clockwork. Hence, in one year, Label Your Data has endured three full lockdowns. But the best part is, we still managed to keep our expert service going with a team of 100 awesome people. Reaching the Peak Right Before the Full-Scale Invasion The outbreak of war is a devastating and unpredictable event. However, if businesses take the right steps beforehand, they can survive any storm that comes their way. When our company faced the realities of a full-scale invasion of our country and unprecedented Russian terror in 2022, our minds were steadfast and clear. We were ready for it. Although I must admit, it was hard to come to terms with the war unfolding in my country until the bitter end. My team had a solid business continuity plan in place, all of our projects were on track, and we made sure that everyone had a backup person who could step in and take over some responsibilities if needed. Of course, it did take us a few days to adjust to the new reality, but thanks to our well-organized work and necessary arrangements, it wasn’t nearly as chaotic as it could have been. One thing that really impressed me during this time was the understanding and support we received from our clients. Owing to this, not only did we manage to maintain our operations during the darkest of times, but we also exceeded our strategic goals for 2022. Our clients were extremely supportive, and my company emerged from the conflict stronger and more resilient than ever before. While it’s tough to acknowledge missed opportunities due to the war, I try to remain optimistic. I may never know what clients we could have gained, but there’s no point in dwelling on the past. Instead, we’re moving on with our global expansion and diversification efforts. Our team is growing in other countries now, while our services continue uninterrupted in Ukraine, thanks to the many additional sources of electricity and communication now available. Today, we’re offering accessible training to anyone without experience, empowering them to work from anywhere, anytime. To me, it just goes to show that with a bit of planning and a lot of perseverance, anything is possible. Moving Forward Through the IT Crisis Looking ahead to the future, we’re preparing for whatever challenges may come our way. While it’s early to talk about the potential IT crisis of 2023, I’m already taking proactive steps to ensure the Label Your Data team is well-equipped to handle it. That is, we are automating our processes, optimizing our expenses, and all teams are working at 100% capacity. And you know what? We’re keeping everyone in the loop and being totally transparent about everything. That way, when tough times do come our way, our team is ready to face them head-on, together. With that said, to achieve successful crisis management in an unsteady IT landscape, I prioritize two things above all else: Fostering crystal-clear communication among my teammates and inspiring their unwavering dedication to our shared goals. My Advice to You (or Proven CEO Tactics, If You Will) To all CEOs out there, try your best to embrace the new realities that are coming your way. Instead of resisting change, adapt and optimize your team performance to find new ways to excel. Don’t let fear of failure hold you back from taking risks and pursuing your dreams. Reframe failure as a learning experience. See challenges as chances to learn and propel. Another piece of advice from me is to prepare for the worst. I’m not saying you have to stay pessimistic, but acknowledging the chances of hard times in business will help you stay sane when they come (and they will; trust me). Be adaptable: Don’t be afraid to pivot, and make changes to your plans as needed. Learn from setbacks and use them as stepping stones toward success. The final tip is to build meaningful relationships within your team. The truth is that success in business often comes down to the relationships you build with your teammates. Take the time to cultivate deep connections with others, and focus on building relationships that will support you in the long term. Always stay connected with your team. When Life Gives You Lemons: Making the Most Out of Tough Times in Business Navigating a single crisis can be overwhelming for any technical start-up. Imagine tackling three? That was the case for Label Your Data and the journey that we conquered with grit, determination, and a can-do spirit, against all odds. As someone who has weathered the storms of CEOship, here’s my advice to future entrepreneurs or the ones struggling right now: Instead of dwelling on the uncontrollable, shift your focus to what you can influence. Be proactive in finding solutions, and surround yourself with a team that shares your passion and dedication. By doing so, you’ll be better equipped to tackle any challenge that comes your way — and emerge stronger on the other side. Trust me, I’ve been there!

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