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At a time when the conversation about the seems to have gone silent, , the Business Development Manager of Seratio, a UK-based think tank, is playing a significant role in building a VR world called . metaverse Shane Oconnor MiMeta In this interview with Olayimika Oyebanji, Shane shares his journey to web3 and his experience  working on what he described as “the metaverse of values”. Read on! Let's begin with you. Can you share your journey to blockchain technology with us? I was always aware of Bitcoin and even mined some in the early days. I didn't really understand the technology so nothing ever came of it. Forward to 2020, I was working for a local authority and a number of colleagues started talking about it and how much money they were making. So I did the newbie thing and invested in their advice and FOMO. Hence to say I made some gains and some losses. But then I decided I wanted to know more. At the time I was lucky enough to get invited to a group called Bullish Boys and Girls who helped, me learn everything I now know and understand about the whole Defi space and how and what to research. The metaverse is potentially a disruptor judging by its spectacular use case. What do you think of it? And where do you see it heading? So in answer to that, I want to highlight that anything we use and interface with on our current digital infrastructure whether it is social media, gaming, retail, and products & services is manipulated and toxic. In some gaming senses, products & services are bombarding you with stuff based on the data you create, so I can't say that the metaverse won’t and can’t be used negatively. But understanding the possibilities and the emerging technology allows genuine platforms to offer real and beneficial interactions with products and services for the consumers and product/service providers. As Seratio Business Development Manager how did you oversee the building of Mimeta from day one? MiMeta is the culmination of nearly two years of building an entire ecosystem around SER and the MCR  tokens that align with the vision and direction we jointly believe is best to create the experience we wish to offer. Each part of the ecosystem is value & sentiment, based on its creation and utility. https://youtu.be/eArxZ7v-tnI Can you elaborate on Mimeta as a metaverse of values? Of course! MiMeta is a metaverse that allows individual users to create their own social gaming and retail experience that is built and interacted with based on a value set that they create when building their world. This allows you to share the same metaverse spaces but has an individual view of what and how you can interact with and the products and services that you will be offered. Values, sentiment, love, and emotion will be more than words. Your imagination will limit a one-stop shop for entertainment, social media, business development, education, one wallet, one set of login details, and passphrases. Does a special relationship exist between the metaverse and blockchain technology? Yes, in my opinion, there has to be a fully functional and reliable metaverse to exist. It will require blockchain and the companies investing in the various and complex issues to facilitate the safe, secure and fast transfer of data and information and assets.  Coins and tokens already being built on blockchain facilitate certain aspects that will be needed whether it be a layer 1-2 or three to provide solutions for users. For example, MTV is a music platform for artists and creators to build and interact on. As mentioned this will be something that offers accountability and transparency to corporations based on the data created from the numerous value sets that could be created, then allowing better products services and experiences for the retailer or end user What are the challenges you faced in building MiMeta from scratch? The hardest thing around developing MiMeta from scratch was finding a programmer who understood what we envisaged and how we saw it being represented as a product, especially when you are using values and sentiment as part of the development process. How to create individual representations and interactions in a shared space is no mean feat and is only the beginning of the journey. What are the social economic problems Mimeta is trying to solve? In the current global economic retail and consumer markets, it's clear to see the change in people's habits when interacting on a day-to-day basis. We now have a need for ethical ecological sustainably sourced products and services which also takes into account values, beliefs, sentiment etc. Another requirement is an environment that is safe, friendly and allows access to all. Another massive part of what we are creating is a tool to highlight inequality in all forms and to share knowledge and understanding, build support, and create communities to converse and interact. Is the metaverse here to stay? In my opinion, we are already somewhat operating in a virtual world. Cashless purchases, VR or Oculus virtual house tours, Zoom and business interactions, social media and gaming apps.  We are now working from home more and moving forward to a new digital age. What is the major challenge with the metaverse? In what sense do you mean? There are always negative ways to look at the emerging space and perceive things and some people will only look to abuse and use that negatively. It's a fact. But focusing on the benefits, opportunities, and offerings for change, global interactions, and transactions for all-around benefit. Any parting words? One last thing to mention is the SER and MCR tokens that are used within the ecosystem and its partners and affiliates. I can go into more detail but all the relevant information is available on our social media platforms. On behalf of Seratio, MiMeta, MiValues and the team, I would like to thank you for your time and urge anyone who wants to get involved to learn more.

"We Are Moving Forward To a New Digital Age": Shane Oconnor, Seratio BDM

Here are some basic Java Interview questions and answers. 1. What is the Java Development Kit (JDK)? JDK is a software development kit that includes tools and libraries necessary for developing java applications. 2. What does Java Runtime Environment(JRE) do? JRE refers to a runtime environment where Java bytecode is executed. JRE supports files and libraries for a runtime environment. 3. What does the Java Virtual Machine(JVM) do? JVM is an abstract machine that provides a runtime environment in which java bytecode can be executed. Learn preface to java virtual machine and architecture. 4. Java is Platform-Independent. Why? In any other programming language source code is compiled into executable code and this code cannot be run across all platforms. Using JVM we can make byte code understandable to any platform and this bytecode is platform-independent. Meanwhile, JVM is different for each platform and java is platform-independent because it does not depend on any type of platform. Hence, java is platform-independent. 5. Java is not 100% object-oriented. Why? Because java uses eight primitive data types such as boolean, byte, char, int, float, double, long, short which are not objects. 6. What are the constructors in java? Constructor is a block of code used to initialize objects. Syntax: { DemoClass()
   {
      ....
   }
} DemoClass obj = DemoClass(); class DemoClass // constructor name is same as class name // calls DemoClass() constructor new For example: { a; ConstructorDemo()
   {
      a = ; } { ConstructorDemo obj = ConstructorDemo();
      System.out.println(obj.a);
   }
} public class ConstructorDemo int // class attribute // create constructor for class ConstructorDemo 26 // initial value for class attribute 'a' public static void main (String[] args) // creating object for ConstructorDemo class // here we're calling constructor ConstructorDemo() new Output: 26 7. What does a singleton class do? Singleton classes can have only one object (an instance of the class) at a time. After object is created and we try to instantiate singleton class, new variable also points to first object created. 8. What are wrapper classes in java? wrapper classes allow primitive data types a way to convert into object and vice-versa. For example: a = ; Integer a = Integer( ); int 7 // using primitive datatype new 7 // using wrapper class 9. What is the difference between == operator and equals method in java? In general == is an operator and equals() is a method. We use == operator for reference comparison of objects in heap. Because in java we don’t have concept of operator overloading. Meanwhile == operator is used for checking address of two objects is same or not. That is, == operator checks if both objects point to the same memory location or not. Also == operator is used to compare object types and primitive types like boolean. While equals() method of String class compares the content of two objects. 10. What are the OOP’s concepts in java? Abstraction is defined as hiding internal implementation and showing only necessary information. Inheritance is a procedure of acquiring all the properties and behaviour of a parent class (super class) into child class (subclass). encapsulation is a procedure of binding data or variables and methods together. Polymorphism literally means many forms. Polymorphism is the ability of a method to perform different tasks. It can be achieved through methods. 11. Why main() method is always static in java? Because to call static method object is not required. If main() were to be a non-static method Java Virtual Machine have to create its object first and then call main() method which will lead to the extra memory allocation. 12. Why strings are immutable in java? Strings are immutable in java because String objects are cached in string constant pool. Learn strings and String constant pool here. 13. What are Arrays and ArrayList in java? Array is an object which holds fixed number of elements of similar type. ArrayList is part of collection framework.Arraylist implements list interface.ArrayList is a re-sizable array that grows dynamically when elements are added and decreased when elements are deleted.For frequent retrieving operation java ArrayList is the best. Because ArrayList elements are stored in consecutive memory locations.ArrayList cannot hold primitive data types such as int, double, char, and long.ArrayList can hold String and wrapper class objects (Double, Integer).ArrayList allows duplicate elements.ArrayList preserves insertion order.ArrayList is widely used because of its functionality and flexibility. It is designed to hold heterogeneous collections of objects.ArrayList can have any number of null values. 14. Difference between hashset and hashmap in java? In HashSet, We can store objects in HashSet. For example HashSet:{“Hello”, “World”}insertion order is not preserved. It is based on hashcode.has add() method.implements Set interface.do not allow duplicate elements.allows single null value. In HashMap, In HashMap we can store key and value pairs. For example {1 ->”Hello”, 2 ->”World”}does not maintain insertion order. It is based on Hash function.has put() method.implements Map interface.allows duplicate values. Does not allow duplicate keys.allows single null key and any number of null values. 16. Difference between this and super keyword in java? this keyword is the reference variable that refers to the current object.this keyword can be used to invoke current class method implicitly.this() keyword used to invoke current class constructor.this keyword can be used to pass as an argument in method call. super keyword is the reference variable which is used to refer immediate parent class object.super keyword can be used to invoke immediate parent class method.super keyword can be used to invoke immediate parent class constructor.super keyword used to access methods of the base class. 17. What is break and continue statement in java? break statement encountered in a loop, that loop will terminate and the control will shift to next statement of the same loop. Example: { { ( a = ; a <= ; a++)
      { (a == )
         { ;  
         }  
         System.out.println(a);  
      }
   }
} public class Example public static void main (String[] args) for int 1 10 if 3 // breaking loop break Output: 1 2 continue statement jumps to next iteration of a loop based on specific condition. Example: { { ( a = ; a <= ; a++)
      { (a % != )
         { ;
         }
         System.out.println(a + );
      }
   }
} public class Example public static void main (String[] args) for int 1 10 if 2 0 continue " " Output: 2 4 6 8 10 18. What are access modifiers in java? Access modifiers define the limit or scope of a variable, constructor, class or a method. There are four types of access modifiers in java; private access modifier, protected access modifier, public access modifier and default access modifier. 19. Difference between for and for each loop in java? for loop, There is no sequence in execution. Here in for loop we can change counter as per our wish.was introduced from start, JDK 1.no need of implementing interface.can have access to index. Hence can replace element in an array.counter can increment and decrement. for each loop, Executes in sequence. Counter is increased by one.was introduced from JDK 5 onwards.To loop over containers using for each loop, container should implement Iterable interface.can’t replace element at given index since there is no access to array index.we can only iterate in incremental order cannot decrement. Example on difference between foreach and for loop. java.util.ArrayList; java.util.Arrays; java.util.List; { {
      List<String> players = ArrayList<>(Arrays.asList( , , )); System.out.println( ); ( a = ; a < players.size(); a++) 
      {
         System.out.println(players.get(a));
      } System.out.println( ); (String str : players)
      {
         System.out.println(str);
      }
   }
} import import import public class DifferenceBetween public static void main (String[] args) new "Virat" "Rohit" "Dhoni" // iterate over List using for loop "using for loop: " for int 0 // iterate over List using enhanced for loop "using for each loop: " for Output: using for loop: Virat Rohit Dhoni using for each loop: Virat Rohit Dhoni Also published on: https://replit.com/talk/learn/Java-interview-questions-and-answers-2021/143902

19 Basic Java Interview Questions and Short Sample Answers — 2021

For any API-first company, implementing the right API analytics platform is critical for tracking the utilization of your APIs and to discover any performance or functional issues that may be impacting customers. There are a variety of open-source projects you can leverage to build a complete API analytics platform. Before jumping into building an API analytics solution yourself, you should first list out your requirements and use cases. Not all tools support all use cases directly, and may require heavy investment in development and integration. API analytics build requirements Need to answer engineering or business questions Engineers commonly turn to API logs and metrics to understand what’s happening over their APIs, inspect payloads, and root cause issues with their services that come up. capabilities is a must for engineers that want to depend on their API analytics solution to put out the (hopefully far and few between) fires due to an API outage or reliability issue. Because real-time logging can raise the compute and storage cost, not all analytics infrastructure maintains a real-time pipeline. On the flip side, only the most recent data is needed to answer hair on fire engineering problems, so data can be after a short time period such as after 24 hours. Real-time API logging retired Engineering and product leaders make strategic decisions based on lines, not dots. Business questions are answered from historical trends in data, which may be over months or even years. This means your API analytics build should be capable of storing data for long retention periods such as for multiple years. This also requires infrastructure that can roll up and compress your data as storing and running aggregations on raw event logs will cripple your analytics infrastructure Real-time alerting and monitoring? While building dashboards and throwing them up on a monitor can be a great way to monitor your metrics, it still requires manually checking them periodically. To become more proactive, many API analytics builds also have some sort of monitoring and alerting features. These can vary from simple threshold-based alerts that sends an email when a metric reaches a certain value, to complex monitoring rules and workflows that can perform complex aggregations in real-time and route alerts to incident response platforms like PagerDuty and BigPanda. Some customer-facing teams like developer relations and customer success may want to build automated workflows to notify customers or internal specific internal stakeholders based on complex user behavioral flows. Access data anywhere vs controlled access The post-COVID world has accelerated the shift towards work from home. This means internal users of your API analytics build may need to access metrics on home networks or on the go without a VPN. Placing unnecessary security restrictions to access the API data may limit the value your API analytics provides to your company or can even backfire creating bad habits such as password sharing or exporting large amounts of data to a personal device rather than using the API analytics build the way it was designed. On the flip side, providing self-service API analytics from anywhere also means having strong security and access control. If you think typical enterprise access control like single sign on and role-based access control may be needed in the future, you should plan your API analytics build accordingly even if not needed immediately. Ripping out and changing authentication and authorization design is not an easy task and could force a complete rewrite. You don’t want to be caught off guard and be the engineer who failed at foreshadowing typical future enhancements. Flexibility of visualizations While most analytics platforms can display event data or plot basic single-value metrics over time, you platform may also be used for more advanced and specialized analysis like or cohort retention analysis. These are common queries used by business functions like marketing and growth teams but rarely used by developers themselves. Yet, building a funnel can be quote challenging if the right data model was not used. funnel analysis Many times, you don’t know the types of queries that need to be displayed but should choose a project that enables flexibility in both the data model and the visualization layer. Comparison There are a variety of open-source analytics and monitoring projects out there. Some are focused on monitoring infrastructure metrics like Kibana and Grafana. While others are more focused on web analytics like Matomo (also known as Piwik). While none of these are designed for API products, you could develop custom code to piece a few components together to build an open-source API analytics platform Kibana Kibana is one of the de facto open-source log visualization tools out there for engineers. It’s part of the official ELK stack (Elasticsearch Logstash Kibana) which makes it one of the quickest visualization tools to get up and running due to it’s tight integration with Elasticsearch relative to tools like Grafana which are far more complex to set up. Elasticsearch itself is well suited for high-cardinality, high-dimension log data which is a must for API logs. The downside is that Kibana is compatible with Elasticsearch. If you want to visualize data stored in a SQL database or other data store, you’ll need to look elsewhere. only While quick to set up, Kibana is also quite limited in the types of visualizations and flexibility supported. Kibana’s primary use case is to provide log search and light analysis on raw event data rather than offering a true API monitoring tool. For debugging use cases, this may be sufficient, but popular business metrics like funnels and retention analysis cannot be performed by Kibana limiting it’s application outside of engineering teams. Kibana and Elasticsearch is designed to be paired with a Logstash instance which enables you to design a logging pipeline to process and enrich API logs such as normalized any HTTP headers or add geo IP information to each API call. Keep in mind Logstash cannot perform aggregations across multiple events at a time. Such processing requires a separate cluster-computing framework for map-reduce operations like Spark or Hadoop. Kibana is designed for use cases where you want to explore your data in an ad hoc fashion rather than create a daily dashboard. You’re able to leverage Elasticsearch query DSL or Lucene query syntax providing great flexibility, but these do have a steep learning curve. By default, Kibana is purely a visualization tool which means things like alerting, anomaly detection, and authentication are separate. This means anyone with access to your Kibana endpoint can access your data so you shouldn’t have it public. However, you can purchase and install the Elasticsearch X-Pack to gain some monitoring functionality along with access control. Grafana Unlike Kibana which focuses on log search, Grafana focuses on time-series based metrics. You can visualize data in a variety of databases including Elasticsearch, InfluxDb, OpenTSDB, Graphite, and Prometheus. Grafana does one thing, and one thing really well, which is visualizing time series metrics stored in a database with beautiful dashboards. This does leave everything else up to you including configuring your data source and processing your data into a time series metric that can be displayed by Grafana. Compared to Kibana, Grafana only works on time-series data already stored in a database and does not have any real-time log search nor a way to browse or explore your raw data in an ad hoc way. The primary use case for Grafana is to design a dashboard to monitor time-series metrics regularly such as on a TV in the office. For example, you may want to display disk utilization, system CPI, and requests per minute for your servers. Grafana has a lot of options to display your metrics in the way you want, like showing storage capacity using base 2 units and percentile based metrics. Due to it’s time-series based architecture, Grafana’s application for high-cardinality, high-dimension analytics on API calls is limited. Instead, you need to spend time deciding exactly what specific time-series metrics you want to track ahead of time and model your data accordingly. This also limits Grafna’s use case for the self-service data exploration that business users may be looking for where you’re looking to segment with multiple or correlate multiple dimensions in your data. group by’s Compared to Kibana, Grafana is known for built-in support for authentication and access control. You can also hook up your Grafana instance to an external Lightweight Directory Access Protocol (LDAP) server or SQL server to better control access in an enterprise setting. You can also connect Grafana to an incident response platform like PagerDuty to create and trigger alerts from your Grafana instance. Keep in mind these alerts are limited to the same time series metrics you are already monitoring in Grafana. Grafana does have a separate product called Loiki, which provides some of the log exploration features that Kibana has. Jaeger Like Grafana which specializes in time-series metrics, Jaeger does one thing and one thing well, which is visualizing distributed traces. This makes Jaeger quite a bit of a different tool than Grafana and Kibana in that each trace is created and viewed in isolation vs monitoring metrics or logs over time. A trace is a snapshot of all context and timing info as a request propagates through a service mesh or hits various services in a microservice architecture. Because trace generation is expensive, sampling is usually employed to snapshot every X requests or specific criteria. Unlike Grafana which focuses on monitoring time-series metrics and Kibana which focuses on log search, Jaeger focuses on root causing specific issues with a service mesh or dependency issues. Jaeger supports multiple data sources like Grafana including Cassandra and Elasticsearch. Since traces are created in isolation, the only view is a trace view as expected. There is no way to create trends over time. Jaeger also doesn’t have any alerting or monitoring features so you’ll want to still have a Grafana or similar instance handy. Moesif Many API teams find needing a multitude of tools for their monitoring needs. Grafana has time-series metrics whereas Kibana enables log search. A faster option is an end to end solution designed specifically for API products like . Unlike Grafana where time-series metrics need to be preplanned, Moesif is designed for ad hoc data exploration using high-cardinality, high-dimension API analytics which is a must for product and engineering leaders looking to make strategic decisions from their API usage data. Moesif Compared to infrastructure monitoring tools like Kibana and Grafana, Moesif leverages a which enables you to align your API metrics to business goals by tying API metrics to individual customers rather than tied to infrastructure. This is also known as which enables understanding complex user flows holistically across multiple user actions and API calls rather than looking at each time-series in isolation. user-centric data model user behavioral analytics A classic example of user behavioral analytics is monitoring a and then breaking it down by user acquisition channel to decide where to invest marketing dollars or viewing for different features or endpoints to make your API products more sticky. This also enables tracking higher level account health for security research and customer success. conversion funnel user retention Compared to Grafana and Kibana, Moesif also provides elaborate real-time alerting and reporting features. This enables you to see which endpoints are causing the most performance issues broken down by each customer email. With behavioral emails and workflows, you’re able to scale customer outreach and support efforts with automated emails with a set of steps.

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