Java
Our Java Capabilities unboxed
- Web Frameworks – Spring boot, Grails
- Database – PostgreSQL, MySQL
- Distributed Transaction – Atomikos (2 phase commit), Eventual consistency using Outbox
- Messaging – IBM MQ, Amazon SQS, Kafka
- Language – Java
- Testing - JUnit
- Cloud – AWS, Azure
- Caching – Redis, GridGain, Caffeine, Hazelcast
- Web Services – RestAPI
- Libraries –Statefulj
Our Java Capabilities unboxed
Distributed Transaction
Atomikos (2 phase commit), Eventual consistency using Outbox
Our Ten High Stories in Java
In an event-driven architecture, the flow of the program is determined by the events that occur and does not follow a predefined sequence of steps. This gives the application more dynamic and flexible behavior as it reacts to a variety of events and does not follow a fixed linear flow.
Event-Driven Architecture
Caching involves storing frequently accessed data in a temporary storage area (cache). This approach improves performance and reduces the load on the original data source. Storing frequently accessed data in cache rather than fetching it from a database or file system, results in faster data retrieval, reduces latency, and processes requests faster increasing throughput.
Caching for High Throughput
Distributed transactions are used to ensure data consistency and integrity when multiple services or databases need to work together to perform a transaction. These transactions involve a set of operations that must either all succeed or all fail as a single atomic unit to maintain Data integrity.
Distributed Transactions for Integrity across Services
Eventual consistency is a consistency model where, all replicas of a data item will converge to the same value over time, assuming that no new updates are made. Eventual consistency allows for temporary inconsistencies between replicas but guarantees that these inconsistencies will be resolved eventually.
Eventual Consistency using Outbox pattern
Highly optimized and dynamic JPA (Java Persistence API) queries reduce database load and allow scalability by fetching only required data. These improve response time and significantly improve application performance.
Highly Optimized and
Dynamic JPA Queries
REST APIs
In a distributed environment where it is essential to maintain data integrity across multiple operations while working with databases, file systems, and other systems, use of transaction manager is critical.
Right use of Transaction management
Schedulers are critically important in modern software development to manage and optimize job processing to improve the efficiency, scalability, and maintainability of applications.
Internal and External Scheduler
for Job Processing
DB schema migration
Entity State
management in Statefulj
Event-Driven Architecture
XIn an event-driven architecture, the flow of the program is determined by the events that occur and does not follow a predefined sequence of steps. This gives the application more dynamic and flexible behavior as it reacts to a variety of events and does not follow a fixed linear flow.
By embracing Event-Driven Architecture and implementing Messaging with messaging services like IBM MQ, Kafka, Amazon SQS, we let our clients successfully transform their eCommerce platform. A more responsive, scalable, and personalized shopping experience delights customers and increases sales.
Messaging Service allows Event-Driven Architecture to work seamlessly by facilitating communication between microservices. It ensures that events are delivered consistently and efficiently to the appropriate microservices. And it also provides asynchronous integration between services.
Caching for High Throughput
X
Caching involves storing frequently accessed data in a temporary storage area (cache). This approach improves performance and reduces the load on the original data source. Storing frequently accessed data in cache rather than fetching it from a database or file system, results in faster data retrieval, reduces latency, and processes requests faster increasing throughput.
We have implemented Caching using various caching libraries and frameworks such as Redis, Caffeine, Hazelcast, and GridGain. We have utilized Caching in read-heavy applications, APIs and Microservices, e-commerce and Mobile applications, and wherever data retrieval performance, response times, and resource utilization are important.
Distributed Transactions for Integrity across Services
X
Caching involves storing frequently accessed data in a temporary storage area (cache). This approach improves performance and reduces the load on the original data source. Storing frequently accessed data in cache rather than fetching it from a database or file system, results in faster data retrieval, reduces latency, and processes requests faster increasing throughput.
We have implemented Caching using various caching libraries and frameworks such as Redis, Caffeine, Hazelcast, and GridGain. We have utilized Caching in read-heavy applications, APIs and Microservices, e-commerce and Mobile applications, and wherever data retrieval performance, response times, and resource utilization are important.
Eventual Consistency using Outbox pattern
X
Eventual consistency is a consistency model where, all replicas of a data item will converge to the same value over time, assuming that no new updates are made. Eventual consistency allows for temporary inconsistencies between replicas but guarantees that these inconsistencies will be resolved eventually.
We use Outbox pattern in conjunction with the two-phase commit protocol to achieve Eventual consistency. This approach decouples the 2PC coordination from the actual data update. So even if the data update fails on some participants or if there are temporary failures. The events in the outbox can be replayed until all replicas converge to the same state, achieving eventual consistency.
Highly Optimized and Dynamic JPA Queries
X
Highly optimized and dynamic JPA (Java Persistence API) queries reduce database load and allow scalability by fetching only required data. These improve response time and significantly improve application performance.
Optimized and dynamic queries provide type safety that checks errors during compilation and can be encapsulated in reusable methods – promoting code reusability and maintainability. Highly optimized queries also provide security from SQL injections. Dynamic queries can be generated based on user input and external conditions that help in providing more interactive and user-friendly applications.
Optimized and dynamic JPA queries lead to cleaner and more concise code for easier understanding and maintainability.
REST APIs
X
The statelessness, scalability, and flexibility make them easier choices for integration. REST APIs can also take the advantage of HTTP caching mechanism and improve performance and reduce the load on the server and client.
The data can be secured during transit using HTTP security mechanisms HTTP(SSL/TLS) and authentication headers. The loose coupling that REST APIs provide between client and server helps in system maintainability.
Right use of Transaction management
Internal and External Scheduler for Job Processing
X
Schedulers are critically important in modern software development to manage and optimize job processing to improve the efficiency, scalability, and maintainability of applications.
We use built-in ‘java.util.concurrent’ framework and third party libraries like Quartz scheduler to manage job processing. Schedulers help in automating jobs or tasks, their efficient execution when time is appropriate, concurrency management, resource allocation, error handling and simplifying task management to make applications stable and efficient.
Tasks/jobs like automated report generation, database cleanup, notifications and alerts, periodic update and processing of data, we use in-built scheduler to manage these types of tasks. For jobs like batch processing, load balancing, distributed task scheduling, cross-platform compatibility and managing jobs having dependencies, we use external scheduler.
DB schema migration
X
Data migration, code changes, scaling, bug-fixing, requirement evolution, data integrity, and various other conditions demand DB Schema migration necessarily. Use of tools and frameworks, that ensure DB schema migration occurs systematically keeping the database consistent and functional throughout its lifecycle is vitally important.
We use Liquibase to manage DB Schema migration. This database migration and version control tool allows writing database changes in database-agnostic way. Managing, versions to rollback changes if needed, reproducing changes, and generating scrips for Database changes are other features of our DB schema migration.
We integrate Liquibase with CI/CD pipelines to enable automated DB schema migration as part of the application’s deployment process. Also, leverage Liquibase’s feature to manage data along with schema management.
Entity State management in Statefulj
X
Managing states and events in an event-driven application is crucial and very essential for performance. We have mastered over a period of time to utilize statefulj for managing states and events and develop event-driven applications for complex work scenarios like workflow management or order processing.
We use statefulj in applications requiring content approval or service provisioning, track order state from creation to processing, payment, and delivery. For applications needing multiple steps and decision points or for applications in microservices architecture requiring management and orchestration of services.
Our Ten High Stories in Java
Event-Driven Architecture –
In an event-driven architecture, the flow of the program is determined by the events that occur and does not follow a predefined sequence of steps. This gives the application more dynamic and flexible behavior as it reacts to a variety of events and does not follow a fixed linear flow.
By embracing Event-Driven Architecture and implementing Messaging with messaging services like IBM MQ, Kafka, Amazon SQS, we let our clients successfully transform their eCommerce platform. A more responsive, scalable, and personalized shopping experience delights customers and increases sales.
Messaging Service allows Event-Driven Architecture to work seamlessly by facilitating communication between microservices. It ensures that events are delivered consistently and efficiently to the appropriate microservices. And it also provides asynchronous integration between services.
Caching for High Throughput –
Caching involves storing frequently accessed data in a temporary storage area (cache). This approach improves performance and reduces the load on the original data source. Storing frequently accessed data in cache rather than fetching it from a database or file system, results in faster data retrieval, reduces latency, and processes requests faster increasing throughput.
We have implemented Caching using various caching libraries and frameworks such as Redis, Caffeine, Hazelcast, and GridGain. We have utilized Caching in read-heavy applications, APIs and Microservices, e-commerce and Mobile applications, and wherever data retrieval performance, response times, and resource utilization are important.
Distributed Transactions for Integrity across Services –
Distributed transactions are used to ensure data consistency and integrity when multiple services or databases need to work together to perform a transaction. These transactions involve a set of operations that must either all succeed or all fail as a single atomic unit to maintain Data integrity.
The Two-Phase Commit (2PC) protocol is a method for achieving distributed transactions ensuring that all participating services or databases agree on whether to commit or abort a transaction, following a two-phase process. The first phase is the Prepare phase and the second is the commit phase.
We use Atomikos with 2PC commit to ensure Data Integrity and ACID properties of transactions.
Eventual Consistency using Outbox pattern –
Eventual consistency is a consistency model where, all replicas of a data item will converge to the same value over time, assuming that no new updates are made. Eventual consistency allows for temporary inconsistencies between replicas but guarantees that these inconsistencies will be resolved eventually.
We use Outbox pattern in conjunction with the two-phase commit protocol to achieve Eventual consistency. This approach decouples the 2PC coordination from the actual data update. So even if the data update fails on some participants or if there are temporary failures. The events in the outbox can be replayed until all replicas converge to the same state, achieving eventual consistency.
Highly Optimized and Dynamic JPA Queries –
Highly optimized and dynamic JPA (Java Persistence API) queries reduce database load and allow scalability by fetching only required data. These improve response time and significantly improve application performance.
Optimized and dynamic queries provide type safety that checks errors during compilation and can be encapsulated in reusable methods – promoting code reusability and maintainability. Highly optimized queries also provide security from SQL injections. Dynamic queries can be generated based on user input and external conditions that help in providing more interactive and user-friendly applications.
Optimized and dynamic JPA queries lead to cleaner and more concise code for easier understanding and maintainability.
REST APIs –
The statelessness, scalability, and flexibility make them easier choices for integration. REST APIs can also take the advantage of HTTP caching mechanism and improve performance and reduce the load on the server and client.
The data can be secured during transit using HTTP security mechanisms HTTP(SSL/TLS) and authentication headers. The loose coupling that REST APIs provide between client and server helps in system maintainability.
Right use of Transaction management –
In a distributed environment where it is essential to maintain data integrity across multiple operations while working with databases, file systems, and other systems, use of transaction manager is critical. Use of proper transaction management system allows creation of YAML changelog file with preconditions, and facilitates commit and rollback features to keep data clean.
In domains such as banking, ecommerce, reservation systems, DBMS, healthcare, supply chain etc. data integrity and consistency are of high essence. The right use of transaction management ensures application performance and data reliability.
Internal and External Scheduler for Job Processing –
Schedulers are critically important in modern software development to manage and optimize job processing to improve the efficiency, scalability, and maintainability of applications.
We use built-in ‘java.util.concurrent’ framework and third party libraries like Quartz scheduler to manage job processing. Schedulers help in automating jobs or tasks, their efficient execution when time is appropriate, concurrency management, resource allocation, error handling and simplifying task management to make applications stable and efficient.
Tasks/jobs like automated report generation, database cleanup, notifications and alerts, periodic update and processing of data, we use in-built scheduler to manage these types of tasks. For jobs like batch processing, load balancing, distributed task scheduling, cross-platform compatibility and managing jobs having dependencies, we use external scheduler.
DB schema migration –
Data migration, code changes, scaling, bug-fixing, requirement evolution, data integrity, and various other conditions demand DB Schema migration necessarily. Use of tools and frameworks, that ensure DB schema migration occurs systematically keeping the database consistent and functional throughout its lifecycle is vitally important.
We use Liquibase to manage DB Schema migration. This database migration and version control tool allows writing database changes in database-agnostic way. Managing, versions to rollback changes if needed, reproducing changes, and generating scrips for Database changes are other features of our DB schema migration.
We integrate Liquibase with CI/CD pipelines to enable automated DB schema migration as part of the application’s deployment process. Also, leverage Liquibase’s feature to manage data along with schema management.
Entity State management in Statefulj -
Managing states and events in an event-driven application is crucial and very essential for performance. We have mastered over a period of time to utilize statefulj for managing states and events and develop event-driven applications for complex work scenarios like workflow management or order processing.
We use statefulj in applications requiring content approval or service provisioning, track order state from creation to processing, payment, and delivery. For applications needing multiple steps and decision points or for applications in microservices architecture requiring management and orchestration of services.
Case Study
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