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From Chaos to Harmony

In this article we will cover a popular topic "Why synchronisation fails in production" Let's unveil some of the challenges, mitigation strategies, and alternative architectures.

Harrison Jnr

Harrison Jnr

— 9 min read
From Chaos to Harmony

"Why do synchronisation fail on production systems?"

Let's explore the intricacies of synchronisation failures as it relates to application processes/tasks & execution workflows. We will examine real-world use cases from companies that have encountered issues, and delve into some mitigation strategies.
Introduction

Synchronisation failures in production environments can pose significant challenges to the seamless operation of applications and systems.

We will discuss the benefits of alternative architectural approaches such as Domain-Driven Design (DDD), serverless computing, micro-services architecture, and event-driven development, and how they can mitigate synchronisation issues.

Understanding Synchronisation Failures in Production

Common Causes of Synchronisation Failures includes:

🧪 Network Connectivity Issues

Interruptions or instability in network connections, such as packet loss, high latency, or network outages, can disrupt synchronisation processes. These issues can occur due to faulty network hardware, misconfigured network settings, or external factors like environmental conditions.

🧪 Data Inconsistency and Integrity

Discrepancies in data between synchronised systems can lead to synchronisation failures and result in incorrect results or actions. Inconsistent data may arise from errors during data transfer, data corruption, or conflicts caused by concurrent updates.

🧪 Misconfigured Synchronisation Mechanisms

Synchronisation mechanisms, such as data replication, mirroring, or distributed transactions, rely on proper configuration and parameter settings. Misconfigurations, including incorrect synchronisation intervals, incompatible protocols, or insufficient buffer sizes, can cause synchronisation failures and data inconsistencies.

🧪 High System Load and Performance Bottlenecks

Synchronisation processes require computational resources and can impose a significant load on systems. When the system is under heavy load or experiences performance bottlenecks, such as CPU or memory constraints, synchronisation may be delayed or fail altogether.

🧪 Version Incompatibilities and Compatibility Problems

Synchronisation failures can occur when there are disparities in software versions or compatibility issues between different components involved in the synchronisation process.

🎯Changes in data formats, protocols, or APIs without proper consideration of backward compatibility can result in synchronisation failures.

🧪 Configuration Errors and Insufficient Permissions

Synchronisation processes often require appropriate configurations, such as access rights, authentication credentials, or firewall rules, to establish communication and data exchange between systems. Configuration errors, such as incorrect credentials or insufficient permissions, can prevent successful synchronisation.

It's important to note that these causes are not exhaustive, and other factors specific to the system architecture, technology stack, or environmental conditions may contribute to synchronisation failures in production environments.

🧠 Understanding these causes helps in identifying potential areas of vulnerability and designing effective mitigation strategies.

Real world scenarios/examples of synchronisation failures

I will instead tag these companies as Company A, B .... etc as i cannot mention the names of the companies due to business dealings & agreements.

🏢 E-commerce Provider (Company A)

Company A operates an e-commerce platform where inventory management and order processing are critical components.

🐞 In the past, the system relied on periodic synchronisation between the inventory and order management systems to ensure up-to-date stock availability.

However, this approach resulted in synchronisation delays, leading to instances of overselling and dissatisfied customers.

To mitigate synchronisation failures:

  • We adopted an event-driven architecture.
  • We decoupled the inventory and order management systems by introducing a messaging infrastructure (Rabbitmq) based on a publish-subscribe pattern.
  • Whenever a change in inventory occurred, such as a new purchase or restocking, an event was published to the messaging system.
  • Subscribers, including the order management system, received these events in real-time, updating their records accordingly.

🎯 This approach ensured accurate inventory tracking without relying on periodic synchronisation.

🏢 Financial Services Provider (Company B)

Company B is a financial services provider handling a large volume of client transactions.

🐞 In their previous monolithic system, synchronisation was used to maintain consistency between client account balances and transaction records.

However, as the system grew, synchronisation became a performance bottleneck, leading to delays and discrepancies.

To address synchronisation failures:

  • We worked with the engineering team to implement microservices coupled with event sourcing strategies for their application.
  • We decomposed the monolithic system into smaller, autonomous services, each responsible for a specific domain. Client account balances and transaction records were managed by separate microservices, each with its own database.
  • The event sourcing pattern was employed to ensure immediate consistency. Whenever a transaction occurred, an event capturing the details of the transaction was stored in an event log.
  • The microservices subscribed to these events, updating their respective databases asynchronously.

🎯 This approach eliminated the need for synchronisation between the systems, as the data was propagated through the event log, ensuring consistency across the system in near real-time.

🏢 Healthcare Provider (Company C)

Company C is a healthcare provider managing electronic health records and billing processes.

🐞 They faced synchronization failures between the EHR and billing systems, leading to billing discrepancies, delayed payments, and potential regulatory compliance issues.

To overcome these challenges:

  • We worked with the engineering team to adopt a Domain Driven Development Approach (DDD) and event-driven architecture.
  • We identified distinct bounded contexts within their system, such as patient information, medical procedures, and billing. Each bounded context was managed by a separate microservices with its own database.
  • To ensure data consistency, events were generated whenever updates occurred within a bounded context.
  • These events were then published and consumed by relevant services responsible for maintaining consistency across the EHR and billing systems.

🎯 By relying on events and decoupled communication, synchronisation failures were mitigated, and accurate billing information was propagated in real-time.

Some early reasons why teams build with synchronisation

Real-Time Data Updates: Synchronisation enables immediate data propagation across systems, ensuring consistency and accuracy. When multiple systems or components share synchronised data, any changes made in one system are promptly reflected in others.

Simplified Development: Synchronisation can simplify application development by relying on shared data sources. When different components or services within an application need access to the same data, synchronisation mechanisms provide a centralised approach.

Developers can focus on implementing the synchronisation logic, ensuring that data updates are propagated efficiently, rather than managing separate copies of the data in each component.

🐞 This simplifies the development process, reduces code duplication, and improves overall maintainability but increases technical debt as the codebase expands over time.

Disadvantages and Drawbacks

✅ Complexity and Scalability Challenges: Synchronisation mechanisms can introduce complexity and scalability limitations, hindering system growth. As the number of systems or components involved in synchronisation increases, the complexity of managing the synchronisation logic also grows.

🎯 Coordinating the synchronisation process, handling conflicts, and ensuring data integrity across multiple systems can become increasingly challenging.

🎯 As the system scales and the data volume or frequency of updates rises, synchronisation mechanisms may struggle to keep up with the increasing demands, resulting in performance bottlenecks and potential synchronisation failures.

✅ Increased Latency: Synchronisation processes can introduce delays, impacting real-time data availability. When changes are made in one system, they need to be propagated to other synchronised systems, which takes time.

🎯 This synchronisation latency can reduce the perceived real-time nature of the data and introduce a delay in accessing the most recent information.

In scenarios where immediate data availability is critical, such as financial transactions or real-time monitoring, relying on synchronisation alone may not be sufficient.

✅ Potential Data Conflicts: Concurrent updates can lead to conflicts and data inconsistencies. In a synchronised environment, if multiple systems or users attempt to modify the same data simultaneously, conflicts can arise.

🎯 If two systems update the same record at the same time, synchronisation mechanisms need to resolve the conflict by determining which update should take precedence or by merging the changes.

🎯 Handling these conflicts effectively requires careful synchronisation strategies and conflict resolution mechanisms to ensure data integrity and consistency across systems.

✅ Single Point of Failure: Synchronisation introduces a single point of failure. If the synchronisation process encounters issues or fails, it can impact the entire system's functionality. A failure in the synchronisation mechanism can lead to data inconsistencies, disrupted workflows, and potential loss of critical information.

🎯 Implementing robust fault-tolerant mechanisms, backup systems, and monitoring tools becomes essential to mitigate the risks associated with a synchronisation failure.

✅ Tight Coupling and Dependency: Synchronisation can create tight coupling and dependencies between systems.

When systems rely heavily on synchronisation:

  • They become interdependent, making it challenging to modify or update individual components without affecting the entire system.
  • This tight coupling can reduce flexibility, agility, and hinder the ability to introduce changes independently.
  • Additionally, introducing new systems or retiring existing ones can be complicated, as synchronisation dependencies need to be carefully managed to avoid disruptions.

It is crucial to consider these advantages, disadvantages, and drawbacks when designing and implementing synchronisation mechanisms in production environments.

While synchronisation can offer real-time data updates and simplify development, the complexity, scalability challenges, potential conflicts, latency, and dependencies associated with synchronisation need to be carefully addressed to ensure a robust and reliable system.

In some cases, alternative architectural approaches like Domain-Driven Design (DDD), serverless computing, microservices architecture, and event-driven development can offer solutions to remove or minimize the reliance on synchronisation, improving system scalability, resilience, and flexibility.

Benefits of leveraging Domain-Driven Design (DDD)

✅ Bounded Contexts and Aggregates

DDD promotes the concept of bounded contexts and aggregates, which define clear boundaries and encapsulation within the system.

By separating different areas of functionality into distinct bounded contexts, synchronisation between them is minimised.

Each bounded context manages its own data and enforces its own consistency rules, reducing the need for synchronisation between different parts of the system. Aggregates within bounded contexts ensure that updates are made atomically within their boundaries, further reducing the risk of data conflicts and the need for synchronisation.

✅ Eventual Consistency

DDD embraces the idea of eventual consistency, where data may temporarily be inconsistent across different parts of the system, but will eventually converge to a consistent state. This reduces the reliance on real-time synchronisation and enables asynchronous processing and propagation of data changes. By designing the system to handle eventual consistency, synchronisation requirements can be minimised, allowing for more scalable and resilient architectures.

Benefits of leveraging serverless computing

✅ Event-Driven Architecture: Serverless computing leverages event-driven patterns, where components communicate through events rather than direct synchronisation.

Events represent meaningful occurrences or changes within the system, and services can react to these events independently and asynchronously.

This decoupled communication eliminates the need for tight synchronisation between components. Each service can process events at its own pace, allowing for greater flexibility and scalability.

✅ Scalability: Serverless platforms offer automatic scaling capabilities, allowing systems to handle increased workloads without the need for explicit synchronisation mechanisms.

As the load on the system grows, the serverless platform can automatically provision resources to handle the demand, ensuring that the system remains responsive and performant.

This scalability eliminates synchronisation bottlenecks and allows the system to scale seamlessly.

Benefits of leveraging Microservices Architecture

✅ Independent Databases: In a microservices architecture, each service typically has its own dedicated database, which reduces the need for synchronisation.

🚀 Each service can manage its data independently, making updates and modifications without requiring synchronisation with other services. This autonomy minimises the risk of data conflicts and simplifies the overall system design.

✅ Asynchronous Communication: Microservices can communicate asynchronously through message queues or event-driven mechanisms, which reduces dependencies and the need for tight synchronisation.

🚀 Services can publish events or messages indicating changes or requests, and other services can consume and process these events independently and asynchronously. This asynchronous communication eliminates the need for synchronous and tightly coupled synchronisation processes, enabling looser coupling and increasing system responsiveness.

Benefits of leveraging Event-Driven Development

✅ Loose Coupling: Event-driven development promotes loose coupling between components, reducing the need for tight synchronisation.

🚀 Components communicate through events, allowing them to be decoupled and independently evolve over time.

🚀 Each component can subscribe to relevant events and react accordingly, without requiring direct synchronisation with other components. This loose coupling enables more flexible and modular system design.

✅ Scalability and Resilience: Event-driven systems are inherently scalable and resilient. Events can be processed asynchronously, allowing components to handle high loads and spikes in traffic without the need for synchronisation.

🚀 Events can be distributed across multiple instances or services, providing horizontal scalability.

🚀 Additionally, event-driven architectures support fault tolerance and resilience since events can be persisted and replayed in case of failures, ensuring reliable processing and eliminating single points of failure.

Conclusion

Synchronisation failures in production environments can be challenging and disruptive, impacting the reliability and performance of applications.

While synchronisation mechanisms offer real-time data updates, they also introduce complexities and drawbacks.

🎯 Alternative architectural approaches such as DDD, serverless computing, microservices architecture, and event-driven development provide potential solutions to remove synchronisation challenges.

By carefully considering the advantages and disadvantages of synchronisation and exploring alternative architectures, organisations can enhance their system's scalability, agility, and data consistency, ultimately improving the overall performance and reliability of their production applications.

References

Domain-Driven Design (DDD):
Serverless Computing:
Microservices Architecture:
Event-Driven Development:

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