6 Best Microservice Practices for Designing Scalable and Reliable Distributed Systems

About 74% of organizations utilize microservices, while another 23% plan to adopt them in the future. This indicates that there is something noteworthy about microservices, and that is they have come a long way from being just an experiment in architectural space.

However, breaking down an application into multiple services doesn’t necessarily make it easy to maintain. First, each service must have an assigned responsibility. Each service must be able to:

• Communicate effectively with other services
• Secure its own data
• Deal with any errors
• Be observable in case of any problem

As the number of such connections increases, poor architectural planning may lead to tangled dependencies.

That is when the Monolithic vs Microservices Architecture discussion gains significance. The objective is not just to develop many individual services. It is about defining boundaries that allow for easier changes and scaling in the long run.

The same logic applies when selecting technology. The best microservices frameworks can make development easier, and AWS Microservices can provide containerization, communication between services, orchestration, and continuous delivery. But none can save bad architectural decisions.

The following practices will illustrate the way microservices should be considered in planning, designing, development, data management, deployment, and maintenance in order to ensure the manageability of the distributed architecture. Before getting into the details, let’s first understand modern microservices.

What Is a Microservice?

Microservices are independent software units that focus on a particular business function, such as handling transactions, order management, or sending notifications. Microservices work independently within a bigger application without needing to coordinate the whole system in terms of development, deployment, scaling, and maintenance.

Whereas, in a monolithic design approach, the business logic, application functionality, and data access layers would be deployed together in one package. In a microservices approach, each of these layers is deployed separately in services that can talk to each other using APIs, events, or messaging.

Core Characteristics of a Microservice:

• Domain Alignment: The services are aligned to specific business capabilities and not any random technical capability.
• Independent Deployability: It is possible for the service to be updated and deployed without necessarily updating other independent services.
• Data Ownership: Each service owns its own data and provides access through defined interfaces rather than letting other services have direct access to its storage.
• Decoupled Communication: The services communicate by contracts and not directly. Communication methods can include REST, gRPC, events, messaging, etc.

6 Key Practices for Microservice Architecture

1) Define Service Boundaries Around Business Capabilities

The lifecycle of a successful microservice begins even before the engineers start coding, posing a fundamental challenge of deciding which component needs to be turned into a service and the reasons for doing so. This is when the question posed by the planning of a microservices architecture is not the number of services that the application needs, but rather whether it is suitable to go down that path.

Those applications which involve high feature velocity, variable traffic surges, or different engineering groups that require complete autonomy can be the ones to derive maximum benefit out of this. However, small applications having known load or lesser transactional complexities might not stand to gain much through this approach.

Start with Business Domains, Not Technical Layers

The most resilient service boundaries are those that mirror the business domains themselves, and not any sort of software layers. The engineering teams should be applying Domain-Driven Design (DDD) to identify the major business sub-domains and classify them into the respective bounded contexts, in which the particular data model will have one definitive meaning. 

For instance, transactional state and checkout should be part of the payment service alone, totally isolated from the service responsible for managing the user profile or product stock management. Consider an EdTech Platform with DevOps & Microservices Architecture, for example. User management, delivery of courses, assessments, payments, and notifications can represent different business capabilities. Each service must be analyzed not in terms of separation since it constitutes a different technical layer but in terms of its responsibility, data ownership, scalability, and pace of change.

Don’t fall into the trap of building services that constitute different technical layers like a database service or UI service. Or even worse, designing services with a one-to-one correspondence to a single database table. A properly designed service will be self-contained and responsible for a meaningful business capability, with a defined purpose.

Establish Clear Service Ownership

An isolated service needs clear and unambiguous service ownership. A cross-discipline engineering team needs to own the service end-to-end and be responsible for the codebase, its data store, API contracts, security configurations, and the current production state. Clearly defined ownership removes inter-team coordination delays and allows quick debugging when something goes wrong in production.

As you consider service boundaries, consider the interactions between the business processes in your company. Where two distinct components need to change in unison through code updates and deployments, there will be a high level of interdependence, and the two would need to reside within the same boundary. A business function that needs its own cadence, controls, and technology platform is a good candidate for microservice development.

Align Boundaries with Operational Requirements

Instead of merely decoupling modules for the mere sake of being able to do so in the design, map service boundaries to real metrics:

• Scalability Needs: Ensure that workloads with volatile traffic patterns are separated from stable ones.
• Availability Goals: Make sure that core functionality (such as the checkout engine) is not coupled with non-essential functionality (like the recommendation carousel).
• Compliance and Security: Organize modules that deal with very sensitive information (PII or credit card numbers) into separate services, and thus limit your regulatory audit scope.
• Frequency of Deployment: Separate frequently changing customer-oriented features from the stable back-office services which require strict compliance.

Prevent Premature and Over Granular Decomposition

Small-sized services are not necessarily better. Decomposing the system too much results in a highly fragmented set of hyperactive APIs, interdependencies, and failures. If the services are made too small, the engineering team spends more time integrating the services through the network than providing the main functionality.

One such approach to design is to start with bigger, modular boundaries and then let them divide naturally as you get a better idea of what you need operationally. A service is considered to have the right size when it is big enough to cover an entire business process but at the same time small enough for one team to understand and manage.

Establish Standards Before Development Begins

Your engineering teams must agree on standard processes for:

• API Design & Contract: Standardizing API formats such as REST/JSON or gRPC to facilitate system interoperability.
• Decentralized Security: Using consistent security mechanisms such as authentication and authorization by means of cryptographically signed tokens.
• Observability Standards: Requiring uniform structured logging and trace metadata.
• Communication Boundaries: Establishing clear guidelines on which methods are appropriate for synchronous and asynchronous communication systems.

This does not mean that the end goal of the planning phase is for you to get locked into a rigid architectural structure. On the contrary, it entails setting the necessary structures for the ownership, scope, and guardrails to ensure that your distributed systems can scale without losing control.

2) Design Services for Independent Communication and Failure

Following the definition of the service boundaries comes the task of developing each service in such a way that each one is able to work independently without generating any unwanted dependencies within the application. This is possible through a careful microservices architecture where services can develop independently of one another.

Give Each Service a Clear Business Responsibility

Each service should have its own well-defined responsibility and sufficient internal cohesion to handle its capabilities. This principle avoids making each service dependent on how its partner service is implemented internally.

For instance, order management services should handle order workflows without actually touching the internal data structure and business logic of the inventory service. In case a service needs some other service’s internal structure in order to work, then perhaps the boundary needs to be re-evaluated.

This is where the importance of loose coupling and high cohesion comes in. Services must only know what they must achieve through an agreement but should not know how another service does it.

Establish Clear and Stable API Contracts

APIs form the most important contracts between independently managed services. An effectively structured microservices API should have clear details about the operations available, the structure of requests and responses, authorization, error handling, and compatibility.

Both REST and gRPC are good choices depending on the workload and communication needs. REST is suitable for externally available APIs and resource-based APIs, whereas gRPC might be helpful for high-performance communication internally.

API versioning and backward compatibility must be considered ahead of time before services start developing independently. The new version must not suddenly fail the consumers that haven't been migrated yet.

Choose Synchronous and Asynchronous Communication Carefully

Not every service call requires an immediate response. There is scope for synchronous communication if there is a genuine need for immediate results, but repeated service calls might introduce unnecessary latency and add failure points.

For suitable workflows, asynchronous communications using events, queues, and publish-subscribe models help decrease direct dependencies among services. In such a scenario, the order service could publish order confirmation events which are then consumed independently by other services such as the payment, inventory, or notification services.

Every communication model involves trade-offs. Choose your approach based on transactional urgency, performance targets, and failure recovery paths rather than a default preference for event-driven patterns. 

Build for Failure at the Design Stage

Failures are expected occurrences in distributed systems. As such, services have to be built to deal with unavailable services and not always assume that requests will be fulfilled.

Useful microservices design patterns include:

• Timeouts: Ensure that the application doesn't hang while trying to access an unresponsive dependent service.
• Retries: Give some time to fix up a problem and allow it to recover.
• Circuit Breakers: Block repeated calls to a broken/invalidated dependent service.
• Bulkheads: Separate resources so that any failure in one place will not drain all other resources in the application.
• Graceful Degradation: Ensure that non-essential features do not crash, and the critical ones continue to function.

This technique needs to be employed carefully because, for instance, poorly designed retries could cause more traffic during the outage.

Plan Security Into Service Communication

Security should be an integral component of the microservices design rather than being an extra layer imposed later on. Every communication between two services should have defined rules for authentication and authorization. 

It depends on the architecture to include API Gateways, service-to-service authentication, TLS/MTLS, role-based access control, secret storage, and identity services. Each service will only be allowed the permissions necessary for its duties.

Select the Right Technology Based on Service Requirements

Microservices enable developers to use various technologies, provided that there is an actual technical need for that, yet too much variety in technologies can become a burden. 

In determining the best microservices frameworks, one should take into consideration:

• The performance needs of the service
• Communication paradigm
• Ecosystem
• Security features
• Skill sets of the development team
• Deployment environment
• Maintenance needs in the long term

This will lead to a set of services that have well-defined roles, stable agreements, controlled communication, and predictable failure behaviors. This will make the development and integration phase much simpler to handle.

3) Build and Integrate Services Without Creating New Dependencies

Now that the architecture has been established, development needs to ensure that the boundaries set up earlier are maintained rather than slowly dissolving away. The emphasis is on how services are developed, tested, secured, and integrated in such a way that no development dependencies are created.

Maintain Development Independence

To keep the work moving, each service must be decoupled enough that engineers can write and maintain code without constantly checking in with the outside teams.

A few practical measures to check upon:

• Keep the business logic inside the service that provides the capability.
• Keep the specific dependencies and configuration for the service separate.
• Do not import the inner code or access the database of another service.
• Share libraries in a selective manner to avoid synchronized changes to the common code.
• Keep build and testing separate where possible.

The main goal here is independent microservices development, where a team can tweak or overhaul their service without accidentally causing a massive wave of extra work for everyone else.

Build Against Explicit Contracts

The agreements created around each service have to be incorporated within the development cycle. There is no need for making assumptions between teams. These can be programmed in such a way that there can be validation automatically.

A contract can define:

• Request and response structures
• Required and optional fields
• Expected error responses
• Authentication requirements
• Supported versions
• Compatibility expectations 

Contracts between APIs provide developers with a common reference point and make it easier to test any modifications that have been made before they impact dependent services.

Automate Multi-Level Testing

A distributed system requires testing at multiple tiers since a service may operate independently yet fail upon integration with another service.

Practical microservices testing includes:

• Unit Tests: Test individual business rules and functionalities.
• Integration Tests: Test the interactions with the database, queue, API, and infrastructure.
• Contract Tests: Test whether the consumers and providers are holding up their end of the bargain.
• End-to-end Tests: Test critical workflows that span multiple services.

Make sure these tests run automatically as part of the CI/CD pipeline to catch integration issues before release.

Embed Security Throughout Development

The security check process should be parallel to the development phase rather than being a final test prior to deployment. Teams can incorporate:

• Dependency scanning
• Vulnerability scanning
• Static code analysis
• Secrets detection
• Container/image scanning
• Automated security testing
• API security validation

They help to uncover weaknesses when changes are being implemented and lessen the probability of vulnerable elements making it to the delivery phase.

Manage Dependencies and Avoid Tight Releases

Independent development becomes meaningless if the services depend on coordinated change. Determine the dependencies among the services and locate workflows where multiple teams have to coordinate the releases of their services regularly.

Make use of automated testing and dependency control to discover these relationships early. If any particular dependency continues to require coordinated releases, then rethink the implementation instead of introducing yet another release process.

This will help keep microservices integration simple while giving individual teams the freedom to release without having to coordinate unnecessarily.

4) Establish Clear Data Ownership Across Services

Managing the data is perhaps the hardest part of the distributed system design. Transitioning from having a singular monolithic database to a distributed one brings about a whole new pattern of distributed data that needs to be governed properly. In the process of decoupling your application logic, you will have to decouple your data logic too.

Give Each Service Ownership of Its Data

The service needs to manage data it owns and make data available via specific interfaces instead of letting other services access its database directly.

This principle is normally practiced by using a database per service methodology. The databases need not be on different database systems or different hardware, but they must be separate logically from the point of view of their schemas and owners.

For instance, the order service would own order information and transaction status, whereas the inventory service would own stock information. The order service cannot query the inventory service tables since it has access to them just like the other database does.

Isolating your databases this way makes microservices data management much cleaner. It means a team can swap out their storage engine or tweak a schema without accidentally breaking an unrelated service down the line. 

Handle Consistency Across Services

A database transaction may not always be feasible in a situation where the business process involves multiple services. What is required in such cases is proper mechanisms for dealing with distributed transactions.

Depending on the workflow, consider:

• ​​Eventual Consistency: Let related data converge across multiple services over time.
• Saga Pattern: Divide a distributed transaction into local transactions with compensation logic in case something goes wrong in a particular step.
• Event-driven Updates: Use business events to inform services about data updates.
• Idempotent Operations: Make sure that the request can be executed repeatedly.

The choice of solution depends on the business need. The process of a payment might have other consistency requirements than the process of content publishing.

Avoid Shared Databases Becoming Hidden Dependencies

The usage of a common database can lead to a tightly coupled architecture for services. This means that several services that rely on the same schema will have to be developed and released simultaneously.

The maintenance of data ownership within the responsible service enables its schema and implementation of storage to develop independently. The shared infrastructure could still work, but direct access to another service’s data is not recommended.

Plan Data Access, Migration, and Recovery

The design of microservices data architecture must also consider how the data is to be transformed and secured as the software is developed. The team must develop policies for data migration, backups, recovery, and access control.

Important considerations include:

• Data encryption and access controls
• Backup and recovery procedures
• Schema migration strategies
• Data retention requirements
• Audit trails for sensitive information
• Data synchronization requirements

5) Build a Deployment Model for Independent Releases

The process of releasing and scaling independent services requires removing manual infrastructure provisioning and embracing automated, cloud-native runtime environments. If your deployment process depends on humans copying files or manually configuring servers, then a distributed architecture will quickly spiral out of control.

Standardize Automated Deployment Pipelines

Every microservice should have its own dedicated CI/CD pipeline. Without this, teams end up managing what is effectively a distributed monolith with all the added complexity and none of the true independence. 

Here’s how it works. The developer pushes the code, and the CI/CD pipeline picks up from there. The pipeline will build the container, run the tests, and push the image into the registry, all without manual intervention. The significance of all of this is that the real value of microservices technology is to allow teams to carry out deployment independently, on their own timelines. If not, then the speed advantage of microservices gets reduced to nothing if each and every deployment needs manual approval. 

Adopt Robust Container Orchestration

With tens of separate containers being used, an orchestration tool is needed to control all of them. The orchestration tool makes the operations process easier, as it takes up many technical responsibilities. Rather than manually keeping track of everything, use the orchestration tools for automation: 

• Service Discovery and Load Balancing: Real-time discovery of container IPs and load balancing of network traffic among the nodes in your cluster.
• Horizontal Scaling: Proper scaling of individual services based on real-world runtime metrics through the configuration of your orchestration layer.
• Self-Healing: Automatic recovery of failed containers and avoiding unhealthy nodes without impacting production.

Leverage managed AWS Microservices Architecture

Reduce operational costs by relying on well-proven, managed AWS infrastructure patterns as opposed to setting everything up yourself. Everything you build as a custom infrastructure requires your engineering staff to then have the responsibility to maintain and patch the same infrastructure as well. Utilization of a managed cloud service environment helps you avoid all this initial grunt work and allows your engineers to focus on building your product:

• Compute: Pair Amazon EKS or Amazon ECS with AWS Fargate for serverless containerization, removing the requirement of dealing with the underlying virtual machines.
• Traffic Management: Direct traffic from clients to Amazon API Gateway to take care of the global entry point rules.
• Event Routing: Handle asynchronous pipeline communication using Amazon MSK or Amazon SQS/SNS.

6) Make Production Behaviour Observable and Measurable

A distributed system will have many independently executing services; thus, it becomes complicated to comprehend the proceedings of the system using the application logs of one software program. Efficient microservices observability helps teams understand what is going on beyond service boundaries and recognize the source of the problems.

Establish Unified Observability

Each service must generate stable operational data that will be analyzed throughout the whole microservices application architecture.

Emphasis on the following three aspects:

• Metrics: Monitoring of requests per second, latency, error rates, availability, and resource usage.
• Centralized Logging: Gather logs that are well-structured in different services and make them searchable.
• Distributed Tracing: Trace requests across different services and find out where the delays or failures happen.

All of these signals need to be combined so that developers can go from an application-related issue to a particular service-related one.

Monitor Business-Critical Workflows

Technical metrics alone might not be sufficient to indicate if the application is meeting its target in terms of business outcome. Microservices monitoring should also include critical workflow processes such as failed payments, incomplete transactions, failed sign-ups, and failed content processing.

This enables teams to differentiate between the availability of the service and the effectiveness of the business process.

Create Actionable Alerts and Review System Health

Alerts are required to focus on conditions that require investigation rather than generating notifications for every minor fluctuation. Teams can define the thresholds around error latency, availability, and critical business operations. Regular operational reviews can then identify recurring failures, unusual resource consumption, unnecessary dependencies, or services that require architectural changes.

This ongoing visibility helps maintain microservices scalability, reliability, and operational controls as the distribution system evolves.

Why Choose Hyperlink InfoSystem for Microservices Development?

Your business model expansion should be compatible with the microservices architecture that you choose, and not the other way around. Our team at Hyperlink InfoSystem can assist you in evaluating the use cases of microservices, implementing a plan that fits well into your current setup, and planning your transition process.

With our expertise in architecture planning, application modernization, cloud migration, and engineering for the long run, we can provide you with a well-defined technical strategy based on tangible priorities. This involves advice on how to implement microservices, manage data in microservices, as well as selecting the optimal microservices framework.

Ultimately, the best microservices framework will be the one that suits your business and its requirements. If you need help designing a whole new architecture for a new product, get in touch with our experts, and they will guide you throughout the process.