Ultimate Guide: What are Microservices?

Software development is an ever-evolving landscape where traditional legacy architectures are giving way to a modular approach embodied by microservices architecture. 

As organizations seek agility, scalability and resilient solutions for business needs, microservices provide application designs for better deployment. This article focuses on exploring key concepts around microservices architecture, including its advantages & disadvantages. 

What is a Microservice in Simple Terms?

A microservice can be thought of as a miniature service that focuses on one specific capability within a large application. For example, a video sharing app might have separate microservices for video uploading, transcoding, streaming, comments, user management, and so on. 

Each microservice is self-contained - it consists of its own codebase and processes that are independent of other services. This decentralized nature of microservices makes them easy to update, scale and maintain. Developers can modify one service without having to rebuild and redeploy the entire application. So if newer video formats emerge, just the transcoding microservice needs to be upgraded without affecting unrelated components.

What are the Three Types of Microservices?

Core Microservices

These are the central microservices that handle the primary business capabilities and functionalities of an application. For example - in an ecommerce app, the core microservices would include the product catalog, user profiles, shopping cart, order management and payment processing.

Core microservices implement critical app logic and data processing that drive central value. They integrate closely with other peripheral services to deliver end-to-end workflows. These services see most frequent updates to add capabilities and are strategically important from a business perspective.

Supporting Microservices

As the name suggests, these microservices provide supporting capabilities that help core services. Example includes - Monitoring, Logging, Configuration, Messaging, Caching, Authentication, Rate Limiting etc.

While not directly tied to business goals, supporting services improve quality of service. Health checks and performance monitoring allows proactively optimizing production. Centralized logging aids debugging issues faster. Message queues ease inter-service coordination. Supporting services are infrastructure-centric vs product centric.

Orchestration Microservices

Orchestration services manage and coordinate how core microservices collaborate to construct application flows. Key duties include:

• Aggregate data/responses from multiple services to fulfill requests.
• Implement workflows by directing request/data across services.
• Provide resiliency via retries, failovers when services fail.
• Enforce policies, controls and compliance across any environment.

These orchestrator services reduce point-to-point integration complexity. Core services integrate with few orchestrators vs many peer services directly. This improves maintainability while abstracting inter-service communications from underlying implementation.

What Is Microservices Architecture Use Cases?

Dynamic Scalability

One of the major benefits of microservices is the ability to scale individual services as per demand. Monolithic applications have to scale all components uniformly even when only specific functions face load spikes. This causes resource wastage. With microservices, the video encoding service can be independently auto-scaled to handle bursts in new video uploads without needing to scale unrelated services. Granular scaling improves cost-efficiency and performance.

Faster Releases

Microservices modular nature allows faster iterations and continuous delivery of new features. Changes can be tested and deployed rapidly for specific services without large regression testing and risks of monolithic deployments. New versions can also be incrementally rolled out to users for canary testing before wider rollouts. This accelerates innovation and version upgrades for better user experience.

Technology Flexibility

Microservices architecture allows different services to use programming languages and frameworks best suited for their needs. So an AI-based recommendation engine can use Python while transactional services use Java without conflicts. This flexibility in technology stack brings developer productivity improvements while allowing innovation velocity across different capability areas. Legacy monoliths often pose limitations on tech choices.

Resilience

Since services are independent, failure of one service does not cascade across others allowing overall application to continue functioning. Microservice redundancy also improves resilience - if one payment service fails, calls can be routed to another instance preventing revenue loss. Such fault-tolerance aids mission-critical environments.

Clear Ownership

With small teams responsible for particular microservices, service boundaries establish clear ownership of capabilities. This DevOps model allows teams to focus innovation on precise solutions. Microservices ownership aligns technical decision-making with business values. Large teams building monoliths cannot adapt as fast.

Monolithic vs. Microservices Architecture

Tight Coupling vs Loose Coupling

Monolithic applications have tight coupling between components - the UI layer, business logic layer, data access layer and other components are interconnected and bundled together. Changes to one module requires rebuilding and redeploying the entire application.

In contrast, microservices comprise loosely coupled independent services. The product catalog microservice does not depend on internal implementation of the ordering system. This isolation allows changing services faster without impacts.

Granular Scaling

Monoliths scale across a common resource pool even when only specific functions face load spikes resulting in over-provisioning. With microservices, only the impacted services scale up or out saving infrastructure costs.

Easier Upgrades

Monolithic applications require extensive integration testing for new versions before deployment. A change in one module can impact others. With independent services, microservice upgrades have localized impact allowing faster deliveries.

Flexible Technology

Monoliths often constrain technology choices given enterprise commitment to Java/NET ecosystems. Microservices allow combining technologies - mobile apps can use JavaScript while AI services use Python for agility.

Failure Isolation

Bugs in monolith components can bring whole systems down. With microservices, failures are isolated and managed independently without outages.

However, microservices also increase distributed systems complexity necessitating coordination frameworks. Monitoring and debugging distributed transactions across services poses challenges as well. These overheads are avoided within monolith boundaries.

Monolith vs Microservices Summary: modular microservices aid complex, scalable apps where automation and fault isolation are critical. Monoliths suit smaller scope apps given simpler coordination between components. Understanding tradeoffs help optimize architecture decisions.

How Microservices Works with Other Technologies

Microservices and APIs

Well-defined APIs enable effective coordination between independent microservices. Standard protocols like REST over HTTP leverage web stacks for service communication. Self-documenting API specifications like OpenAPI helps discoverability and consumption. Versioning ensures that API changes don't break existing integrations or clients. Overall, APIs are the connectivity fabric for reliable microservices orchestration.

Microservices and Containers

Containers package microservices code, configs, dependencies into lightweight virtual images for portability across environments - from dev test to production. This bridging of the deployment gap aids continuous deployment. Container orchestration engines like Kubernetes handle provisioning, scaling, health-checking of containerized apps enabling automation. Namespaces, quotas aid access controls.

Microservices and Service Mesh

A dedicated infrastructure layer called service mesh manages complex microservices communications challenges like - connection establishment, retries, routing, security, observability. Open source tools like Istio reduce service-to-service complexity through capabilities like resiliency testing, staged rollouts, metrics collection making it easier for microservices to interact reliably.

Microservices vs SOA

Microservices evolve earlier SOA concepts around modular architecture by decentralizing into independently deployable services aligned to product capabilities vs enterprise concerns in SOA. And emphasize automation in the middleware. SOA uses web services standards like XML, SOAP, WS-* etc while microservices embrace lighter protocols like REST. Overall, Microservices amplify SOA benefits for continuous delivery expectations.

Microservices and Cloud

Dynamic microservices meshes thrive on cloud infrastructure for rapid provisioning of compute, databases, analytics etc. as modular building blocks. Availability of managed specialized network, security, queueing services further boost productivity. Auto-scaling streamlines resource footprint. Microservices and cloud revolutionize legacy architectures with agility and innovation velocity.

How DevOps is Enabled by Microservices

Agile Development Workflows

Microservices empower developers to use optimum practices by decomposing large codebases into modular services aligned to product capabilities. Small teams own services end-to-end using agile sprints to evolve functionality. Services can be developed, tested and deployed independently without coordination overhead. This improves productivity and innovation. Changes propagate faster while quality issues have localized impact.

Automated Testing

Automated test suites can run on each microservice build verifying quality prior to deployment. Unit testing validates modules functionally. Integration testing with test doubles asserts coordination logic between services by simulating connectivity. Performance testing under simulated loads maintains responsiveness standards for real-world conditions. Test automation confidence allows faster releases.

Simplifies Deployments

Containers standardize the environment allowing services to be deployed consistently across infrastructure. Automation tools help manage and orchestrate containers at scale. Immutable container images represent an unchanging snapshot of code/config easing rollbacks. Infrastructure as code automates provisioning needs. Together this enables continuous delivery pipelines.

Dynamic Resource Allocation

Auto-scaling adapts to changing operational loads by dynamically increasing or decreasing underlying infrastructure resources. Services can scale independently rather than whole applications allowing efficient computing. This grants flexibility to fulfill dynamic demands.

Rapid Fixes

Isolating failures to specific services prevents wide-spread cascading outages. Distributed tracing and microservices monitoring provides fine-grained visibility to diagnose root causes faster. Fault detection triggers auto-healing mechanisms or alerts site reliability engineers for rapid fixes. This improves resilience and uptime.

In essence, microservice is the DevOps tool to help optimize workflows, automation and infrastructure management - directly fulfilling key DevOps goals and accelerating service deliveries.

Business Benefits of Microservices

Faster Time-to-Market

The modular architecture of microservices empowers rapid innovation by decentralizing development, testing and deployment. New features can be incrementally added to specific services and rolled out faster without waiting on large release cycles. This agility is vital for continuously delighting customers with new capabilities before competitors. Frequent deliveries provide user feedback more often as well. Together this accelerates time-to-market.

Cost Optimization

Microservices enable selectively allocating and scaling resources only for impacted application areas rather than the entire monolith. Cloud usage-based billing combined with auto-scaling further optimizes the resource footprint according to demand curves by turning off unused capacity. This minimizes infrastructure costs.

Improved Resilience

Independently deployable services with multiple versions provides redundancy to absorb some failures. If the payment processing service has issues, requests can be routed to a different instance minimizing revenue impact. Microservices design for fault isolation significantly improves system resilience versus monoliths.

Innovation Velocity

Microservices empowers product teams to rapidly experiment with new technologies like AI/ML, AR/VR to develop differentiated capabilities rather than wait on long enterprise approval processes. This drives innovation velocity across various application areas to boost competitive advantage.

Accelerate Growth

The combination of above factors like improved time-to-market, resilient operations and optimized costs accelerates business growth. The software delivery efficiency aids enterprises meet digital transformation goals for the modern marketplace - one that expects instant, customized and delightful experiences from products and services.

Key Challenges of a Microservices Architecture

While microservices provide significant benefits around independent scalability and accelerating feature velocity for large and complex applications, they also introduce a number of complexity, debugging, cost and data integrity challenges that should not be underestimated. The switch to microservices needs to be strategically planned based on these tradeoffs.

• Complexity - A microservices architecture can introduce significant additional complexity in terms of the number of moving parts and services that need to be managed. Instead of a single monolithic application, you now have dozens or hundreds of smaller services that need to be deployed, scaled, updated, monitored, etc. This also leads to complex distributed transactions and consistency issues that need to be handled.
• Testing and Debugging - With a large number of separate services, testing and debugging becomes much more difficult. Issues may only appear when multiple services interact, and it can be hard to replicate production issues in a test environment. Sophisticated tracing, logging, and monitoring capabilities are required.
• Operational Costs - There are major operational overhead costs with microservices around provisioning infrastructure, configuring multiple environments, implementing CI/CD pipelines with microservices, handling deployment orchestration, and ongoing management of many more moving parts. These costs can quickly add up and overwhelm the benefits of microservices if not adequately accounted for.
• Data Integrity - When data is decentralized across multiple databases owned by different services, ensuring data integrity, transactions, and consistency becomes extremely challenging. Things like two-phase commits, event sourcing, and API gateways may be required to avoid race conditions and keep data in sync across services.

Should you consider migrating to a microservice architecture?

Here are a few signals indicating microservices suitability:

✔ ️ Applications are struggling under large-scale monolithic loads.

✔ ️Significant complexity is limiting developer velocity.

✔ ️ Codebase has grown unmanageable, inhibiting feature delivery.

✔ ️ Business is seeking cost-efficient scalability.

If these factors apply, a gradual migration to microservices could be advantageous. But simpler apps may not benefit as greatly with increased intricacy. So an incremental transition focused on most impacted areas first allows evaluating gains for long-term plans.

How can Kong help?

Kong is an open source API gateway and service mesh that can help organizations migrate to a microservices architecture by providing solutions to some of the key challenges like splitting monoliths, service discovery and more! Kong Gateway provides critical infrastructure capabilities like an API gateway, service mesh and service control platform designed for cloud-native microservices. Kong solves several key operational and architectural challenges organizations face in adopting microservices at scale. Its platform significantly reduces migration complexity, cost and risk!