After an initial wave of enthusiasm, many developers are now gradually becoming disillusioned with working with microservices architectures. Although microservices continue to offer significant advantages, such as faster delivery, better scalability, and greater independence from specific technologies, considerable challenges have also emerged. Unlike monolithic architectures, where all components are closely intertwined, microservices form a distributed system. This decentralization makes it difficult to monitor, control, and comprehensively secure the individual services. Furthermore, communication between microservices takes place over the network, which can not only impair speed but also potentially jeopardize the stability of the entire system.
Despite these complex challenges, microservices remain popular, suggesting that their benefits often outweigh the difficulties they present. To reduce the complexity of microservice architectures, the concept of a service mesh is becoming increasingly important.
But what exactly is a service mesh, why and when should it be used, and could it have a lasting impact on the future of microservices architecture? Our Xperts address precisely these questions in our two-part blog series.
In the first part, our experts take a look at the challenges of microservice architectures and explore how a service mesh can help address them. We explain the basics of this infrastructure layer and introduce the most common implementations.
Challenges of Microservices
For developers, it’s often natural to tackle technical challenges using a consistent framework. However, a microservices framework has the drawback that it typically supports only a specific programming language. This limits the selection of technologies that can be used to implement the microservices. As a result, a key advantage of microservices—technological freedom—is lost. This freedom makes it possible to choose the most suitable technology for each microservice. For example, if a different programming language or technology stack is better suited for a specific problem, it can be used without any issues in the respective microservice. However, if the framework being used is not compatible with the new programming language or technology stack, this flexibility is severely limited or even impossible.
Microservices Without Libraries
Even within a unified technology stack, technology freedom offers significant advantages. Sooner or later, every technology becomes obsolete and thus poses a risk or becomes completely unusable. Microservices architectures make it possible to first test an upgrade to a new version of the technology stack or a library within a single microservice. This not only reduces risk but also makes the gradual modernization of a system much easier. However, if the microservices framework is not compatible with the new version of the technology stack or library, the update becomes significantly more difficult or may even be completely blocked.
Microservices Using Libraries
Using different libraries in a large and complex microservices architecture can have several problematic consequences:
- Incompatibility and Inconsistency: Libraries may have different versions, APIs, and configuration requirements. If different microservices are incompatible with each other or with the underlying infrastructure, this often leads to inconsistencies. Differences in error handling, logging methods, or security practices across libraries can lead to unpredictable system behavior and bugs that are difficult to track down.
- Maintenance Effort and Technical Debt: Maintaining and updating a large number of libraries significantly increases the maintenance burden. Each library must be managed separately and updated regularly to fix security vulnerabilities and integrate new features. This can quickly lead to technical debt, especially when libraries become outdated or are no longer maintained.
One possible solution to all these problems is the use of a service mesh.
Why Use a Service Mesh? An Introduction to Service Meshes
Microservices that use a service mesh can do without many libraries that were previously required, such as those for monitoring, tracing, and circuit breaking. A service mesh shifts these and other functions from the application layer to the infrastructure.
Using a Service Mesh (Offloading to Sidecars)
It is not the first concept to pursue this strategy, but it is the first to integrate seamlessly with the decentralized nature of a microservices architecture. While other solutions, such as API gateways, rely on centralized components, a service mesh pairs each microservice instance with an additional application that implements functions such as monitoring and circuit breaking. This additional application communicates with the microservice instance via localhost—an approach known as a „sidecar.“ All incoming and outgoing traffic for the microservice application is routed through this sidecar application, which is also referred to as a service proxy. To automatically route traffic to the service proxies, network configurations are adjusted so that the microservices themselves remain unchanged.
Components of a Service Mesh (Source: Istio)
Service Mesh Implementations
There are numerous service mesh implementations that differ in terms of functionality, architecture, and supported platforms. Among the best-known and most widely used are:
- Istio is one of the best-known and most widely used service mesh implementations. Developed by Google, IBM, and Lyft, Istio offers a comprehensive solution for managing microservice communication. Istio uses sidecar proxies to manage communication between microservices and provides an extensive API for controlling and monitoring traffic.
- Linkerd is another popular service mesh originally developed by Buoyant. It is known for its ease of use and simple implementation. Linkerd stands out for its straightforward configuration and low overhead, making it a popular choice for small and medium-sized deployments.
- Consul Connect is a service mesh solution offered as part of HashiCorp's Consul platform. Consul Connect is tightly integrated with the Consul platform, which also includes service discovery and configuration management.
- AWS App Mesh is a service mesh solution offered by Amazon Web Services that was developed specifically for AWS environments. AWS App Mesh is particularly useful for companies that are heavily integrated with the AWS cloud.
- Kuma is a service mesh developed by Kong Inc. that can be used in both Kubernetes and other environments. Kuma places a strong emphasis on simplicity and scalability and offers user-friendly configuration.
In the next part of our series, we’ll explore the key features of a service mesh, including monitoring, resilience, routing, and security aspects. At the same time, we’ll also address the challenges associated with implementation. These include, in particular, the steep learning curve, the associated costs, increased latency, and resource requirements. Our experts will provide valuable insights into how these challenges can be overcome.
