HomeDevelopmentAgileThe various functions of a service mesh in cloud native systems

The various functions of a service mesh in cloud native systems

Today, with the rise of microservices, most organizations struggle to keep up with the increased complexity of their mission-critical workloads. While orchestration tools like Kubernetes help with the creation, management, and decommissioning of containers, they don’t aid teams in managing traffic between various services. When teams build new services, they must do additional work to add the business logic into each service. Doing so leads to the services becoming tightly coupled, thereby limiting reusability. Reusability is one of the most sought-after features of microservices, and without that, teams are left with a distributed monolith.

The need for a service mesh

A service mesh helps teams manage east-west traffic inside their workloads and helps implement policies to make their services independent and secure. Service mesh consists of two components, a data plane, and a control plane. The data plane aids with the transportation of packets to and from each service via a proxy. This is done by running a process alongside each service as a sidecar. On the other hand, the control plane helps teams control this traffic and apply policies conditionally or globally via a single console. Service mesh also helps teams by arming them with a catalog of impressive features that help them take control of their workloads like never before.

An ideal service mesh will help with connectivity by letting teams route traffic efficiently and conditionally split it. Teams can also use a service mesh for service discovery and perform canary releases to carefully deliver updates to the userbase. Teams can also ensure reliability inside their workloads through features like circuit breaking and chaos testing. Security is a vital feature of the service mesh. With mutual TLS, certificate management, user authorization/ authentication, and encryption, teams can ensure their services and the overall workload are safe from any attacks. Teams can also use metrics like success rate, request volume, and latencies to configure load balancing algorithms and plug these metrics into a visualization tool of their choice for observability and monitoring.

Service mesh use cases

Service meshes are incredibly vital for distributed applications and find their implementation in various use cases. Teams can get a lot out of the right service mesh.

Service discovery and traffic management

Services inside a distributed application are dynamic in nature, which means they are assigned dynamic network locations that keep changing due to autoscaling, failures, and upgrades. A service mesh helps discover these services dynamically so they can be invoked when needed.

Traffic management allows teams to perform tasks like traffic shadowing, which helps them duplicate traffic and perform tests on their workloads. Traffic splitting is another essential feature teams can leverage to perform canary releases of updates and test these releases with a fraction of their userbase. Teams can also use the traffic splitting functionality to perform A/B type experimentation.

Inter-service communication reliability

Services communicate with each other to perform business-specific tasks. However, in a microservices-based system, with hundreds of services, many factors can be responsible for the failure of inter-service communication, impacting business. Service meshes help make inter-service communication reliable through various features. Teams can enable request retries and timeouts to ensure communication isn’t halted due to congestion. Features like rate-limiting allow operators to limit the number of calls to a service to avoid congestion. While circuit-breaking ensures network issues in one service aren’t cascaded to other services in the application.


Distributed applications can become harder to observe as their size grows. As the service mesh data plane acts as a gateway for all requests to and from each service, operators can use it to fetch important metrics like success rates, frequency of HTTP error codes, latency, and distributed telemetry. Using these quantifiable metrics, operators can properly view traffic flows inside their workloads.


Services communicating with each other pass critical data back and forth to perform specified tasks. Malicious actors can easily intercept exposed data. To protect communication between services, service meshes provide features like encryption and mTLS. With the help of efficient certificate management, operators can rest assured that communication between services is secure. With user authentication and authorization, operators can ensure that the services are accessible only by verified actors. Operators can also enable access control lists to assign proper roles to different individuals.

Picking the right service mesh

Picking the right service mesh

There are various service mesh solutions available in the market that organizations can choose from. However, it can be a time-consuming process to pick the right solution. A lot is happening in the service mesh space, and all the tools are constantly innovating. It’s tough to keep up with these developments to make the right decision. Tools like Istio and Linkerd are pretty popular. However, organizations should also consider other tools like Kuma, Consul, NGINX Service Mesh, and Kong, among many others. Making the right decision can take some time, but it’s better than picking a solution in haste and having to redo everything in the future. Demos and documentation are available for each service mesh online, which can be referred to before making an informed decision.

The future of service mesh

The innovation in the service mesh space is swift. There is a lot to look forward to, with hordes of new service mesh projects being developed. Several multi-cloud, multi-cluster, and multi-tenant service mesh solutions are in the works that will help expand service mesh to various platforms, so operators don’t have to manage a separate service mesh for different infrastructures. Chaos Mesh, a CNCF project, is another variation of service mesh that allows teams to perform chaos engineering experiments on their workloads using fault injections. Media Service Mesh, a project developed by Cisco, uses service mesh capabilities of load-balancing and observability and finds applications in streaming, gaming, video conferencing, and CCTV surveillance.

The future seems bright for the service mesh landscape, and it’s going to be exciting to witness innovations and new service mesh practices.

If you have questions related to this topic, feel free to book a meeting with one of our solutions experts, mail to sales@amazic.com.


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