Monolithic applications and workloads have become a thing of the past. Today, most organizations are either running microservices-based workloads in production or at the very least experimenting with it. There are numerous benefits of a distributed architecture. Organizations can now deliver software faster, migrate easily, and enjoy the benefits of genuinely cloud-native architecture. However, as applications grow and the number of services increase, it can become highly challenging to manage service-to-service communication. Distributed workloads can become highly complex and can start to feel like a cage you’re building if you don’t use tools to manage them. A service mesh does just that. A service mesh manages service-to-service communication and helps build more reliable applications.
What is a service mesh?
When you have so many ephemeral services that communicate with each other to perform specific tasks, you need a way to manage traffic. Services might fail when they don’t get a response from another service due to congestion or other reasons. A service mesh forms an infrastructure layer inside your workloads and helps manage requests between different services. Without a service mesh, developers will have no other choice but to write communication logic inside each service, which can take a lot of time and effort. This can distract developers from actual development and lead to slower delivery. A service mesh is exceptionally vital for any microservice-based application. Sidecars are proxies that run alongside each service and constitute a service mesh. These sidecars take care of all the communication logic while letting services written by different teams in different programming languages do their specific tasks.
Sidecars are proxies that can be plugged into services and handle requests to and from the service they are attached to, thereby encapsulating the communication logic from the services. A service mesh is not a mesh of services; it is a mesh of these sidecars. The collection of all the sidecars in a mesh constitutes the data plane. A service mesh also helps you configure your proxies, configuring your entire mesh through the control plane component. The control plane collects metrics from all the proxies regarding traffic, downtime, invalid requests and allows you to make configurations that avoid any hassle at runtime.
Why do you need a service mesh?
Most organizations trying to adopt microservices tend not to factor in the complexity of inter-service communication. This is because, in traditional monolithic workloads, networking wasn’t something you worried about till the very end when you had to bring together all three tiers (application logic, storage logic, and the web-serving logic). Since the applications were monoliths, networking could be imbued easily inside the code at later stages. However, in the cloud-native landscape, things are pretty different. When you create a microservices-based application, you need to leverage a container orchestration tool like Kubernetes and additional tools to help monitor the cluster and containers. Sometimes, organizations might just leave out the service mesh, thinking Kubernetes will handle everything. However, Kubernetes can orchestrate and create containers and resources; it cannot orchestrate inter container communication. By the time this realization hits, it’s too late.
Containers are created and destroyed based on how the workload is supposed to run. This makes service-to-service communication super complicated. When a service sends a request to another service that isn’t yet available, has been destroyed, or just isn’t reachable because of bottlenecks, the application breaks. Hence there is a need for a layer that handles all of the networking requirements of an application. That is what a service mesh does.
Make your applications more reliable
A service mesh helps organizations build applications they can have a hundred percent faith in. With service mesh, your workloads will be resilient, secure, and always available. Let’s look at some ways a service mesh helps with that.
To ensure your application is reliable, you need to make sure you have eyes on what is happening inside your application at all times. It becomes harder to monitor microservices and how they interact with each other when your workload consists of hundreds of services. Fret not, however, since a service mesh helps you monitor interservice communications by capturing the telemetry metrics and storing them in the control plane. The services are treated as blackboxes, and information like the URL, protocol, source, destination, duration, status, and latency are captured. These metrics can then visualize this information via a visualization tool of your choice. Tracing can also be done; however, you must configure every service to read the tracing header with every input and forward it to other services.
Traffic control is crucial in distributed workloads. Some services are bound to be requested more often, and that can run a risk of downtime. Service meshes provide destination-based traffic control, which means they can control calls to a service from multiple sources, but not the other way around. Service meshes support latency-based load balancing, also referred to as intelligent load balancing. This is done by the control plane that configures the data plane. Many service meshes allow developers to implement resiliency patterns like retries, timeout, circuit breaking, A/B releases, and canary releases. You can set a timeout for requests and trigger a circuit breaker when a service doesn’t respond in the given time. This way, you can keep your request open until the service becomes available again. You can also enforce quotas on the clients requesting certain services quite often to ensure other clients aren’t refrained from accessing the service when they need it.
Your application cannot be reliable if it isn’t secure. Distributed applications offer a large attack surface are because of the sheer amount of services involved. A malicious or rogue service can easily slip into your workload and wreak havoc. Service meshes like Istio help secure services and their data by creating, revolving, and managing certificates. These certificates help services identify and verify other services requesting to communicate with them. Additionally, you can also enforce mTLS to create encrypted channels between services for secure communication.
Service meshes are incredibly important and help your applications be resilient and more reliable. Organizations looking to migrate their workloads to microservices should not have myopic vision, and should implement the appropriate service mesh from the very beginning.
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