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How you can Improve Latency in Microservices

By Unni Mohan Nov. 22, 2022, 3:51 p.m. Application development company
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Scaling microservices in a cloud-native environment

Modern microservices systems are packaged as small container images, then deployed to clusters, updated when required, and scaled independently.


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Different parts of the system can affect the latency of microservices,and they are hardware, application, network transit, etc.


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How you can Improve Latency in Microservices

Microservices are typically used in large organizations that have complex applications. This architecture model helps to increase business agility and enables software development and deployment to become faster. However, microservices latency gives rise to challenges that prevent organizations from reaping the many benefits that microservices have to offer.

For a distributed Services environment, some challenges have to be addressed carefully:

  • A mature DevOps practice in the organization should be in place
  • Environment provisioning should be available whenever required and be very quick
  • Automation is required at all places in the test, build and deployment areas
  • Applications have to be designed so that they can work in distributed environments
  • Applications have to be designed for resiliency in changing load conditions and for failures
  • Applications and data should be refactored properly to suit microservices 
  • Remote calls will serve to introduce latency and slow down response times

Microservices Advantages

Microservices are nothing but applications running as different services, each of them capable of performing a specific function, developed and deployed independently by different teams. Whereas one service would handle user inputs, another would be used to generate reports. 

This is a clear departure from monolithic architecture where the entire application exists in a large codebase. Any small change to be brought about requires restructuring the entire codebase. This requires spending time, planning, and resources, every single time. 

Whereas scaling with monolithic architectures models is difficult, in microservices, only the required services are scaled by adding more containerized instances of these services. This superior agility that microservices offer has prompted large and geographically spread enterprises to take to this architecture model and smoothen their operations. 

Read our blog “Microservices architecture and distributed tracing”.

Latency Challenges

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However, many organizations do not realize that microservices also have inherent challenges with latency. Let us see where the latency stems from. Microservices are capable of running many functions in tandem and many components run in different places. Any network delay, therefore, can affect the response times adversely. 

Individual services may be simultaneously used by several applications at the same time. This means that these applications have to be able to find the services. To facilitate this, there is an Application Performance Interface (API) that helps to link the applications to the services that are required. 

These delays also have to be controlled for proper scalability. Scaling microservices involves introducing new instances of the required components in various locations. Load balancing solutions then distribute the loads across these instances. However, having load balancing in a single location while multiple instances appear at different places also creates additional latency. 

Running Microservices at the edge

Running microservices at the periphery or the edge of the services helps to reduce latency. This means removing the data processing from the central core and placing it as close as possible to the end users. When data is processed at a place that is close to the origination, then round-trip latencies are reduced to a large extent. This also helps to significantly increase scalability and flexibility. Load balancing also takes a fillip because of shorter network paths and improved data relay paths. Microservices without latency issues can function at high speeds. Development and deployment speeds are also optimized. 

Ultra-low latency data can be made possible with modern colocation data centers facilitating high-speed data transmission between application services. 

Download our eBook for FREE “MICROSERVICES- A Short Guide”.

Looking for the best microservices vendor? Give us a call today.

Making Data Representations

As the very idea behind microservices is to provide speedy responses, data dependencies have to be at a minimum. Services in a system cooperate via communication. They send messages to one another using either asynchronous/synchronous protocols as part of notifications, commands, or both. Additionally, a service may also rely on a persistence mechanism to store data for later retrieval. Either way, data has to be assembled and arranged to and from a representation that may be outside of the main memory. However, this can be understood by the collaborating services.

Explicit coupling is easier to understand. However, you cannot call this data if the service moves to a different location or it goes down. The effects of implicit data coupling, on the other hand, are harder to see and understand. A service may change its data format and another service may not be prepared to receive this. This may also fail only on some requests. These are hard to spot. 

To overcome these issues, you may have to settle for a technology not built into the language that you are using. Using JSON and XML and binary formats such as protocol buffers (Apache Thrift and Apache Avro) are some solutions. 

Preserving data compatibilities

Newer code, because of changes, should be able to recognize and deal with data formats that were associated with the older code. Moreover, older versions should still work even with newer versions. Both forward and backward compatibilities have to be maintained. 

Moreover, when the caretakers or maintainers of the services change, it is important to explicitly list the dependencies so that they can easily maintain the forward and backward compatibilities.

Conclusion

Thus a microservices architecture model is an evolving setup that will help you deliver value to your customers only through feedback, experimentation, and iteration. Therefore it is important to stay focused and optimize your microservices system for speed.

Do you want to migrate to microservices? Talk to us today!

Why choose SayOne for microservices development

At Sayone, we design and implement microservices systems that do not have complex architectural layers, and this enables the services to deliver exceptionally fast performance. Moreover, we provide services that are significantly decoupled, allowing you to launch independent services and not end up with the usual inter-dependent microservices that work more or less like a monolith.

 We design the microservices keeping in mind the margin required to allow for the transitioning into the new system of your organization’s legacy architecture as well as expanding into the cloud system. Our microservices comprise lightweight code and we provide competitive pricing options for our clients.

 Our microservices are built according to the latest international security guidelines that ensure complete safety of all the data. We also ensure that we deliver the services within stipulated deadlines and we always assure a quick turnaround time for our clients. Equipped with the best infrastructure and the latest tools and technologies, our expert developers will provide you with the best microservices that are easily scalable, enabling a good ROI in the shortest period of time.

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