Do we really need to use microservices and containers together? Do they really compliment each other? Let’s try to understand the relation between the two.
Microservices basically split your application into multiple services that perform specific functions that are a part of your application as a whole. Each microservice will ideally have a different logical function for your app. This is a more modern approach when compared to the old monolithic architecture.
As evident in the diagram above, monolithic applications are cumbersome and hard to develop fast. Benefits of using microservices include:
- Developers work on a smaller codebase compared to a larger one in monolithic apps. Developers can easily understand the source code, something that speeds up development. There is also no need to deal with the complexities and dependencies of functions of monolithic apps.
- Responsibilities of the developers are better defined. A team can be assigned by components or microservices of the app. Code reviews are much faster and accurate. Updates become quicker and there is no need to build and deploy everything like required by monolithic apps
- The application’s technology stack can be more versatile with microservices, which is becoming a requirement in today’s dynamic space. The app doesn’t depend on one language or library. Microservices can leverage different programming languages as required.
- Continuous Delivery becomes easier. Compared to monolithic apps you simply don’t need to deploy everything again for a simple change. You can only rebuild and deploy the specific microservice that needs to be updated. Frequent updates are faster with less errors.
- Scalability will be independent to each microservice. You can choose to scale each component of your app depending on the resources it needs, without making multiple instances of everything. Scaling the microservices efficiently uses the resources available.
Despite the aforementioned advantages of implementing microservices and transforming your ecosystem, there can be some challenges while doing so.
- Services distributed across multiple hosts can become hard to track and monitor. Rather than a single stop to tweak monolithic apps, collaborating microservices scattered throughout your environment need to be inventoried, documented, and quickly accessible.
- There is also a scaling challenge. Each microservice consumes far less resources than monolithic applications, but the number of microservices in production will grow rapidly as your architecture scales. Without proper management, you can find yourself in trouble during peak times.
- Inefficient minimal resourcing can also become a problem as there is a bottom limit to the resources you can assign to any task (for example, with Amazing Web Services). Microservices may require only a portion of a minimal EC2 instance, resulting in wasted resources and costs.
Furthermore, microservices can be developed in a wide array of programming languages. However, these multiple programming languages in play will require a completely different set of libraries and frameworks. This grows resource overhead (and costs), and makes deployment a complex consideration.
As mentioned earlier, picking containers while implementing microservices is becoming more and more common. The top three reasons are as follows.
Runtime Options – Containers encapsulate a lightweight runtime environment for your app, presenting a consistent software environment that can follow the application from the developer’s desktop, via testing, all the way to the final production deployment. Also, containers can run on physical or VMs.
Better Execution Environments – Containers perform execution isolation at the operating system level. A single operating system instance can support multiple containers, each running within its own, separate execution environment. This reduces overhead and frees up processing power for your app components.
Optimal Component Cohabitation – Containers enable multiple execution environments to exist on a single OS instance. The implications of this can be subtle, because app characteristics vary. But by being clever with workload placement, container users can maximize server resource utilization levels.
There is also the performance aspect. Let’s compare containers to VMs. Containers are small, perhaps one hundredth the size of VMs.
Because they do not require the operating system spin-up time associated with VMs, containers are more efficient at initialization. Overall, containers start in seconds, or even milliseconds in some cases. That’s much faster. That’s why containers are a better execution foundation for microservices architectures.
Now that we have established that containerization is the natural successor to virtualization, it’s important to understand the importance of automation.
The microservices methodology was devised to encourage and enable rapid deployment of discrete software functionality to cater to the growing needs of the consumer requirements. Unfortunately, having a complex ecosystem of microservices can complicate your infrastructure, especially while scaling up.
Only a comprehensive database management solution can allow you to monitor all changes in real-time and allow you to respond to events as they happen. Not doing so will almost certainly result in lack of visibility, version mayhem, and eventually a product that cannot be tested properly prior to release.
The microservice architecture, when used in tandem with containers, offers flexibility that a monolithic architecture can’t. However, having this kind of ecosystem can result in a wide range of problems when not monitored properly. This is where database automation and management solutions enter the picture.
A comprehensive automated solution, with in-depth reporting, tracking, and customization capabilities, is a natural ally of microservices and containers.