My team is loving building applications on the cloud and scaling them. Some of the best practices that we implemented in the last few cloud projects are as follows:
1. Infrastructure as Code: It is imperative that you develop automation to build-up and tear-down your complete application infrastructure with just a click of a button. This includes provisioning data services such as RDBMS database, NoSQL data store and populating the data-stores with data. Follow this by deployment of your docker containers containing your web apps/microservices - all managed by Kubernetes. Then finally run a few synthetic transactions to validate the complete setup.
In one of our projects, we could build-up and tear-down the complete pre-prod environment using automation scripts.
2. Stateless Services: In order to have seamless elastic scalability on the cloud, it is important to design your services to be completely stateless. Any state that needs to be saved, should be done in an external store. We have successfully used Redis as the store for many stateful applications or sharing data across microservices.
3. Circuit Breakers and Graceful Degradation: Make sure that service calls happen through a circuit breaker (e.g. Netflix Hystrix). This prevents overloading any system component in the event of a partial failure. Put in mechanisms for graceful degradation where ever possible - e.g. return data from a cache if database is down. Such measures avoid cascading failures.
4. Rolling updates and Canary Deployments: Kubernetes also supports a rolling update, so your downtime is reduced during service updates. Also canary deployments reduce the risk of introducing new features with faster GTM.
5. Autoscaling: Automate for elastic scalability - e.g. if a microservice is running on 4 containers, you should be able to scale-up and scale-down by a click of a button.
6. Redundancy / High Availability: Make sure that all your infrastructure services that are available as managed services on the cloud have redundancy across geographies built in - data stores, messaging middleware, noSQL stores, etc. Make sure that your services are also deployed in a redundant manner across data centers.
1. Infrastructure as Code: It is imperative that you develop automation to build-up and tear-down your complete application infrastructure with just a click of a button. This includes provisioning data services such as RDBMS database, NoSQL data store and populating the data-stores with data. Follow this by deployment of your docker containers containing your web apps/microservices - all managed by Kubernetes. Then finally run a few synthetic transactions to validate the complete setup.
In one of our projects, we could build-up and tear-down the complete pre-prod environment using automation scripts.
2. Stateless Services: In order to have seamless elastic scalability on the cloud, it is important to design your services to be completely stateless. Any state that needs to be saved, should be done in an external store. We have successfully used Redis as the store for many stateful applications or sharing data across microservices.
3. Circuit Breakers and Graceful Degradation: Make sure that service calls happen through a circuit breaker (e.g. Netflix Hystrix). This prevents overloading any system component in the event of a partial failure. Put in mechanisms for graceful degradation where ever possible - e.g. return data from a cache if database is down. Such measures avoid cascading failures.
4. Rolling updates and Canary Deployments: Kubernetes also supports a rolling update, so your downtime is reduced during service updates. Also canary deployments reduce the risk of introducing new features with faster GTM.
5. Autoscaling: Automate for elastic scalability - e.g. if a microservice is running on 4 containers, you should be able to scale-up and scale-down by a click of a button.
6. Redundancy / High Availability: Make sure that all your infrastructure services that are available as managed services on the cloud have redundancy across geographies built in - data stores, messaging middleware, noSQL stores, etc. Make sure that your services are also deployed in a redundant manner across data centers.