How to Manage a Cloud App Deployment

Today, application delivery in the cloud is taken for granted. Whether you are using containers, microservices, or anything else, applications are always deployed in the cloud. This makes sense considering nearly all of our workloads are now based in the cloud. To ensure high availability and scalability, applications are frequently replicated across multiple data centers. While this sounds like a pain to manage, there are tools and best practices that can make this process much easier. In this blog post, we will share some of these tools and best practices, which can help you to manage your cloud app deployments.

Monitoring And Analytics

You might be in good company if you have heard of AWS CloudWatch. Created by Amazon, this service is a core part of the AWS ecosystem and is used by developers to monitor and troubleshoot their applications running in the cloud. Monitoring and analytics are vital to keep up with all of the changes in the industry and ensure that your
applications are ready to scale accordingly. CloudWatch can help with application monitoring and performance analysis, as well as log aggregation and visualisation. It provides data points around a variety of metrics, including memory usage, response times, network traffic, and much more.

Similarly, Google Cloud Platform provides a wide range of monitoring technologies that can help with the management of complex cloud deployments. These tools can help you to monitor your applications for errors, performance issues, and security breaches.

Replication And Backup

When we talk about managing the scalability and availability of applications in production, we normally think about data replication and backup. There is a lot of overlap between these technologies, and they can both be used to ensure that your application is always ready to go. While replication technologies like DRBD and Slony-I periodically replicate data across multiple servers, backup products like Amazon’s Glacier and Google’s Cloud Backup storage offer persisting storage for data at really great prices. This way, you can replicate the data exactly, as it was at one point in time. The only downside is that they require more maintenance and management than regular storage would.

Docker

Containers are a fantastic way to package and ship applications with the minimum amount of friction. They are also a great way to deploy applications in the cloud, as they enable you to package all of your sources (e.g. code, configuration files, and databases) into a portable image that can be deployed instantly. This is in contrast to traditional methods of deployment, which often require many steps and a lot of hands-on work. Using containers to deploy your applications in the cloud is easy and instantaneous; however, this comes with its own set of challenges. The first being that all of your applications must be packaged into a single image, which increases the size of the final application package. Second, since all of your applications are within the same container, they will share the same network namespace. This can lead to problems with application isolation and security. Third, the creation of these containers takes a bit of skill, and this is where using a tool like Docker can really help.

Docker makes it easy to spin up and manage containers on-demand, which can significantly reduce the workload and overhead that comes with doing this yourself. Additionally, Docker offers a CLI utility, dockerize, which makes it easy to convert any directory into a container. This can be a huge time-saver when compared to traditional methods of deployment.

Terraform

Terraform is a tool designed to make configuring complex cloud infrastructures easy. It was originally released by the HashiCorp team, but is now one of its own. Terraform offers a great deal of flexibility, as it can be used to provision almost any type of resource (e.g. server, database, load balancer, etc.). It also enables you to configure all of this through declarative YAML files, which significantly reduces the amount of code required to do this. The advantage of using Terraform is that, since it is declarative, you can rest assured that your configuration will remain and that you can always go back to it if required.

Cloud Formation

Cloud Formation was originally designed to make it easy to provision AWS resources through simple templates. It offers a graphical interface that makes defining and deploying AWS resources a breeze. Cloud Formation enables you to significantly reduce the amount of code required to do this. It also provides you with a history of all of the changes that you have made, which can be a time-saver when compared to manually creating and destroying these resources
hundreds of times. It’s a great tool for quickly setting up and managing infrastructure in the cloud.

Salt

Salt is another tool from HashiCorp that provides you with a set of highly-configurable functions that can be used to provision and manage various types of physical and virtual servers. It is designed to be efficient and it provides a set of functions that you can call to quickly deploy and manage your applications. Salt supports all of the things that we have discussed so far, as well as many more. It runs on AWS, Azure, and Google Cloud Platform, and can be used to create virtual machines, install and configure operating systems and applications, and a range of other tasks.

Salt has a fairly straightforward and intuitive user interface, which provides a decent amount of visual feedback and makes it easy to use. This tool can also be configured to run in parallel, which can help reduce provisioning times significantly.

Python

Python is a great language to learn, as it is used by developers to build some of the most popular applications in the world. This being said, deploying and managing a Python application in the cloud can be a bit challenging. It requires a different approach to what is normally required for a traditional LAMP stack. The first and most fundamental rule is to keep things light. You don’t want to burden the server with too much load, as it will impact both performance and scalability. Additionally, Python is not natively thread-safe, so making use of multiple processors or cores can help to mitigate this issue.

Database

Databases are vital to any computing environment, as they store all of the data that your applications work with. While it is possible to manually manage a traditional SQL Server installation, this can be a time-consuming and error-prone process. A much better option is to use a database as a service, like AWS RDS for MySQL and PostgreSQL. These databases are fully managed by AWS and require very little ongoing maintenance thanks to their auto-scaling
and high availability features.

Elastic Container Service

Elastic Container Service (ECS) is a container management service that was created by Amazon. It is designed to make it easy to run and manage containers on a variety of platforms, including AWS. ECS offers highly-scalable container-based workloads, as well as providing some native Kubernetes functionality, like scheduling, orchestrating, and rolling back operations.

To learn more, check out our guide to learn how to use ECS to deploy and manage your cloud apps.