What is Terraform?
Who uses Terraform?
Here are some stack decisions, common use cases and reviews by companies and developers who chose Terraform in their tech stack.
We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).
We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .
Read the blog post to go more in depth.
Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.
Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!
Check Out My Architecture: CLICK ME
Check out the GitHub repo attached
We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.
To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas
To build #Webapps we decided to use Angular 2 with RxJS
#Devops - GitHub , Travis CI , Terraform , Docker , Serverless
Terraform Preferred for infrastructure-as-code (IAC), deploying infrastructure to AWS.
Hi, I am building an enhanced web-conferencing app that will have a voice/video call, live chats, live notifications, live discussions, screen sharing, etc features. Ref: Zoom.
I need advise finalizing the tech stack for this app. I am considering below tech stack:
- Frontend: React
- Backend: Node.js
- Database: MongoDB
- IAAS: #AWS
- Containers & Orchestration: Docker / Kubernetes
- DevOps: GitLab, Terraform
- Brokers: Redis / RabbitMQ
I need advice at the platform level as to what could be considered to support concurrent video streaming seamlessly.
Also, please suggest what could be a better tech stack for my app?
#SAAS #VideoConferencing #WebAndVideoConferencing #zoom #stack
We use both these tools and are relatively new to them. We have a few questions:
- With Terraform, how are you handling changes done outside of Terraform in the Infrastructure?
- Are there any limitations or features that we miss in Ansible that Terraform can do? What are those?
- Infrastructure as Code: Infrastructure is described using a high-level configuration syntax. This allows a blueprint of your datacenter to be versioned and treated as you would any other code. Additionally, infrastructure can be shared and re-used.
- Execution Plans: Terraform has a "planning" step where it generates an execution plan. The execution plan shows what Terraform will do when you call apply. This lets you avoid any surprises when Terraform manipulates infrastructure.
- Resource Graph: Terraform builds a graph of all your resources, and parallelizes the creation and modification of any non-dependent resources. Because of this, Terraform builds infrastructure as efficiently as possible, and operators get insight into dependencies in their infrastructure.
- Change Automation: Complex changesets can be applied to your infrastructure with minimal human interaction. With the previously mentioned execution plan and resource graph, you know exactly what Terraform will change and in what order, avoiding many possible human errors