Since the aim is to launch the cluster into a VPC (providing the network isolation we need to keep the cluster from being accessed over the internet), you’ll define the VPC first, then define a private subnet within it, and then finally designate a Redshift subnet group to tell AWS where to provision the cluster: Next, define a new VPC and the associated network resources for the Redshift cluster. require ( "region" ) # Create an S3 bucket to store some raw data. Config ( "aws" ) aws_region = provider_config. require_secret ( "clusterDBPassword" ) # Import the provider's configuration settings. require ( "clusterDBUsername" ) cluster_db_password = config. require ( "clusterDBName" ) cluster_db_username = config. require ( "clusterNodeType" ) cluster_db_name = config. require ( "clusterIdentifier" ) cluster_node_type = config. Import json import pulumi from pulumi_aws import ec2, iam, redshift, s3 # Import the stack's configuration settings. (And if you haven’t already, make sure you’ve installed Pulumi and configured your AWS credentials in the usual way.) We’ll begin, as always, by creating a new Pulumi project. We’ll load this data manually at first, just to get a sense of how everything works when it’s all wired up, and then later, in a follow-up post, we’ll go a step further and weave in some automation to load the data on a schedule. Specifically, we’re going to walk through the process of writing a Pulumi program that provisions a single-node Redshift cluster in an Amazon VPC, then we’ll load some sample data into the warehouse from Amazon S3. Today, though, we’re going to focus on Amazon Redshift. Examples of data-warehouse products include Snowflake, Google BigQuery, Azure Synapse Analytics, and Amazon Redshift - all of which, incidentally, are easily managed with Pulumi. Unlike general-purpose databases like MySQL or PostgreSQL, which are designed to meet the real-time performance and transactional needs of applications, a data warehouse is designed to collect and process the data produced by those applications, collectively and over time, to help you gain insight from it. And for that, you might want to consider a data warehouse.Ī data warehouse is a specialized database that’s purpose built for gathering and analyzing data. That data will likely exist in many forms and in multiple places - flat file here, transactional database there, the REST API of some third-party service - so before you can really look at it, you’ll need to figure out how to get it all into one place. But even so, there’s a good chance whatever system you’re building can and will produce useful data of its own, and there’s an equally good chance you’ll want to learn something from it. Of course, the volume of data you care about is probably a lot more modest. That’s a lot of data - and there’s more every day. If you could pull all that data into an HD movie, and you sat down to start watching that movie 2.5 million years ago (with your favorite saber-toothed friend, say), you’d still be watching the same movie today. If you could store all that data on 3.5" floppies, you’d need more than a hundred quadrillion floppies to capture it all - enough to cover the planet entirely (with much room for overlap) or to pave a nice bridge for yourself from your front porch well into interstellar space. If you could convert all the world’s data into droplets of water, for instance, at one megabyte per drop, you’d have enough 1MB drops to fill two more Lake Washingtons. However you choose to measure it (and there are various ways), it’s a quantity so massive - hundreds of zettabytes, by some estimates - that it’s kind of a hard thing to quite get your head around. It’s fun to think about how much data there is swirling around in the global datasphere these days. Pulumi Resource Search: Find the Needle in the Haystack.Leveling up Pulumi AI with the Pulumi Registry.Iac Recommended Practices: RBAC and Security.Announcing the Speaker Lineup for PulumiUP 2023.Pulumi Release Notes: Resource Search, Deployment Actions, Projects in Self-Managed Backends, and more.Announcing Slack and Deployment Notifications for Pulumi Cloud.Announcing OIDC Support for Pulumi Azure Providers.Converting Full Terraform Programs to Pulumi.Enhanced search & Navigation: The new Pulumi Docs experience.
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