Follow the request/data flow through the architecture.
Work through each concept and mark it understood. This unlocks the knowledge check.
Fully managed serverless NoSQL key-value/document database.
Why it matters
Single-digit-millisecond latency at any scale with no servers.
When to use it
Use for known access patterns at high scale. Avoid for ad-hoc analytical queries (use Athena/Redshift).
Example
table.put_item(Item={
"pk": "USER#42", "sk": "PROFILE",
"name": "Ada", "plan": "pro"
}) # design around access patterns, not normalized tablesGotcha (exam trap)
You model around access patterns, not relations. A poor partition key creates "hot partitions" that throttle.
A realistic main.tf for this mission. Read it top to bottom — it mirrors the concepts above.
# Carbon Credit Ledger: Database or Blockchain?
# BleepxCloud — ESG · Intermediate
# Realistic starter — adapt names, regions and CIDRs to your environment.
terraform {
required_providers { aws = { source = "hashicorp/aws", version = "~> 5.0" } }
}
provider "aws" {
region = "eu-west-1" # pick a region close to users / data-residency rules
}
# FinOps: mandatory cost-allocation tags on every resource.
locals {
common_tags = {
Project = "bleepx-cloud"
Domain = "esg"
Mission = "carbon-ledger"
ManagedBy = "terraform"
CostCenter = "REPLACE_ME"
}
}
data "aws_caller_identity" "current" {}
# Single-table design with on-demand billing and a GSI.
resource "aws_dynamodb_table" "app" {
name = "bleepx-app"
billing_mode = "PAY_PER_REQUEST" # no capacity planning
hash_key = "pk"
range_key = "sk"
attribute { name = "pk"; type = "S" }
attribute { name = "sk"; type = "S" }
attribute { name = "gsi1pk"; type = "S" }
global_secondary_index {
name = "gsi1"
hash_key = "gsi1pk"
projection_type = "ALL"
}
point_in_time_recovery { enabled = true }
}
Finish the walkthrough above to unlock the check.
Bleepx skills build on each other. Continue your learning path across Query, Lab, and Cloud.