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AWS Cloud Practitioner > AWS pt 0-1 > Flashcards

AWS pt 0-1 Flashcards

1
Q

RDS (Multi-AZ)

A
  • High availability
  • Non-Aurora: synchronus replication
  • Aurora: asynchronous replication
  • Always span at least two AZs within a single region
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2
Q

RDS (Multi-Region Deployments)

A
  • Main purpose is disaster recovery and local performance
  • Asynchronous replication
  • Each region can have a Multi-AZ deployment
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3
Q

Read Replicas

A
  • Main purpose is scalability
  • Asynchronus replication
  • Can be within an Availability zone, Cross-AZ, or Cross-Region
  • Up to 15
  • Writing is limited to the main DB
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4
Q

DynamoDB

A
  • key-value and document database delivers sub-millisecond performance at any scale
  • Serverless: No need for hardware provisioning, setup and configuration, throughput capacity planning, replication, sw patching or cluster scaling
  • integrated with IAM
    -Standard and infrequent Access
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5
Q

Security Shared Responsibility (customer)

A
  • Security ‘in’ the cloud
  • Platform, app, IAM
  • OS, Network and firewall config
  • Client side data, encrytption, data integrit yand authentication
  • Server-side encryption
  • Network traffic protection
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5
Q

Storage Gateway

A
  • File Gateway (store files as objects in S3)
  • Tape Gateway
  • Volume Gateway
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6
Q

Security shared responsibility (AWS)

A
  • SW: compute, storage, db, networking
  • HW/Global infra: Regions, AZ, edge lcoations
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7
Q

RDS

A
  • (OLTP)
  • Managed DB: cannot ssh into your instance
  • Automated provisioning, OS patching
  • Auto-backups = Restoring to a specific timestamp
  • Storage backed by EBS
  • Scalable
  • Deployments (Create a snapshot of your DB -> Transfer into a different AZ)
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8
Q

Amazon Aurora

A
  • SQL
  • Storage auto grows in increments from 10 GB to 128 TB
  • Costs more than RDS
  • Automated Aurora Serverless:
    • DB instantiation & auto-scaling based on usage
    • SQL work in Aurora serverless
      -No capacity planning/ Least managemet overhead
    • Pay per second
    • Good for infrequent or unpredictable workloads
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9
Q

Amazon Elasticache

A
  • Get managed Redis or Memcached
  • Load off db for intensive workloads -> lower latency = high performance
  • EC2 will read and write from cache if faster than RDS
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10
Q

Redshift

A
  • Online analytical processing
  • Load every hour
  • Highly available: Massively parallel query execution
  • Pay as you go: Based on instance provisional
  • SQL interface
  • Redshift Serverless:
    • Auto provisions + scales Data warehousing
    • Pay for what you use
    • Use cases: Reporting dashboards, real time analysis
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11
Q

Amazon EMR

A
  • Hadoop Clusters (Big data) analysis: Use hundreds of EC2 instances (Apache Spark)
  • Provisions and configures these EC2 instances
  • Auto-scaling and integrated with spot instances
  • Data processing, ML, web-indexing and big data
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12
Q

Amazon Athena

A
  • Analyze data in S3 using Serverless SQL
  • BI, analytics, reporting, ELB logs, cloudtrail Logs
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13
Q

Amazon Quicksight

A
  • serverless, ML powered for interactive dashboards
  • Fast, auto scalable, embeddable, with pre-session pricing
  • Building visualizations, ad-hoc analysis, business insight with data
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14
Q

DocumentDB

A
  • MongoDB
  • Json data
  • Fully managed, highly available, replication across 3 AZs
  • Storage auto-grows in increments of 10 GB
  • Auto scales to millions of requests
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15
Q

DynamoDB accelerator

A
  • DynamoDB version of Elasticache
16
Q

DynamoDB global tables

A
  • low-latency active-active replication
17
Q

Neptune

A
  • Fully managed Graph database
  • Replication across 3 AZs
  • Run applications with highly connected datasets
  • Social networks, fraud detection, recommendations
18
Q

Timestreams

A
  • Time series data
  • Auto-scales according to capacity
19
Q

QLDB

A
  • Ledger
  • Fully managed, serverless
  • Highly available, replication across 3 AZ
  • Review history of all the changes to your data
  • Immutable
  • SQL manipulation is available
  • no decentralization
20
Q

Managed Blockchain

A
  • Blockchain + hyper ledger
21
Q

AWS Glue

A
  • ETL
  • Transform data for analytics
  • Load into Redshift for analysis
  • Catalog datasets
22
Q

DMS (data migration service)

A
  • Source availble during migration
  • Resilient
  • Supports: Homo migrations and hetero migrations
23
Q

Docker

A
  • Sw platform to develop apps
  • Apps can run the same regardless of where they run
  • Scale containers up and down quickly
  • Easier to run in an EC2 instance
  • Stored: Public (Docker Hub), Pvt (Amazon ECR)
24
Q

Elastic Container Service

A
  • Take your docker and decide which EC2 it should go
  • Provision and maintain the EC2 infra
  • AWS takes care of starting and stopping containers
  • Integration with ALB
25
Q

Fargate

A
  • Serverless of ECS
  • Launch Docker on AWS for you
26
Q

Elastic container Registry

A
  • Store your dockers
  • Deploy

AWS Cloud Practitioner (13 decks)

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