Native AWS Services

Network Code Tech Talks

Diego Cardozo @ Aug 2021

Who am I?

Goal for this talk

  • Too many services to cover (175+)
  • Go over the core building blocks
  • Focus on understanding how to
    choose the right service
    • Tradeoffs
    • Limitations

Sample project

Use cases

  1. Register devices
  2. Collect metrics



First decision: use NAWS?

Simplified network monitoring service

Sample project

What do we need?

  • Storage
    • Device registry (database)
    • Alert configuration (files)
  • Computing
    • Register device
    • Collect metrics
  • Messaging
  • Infrastructure management

Simplified network monitoring service


Things to consider

  • Data structure
    • How is data related to each other?
    • Will the structure change over time?
  • Scalability
    • Volume, reads and writes
  • Access patterns
    • Read heavy? Write heavy?
    • Consistency, Availability, Partition Tolerance

Storage: S3

  • Data structure
    • Stores objects (files)
    • Can also store pictures and static websites
  • Scalability
    • Serverless
    • High latency - double digit milliseconds
    • Can store large objects (up to 5TB)
    • ~5500 writes p/s, ~3500 reads p/s on a bucket
  • Access patterns
    • Global service, global bucket names
    • Not a file system! Even if it looks like one
    • Read after write consistency

Storage: DynamoDB

  • Data structure
    • Stores data (document store, JSON)
    • Semi-structured, schema-less
    • No explicit relationships
    • Primary key: partition key (ID), sort key (timestamp)
  • Scalability
    • Serverless
    • Low latency - single digit millisecond
    • Small objects (up to 400KB)
    • Can scale on demand
    • Easily > 40k reads and writes per second
  • Access patterns
    • Search: query, scan
    • You need to know how you are going to search
      • DDB not great to search by random attributes 
    • Secondary indexes
      • LSI - same PK, different SK
      • GSI - different view of the data
        • Pick a new primary key (PK and SK)
        • Can have up to 20
    • Consistency, Availability, Partition Tolerance
    • Global tables, streams

Storage: DynamoDB

Storage: RDS

  • Data structure
    • Stores structured data
    • Strong relationships
    • DB as a service: MySQL, PostgreSQL, Aurora, etc
  • Scalability
    • Not serverless, unless you use Aurora serverless
    • Example: bring DB down for updates
    • Scales a lot less than DynamoDB
  • Access patterns
    • Opinion: only strong benefit is ability to write random queries

Highly discouraged to use RDS

Storage: Comparison




Access speed ✅ ✅
Large objects
Number of objects
Schema changes ✅ ❌
Searchability ✅ ✅


Things to consider

  • Invocation patterns
    • Reacts to events or runs permanently?
    • How long do actions take?
  • Scalability
    • Scale horizontally (multiple instances)
    • Scale vertically (bigger instances)
  • Overhead
    • How much work do I need to keep it running?

Compute: EC2

  • Invocation patterns
    • In a nutshell, it is a VM. Runs permanently. 
    • Connect it to a VPC
  • Scalability
    • Scale horizontally (multiple instances)
    • You choose specific instance sizes
  • Overhead
    • Conceptually very simple
    • It is your responsibility to keep it up to date
  • Invocation patterns
    • Container: you describe the environment
    • Has a concept of tasks (container, roles and VPC)
    • Has 2 modes: EC2 and Fargate 

Compute: ECS

  • Scalability
    • Scale horizontally by starting more instances (Fargate does it for you)
    • Scale vertically by changing container descriptor
  • Overhead
    • Conceptually more complex because you need to understand containers
    • Less effort to maintain than EC2
    • You can run the same Docker container locally


Also similar offering: EKS (Elastic Kubernetes Service)

Compute: ECS

Compute: Lambda

  • Invocation patterns
    • Fully serverless
    • You bring code and AWS runs if for you
    • Define triggers
  • Scalability
    • Scales horizontally automatically up to 1000
    • Scales vertically by choosing available RAM
    • Need to be careful with limitations
  • Overhead
    • Conceptually very simple
    • Need to update runtime once in a while
    • Uploading dependencies can be painful


  • Max 15 min execution
  • Max 10 GB of RAM
  • You do not specify CPU, depends on memory
  • If you want an API, you will need API Gateway
  • ZIP file cannot be larger than 50MB or 250MB unpacked
  • Example: RIP v1 uses a huge JSON file. Too big to upload. Need to use RIP v2
  • Cold start latency

Compute: Lambda

Compute: Comparison




Invocation ✅ ✅ ✅ ✅

My opinion: use Lambda unless you can't

Messaging: SQS

  • Producer adds messages to a queue
  • Consumer reads messages from the queue
  • Good pattern for distributing work asynchronously
  • Messages up to 256KB
  • Can store unlimited messages. Max retention 14 days
Standard FIFO
No guaranteed order Ordered
Possible duplicates No duplicates
3000 messages per second 300 messages per second
120k inflight messages 20k inflight messages

Messaging: SNS

  • Producer adds messages to a topic
  • Consumer reads messages from the topic (subscribes)
  • Consumer completely unaware of the producer
  • Potentially multiple consumers
  • Messages have attributes and you can filter
  • Great for decoupling services
  • Limit on max messages per second depends on the region

Messaging: Kinesis

  • There are multiple flavours of Kinesis (data stream, video stream, firehose and analytics)
  • Common use case: telemetry
  • Low latency, guarantees in-order delivery
  • Supports replaying and multiple consumers
  • A stream is made of shards
    • Each shard supports 1MB/s ingest, 2MB/s egress
    • Determined by partition key
  • Retention up to 7 days

Infrastructure as code


Other services worth mentioning

  • IAM

    • Users, roles, permissions
  • CloudWatch

    • Logs, metrics, alarms
  • EventBridge

    • Rules-based messaging service


In chat

Thank you!

Native AWS Services - Network Code Tech talks

By diegocard

Native AWS Services - Network Code Tech talks

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