heitorlessa

from __future__ import annotations

from typing import List, Optional

from aws_lambda_powertools.utilities.parser.models import EventBridgeModel
from aws_lambda_powertools.utilities.parser.envelopes import (
    EventBridgeEnvelope,  # only if you want to discard EventBridge metadata
)
from aws_lambda_powertools.utilities.parser.parser import event_parser
from pydantic import BaseModel

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Links

• [Article] AWS Builder's Library - CI/CD Pipeline: https://aws.amazon.com/builders-library/automating-safe-hands-off-deployments/
• DevOps/Microservices thread: https://twitter.com/heitor_lessa/status/1450006862112432137 https://samnewman.io/books/monolith-to-microservices/
• [Talk] Designing EDA and team dynamics: https://www.youtube.com/watch?v=W3Rh70jG-LM
• [Article] Misunderstandings in Tribes & Squads land: https://www.jeremiahlee.com/posts/failed-squad-goals/
• [Book] Team Topologies: https://teamtopologies.com/key-concepts
• [Article] Docker Team Topologies case: https://www.docker.com/blog/building-stronger-happier-engineering-teams-with-team-topologies/

heitorlessa

Todos os links que estavam na apresentação

• Inside Amazon CI/CD pipelines - https://aws.amazon.com/builders-library/automating-safe-hands-off-deployments/
• Livro Monolith to Microservices - https://samnewman.io/books/monolith-to-microservices/
• Ports & Adapters (Hexagonal Architecture) - https://alistair.cockburn.us/hexagonal-architecture/
• O modelo Tribe-Squad Spotify depois do piloto - https://www.jeremiahlee.com/posts/failed-squad-goals/
• Team topologies - https://teamtopologies.com/key-concepts
• Docker use case with team topologies - https://www.docker.com/blog/building-stronger-happier-engineering-teams-with-team-topologies/
• Team topologies remote-first - https://teamtopologies.com/key-concepts-content/remote-first-team-interactions-with-team-topologies
• Developer Experience - What drives productivity: https://queue.acm.org/detail.cfm?id=3595878

heitorlessa

heitorlessa

There are three participants: Client, Server, Database.

First scenario

• Client makes a GET /products request to the Server
• Server verifies whether Client is authorized to make this request
• Server confirms Client is authorized and makes a request to the Database to fetch all products
• Database returns 100 products to the Server, along with a pagination token to retrieve 100 more tiems
• Create a loop between Server and Database, where Server fetches 100 more products with the pagination token provided by Database until there are no more products to be fetched
• Server returns response to the Client

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class CustomTracerProvider(BaseProvider):
    def start_segment(self):
        """This method is proposed as a solution as it exists for other providers
        This method is responsible for starting the trace. This might involve initializing some data structures,
        connecting to an external service, or performing some other setup work"""

    def end_segment(self):
        """This method is proposed as a solution as it exists for other providers.
        This method is responsible for ending the trace. This might involve finalizing data structures,
        sending data to an external service, or performing some other cleanup work"""

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AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: partial batch response sample

Globals:
    Function:
        Timeout: 5
        MemorySize: 256
        Runtime: python3.8
        Tracing: Active

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{
    "StartAt": "Sit and wait",
    "States": {
        "Sit and wait": {
            "Type": "Wait",
            "Seconds": 1,
            "Next": "Dummy Output"
        },
        "Dummy Output": {
            "Type": "Pass",

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Open At Amazon Lessons Learned

• Event. https://openatamazon.splashthat.com/
• Talk. AWS Lambda Powertools for Python: Lessons learned on the road to 1M downloads (now 6M)
• General
  • Project tenets
  • Documentation system - Featureful Technical Documentation theme
  • Project progressive tutorial
  • Central Roadmap - worked to an extent, we'll migrate back to each runtime repo using the new GitHub Project beta (tabular view)
• Contribution

heitorlessa

Export custom flag PT_409 when running locally to log in plain text and write output into log.txt file

PT_409="1" python prod.py 

Output should look like this:

2021-05-13 19:05:25,506+0200 — INFO — main:32 — Hello - {'context': {'device_id': '11e9034354f', 'device_location': 'London'}} - -