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Serverless Data Processing with AWS Step Functions, Part II.

Back in Part I of Deploying a Serverless Data Processing Workflow with AWS Step Functions, Nuatu mentioned one key benefit of using step functions is their visibility into business critical workflows. Outside stakeholders, support staff, and other engineers can look at a state machine execution in AWS or Stackery, and can easily understand the process.

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Running Lambdas on your Laptop

Serverless has the potential to bring massive ops advantages to projects of all sizes, but while it presents great business benefits, we need to spare a thought for how teams develop on serverless. I recently published ‘Serverless Development is Broken’ a list of concerns about how developers can work with long deploy times inherent in a cloud-only code environment.

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Write to S3 and call other Lambdas with Python

Many people writing about AWS Lambda view Node as the code-default. I’ve been guilty of this in my own articles, but it’s important to remember that Python is a ‘first-class citizen’ within AWS and is a great option for writing readable Lambda code. Take a look at these two starter examples of writing functionality in Python.

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Deploying a serverless data processing workflow with AWS Step Functions

This is the first of a two-part blog series. In this post we’ll use Stackery to configure and deploy a serverless data processing architecture that utilizes AWS Step Functions to coordinate multiple steps within a workflow. In the next post we’ll expand this architecture with additional workflow logic to highlight techniques for increasing resiliency and reliability.

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How do we set up a proper serverless development workflow?

If you’ve built a serverless application or two, you’re probably familiar with the benefits of serverless architecture. You take advantage of already built, managed cloud services to handle standard application requirements like authentication, storage, compute, API gateways, and a long list of other infrastructure needs. You can spin up these resources in a matter of minutes and add your own specific business logic (usually as AWS Lambda function code).

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Building a Better Product Through Customer Service

Like many startups, Stackery is a small team. For this reason, employees often need to go beyond their official job title to ensure everything gets done. As the Stackery product matures and gains more exposure, we’ve seen an increase in customer support inquiries and decided to further refine our customer support process through the creation of a customer support rotation that rotates amongst the software engineers on a weekly basis.

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How Vydia Uses Serverless with Stackery

Vydia is dedicated to helping creators gain more control over their audio and video content with a centralized tool for distributing, managing, protecting, and optimizing AV files. Vydia’s software team describes themselves as a “DevOps team first and foremost” delivering new features and updates in a tight loop. They are always in search of new ways to improve and modernize the development process.