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How Stream Processing Makes Your Event-Driven Architecture Even Better

By Michael Bogan in heroku

December 11, 2019

We will discuss why you might pick stream processing as your architecture, some of the pros and cons, and a quick-to-deploy reference architecture using Apache Kafka.

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Scale Your Microservices with an Easy Message Queue on Redis

By Michael Bogan in heroku

November 28, 2019

Event-driven architecture can help you to create apps that are both performant and easily scalable. We’ll show you how to create and deploy a simple message queue using Heroku, Redis, and RSMQ.

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Postgres Is Underrated—It Handles More than You Think

By Jason Skowronski in heroku

October 16, 2019

Thinking about adding another data store like Redis or Elasticsearch? Take a minute and think again. Postgres offers powerful features which are not obvious at first sight.

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Best Practices for Event-Driven Microservice Architecture

By Michael Bogan in heroku

September 11, 2019

If you’re an enterprise architect, you’ve probably heard of and worked with a microservices architecture. While you might have used REST as your service communications layer in the past, more and more projects are moving to an event-driven architecture. Let’s dive into the pros and cons of this popular architecture, some of the key design choices it entails, and common anti-patterns.

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PaaS versus Serverless: Which to choose in 2019?

By Artem Nikitin in heroku

September 11, 2019

Serverless computing is increasingly popular, so when building a new application in 2019 should you go serverless or stick with PaaS? Which approach should we choose for building apps today? Should you make the switch to serverless? The first step is to look at all our options objectively, evaluate them for our specific situation, and make a reasoned choice. Both can solve basic development needs: delivering functionality quickly and reliably. Understanding the technical differences will help you determine which approach is best for a particular project.

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Open Data Shines a Light on Cities’ Top Challenges

By Andre Newman in heroku

August 21, 2019

From reports of potholes and broken streetlights to complaints about garbage and vandalism, cities process more non-emergency requests from residents than ever before. Baltimore, the first U.S. city to deploy a 311 system, has processed over 13 million requests since its inception. The result is a repository of data detailing the interactions between a city and its residents. Analyzing this data can help cities learn more about their residents’ needs, prioritize tasks and projects, track performance, and improve collaboration across departments.

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7 Ways to Optimize Python Performance Using APM

By Zeashan Pappa in appoptics

August 19, 2019

Your website performance is critical for success. Poor page load times and responsiveness can lead to lost sales, lost ranking on search engines like Google, frustrated customers, and more. Even beyond that, inefficient code can increase infrastructure costs and potentially even affect the ability of your business to scale. We’ll discuss how to run high(er) performance Python for web applications using the popular Django framework. We’ll cover some of the common problems and patterns so you know what to look for.

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Identifying Trolls and Bots on Reddit with Machine Learning (Part 2)

By Jason Skowronski in heroku

July 30, 2019

Trolls and bots are widespread across social media, and they influence us in ways we are not always aware of. Trolls can be relatively harmless, just trying to entertain themselves at others’ expense, but they can also be political actors sowing mistrust or discord. While some bots offer helpful information, others can be used to manipulate vote counts and promote content that supports their agenda. We’ll show you how machine learning can help protect our communities from abuse.

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Trolls and Bots Are Disrupting Social Media — Here’s How AI Can Stop Them (Part 1)

By Jason Skowronski in heroku

July 30, 2019

Trolls and bots have a huge and often unrecognized influence on social media. They are used to influence conversations for commercial or political reasons. They allow small hidden groups of people to promote information supporting their agenda and a large scale. They can push their content to the top of people’s news feeds, search results, and shopping carts. Some say they can even influence presidential elections. Can we use machine learning to identify suspicious posts and comments?

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Twelve-Factor Apps: A Retrospective and Look Forward

By Jason Skowronski in heroku

July 17, 2019

If your team is creating apps for the cloud, chances are the Twelve-Factor App methodology has influenced the frameworks and platforms you’re using. Popular frameworks such as Spring Boot, Magento, and more credit the twelve factors as part of their design. Leading companies such as Heroku, Amazon, and Microsoft use and recommend the methodology. While new frameworks and methodologies are released every month, few have the far-reaching impact of this one.

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