Try it now ! : https://welovedevs.com/app/companies
Learn more :
Serverless CPH : https://serverlesscph.dk/
WeLoveDevs.com : https://welovedevs.com/
Spread the love <span class="emoji-outer emoji-sizer"><span class="emoji-inner" style="background: url(chrome-extension://immhpnclomdloikkpcefncmfgjbkojmh/emoji-data/sheet_apple_32.png);background-position:50% 28.025851938895418%;background-size:5418.75% 5418.75%" data-codepoints="1f499"></span></span>
Apex Liberation - the evolution of Flex Queue (DF15)Stephen Willcock
Using Batch Apex FlexQueue, the history of the feature and developer considerations in implementation.
Presented at Dreamforce 2015 by Carolina Ruiz Medina and Stephen Willcock
Links:
Speakers
https://twitter.com/carolenlanube
https://twitter.com/CodeCoffeeCloud
http://codeandvogue.com/
https://twitter.com/stephenwillcock
http://foobarforce.com/
http://www.financialforce.com/
Simple Batch Apex examples
https://github.com/stephenwillcock/apex-misc
Async Execution Governors
https://developer.salesforce.com/docs/atlas.en-us.apexcode.meta/apexcode/apex_gov_limits.htm#non_transactional_gov_limits_section
Enhanced Futures blog post
mailto:https://developer.salesforce.com/blogs/engineering/2014/06/bigger-apex-limits-enhanced-futures.html#https://developer.salesforce.com/blogs/engineering/2014/06/bigger-apex-limits-enhanced-futures.html
Winter 16 Release Notes - FlexQueue Class
http://releasenotes.docs.salesforce.com/en-us/winter16/release-notes/rn_apex_flexqueue_class.htm
Winter 16 Release Notes - New Methods
http://releasenotes.docs.salesforce.com/en-us/winter16/release-notes/rn_apex_new_classes_methods.htm
BatchMan
https://twitter.com/innovativebrad
When we first started out with Azure, we created VM’s to run our web applications and backend services. Afterwards we moved our web application logic into App Services while using native Azure Services for our backend requirements. With containers we could isolate our individual web application components even further and allowed us to go full DevOps. Now Azure Functions allows us to remove a complete application stack allowing us to focus purely on functionality.
In this talk I go over the several phases we went through getting our application from bare metal into the cloud and how we now leverage Azure Functions to achieve higher throughput and faster delivery times while reducing the complexity of the web application and costs.
Meteor MIT Tech Talk 9/18/14: Designing a New Platform For Modern AppsSashko Stubailo
These are the slides for the talk Emily Stark and I presented at MIT on September 9, 2014.
We talked about the components that make up Meteor and how they fit together, finishing off with a more in-depth discussion of DDP, Meteor's Distributed Data Protocol.
Whizlabs webinar - Deploying Portfolio Site with AWS ServerlessDhaval Nagar
In this session, we go through the AWS Serverless eco-system and demo of how to deploy a static site using the following services.
Serverless Framework
Route53
AWS Certification Manager
S3
CloudFront
API Gateway
DynamoDB
SNS
GraphQL can be one of the best ways to make your product development more fun and productive. In this presentation I talk about how GraphQL makes your life simpler, and how to write and deploy a GraphQL API with Apollo Server 2.0 and serverless deployment via Netlify Functions.
Manageable Data Pipelines With Airflow (and kubernetes) - GDG DevFestJarek Potiuk
Apache Airflow is a platform to programmatically author, schedule and monitor workflows. Airflow is not a data streaming solution. Tasks do not move data from one to the other (though tasks can exchange metadata!). Airflow is not in the Spark Streaming or Storm space, it is more comparable to Oozie or Azkaban. It's primary goal is to solve problem nicely described in this XKCD comic (https://xkcd.com/2054/) What's unique about Airflow is that it brings "infrastructure as a code" concept to building scalable, manageable and elegant workflows. Workflows are defined as Python code - thus making dynamic workflow possible. It provides hundreds of out-of-the-box Operators that allow your pipeline to tap into pretty much any resource possible - starting from resources from multiple cloud providers as well as on-the-premises systems of yours. It's super-easy to write your own operators and leverage the power of data pipeline infrastructure provided by Airflow. This talk will be about general concepts behind Airflow - how you can author your workflow, write your own operators and run and monitor your pipelines. It will also explain how you can leverage Kubernetes (in recent release of Airflow) to make use of your on-premises or in-the-cloud infrastructure efficiently. You leave the talk armed with enough knowledge to evaluate if Airflow is good for you to solve your data pipeline problems and get some insight from Airflow contributors in case you are already an Airflow user.
Apex Liberation - the evolution of Flex Queue (DF15)Stephen Willcock
Using Batch Apex FlexQueue, the history of the feature and developer considerations in implementation.
Presented at Dreamforce 2015 by Carolina Ruiz Medina and Stephen Willcock
Links:
Speakers
https://twitter.com/carolenlanube
https://twitter.com/CodeCoffeeCloud
http://codeandvogue.com/
https://twitter.com/stephenwillcock
http://foobarforce.com/
http://www.financialforce.com/
Simple Batch Apex examples
https://github.com/stephenwillcock/apex-misc
Async Execution Governors
https://developer.salesforce.com/docs/atlas.en-us.apexcode.meta/apexcode/apex_gov_limits.htm#non_transactional_gov_limits_section
Enhanced Futures blog post
mailto:https://developer.salesforce.com/blogs/engineering/2014/06/bigger-apex-limits-enhanced-futures.html#https://developer.salesforce.com/blogs/engineering/2014/06/bigger-apex-limits-enhanced-futures.html
Winter 16 Release Notes - FlexQueue Class
http://releasenotes.docs.salesforce.com/en-us/winter16/release-notes/rn_apex_flexqueue_class.htm
Winter 16 Release Notes - New Methods
http://releasenotes.docs.salesforce.com/en-us/winter16/release-notes/rn_apex_new_classes_methods.htm
BatchMan
https://twitter.com/innovativebrad
When we first started out with Azure, we created VM’s to run our web applications and backend services. Afterwards we moved our web application logic into App Services while using native Azure Services for our backend requirements. With containers we could isolate our individual web application components even further and allowed us to go full DevOps. Now Azure Functions allows us to remove a complete application stack allowing us to focus purely on functionality.
In this talk I go over the several phases we went through getting our application from bare metal into the cloud and how we now leverage Azure Functions to achieve higher throughput and faster delivery times while reducing the complexity of the web application and costs.
Meteor MIT Tech Talk 9/18/14: Designing a New Platform For Modern AppsSashko Stubailo
These are the slides for the talk Emily Stark and I presented at MIT on September 9, 2014.
We talked about the components that make up Meteor and how they fit together, finishing off with a more in-depth discussion of DDP, Meteor's Distributed Data Protocol.
Whizlabs webinar - Deploying Portfolio Site with AWS ServerlessDhaval Nagar
In this session, we go through the AWS Serverless eco-system and demo of how to deploy a static site using the following services.
Serverless Framework
Route53
AWS Certification Manager
S3
CloudFront
API Gateway
DynamoDB
SNS
GraphQL can be one of the best ways to make your product development more fun and productive. In this presentation I talk about how GraphQL makes your life simpler, and how to write and deploy a GraphQL API with Apollo Server 2.0 and serverless deployment via Netlify Functions.
Manageable Data Pipelines With Airflow (and kubernetes) - GDG DevFestJarek Potiuk
Apache Airflow is a platform to programmatically author, schedule and monitor workflows. Airflow is not a data streaming solution. Tasks do not move data from one to the other (though tasks can exchange metadata!). Airflow is not in the Spark Streaming or Storm space, it is more comparable to Oozie or Azkaban. It's primary goal is to solve problem nicely described in this XKCD comic (https://xkcd.com/2054/) What's unique about Airflow is that it brings "infrastructure as a code" concept to building scalable, manageable and elegant workflows. Workflows are defined as Python code - thus making dynamic workflow possible. It provides hundreds of out-of-the-box Operators that allow your pipeline to tap into pretty much any resource possible - starting from resources from multiple cloud providers as well as on-the-premises systems of yours. It's super-easy to write your own operators and leverage the power of data pipeline infrastructure provided by Airflow. This talk will be about general concepts behind Airflow - how you can author your workflow, write your own operators and run and monitor your pipelines. It will also explain how you can leverage Kubernetes (in recent release of Airflow) to make use of your on-premises or in-the-cloud infrastructure efficiently. You leave the talk armed with enough knowledge to evaluate if Airflow is good for you to solve your data pipeline problems and get some insight from Airflow contributors in case you are already an Airflow user.
FaaS or not to FaaS. Visible and invisible benefits of the Serverless paradig...Vadym Kazulkin
When we talk about prices, we often only talk about Lambda costs. In our applications, however, we rarely use only Lambda. Usually we have other building blocks like API Gateway, data sources like SNS, SQS or Kinesis. We also store our data either in S3 or in serverless databases like DynamoDB or recently in Aurora Serverless. All of these AWS services have their own pricing models to look out for. In this talk, we will draw a complete picture of the total cost of ownership in serverless applications and present a decision-making list for determining if and whether to rely on serverless paradigm in your project. In doing so, we look at the cost aspects as well as other aspects such as understanding application lifecycle, software architecture, platform limitations, organizational knowledge and plattform and tooling maturity. We will also discuss current challenges adopting serverless such as lack of high latency ephemeral storage, unsufficient network performance and missing security features.
GraphQL across the stack: How everything fits togetherSashko Stubailo
My talk from GraphQL Summit 2017!
In this talk, I talk about a future for GraphQL which builds on the idea that GraphQL enables lots of tools to work together seamlessly across the stack. I present this through the lens of 3 examples: Caching, performance tracing, and schema stitching.
Stay tuned for the video recording from GraphQL Summit!
Alon Fliess: APM – What Is It, and Why Do I Need It? - Architecture Next 20CodeValue
So, you have a mature development process, and you also embrace DevOps. Your development team uses agile methodology. You use Git, and you have a continuous dev, test, and deployment process. But do you sleep well at night? Do you know that your services are up and running? That there are no availability, performance, and stability problems? Do you know if your customers are happy? The answer to all of those questions is precisely what APM systems provide.
Application Performance Monitoring systems have become the IDE of the Site Reliability Engineers (SRE) and, as a matter of fact, for the all DevOps team, including the Dev part. In this session, you will get to know the essence of the APM systems, the good, the bad, and the vision about their future.
At Fluent Conference 2018, Nic Jansma and Charles Vazac perform an honest audit of several popular third-party libraries to understand their true cost to your site, exploring loading patterns, SPOF avoidance, JavaScript parsing, long tasks, runtime overhead, polyfill headaches, security and privacy concerns, and more. They also share tools to help you decide if a library’s risks and unseen costs are worth it.
In this talk, I go over some of the concerns people initially have when adding GraphQL to their existing frontends and backends, and cover some of the tools that can be used to address them.
Adopting Java for the Serverless world at Serverless Meetup New York and BostonVadym Kazulkin
Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless Community. Java is known for its high cold start times and high memory footprint. For both you have to pay to the cloud providers of your choice. That's why most developers tried to avoid using Java for such use cases. But the times change: Community and cloud providers improve things steadily for Java developers. In this talk we look at the features and possibilities AWS cloud provider offers for the Java developers and look the most popular Java frameworks, like Micronaut, Quarkus and Spring (Boot) and look how (AOT compiler and GraalVM native images play a huge role) they address Serverless challenges and enable Java for broad usage in the Serverless world.
Writing less code with Serverless on AWS at OOP 2022Vadym Kazulkin
The purpose of Serverless is to focus on writing the code that delivers business value and offload undifferentiated heavy lifting to the Cloud providers or SaaS vendors of your choice. Today’s code quickly becomes tomorrow’s technical debt even if you meet the perfect decision. The less you own, the better it is from the maintainability point of view. In this talk I will go through examples of the various Serverless architectures on AWS where you glue together different Serverless managed services relying mostly on configuration, significantly reducing the amount of the code written to perform the task. Own less, build more!
There are a lot of tools and processes involved in modern front-end development: Component development, design, data fetching, testing, and more. At Stripe, our team have put a lot of effort into making these things work together in a way that's more than the sum of their parts.
FaaS or not to FaaS. Visible and invisible benefits of the Serverless paradig...Vadym Kazulkin
When we talk about prices, we often only talk about Lambda costs. In our applications, however, we rarely use only Lambda. Usually we have other building blocks like API Gateway, data sources like SNS, SQS or Kinesis. We also store our data either in S3 or in serverless databases like DynamoDB or recently in Aurora Serverless. All of these AWS services have their own pricing models to look out for. In this talk, we will draw a complete picture of the total cost of ownership in serverless applications and present a decision-making list for determining if and whether to rely on serverless paradigm in your project. In doing so, we look at the cost aspects as well as other aspects such as understanding application lifecycle, software architecture, platform limitations, organizational knowledge and plattform and tooling maturity. We will also discuss current challenges adopting serverless such as lack of high latency ephemeral storage, unsufficient network performance and missing security features.
What do the terms serverless, containers, and virtual machines mean? Which should I use to build my app? The answer (as always) is "it depends." In this session learn the tradeoffs between these different approaches, whether you're building your app from scratch or want to move an existing web or mobile application to the cloud. We'll discuss open source tools such as Kubernetes, Istio, and Knative, and we'll discuss Google Cloud Platform tools like Compute Engine, Google Kubernetes Engine (GKE), App Engine, and Cloud Functions.
Real User Measurement Insights, London WebPerf 2018-Nov-06Paul Calvano
Many websites use real user measurement (RUM) data to analyze their performance, as well as to validate the impact of optimizations. During this session, we’ll discuss how RUM is used and then explore some of the fascinating insights into the web that we can learn from it.
Video: https://youtu.be/VOyEU9o1wL4
NYC WebPerf Meetup Feb 2020 - Measuring the Adoption of Web Performance Techn...Paul Calvano
Performance optimization is a cyclical process. We are constantly learning new ways to optimize, while simultaneously adopting new technologies and techniques that negatively impact performance. The HTTP Archive provides a great historical record of the technical side of the web, with almost 10 years of history and an ever growing dataset of sites.
During this session Paul will provide a brief overview of the HTTP Archive and then dive into some insights into the adoption of common web performance techniques and some of their measurable impacts.
Revolutionize DevOps with ML capabilities. Introduction to Amazon CodeGuru an...Vadym Kazulkin
I will introduce two AWS services: CodeGuru and DevOps Guru.
CodeGuru Reviewer uses ML and automated reasoning to automatically identify critical issues, security vulnerabilities, and hard-to-find bugs during application development.
DevOps Guru analyzes data like application metrics, logs, events, and traces to establish baseline operational behavior and then uses ML to detect anomalies. It does this by having the ability to correlate and group metrics together to understand the relationships between those metrics, so it knows when to alert.
Tired of rebuilding your brand's UI in every new app your team works on? Whatever happened to DRY? This is exactly the reason why you should use a robust UI kit, like the AtlasKit, or build your own from scratch.
In this talk, Árni Freyr Snorrason, Developer and Team Lead at Tempo, will share Tempo's journey into the world of custom UI kits. He'll share how Tempo's growing visual identity for its products across multiple ecosystems, (most notably Jira Cloud and Jira Server) led to the decision to design, implement and maintain their very own Tempo UI kit, and also how the kit proved to be a crucial tool for developers to move faster and become more autonomous when developing front end features for cloud and server at the same time.
Our Cakephp developers have several years of experience in Cakephp Development who write well optimized code that can handle large volume of traffic. Please give us a call and learn more about how we can build and promote your business
FaaS or not to FaaS. Visible and invisible benefits of the Serverless paradig...Vadym Kazulkin
When we talk about prices, we often only talk about Lambda costs. In our applications, however, we rarely use only Lambda. Usually we have other building blocks like API Gateway, data sources like SNS, SQS or Kinesis. We also store our data either in S3 or in serverless databases like DynamoDB or recently in Aurora Serverless. All of these AWS services have their own pricing models to look out for. In this talk, we will draw a complete picture of the total cost of ownership in serverless applications and present a decision-making list for determining if and whether to rely on serverless paradigm in your project. In doing so, we look at the cost aspects as well as other aspects such as understanding application lifecycle, software architecture, platform limitations, organizational knowledge and plattform and tooling maturity. We will also discuss current challenges adopting serverless such as lack of high latency ephemeral storage, unsufficient network performance and missing security features.
GraphQL across the stack: How everything fits togetherSashko Stubailo
My talk from GraphQL Summit 2017!
In this talk, I talk about a future for GraphQL which builds on the idea that GraphQL enables lots of tools to work together seamlessly across the stack. I present this through the lens of 3 examples: Caching, performance tracing, and schema stitching.
Stay tuned for the video recording from GraphQL Summit!
Alon Fliess: APM – What Is It, and Why Do I Need It? - Architecture Next 20CodeValue
So, you have a mature development process, and you also embrace DevOps. Your development team uses agile methodology. You use Git, and you have a continuous dev, test, and deployment process. But do you sleep well at night? Do you know that your services are up and running? That there are no availability, performance, and stability problems? Do you know if your customers are happy? The answer to all of those questions is precisely what APM systems provide.
Application Performance Monitoring systems have become the IDE of the Site Reliability Engineers (SRE) and, as a matter of fact, for the all DevOps team, including the Dev part. In this session, you will get to know the essence of the APM systems, the good, the bad, and the vision about their future.
At Fluent Conference 2018, Nic Jansma and Charles Vazac perform an honest audit of several popular third-party libraries to understand their true cost to your site, exploring loading patterns, SPOF avoidance, JavaScript parsing, long tasks, runtime overhead, polyfill headaches, security and privacy concerns, and more. They also share tools to help you decide if a library’s risks and unseen costs are worth it.
In this talk, I go over some of the concerns people initially have when adding GraphQL to their existing frontends and backends, and cover some of the tools that can be used to address them.
Adopting Java for the Serverless world at Serverless Meetup New York and BostonVadym Kazulkin
Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless Community. Java is known for its high cold start times and high memory footprint. For both you have to pay to the cloud providers of your choice. That's why most developers tried to avoid using Java for such use cases. But the times change: Community and cloud providers improve things steadily for Java developers. In this talk we look at the features and possibilities AWS cloud provider offers for the Java developers and look the most popular Java frameworks, like Micronaut, Quarkus and Spring (Boot) and look how (AOT compiler and GraalVM native images play a huge role) they address Serverless challenges and enable Java for broad usage in the Serverless world.
Writing less code with Serverless on AWS at OOP 2022Vadym Kazulkin
The purpose of Serverless is to focus on writing the code that delivers business value and offload undifferentiated heavy lifting to the Cloud providers or SaaS vendors of your choice. Today’s code quickly becomes tomorrow’s technical debt even if you meet the perfect decision. The less you own, the better it is from the maintainability point of view. In this talk I will go through examples of the various Serverless architectures on AWS where you glue together different Serverless managed services relying mostly on configuration, significantly reducing the amount of the code written to perform the task. Own less, build more!
There are a lot of tools and processes involved in modern front-end development: Component development, design, data fetching, testing, and more. At Stripe, our team have put a lot of effort into making these things work together in a way that's more than the sum of their parts.
FaaS or not to FaaS. Visible and invisible benefits of the Serverless paradig...Vadym Kazulkin
When we talk about prices, we often only talk about Lambda costs. In our applications, however, we rarely use only Lambda. Usually we have other building blocks like API Gateway, data sources like SNS, SQS or Kinesis. We also store our data either in S3 or in serverless databases like DynamoDB or recently in Aurora Serverless. All of these AWS services have their own pricing models to look out for. In this talk, we will draw a complete picture of the total cost of ownership in serverless applications and present a decision-making list for determining if and whether to rely on serverless paradigm in your project. In doing so, we look at the cost aspects as well as other aspects such as understanding application lifecycle, software architecture, platform limitations, organizational knowledge and plattform and tooling maturity. We will also discuss current challenges adopting serverless such as lack of high latency ephemeral storage, unsufficient network performance and missing security features.
What do the terms serverless, containers, and virtual machines mean? Which should I use to build my app? The answer (as always) is "it depends." In this session learn the tradeoffs between these different approaches, whether you're building your app from scratch or want to move an existing web or mobile application to the cloud. We'll discuss open source tools such as Kubernetes, Istio, and Knative, and we'll discuss Google Cloud Platform tools like Compute Engine, Google Kubernetes Engine (GKE), App Engine, and Cloud Functions.
Real User Measurement Insights, London WebPerf 2018-Nov-06Paul Calvano
Many websites use real user measurement (RUM) data to analyze their performance, as well as to validate the impact of optimizations. During this session, we’ll discuss how RUM is used and then explore some of the fascinating insights into the web that we can learn from it.
Video: https://youtu.be/VOyEU9o1wL4
NYC WebPerf Meetup Feb 2020 - Measuring the Adoption of Web Performance Techn...Paul Calvano
Performance optimization is a cyclical process. We are constantly learning new ways to optimize, while simultaneously adopting new technologies and techniques that negatively impact performance. The HTTP Archive provides a great historical record of the technical side of the web, with almost 10 years of history and an ever growing dataset of sites.
During this session Paul will provide a brief overview of the HTTP Archive and then dive into some insights into the adoption of common web performance techniques and some of their measurable impacts.
Revolutionize DevOps with ML capabilities. Introduction to Amazon CodeGuru an...Vadym Kazulkin
I will introduce two AWS services: CodeGuru and DevOps Guru.
CodeGuru Reviewer uses ML and automated reasoning to automatically identify critical issues, security vulnerabilities, and hard-to-find bugs during application development.
DevOps Guru analyzes data like application metrics, logs, events, and traces to establish baseline operational behavior and then uses ML to detect anomalies. It does this by having the ability to correlate and group metrics together to understand the relationships between those metrics, so it knows when to alert.
Tired of rebuilding your brand's UI in every new app your team works on? Whatever happened to DRY? This is exactly the reason why you should use a robust UI kit, like the AtlasKit, or build your own from scratch.
In this talk, Árni Freyr Snorrason, Developer and Team Lead at Tempo, will share Tempo's journey into the world of custom UI kits. He'll share how Tempo's growing visual identity for its products across multiple ecosystems, (most notably Jira Cloud and Jira Server) led to the decision to design, implement and maintain their very own Tempo UI kit, and also how the kit proved to be a crucial tool for developers to move faster and become more autonomous when developing front end features for cloud and server at the same time.
Our Cakephp developers have several years of experience in Cakephp Development who write well optimized code that can handle large volume of traffic. Please give us a call and learn more about how we can build and promote your business
Introducing the Hub for Data OrchestrationAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Introducing the Hub for Data Orchestration
Danny Linden, Chapter Lead Software Engineer (Ryte)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Serverless in production, an experience report (FullStack 2018)Yan Cui
AWS Lambda has changed the way we deploy and run software, but this new serverless paradigm has created new challenges to old problems - how do you test a cloud-hosted function locally? How do you monitor them? What about logging and config management? And how do we start migrating from existing architectures?
In this talk Yan and Scott will discuss solutions to these challenges by drawing from real-world experience running Lambda in production and migrating from an existing monolithic architecture.
Serverless in Production, an experience report (AWS UG South Wales)Yan Cui
AWS Lambda has changed the way we deploy and run software, but this new serverless paradigm has created new challenges to old problems - how do you test a cloud-hosted function locally? How do you monitor them? What about logging and config management? And how do we start migrating from existing architectures?
In this talk Yan and Scott will discuss solutions to these challenges by drawing from real-world experience running Lambda in production and migrating from an existing monolithic architecture.
WinOps Conf 2016 - Michael Greene - Release PipelinesWinOps Conf
There are benefits to be gained when patterns and practices from developer techniques are applied to operations. Notably, a fully automated solution where infrastructure is managed as code and all changes are automatically validated before reaching production. This is a process shift that is recognized among industry innovators. For organizations already leveraging these processes, it should be clear how to leverage Microsoft platforms. For organizations that are new to the topic, it should be clear how to bring this process to your environment and what it means to your organizational culture. This presentation explains the components of a Release Pipeline for configuration as code, the value to operations, and solutions that are used when designing a new Release Pipeline architecture.
GraphQL has many advantages over RESTful APIs. A lot of companies start thinking about migration paths for adopting GraphQL, which not only come with technological but also with organizational challenges!
This talk is an application-driven walkthrough to modern stream processing, exemplified by Apache Flink, and how this enables new applications and makes old applications easier and more efficient. In this talk, we will walk through several real-world stream processing application scenarios of Apache Flink, highlighting unique features in Flink that make these applications possible. In particular, we will see (1) how support for handling out of order streams enables real-time monitoring of cloud infrastructure, (2) how the ability handle high-volume data streams with low latency SLAs enables real-time alerts in network equipment, (3) how the combination of high throughput and the ability to handle batch as a special case of streaming enables an architecture where the same exact program is used for real-time and historical data processing, and (4) how stateful stream processing can enable an architecture that eliminates the need for an external database store, leading to more than 100x performance speedup, among many other benefits.
Building your own calendly using amazon app syncDhaval Nagar
This session will showcase how SaaS applications like Calendly.com can be designed using AWS Serverless technologies like AppSync, API Gateway, DynamoDB, and Cognito.
Serverless technologies and capabilities are here and are accessible now more than ever.
The power of infinite scale and system capabilities has never been more accessible. This also affects traditional front end development as serverless technologies allow for easy construction of backend support for any frontend with ease and simplicity.
In this talk, we will demonstrate how to build a fully functional Graphql endpoint for FE applications using Apollo Server and Client libraries, utilizing different cloud providers. We will also demonstrate the usage of Servless.com framework to set up the required infrastructure as code to simplify and support this setup
The video of the presentation (Hebrew):
https://youtu.be/8ba4cpdtK-8
Session slide from Open Space (theme : performance).
There are many dimensions of performance and scale.
We’ll revisit what server capabilities are in play in a web application, and their relation to performance.
Then we're ready to talk about service and team boundaries and organizational performance, building a web application using multiple teams/services integrating through server side composition.
Let's take a look at what server capabilities could bring to web applications, built by multiple teams.
Presentation de l'article universitaire :
REST How-to
Un guide pour une architecture REST.
Les questions qu'il est nécessaire de se poser pour établir un cahier des charges efficace et éviter les pièges de SOAP.
10 Décembre 2012 UQAC ISEN
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
2. Serverless CPH
15-04-18
About
We built a 10K MAU WebApp using Firebase, some Javascript and as less
servers as possible.
Why ?
How ?
What are the anti-patterns ? Good surprises ?
4. Serverless CPH
15-04-18
What is the app about ?
8000+ Content pages
Companies, jobs, landing pages : developer’s "god mode" on job market to find a company he will loves to work at
5. Serverless CPH
15-04-18
Dev likes companies he would like to work at
App is learning what companies you like
and predict companies you will like
You can also use a search engine,
a map and some editorial content
to find companies
1
6. Serverless CPH
15-04-18
When ready, a developer a can fill a profile
Developer's profiles are anonymous
and confidentials
It's a safe place where a developer can
explain her career path, what she has
learned and built.
But also what are her expectations
about is future positions.
2
7. Serverless CPH
15-04-18
Conversations with real people working at thoses companies
Conversations are real time and can
support multiple agents
You get one-click link by SMS, mobile
layout is available and the green dot shows
who is online
3
10. Serverless CPH
15-04-18
We founded the company as two developers
Content, users,
marketing, sales,
operations
More SaaS less work
We wanted to spend time
with users and ship features
on a daily basis.
Not spend hours
maintaining a large app and
systems we have built
ourselves.
It's okay to have vendor-
locking (tight coupling)
and more expensives
services if it reduces the
human time needed at
operation.
11. Serverless CPH
15-04-18
From idea to production in a day
● Developer’s journey…
Talk with a customer over livechat in morning
Build a PoC during day
● Deploy in production and give feedback to user
● Go Home !
Whether there is 2 or 20 of us
13. Serverless CPH
15-04-18
What was key ?
Services we relied
on early
ElasticSearch
Allowed us to provide a good search experience thanks to
SearchKit. Bonsai provided a free shared instance to startup.
At launch we only had one index and 20 documents.
Firebase
Allowed us to quickly setup authentication and be realtime at
day0.
Users testified : "this looks like MeteorJS"
Redux was key to solve the callback spaghetti
Clever Cloud
Does more than Hosting
It also operate continuous integration by building and deploying
every commit on Github's master. #WebpackInTheCloud
14. Serverless CPH
15-04-18
What was hell ?
Requiring
monitoring and fixing
Redis
Redis instance as too many clients.
Provided Redis instance is now too small. Migration to a larger
one is required
Node Worker Processes
Redis instance refused connection, process is stalled.
Process crashed, PM2 rebooted.
Flashlight was crashed, updates has not been pushed to
ElasticSearch
COMMAND Jobbing over HTTP
Client create jobs via an express API.
Consistency hell : "Didn't got an HTTP reply, should I resend ?"
Authentication hell : "Okay got your request, need to check your
credential"
XHR
15. Serverless CPH
15-04-18
How is Firebase Working
Large JSON
Tree
Websocket
Listen for a node in the tree
Ref : root/ref/is/a/path
Downstream updates
Path : root/ref/is/a/path
Event : updated/created/deleted
16. Serverless CPH
15-04-18
How is Firebase Working
Also Functions SDK provide authentication out of the box
Triggers
Node Updated
Node created
Node Deleted
User registerd
User deleted
…
20. Serverless CPH
15-04-18
There is no more jobs useful
Shutting down redis
Shutting down PM2 and worker process on node app
Removing API endpoints on express server
Few month later...
21. Serverless CPH
15-04-18
New services !
New Kids On The
Block
Algolia : Search as a Service
"Hey ! I tried Algolia and reproduced our Elastic Search setup in
a 4h"
Shutting down Elastic Search and Bonsai
Sendgrid : Transactional Emails
Templates using a Wysiwyg.
Locked-in for the best. Nobody likes to code emails anyway.
Twilio for SMS
"Wouldn't be great to send a transactionnal SMS at this moment
?
Let me try Twilio ? … `firebase deploy`...
Done, works great "
""
27. Serverless CPH
15-04-18
How to
implement ?
Train LSTM with Watson 0,50€ / 1000 predictions
Training : $0.50/h
Train LSTM with Tensorflow
Easy to deploy on Google Cloud AI
But, at the time, only in python
Implement FP Growth in Node
Run it as a Cloud Function
It took me two weeks to get
access to documentation.
Training : $0.49/h
Batch Prediction :
$0.09262/h
Online Predictions :
$0.3/h
Compute time :
$0,1/h
28. Serverless CPH
15-04-18
Building the tree
Machine Learning + In-production learning
Pre-flight Checklist
1. 1. Preprocess (SPSS, Node, Python)
2. Train a model
3. Produce a batch of predictions
4. Control and report training
2. On the fly : Predict
29. Serverless CPH
15-04-18
FP Growth in detail
Building this locally
1. Preprocess => Node Script => Transactions as JSON
2. Train a model => Node Script => FPtree as JSON
3. Produce a batch of predictions => Node Script => JSON
4. Control and report training => Node Script => Console output
On the fly : Predict => Traverse FPTree with a Node Script =>
Console Output
32. Serverless CPH
15-04-18
Function-based FPGrowth Training
Training
Function
Fetch all likes
Preprocess
Make tree
Store Tree
Batch
Predictions Store Predictions
Control
Store Distribution
Remote Cron Trigger
Distribution
update
Trigger
Reporting
email
Boostrap
DataStore Bootstrap
42. Serverless CPH
15-04-18
Do : Use HTTP Triggers with an external Cron Service
We are using SetCronJob.com
Warning : Optimization !
This data fetch used to consume 6Gb of
bandwidth every day
Once optimized it wasn’t significant anymore
(need an .indexOn in database rules)
Firebase SDK will show a warning in logs
Firebase CLI offers an handy profiler
1
43. Serverless CPH
15-04-18
The Cold Start is going to give you a very bad experience !
Better run a Express server somewhere on a PaaS.
2
Don’t : Use HTTP Triggers as a WebServer
44. Serverless CPH
15-04-18
Hard to reproduce and debug
Easy to have side effects
Check events and data before executing the core of the function
3
Don’t : Triggers Cloud Functions recursively
45. Serverless CPH
15-04-18
If you can reproduce each jobs it’s okay.
Make sure the writing of the job is not triggering an other functions
Pub/Sub is also a good option
4
Do : Use Firebase RDB as a Queue
46. Serverless CPH
15-04-18
It’s easier to manage side effects if it’s all contained in one function
5
Don’t : Two functions aren’t better than one
47. Serverless CPH
15-04-18
Do : Realtime feedback in a function
It’s easy to push an update to firebase
6
Acknowledge : ”received”
Fetch data from external
Parse data
Persist “pushing”
Done
48. Serverless CPH
15-04-18
Do : Have an Express process listen to Firebase DB
Very efficient for response time
(No need to query a SGBD)
Need to be carefull about process
memory
Pretty convenient for Server Side
Rendering
Warning : React ServerSide rendering
mean you are going to
Babel/Webpack your server
7
49. Serverless CPH
15-04-18
Don’t : Create Race Condition
For concurrency purpose :
Functions can be executed multiple
time in the same runtime or in the
same container (you shouldn't rely on
it).
Because of cold start and resource
sharing, concurrent functions can
show race condition
If you have to :
Look for Transactions on RDB
8
50. Serverless CPH
15-04-18
Do : Use RDB for Uncoupling & Function as Couplers
Get out of the Client/Server logic : Stripe Checkout use case
9
listen CustomerId
write customerId:tbd
No
CustomerId
Write Trigger Function
(hold Stripe
SK)
Fetch
write
customerId
Render
Get Payment
Source write Source
Confirmation Write Request
Subscription
Function
(hold Stripe
SK)
Write Trigger Create
Sub
write
currentPlan
Render
51. Serverless CPH
15-04-18
Do : Functions are great for ETL
Multiposting Usecase : Extract / Load / Transform
10
Extract (Parse) Transform
Extract and Transform
Load
Load
Trigger
Email
Email
Email
Load
52. Serverless CPH
15-04-18
Do and Don’t : Summary
1. Do : Use HTTP Triggers with an external Cron Service
2. Don’t : Use HTTP Triggers as Express servers
3. Don’t : Triggers Cloud Functions in a recursive way
4. Do : Use Firebase RDB as a Queue
5. Don’t : Two functions aren’t better than one
6. Do : Realtime feedback in a function
7. Do : Have an Express process listen to Firebase DB
8. Don’t : Create Race Condition
9. Do : Use RDB for Uncoupling & Function as Couplers
10. Do : Use Functions as ETL