Approaches for application request throttling - Cloud Developer Days Poland

Watch this Tech Talk: https://do.co/video_dworth Dave Worth, Engineering Manager at Strava, lays out a strategy for choosing the right tech stack depending on your business and team need. Watch as he guides you through tool sets that navigate around business constraints and regulatory concerns. About the Presenter Dave Worth’s professional life consists of being a web and backend engineer who developed specialization in observability through building reliable distributed systems at Strava, and previously DigitalOcean. In his spare time, Dave loves cycling, jiu jitsu, and searching for another great math book to only read the first 50 pages of. New to DigitalOcean? Get US $100 in credit when you sign up: https://do.co/deploytoday To learn more about DigitalOcean: https://www.digitalocean.com/ Follow us on Twitter: https://twitter.com/digitalocean Like us on Facebook: https://www.facebook.com/DigitalOcean Follow us on Instagram: https://www.instagram.com/thedigitalocean/ We're hiring: http://do.co/careers

Session Presentation by Brian Kelly Microservices appear simple to build on the surface, but there's more to creating them than just launching some code running in a container. This talk outlines 10 important questions that should be answered about any new microservice before development begins on it - - and certainly before it gets deployed into production.

In this series of 15-minute technical flash talks you will learn directly from Amazon CloudFront engineers and their best practices on debugging caching issues, measuring performance using Real User Monitoring (RUM), and stopping malicious viewers using CloudFront and AWS WAF.

Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analyzed, often with many consumers or systems interested in all or part of the events. Storing such huge event streams into HDFS or a NoSQL datastore is feasible and not such a challenge anymore. But if you want to be able to react fast, with minimal latency, you can not afford to first store the data and doing the analysis/analytics later. You have to be able to include part of your analytics right after you consume the data streams. Products for doing event processing, such as Oracle Event Processing or Esper, are available for quite a long time and used to be called Complex Event Processing (CEP). In the past few years, another family of products appeared, mostly out of the Big Data Technology space, called Stream Processing or Streaming Analytics. These are mostly open source products/frameworks such as Apache Storm, Spark Streaming, Flink, Kafka Streams as well as supporting infrastructures such as Apache Kafka. In this talk I will present the theoretical foundations for Stream Processing, discuss the core properties a Stream Processing platform should provide and highlight what differences you might find between the more traditional CEP and the more modern Stream Processing solutions.

Integrating content delivery networks into your application infrastructure can offer many benefits, including major performance improvements for your applications. So understanding how CDNs perform — especially for your specific use cases — is vital. However, testing for measurement is complicated and nuanced, and results in metric overload and confusion. It's becoming increasingly important to understand measurement techniques, what they're telling you, and how to apply them to your actual content. In this session, we'll examine the challenges around measuring CDN performance and focus on the different methods for measurement. We'll discuss what to measure, important metrics to focus on, and different ways that numbers may mislead you. More specifically, we'll cover: Different techniques for measuring CDN performance Differentiating between network footprint and object delivery performance Choosing the right content to test Core metrics to focus on and how each impacts real traffic Understanding cache hit ratio, why it can be misleading, and how to measure for it

This document discusses a presentation on fraud detection application architectures using Hadoop. It provides an overview of different fraud use cases and challenges in implementing Hadoop-based solutions. Requirements for the applications include handling high volumes, velocities and varieties of data, generating real-time alerts with low latency, and performing both stream and batch processing. A high-level architecture is proposed using Hadoop, HBase, HDFS, Kafka and Spark to meet the requirements. Storage layer choices and considerations are also discussed.

What are some of the performance implications of using lambdas and what strategies can be used to address these. When might be want an alternative to using a lambda and how can we design our APIs to be flexible in this regard. What are the principles of writing low latency code in Java? How do we tune and optimize our code for low latency? When don’t we optimize our code? Where does the JVM help and where does it get in our way? How does this apply to lambdas? How can we design our APIs to use lambdas and minimize garbage?

This document discusses enabling the lean enterprise through technologies like microservices, continuous integration/deployment, and cloud computing. It begins by defining the lean enterprise and the OODA loop concept. It then explains how technologies like AWS, big data, and microservices can help organizations continuously observe, orient, decide, and act. Specific AWS services like EC2, EMR, Kinesis, Redshift, S3, and DynamoDB are reviewed. The benefits of breaking up monolithic systems into microservices and implementing devops practices like CI/CD are also summarized.

Reactive programming allows for non-blocking and concurrent executions. It is designed to be more efficient by using fewer threads and less memory. This makes applications more resilient and scalable to handle high connection volumes and traffic variability. The developer experience is improved through actionable stacktraces and debugging of reactive flows.

Presented by Stephane Maldini at Reactive Enterprise with Reactor and Spring in Toronto on June 13th, 2019.

This document contains the slides from a workshop on observability presented by Kevin Crawley of Instana and Single Music. The workshop covered distributed tracing using Jaeger and Prometheus, challenges with open source monitoring tools, and advanced use cases for distributed tracing demonstrated through Single Music's experience. The agenda included labs on setting up Kubernetes and applications, monitoring metrics with Grafana and Prometheus, distributed tracing with Jaeger, and analytics use cases.

Another day, another buzzword in the world of software development! ‘Microservices’ is a new approach to structuring server-side software. But is it really new? In this talk I’ll walk you through the birth and ‘raison d’etre’ of microservices and tell about pro’s and con’s of the approach. Having laid the foundation, we will take a look at best-practices and patterns for building micro service architectures and combine this with a tour of current technologies and development tools. Finally, I will take a quick look at the future and discuss some of the remaining challenges. All parts of the presentation will be accompanied by structural examples based on a real ecommerse system.

Collecting logs from the entire stateless environment is challenging parts of the application lifecycle. Correlating business logs with operating system metrics to provide insights is a crucial part of the entire organization. We will see the technical presentation on how to manage a large amount of the data in a typical environment with microservices.

Collecting logs from the entire stateless environment is challenging parts of the application lifecycle. Correlating business logs with operating system metrics to provide insights is a crucial part of the entire organization. What aspects should be considered while you design your logging solutions?

We already know that the Internet of Things is big. It isn't something that's coming. It's already here. From manufacturing to healthcare, retail and hospitality, transportation, utilities and energy, the shift from Information Technology to Operational Technology and the value that this massive explosion of data can provide is taking the world by storm. But IoT isn't a product. It's not something you can buy. As with any gold rush, snake oil abounds. The potential is massive and the good news is that the technology and platforms are already here! But how do you get started? What are the application and networking protocols at play? How do you handle the ingestion of massive, real-time streams of data? Where do you land the data? What kind of insights does the data at scale provide? How do you make sense of it and/or take action on the data in real time scaling to hundreds if not hundreds of thousands of devices per deployment? In this session, Rick G. Garibay will share a pragmatic reference architecture based on his experience working with dozens of customers in the field and provide an insider’s view on some real-world IoT solutions he's led. He'll demystify what IoT is and what it isn't, discuss patterns for addressing the challenges inherent in IoT projects and how the most popular public cloud vendors are already providing the capabilities you need to build real-world IoT solutions today.

Serverless introduces a number of challenges to existing tools for observability, we need to adapt our practices to fit this new paradigm. In this talk, we will discuss how we can build observability into a serverless application. We will see how you can implement log aggregation, distributed tracing and correlation IDs through both synchronous as well as asynchronous events.

Presented at the BDAM meetup in Palo Alto on Sept 14th. Jags Ramnarayan, CTO, SnappyData, discusses an ad analytics use case running on SnappyData.

The C# nullability features help you minimize the likelihood of encountering that dreaded System.NullReferenceException. Nullability syntax and annotations give hints as to whether a type can be nullable or not, and better static analysis is available to catch unhandled nulls while developing your code. What's not to like? Introducing explicit nullability into an existing code bases is a Herculean effort. There's much more to it than just sprinkling some `?` and `!` throughout your code. It's not a silver bullet either: you'll still need to check non-nullable variables for null. In this talk, we'll see some techniques and approaches that worked for me, and explore how you can migrate an existing code base to use the full potential of C# nullability.

After buying a set of Sonos-compatible speakers at IKEA, I was disappointed there's no support for playing audio from a popular video streaming service. They stream Internet radio, podcasts and what not. Well, not that service I want it to play! Determined - and not knowing how deep the rabbit hole would be - I ventured on a trip that included network sniffing on my access point, learning about UPnP and running a web server on my phone (without knowing how to write anything Android), learning how MP4 audio is packaged (and has to be re-packaged). This ultimately resulted in an Android app for personal use, which does what I initially wanted: play audio from that popular video streaming service on Sonos. Join me for this story about an adventure that has no practical use, probably violates Terms of Service, but was fun to build!

Space is a team tool that integrates chats, meetings, git hosting, automation, and more. It has an HTTP API to integrate third party apps and workflows, but it's massive! And slightly opinionated. In this session, we will see how we built the .NET SDK for Space, and how we make that massive API more digestible. We will see how we used code generation, and incrementally made the API feel more like a real .NET SDK.

Ever wondered how IDE’s are built? In this talk, we’ll skip the marketing bit and dive into the architecture and implementation of JetBrains Rider. We’ll look at how and why we have built (and open sourced) a reactive protocol, and how the IDE uses a “microservices” architecture to communicate with the debugger, Roslyn, a WPF renderer and even other tools like Unity3D. We’ll explore how things are wired together, both in-process and across those microservices.

Which NuGet package was that type in again? In this session, let's build a "reverse package search" that helps finding the correct NuGet package based on a public type. Together, we will create a highly-scalable serverless search engine using Azure Functions and Azure Search that performs 3 tasks: listening for new packages on NuGet.org (using a custom binding), indexing packages in a distributed way, and exposing an API that accepts queries and gives our clients the best result.

Ever wondered how IDE’s are built? In this talk, we’ll skip the marketing bit and dive into the architecture and implementation of JetBrains Rider. We’ll look at how and why we have built (and open sourced) a reactive protocol, and how the IDE uses a “microservices” architecture to communicate with the debugger, Roslyn, a WPF renderer and even other tools like Unity3D. We’ll explore how things are wired together, both in-process and across those microservices. Let’s geek out!

This document discusses .NET memory management and the garbage collector. It explains that the CLR manages memory in a heap and the garbage collector reclaims unused memory. It describes how objects are allocated in generations and discusses how to help the garbage collector perform better by reducing allocations, using value types when possible, and properly disposing of objects. The document also provides examples of hidden allocations and demonstrates tools for analyzing memory usage like ClrMD and dotMemory Unit.

Which NuGet package was that type in again? In this session, let's build a "reverse package search" that helps finding the correct NuGet package based on a public type. Together, we will create a highly-scalable serverless search engine using Azure Functions and Azure Search that performs 3 tasks: listening for new packages on NuGet.org (using a custom binding), indexing packages in a distributed way, and exposing an API that accepts queries and gives our clients the best result. https://blog.maartenballiauw.be/post/2019/07/30/indexing-searching-nuget-with-azure-functions-and-search.html

Which NuGet package was that type in again? In this session, let's build a "reverse package search" that helps finding the correct NuGet package based on a public type. Together, we will create a highly-scalable serverless search engine using Azure Functions and Azure Search that performs 3 tasks: listening for new packages on NuGet.org (using a custom binding), indexing packages in a distributed way, and exposing an API that accepts queries and gives our clients the best result.

Which NuGet package was that type in again? In this session, let's build a "reverse package search" that helps finding the correct NuGet package based on a public type. Together, we will create a highly-scalable serverless search engine using Azure Functions and Azure Search that performs 3 tasks: listening for new packages on NuGet.org (using a custom binding), indexing packages in a distributed way, and exposing an API that accepts queries and gives our clients the best result.

This document discusses indexing NuGet packages using Azure Functions and Azure Search to power search capabilities in ReSharper and Rider. It proposes using Functions triggered by changes to the NuGet.org catalog to download packages, index them using reflection metadata, and upload the results to an Azure Search index. Each step would be a separate function to allow independent scaling. The final system would watch the catalog, index new/updated packages, and provide APIs for searching packages by type or namespace.

The .NET Garbage Collector (GC) is really cool. It helps providing our applications with virtually unlimited memory, so we can focus on writing code instead of manually freeing up memory. But how does .NET manage that memory? What are hidden allocations? Are strings evil? It still matters to understand when and where memory is allocated. In this talk, we’ll go over the base concepts of .NET memory management and explore how .NET helps us and how we can help .NET – making our apps better. Expect profiling, Intermediate Language (IL), ClrMD and more!

Ever wondered how IDE’s are built? In this talk, we’ll skip the marketing bit and dive into the architecture and implementation of JetBrains Rider. We’ll look at how and why we have built (and open sourced) a reactive protocol, and how the IDE uses a “microservices” architecture to communicate with the debugger, Roslyn, a WPF renderer and even other tools like Unity3D. We’ll explore how things are wired together, both in-process and across those microservices. Let’s geek out!

Ever wondered how IDE’s are built? In this talk, we’ll skip the marketing bit and dive into the architecture and implementation of JetBrains Rider. We’ll look at how and why we have built (and open sourced) a reactive protocol, and how the IDE uses a “microservices” architecture to communicate with the debugger, Roslyn, a WPF renderer and even other tools like Unity3D. We’ll explore how things are wired together, both in-process and across those microservices. Let’s geek out!

The .NET Garbage Collector (GC) is really cool. It helps providing our applications with virtually unlimited memory, so we can focus on writing code instead of manually freeing up memory. But how does .NET manage that memory? What are hidden allocations? Are strings evil? It still matters to understand when and where memory is allocated. In this talk, we’ll go over the base concepts of .NET memory management and explore how .NET helps us and how we can help .NET – making our apps better. Expect profiling, Intermediate Language (IL), ClrMD and more!

The .NET Garbage Collector (GC) is really cool. It helps providing our applications with virtually unlimited memory, so we can focus on writing code instead of manually freeing up memory. But how does .NET manage that memory? What are hidden allocations? Are strings evil? It still matters to understand when and where memory is allocated. In this talk, we’ll go over the base concepts of .NET memory management and explore how .NET helps us and how we can help .NET – making our apps better. Expect profiling, Intermediate Language (IL), ClrMD and more!

We all like building and deploying cloud applications. But what happens once that’s done? How do we know if our application behaves like we expect it to behave? Of course, logging! But how do we get that data off of our machines? How do we sift through a bunch of seemingly meaningless diagnostics? In this session, we’ll look at how we can keep track of our Azure application using structured logging, AppInsights and AppInsights analytics to make all that data more meaningful.

The .NET Garbage Collector (GC) is really cool. It helps providing our applications with virtually unlimited memory, so we can focus on writing code instead of manually freeing up memory. But how does .NET manage that memory? What are hidden allocations? Are strings evil? It still matters to understand when and where memory is allocated. In this talk, we’ll go over the base concepts of .NET memory management and explore how .NET helps us and how we can help .NET – making our apps better. Expect profiling, Intermediate Language (IL), ClrMD and more!

Everybody is consuming or producing NuGet packages these days. It’s easy, right? We’ll look beyond what everyone is doing. How can we use the NuGet client API to fetch data from NuGet? Can we build an application plugin system based on NuGet? What hidden gems are there in the NuGet server API? Can we create a full copy of NuGet.org?

Everybody is consuming NuGet packages these days. It’s easy, right? But how can we create and share our own packages? What is .NET Standard? How should we version, create, publish and share our package? Once we have those things covered, we’ll look beyond what everyone is doing. How can we use the NuGet client API to fetch data from NuGet? Can we build an application plugin system based on NuGet? What hidden gems are there in the NuGet server API? Can we create a full copy of NuGet.org? Good questions! In this talk, we will get them answered.

Is your patent a vanity piece of paper for your office wall? Or is it a reliable, defendable, assertable, property right? The difference is often quality. Is your patent simply a transactional cost and a large pile of legal bills for your startup? Or is it a leverageable asset worthy of attracting precious investment dollars, worth its cost in multiples of valuation? The difference is often quality. Is your patent application only good enough to get through the examination process? Or has it been crafted to stand the tests of time and varied audiences if you later need to assert that document against an infringer, find yourself litigating with it in an Article 3 Court at the hands of a judge and jury, God forbid, end up having to defend its validity at the PTAB, or even needing to use it to block pirated imports at the International Trade Commission? The difference is often quality. Quality will be our focus for a good chunk of the remainder of this season. What goes into a quality patent, and where possible, how do you get it without breaking the bank? ** Episode Overview ** In this first episode of our quality series, Kristen Hansen and the panel discuss: ⦿ What do we mean when we say patent quality? ⦿ Why is patent quality important? ⦿ How to balance quality and budget ⦿ The importance of searching, continuations, and draftsperson domain expertise ⦿ Very practical tips, tricks, examples, and Kristen’s Musts for drafting quality applications https://www.aurorapatents.com/patently-strategic-podcast.html

Cybersecurity is a major concern in today's connected digital world. Threats to organizations are constantly evolving and have the potential to compromise sensitive information, disrupt operations, and lead to significant financial losses. Traditional cybersecurity techniques often fall short against modern attackers. Therefore, advanced techniques for cyber security analysis and anomaly detection are essential for protecting digital assets. This blog explores these cutting-edge methods, providing a comprehensive overview of their application and importance.