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!
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!
CodeStock - Exploring .NET memory management - a trip down memory laneMaarten Balliauw
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!
Understanding Java Garbage Collection - And What You Can Do About ItAzul Systems Inc.
Garbage collection is an integral but often misunderstood part of application behavior on Java platforms. As such, it is important for Java developers to understand how collector mechanisms work. This presentation reviews and classifies the major garbage collectors available in JVMs today. Following an overview of common garbage collection techniques such as generational, parallel, stop-the-world, incremental, and concurrent algorithms, it defines terms and metrics common to all collectors. It also discusses trade-offs in balancing requirements for responsiveness, throughput, space, and available memory and covers some pitfalls, common misconceptions, and garbage collection behavior myths.
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!
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!
CodeStock - Exploring .NET memory management - a trip down memory laneMaarten Balliauw
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!
Understanding Java Garbage Collection - And What You Can Do About ItAzul Systems Inc.
Garbage collection is an integral but often misunderstood part of application behavior on Java platforms. As such, it is important for Java developers to understand how collector mechanisms work. This presentation reviews and classifies the major garbage collectors available in JVMs today. Following an overview of common garbage collection techniques such as generational, parallel, stop-the-world, incremental, and concurrent algorithms, it defines terms and metrics common to all collectors. It also discusses trade-offs in balancing requirements for responsiveness, throughput, space, and available memory and covers some pitfalls, common misconceptions, and garbage collection behavior myths.
Quantifying the Performance of Garbage Collection vs. Explicit Memory ManagementEmery Berger
This talk answers an age-old question: is garbage collection faster/slower/the same speed as malloc/free? We introduce oracular memory management, an approach that lets us measure unaltered Java programs as if they used malloc and free. The result: a good GC can match the performance of a good allocator, but it takes 5X more space. If physical memory is tight, however, conventional garbage collectors suffer an order-of-magnitude performance penalty.
JetBrains Australia 2019 - Exploring .NET’s memory management – a trip down m...Maarten Balliauw
The .NET Garbage Collector (GC) helps provide 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? Can we do without 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!
Azul Product Manager Matt Schuetze's presentation on JVM memory details to the Philadelphia Java User Group.
This session dovetails with the March, 2014 PhillyJUG deep dive session topic focused on Java compiler code transformation and JVM runtime execution. That session exposes myths that Java is slow and Java uses too much memory. In this session we will take a deeper look at Java memory management. The dreaded Out of Memory (OOM) error is one problem. Garbage collector activity and spikes leading to long pauses is another. He covers the foundations of garbage collection and why historically Java gets a bad rap, even though GC provides a marvelous memory management paradigm.
Garbage Collection is an integral part of application behavior on Java platforms, yet it is often misunderstood. As such, it is important for Java developers to understand the actions you can take in selecting and tuning collector mechanisms, as well as in your application architecture choices. Azul Product Manager Matt Schuetze describes the different collectors available and how to choose.
Ice Age melting down: Intel features considered usefull!Peter Hlavaty
Decades history of kernel exploitation, however still most used techniques are such as ROP. Software based approaches comes finally challenge this technique, one more successful than the others. Those approaches usually trying to solve far more than ROP only problem, and need to handle not only security but almost more importantly performance issues. Another common attacker vector for redirecting control flow is stack what comes from design of today’s architectures, and once again some software approaches lately tackling this as well. Although this software based methods are piece of nice work and effective to big extent, new game changing approach seems coming to the light. Methodology closing this attack vector coming right from hardware - intel. We will compare this way to its software alternatives, how one interleaving another and how they can benefit from each other to challenge attacker by breaking his most fundamental technologies. However same time we go further, to challenge those approaches and show that even with those technologies in place attackers is not yet in the corner.
This session is all about - the mechanism provided by Java Virtual Machine to reclaim heap space from objects which are eligible for Garbage collection.
As @nicowaisman mentioned in his talk Aleatory Persistent Threat, old school heap specific exploiting is dying. And with each windows SP or new version, is harder to attack heap itself. Heap management adapt quickly and include new mittigation techniques. But sometimes is better to rethink the idea of mittigation and do this technique properly even half version of it will cover all known heap exploit techniques…
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?
Profilers find performance bottlenecks in your app but provide confusing information. Let's give you insights into how your profiler and your app are really interacting. What profiling APIs are available, how they work, and what their implementation on the JVM (OpenJDK) side looks like:
Stack sampling profilers: stop motion view of your app
GetCallTrace(JVisualVM case study): The official stack sampling API
Safepoints and safepoint sampling bias
AsyncGetCallTrace(Honest Profiler Case Study): The unofficial API
JVM Profilers vs System Profilers: No API needed?
This talk will cover how powerfull are buffer overflows, how weak are mitigations against them, why are buffer overflows still possible in those days, how generic are they, and example how useful is turn race conditions to buffer overflow. Race conditions are nice example for that, because they are one of the hardest to find and on of the easiest to make. example is on Linux kernel (droids included), but talk will be keeped for buffer overflows in general (mainly for windows & Linux kernel)
Exploring .NET memory management - A trip down memory lane - Copenhagen .NET ...Maarten Balliauw
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!
ConFoo - Exploring .NET’s memory management – a trip down memory laneMaarten Balliauw
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!
Quantifying the Performance of Garbage Collection vs. Explicit Memory ManagementEmery Berger
This talk answers an age-old question: is garbage collection faster/slower/the same speed as malloc/free? We introduce oracular memory management, an approach that lets us measure unaltered Java programs as if they used malloc and free. The result: a good GC can match the performance of a good allocator, but it takes 5X more space. If physical memory is tight, however, conventional garbage collectors suffer an order-of-magnitude performance penalty.
JetBrains Australia 2019 - Exploring .NET’s memory management – a trip down m...Maarten Balliauw
The .NET Garbage Collector (GC) helps provide 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? Can we do without 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!
Azul Product Manager Matt Schuetze's presentation on JVM memory details to the Philadelphia Java User Group.
This session dovetails with the March, 2014 PhillyJUG deep dive session topic focused on Java compiler code transformation and JVM runtime execution. That session exposes myths that Java is slow and Java uses too much memory. In this session we will take a deeper look at Java memory management. The dreaded Out of Memory (OOM) error is one problem. Garbage collector activity and spikes leading to long pauses is another. He covers the foundations of garbage collection and why historically Java gets a bad rap, even though GC provides a marvelous memory management paradigm.
Garbage Collection is an integral part of application behavior on Java platforms, yet it is often misunderstood. As such, it is important for Java developers to understand the actions you can take in selecting and tuning collector mechanisms, as well as in your application architecture choices. Azul Product Manager Matt Schuetze describes the different collectors available and how to choose.
Ice Age melting down: Intel features considered usefull!Peter Hlavaty
Decades history of kernel exploitation, however still most used techniques are such as ROP. Software based approaches comes finally challenge this technique, one more successful than the others. Those approaches usually trying to solve far more than ROP only problem, and need to handle not only security but almost more importantly performance issues. Another common attacker vector for redirecting control flow is stack what comes from design of today’s architectures, and once again some software approaches lately tackling this as well. Although this software based methods are piece of nice work and effective to big extent, new game changing approach seems coming to the light. Methodology closing this attack vector coming right from hardware - intel. We will compare this way to its software alternatives, how one interleaving another and how they can benefit from each other to challenge attacker by breaking his most fundamental technologies. However same time we go further, to challenge those approaches and show that even with those technologies in place attackers is not yet in the corner.
This session is all about - the mechanism provided by Java Virtual Machine to reclaim heap space from objects which are eligible for Garbage collection.
As @nicowaisman mentioned in his talk Aleatory Persistent Threat, old school heap specific exploiting is dying. And with each windows SP or new version, is harder to attack heap itself. Heap management adapt quickly and include new mittigation techniques. But sometimes is better to rethink the idea of mittigation and do this technique properly even half version of it will cover all known heap exploit techniques…
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?
Profilers find performance bottlenecks in your app but provide confusing information. Let's give you insights into how your profiler and your app are really interacting. What profiling APIs are available, how they work, and what their implementation on the JVM (OpenJDK) side looks like:
Stack sampling profilers: stop motion view of your app
GetCallTrace(JVisualVM case study): The official stack sampling API
Safepoints and safepoint sampling bias
AsyncGetCallTrace(Honest Profiler Case Study): The unofficial API
JVM Profilers vs System Profilers: No API needed?
This talk will cover how powerfull are buffer overflows, how weak are mitigations against them, why are buffer overflows still possible in those days, how generic are they, and example how useful is turn race conditions to buffer overflow. Race conditions are nice example for that, because they are one of the hardest to find and on of the easiest to make. example is on Linux kernel (droids included), but talk will be keeped for buffer overflows in general (mainly for windows & Linux kernel)
Exploring .NET memory management - A trip down memory lane - Copenhagen .NET ...Maarten Balliauw
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!
ConFoo - Exploring .NET’s memory management – a trip down memory laneMaarten Balliauw
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!
Even if your program is just a few lines of code, .NET's runtime will create a number of object in memory. Are all objects being destroyed by the garbage collector? Or is there a potential memory leak? And why is the application seemingly slow when having lots of objects in memory? In this webinar, we'll explore the new dotMemory 4 memory profiler. We'll see why we want to use a memory profiler and how easy it is to use JetBrains dotMemory for that.
These days fast code needs to operate in harmony with its environment. At the deepest level this means working well with hardware: RAM, disks and SSDs. A unifying theme is treating memory access patterns in a uniform and predictable way that is sympathetic to the underlying hardware. For example writing to and reading from RAM and Hard Disks can be significantly sped up by operating sequentially on the device, rather than randomly accessing the data. In this talk we’ll cover why access patterns are important, what kind of speed gain you can get and how you can write simple high level code which works well with these kind of patterns.
For More information, refer to Java EE 7 performance tuning and optimization book:
The book is published by Packt Publishing:
http://www.packtpub.com/java-ee-7-performance-tuning-and-optimization/book
Cgroups, namespaces, and beyond: what are containers made from? (DockerCon Eu...Jérôme Petazzoni
Linux containers are different from Solaris Zones or BSD Jails: they use discrete kernel features like cgroups, namespaces, SELinux, and more. We will describe those mechanisms in depth, as well as demo how to put them together to produce a container. We will also highlight how different container runtimes compare to each other.
This talk was delivered at DockerCon Europe 2015 in Barcelona.
Mon, August 22, 2:00pm – 2:30pm
Youtube: https://youtu.be/OlJZMHLTfuc
Description
Abstract: Spur is the new memory manager for the Cog virtual machine used by Pharo, Newspeak and Squeak. It features a two generation scavenger garbage collector with an adaptative tenuring policy, lazy become, (transparent) segmented memory, a new 64bit-compatible object-format, ephemerons, pinned objects, a class table, among others. If you're high-level application developer, or a programming amateur, but not a VM expert, but you're interested in understanding these concepts and what is their impact on your day to day development this talk is for you.
Bio: Guille Polito is research engineer at CNRS, France. Pharoer since 2010, he participates actively in the Pharo open source community since several years. He currently works on the modularization of Pharo where he does software archeology, refactoring, library rewriting and participates in the Virtual Machine development.
Best Practices for performance evaluation and diagnosis of Java Applications ...IndicThreads
Session Presented at 5th IndicThreads.com Conference On Java held on 10-11 December 2010 in Pune, India
WEB: http://J10.IndicThreads.com
------------
Enterprise applications typically comprise of multi layered stacks including the application modules, application servers, the Java Virtual Machine and the underlying Operating System. Consequently the performance of these applications are a factor of these different layers. In the eventuality of a performance problem, it is often difficult to determine the starting point for diagnosis. The Java Virtual Machine is the ‘engine’ for most of the applications. It is responsible broadly for efficient execution and memory management of applications. End users have difficulty attributing the effect of the JVM on the performance of the application. This is because usually JVM is viewed as a ‘black box’.
This talk provides an insight into the key subsystems of the JVM by looking under the hood of a high performance JVM. It ventures onto talk about approaches and techniques for analyzing performance issues. It concludes by introducing the audience to a tool called the “Health Center” which is useful for evaluating and comprehending the JVM behavior of a running application in an unobtrusive, lightweight manner.
Takeaways for the Audience A better understanding of key JVM components, approaches and techniques to diagnose performance issues and performance evaluation using the Health Center
Java Tools and Techniques for Solving Tricky ProblemWill Iverson
Most Java software problems come from the little “broken windows” – a null pointer here or there. Sometimes, however, you find yourself in a nasty section of town, with the heap, stack, and permgen brutally fighting for memory. Threads in nasty knife fights over resources. Sometimes just plain freaky things – how did I wind up with 1.5GB of HashSet allocations?
In this edition of CSI: Seattle Java Edition, we’ll look at the tools available to combat these nasty foes and even see some of them in action – we will blow up a lot of application servers and JVMs in the process, with graphic results.
When Node.js Goes Wrong: Debugging Node in Production
The event-oriented approach underlying Node.js enables significant concurrency using a deceptively simple programming model, which has been an important factor in Node's growing popularity for building large scale web services. But what happens when these programs go sideways? Even in the best cases, when such issues are fatal, developers have historically been left with just a stack trace. Subtler issues, including latency spikes (which are just as bad as correctness bugs in the real-time domain where Node is especially popular) and other buggy behavior often leave even fewer clues to aid understanding. In this talk, we will discuss the issues we encountered in debugging Node.js in production, focusing upon the seemingly intractable challenge of extracting runtime state from the black hole that is a modern JIT'd VM.
We will describe the tools we've developed for examining this state, which operate on running programs (via DTrace), as well as VM core dumps (via a postmortem debugger). Finally, we will describe several nasty bugs we encountered in our own production environment: we were unable to understand these using existing tools, but we successfully root-caused them using these new found abilities to introspect the JavaScript VM.
These days fast code needs to operate in harmony with its environment. At the deepest level this means working well with hardware: RAM, disks and SSDs. A unifying theme is treating memory access patterns in a uniform and predictable that is sympathetic to the underlying hardware. For example writing to and reading from RAM and Hard Disks can be significantly sped up by operating sequentially on the device, rather than randomly accessing the data.
In this talk we’ll cover why access patterns are important, what kind of speed gain you can get and how you can write simple high level code which works well with these kind of patterns.
Cgroups, namespaces and beyond: what are containers made from?Docker, Inc.
Linux containers are different from Solaris Zones or BSD Jails: they use discrete kernel features like cgroups, namespaces, SELinux, and more. We will describe those mechanisms in depth, as well as demo how to put them together to produce a container. We will also highlight how different container runtimes compare to each other.
Stream Processing with CompletableFuture and Flow in Java 9Trayan Iliev
Stream based data / event / message processing becomes preferred way of achieving interoperability and real-time communication in distributed SOA / microservice / database architectures.
Beside lambdas, Java 8 introduced two new APIs explicitly dealing with stream data processing:
- Stream - which is PULL-based and easily parallelizable;
- CompletableFuture / CompletionStage - which allow composition of PUSH-based, non-blocking, asynchronous data processing pipelines.
Java 9 will provide further support for stream-based data-processing by extending the CompletableFuture with additional functionality – support for delays and timeouts, better support for subclassing, and new utility methods.
More, Java 9 provides new java.util.concurrent.Flow API implementing Reactive Streams specification that enables reactive programming and interoperability with libraries like Reactor, RxJava, RabbitMQ, Vert.x, Ratpack, and Akka.
The presentation will discuss the novelties in Java 8 and Java 9 supporting stream data processing, describing the APIs, models and practical details of asynchronous pipeline implementation, error handling, multithreaded execution, asyncronous REST service implementation, interoperability with existing libraries.
There are provided demo examples (code on GitHub) using Completable Future and Flow with:
- JAX-RS 2.1 AsyncResponse, and more importantly unit-testing the async REST service method implementations;
- CDI 2.0 asynchronous observers (fireAsync / @ObservesAsync);
Bringing nullability into existing code - dammit is not the answer.pptxMaarten Balliauw
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.
Nerd sniping myself into a rabbit hole... Streaming online audio to a Sonos s...Maarten Balliauw
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!
Building a friendly .NET SDK to connect to SpaceMaarten Balliauw
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.
Microservices for building an IDE - The innards of JetBrains Rider - NDC Oslo...Maarten Balliauw
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.
Indexing and searching NuGet.org with Azure Functions and Search - .NET fwday...Maarten Balliauw
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.
NDC Sydney 2019 - Microservices for building an IDE – The innards of JetBrain...Maarten Balliauw
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!
.NET Conf 2019 - Indexing and searching NuGet.org with Azure Functions and Se...Maarten Balliauw
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
CloudBurst 2019 - Indexing and searching NuGet.org with Azure Functions and S...Maarten Balliauw
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.
NDC Oslo 2019 - Indexing and searching NuGet.org with Azure Functions and SearchMaarten Balliauw
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.
Approaches for application request throttling - Cloud Developer Days PolandMaarten Balliauw
Speaking from experience building a SaaS: users are insane. If you are lucky, they use your service, but in reality, they probably abuse. Crazy usage patterns resulting in more requests than expected, request bursts when users come back to the office after the weekend, and more! These all pose a potential threat to the health of our web application and may impact other users or the service as a whole. Ideally, we can apply some filtering at the front door: limit the number of requests over a given timespan, limiting bandwidth, ...
In this talk, we’ll explore the simple yet complex realm of rate limiting. We’ll go over how to decide on which resources to limit, what the limits should be and where to enforce these limits – in our app, on the server, using a reverse proxy like Nginx or even an external service like CloudFlare or Azure API management. The takeaway? Know when and where to enforce rate limits so you can have both a happy application as well as happy customers.
Indexing and searching NuGet.org with Azure Functions and Search - Cloud Deve...Maarten Balliauw
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.
Approaches for application request throttling - dotNetCologneMaarten Balliauw
Speaking from experience building a SaaS: users are insane. If you are lucky, they use your service, but in reality, they probably abuse. Crazy usage patterns resulting in more requests than expected, request bursts when users come back to the office after the weekend, and more! These all pose a potential threat to the health of our web application and may impact other users or the service as a whole. Ideally, we can apply some filtering at the front door: limit the number of requests over a given timespan, limiting bandwidth, ...
In this talk, we’ll explore the simple yet complex realm of rate limiting. We’ll go over how to decide on which resources to limit, what the limits should be and where to enforce these limits – in our app, on the server, using a reverse proxy like Nginx or even an external service like CloudFlare or Azure API management. The takeaway? Know when and where to enforce rate limits so you can have both a happy application as well as happy customers.
ConFoo Montreal - Microservices for building an IDE - The innards of JetBrain...Maarten Balliauw
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!
ConFoo Montreal - Approaches for application request throttlingMaarten Balliauw
Speaking from experience building a SaaS: users are insane. If you are lucky, they use your service, but in reality, they probably abuse. Crazy usage patterns resulting in more requests than expected, request bursts when users come back to the office after the weekend, and more! These all pose a potential threat to the health of our web application and may impact other users or the service as a whole. Ideally, we can apply some filtering at the front door: limit the number of requests over a given timespan, limiting bandwidth, ...
In this talk, we’ll explore the simple yet complex realm of rate limiting. We’ll go over how to decide on which resources to limit, what the limits should be and where to enforce these limits – in our app, on the server, using a reverse proxy like Nginx or even an external service like CloudFlare or Azure API management. The takeaway? Know when and where to enforce rate limits so you can have both a happy application as well as happy customers.
Microservices for building an IDE – The innards of JetBrains Rider - TechDays...Maarten Balliauw
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!
VISUG - Approaches for application request throttlingMaarten Balliauw
Speaking from experience building a SaaS: users are insane. If you are lucky, they use your service, but in reality, they probably abuse. Crazy usage patterns resulting in more requests than expected, request bursts when users come back to the office after the weekend, and more! These all pose a potential threat to the health of our web application and may impact other users or the service as a whole. Ideally, we can apply some filtering at the front door: limit the number of requests over a given timespan, limiting bandwidth, ...
In this talk, we’ll explore the simple yet complex realm of rate limiting. We’ll go over how to decide on which resources to limit, what the limits should be and where to enforce these limits – in our app, on the server, using a reverse proxy like Nginx or even an external service like CloudFlare or Azure API management. The takeaway? Know when and where to enforce rate limits so you can have both a happy application as well as happy customers.
What is going on - Application diagnostics on Azure - TechDays FinlandMaarten Balliauw
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.
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?
Speaking from experience building MyGet.org: users are insane. If you are lucky, they use your service, but in reality, they probably abuse. Crazy usage patterns resulting in more requests than expected, request bursts when users come back to the office after the weekend, and more! These all pose a potential threat to the health of our web application and may impact other users or the service as a whole. Ideally, we can apply some filtering at the front door: limit the number of requests over a given timespan, limiting bandwidth, ...
In this talk, we’ll explore the simple yet complex realm of rate limiting. We’ll go over how to decide on which resources to limit, what the limits should be and where to enforce these limits – in our app, on the server, using a reverse proxy like Nginx or even an external service like CloudFlare or Azure API management. The takeaway? Know when and where to enforce rate limits so you can have both a happy application as well as happy customers.
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.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
"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.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
2. Who am I?
Maarten Balliauw
Antwerp, Belgium
Developer Advocate, JetBrains
AZUG
Focus on web and .NET
ASP.NET MVC, Azure, SignalR, ...
Former MVP Azure & ASPInsider
https://blog.maartenballiauw.be
@maartenballiauw
3. .NET runtime
Manages execution of programs
Just-in-time compilation: Intermediate Language (IL) ->machine code
Type safety
Exception handling
Security
Thread management
Memory management
Garbage collection (GC)
5. Memory management and GC
“Virtually unlimited memory for our applications”
Big chunk of memory pre-allocated
Runtime manages allocation in that chunk
Garbage Collector (GC) reclaims unused memory, making it available again
6. .NET memory management 101
Memory allocation
Objects allocated in “managed heap” (big chunk of memory)
Allocating memory is fast, it’s just adding a pointer
Some unmanaged memory is also consumed (not GC-ed)
.NET CLR, Dynamic libraries, Graphics buffer, …
Memory release or “Garbage Collection” (GC)
Generations
Large Object Heap
7. .NET memory management 101
Memory allocation
Memory release or “Garbage Collection” (GC)
GC releases objects no longer in use by examining application roots
GC builds a graph of all the objects that are reachable from these roots
Object unreachable? Remove object, release memory, compact heap
Takes time to scan all objects!
Generations
Large Object Heap
8. .NET memory management 101
Memory allocation
Memory release or “Garbage Collection” (GC)
Generations
Large Object Heap
Generation 0 Generation 1 Generation 2
Short-lived objects (e.g. Local
variables)
In-between objects Long-lived objects (e.g. App’s
main form)
9. .NET memory management 101
Memory allocation
Memory release or “Garbage Collection” (GC)
Generations
Large Object Heap (LOH)
Special segment for large objects (>85KB)
Collected only during full garbage collection
Not compacted (by default) -> fragmentation!
Fragmentation can cause OutOfMemoryException
10. The .NET garbage collector
Runs very often for gen0
Short-lived objects, few references, fast to clean
Local variable, web request/response
Higher generation
Usually more references, slower to clean
GC pauses the running application to do its thing
Usually short, except when not…
Background GC (enabled by default)
Concurrent with application threads
May still introduce short locks/pauses, usually just for one thread
11. The .NET garbage collector
When does it run? Vague… But usually:
Out of memory condition – when the system fails to allocate or re-allocate memory
After some significant allocation – if X memory is allocated since previous GC
Failure of allocating some native resources – internal to .NET
Profiler – when triggered from profiler API
Forced – when calling methods on System.GC
Application moves to background
GC is not guaranteed to run
http://blogs.msdn.com/b/oldnewthing/archive/2010/08/09/10047586.aspx
http://blogs.msdn.com/b/abhinaba/archive/2008/04/29/when-does-the-net-compact-framework-garbage-collector-run.aspx
12. Helping the GC, avoid pauses
Optimize allocations (use struct when it makes sense, Span<T>, object pooling)
Don’t allocate when not needed
Make use of IDisposable / using statement
Clean up references, giving the GC an easy job
Weak references
Allow the GC to collect these objects, no need for checks
Finalizers
Beware! Moved to finalizer queue -> always gen++
15. When is memory allocated?
Not for value types (int, bool, struct, decimal, enum, float, byte, long, …)
Allocated on stack, not on heap
Not managed by garbage collector
For reference types
When you new
When you load data into a variable, object, property, ...
16. Hidden allocations!
Boxing!
Put an int in a box
Take an int out of a box
Lambda’s/closures
Allocate compiler-generated
DisplayClass to capture state
Params arrays
And more!
int i = 42;
// boxing - wraps the value type in an "object box"
// (allocating a System.Object)
object o = i;
// unboxing - unpacking the "object box" into an int again
// (CPU effort to unwrap)
int j = (int)o;
17. How to find them?
Past experience
Intermediate Language (IL)
Profiler
“Heap allocations viewer”
ReSharper Heap Allocations Viewer plugin
Roslyn’s Heap Allocation Analyzer
19. Measure!
Don’t do premature optimization – measure!
Allocations don’t always matter (that much)
Measure!
How frequently are we allocating?
How frequently are we collecting?
What generation do we end up on?
Are our allocations introducing pauses?
www.jetbrains.com/dotmemory (and www.jetbrains.com/dottrace)
23. Object pools / object re-use
Re-use objects / collections (when it makes sense)
Fewer allocations, fewer objects for the GC to scan
Less memory traffic that can trigger a full GC
Object pooling - object pool pattern
Create a pool of objects that can be re-used
https://www.codeproject.com/articles/20848/c-object-pooling
“Optimize ASP.NET Core” - https://github.com/aspnet/AspLabs/issues/3
System.Buffers.ArrayPool
24. Garbage Collector summary
GC is optimized for high memory traffic in short-lived objects
Use that knowledge! Don’t fear allocations!
Don’t optimize what should not be optimized…
GC is the concept that makes .NET / C# tick – use it!
Know when allocations happen
GC is awesome
Gen2 collection that stop the world not so much…
Measure!
26. How would you...
…build a managed type system, store in memory, CPU/memory friendly
Probably:
Store type info (what’s in there, what’s the offset of fieldN, …)
Store field data (just data)
Store method pointers
Inheritance information
28. Stuff on the Managed Heap
(scroll down for more...)
29. Theory is nice...
Microsoft.Diagnostics.Runtime (ClrMD)
“ClrMD is a set of advanced APIs for programmatically inspecting a crash dump of
a .NET program much in the same way that the SOS Debugging Extensions (SOS)
do. This allows you to write automated crash analysis for your applications as well
as automate many common debugger tasks. In addition to reading crash dumps
ClrMD also allows supports attaching to live processes.”
“LINQ-to-heap”
Maarten’s definition
31. But... Why?
Programmatic insight into memory space of a running project
Unit test critical paths and assert behavior (did we clean up what we expected?)
Capture memory issues in running applications
Other (easier) options in this space
dotMemory Unit (JetBrains)
Benchmark.NET
34. Conclusion
Garbage Collector (GC) optimized for high memory traffic + short-lived objects
Don’t fear allocations! But beware of gen2 “stop the world”
Don’t optimize what should not be optimized…
Measure!
Using a profiler/memory analysis tool
ClrMD to automate inspections
dotMemory Unit, Benchmark.NET, … to profile unit tests
Blog series: https://blog.maartenballiauw.be
Application roots: Typically, these are global and static object pointers, local variables, and CPU registers.
Application roots: Typically, these are global and static object pointers, local variables, and CPU registers.
Application roots: Typically, these are global and static object pointers, local variables, and CPU registers.
Open TripDownMemoryLane.sln
Show WeakReferenceDemo (demo “1-1”)
Explain weak reference allows GC to collect reference
Show Cache object – has weak references to data, we expect these to probably be cleaned up by GC
Attach profiler, run demo “1-1”, snapshot, see 20 instances of WeakReference<Data>
Snapshot again, compare – see WeakReference<Data> has been regenerated a couple of times
Show DisposeObjectsDemo (demo “1-2”)
Explain first demo does not dispose and relies on GC + finalizers. This will mean our object remains in memory for two GC cycles!
Explain dispose does clean them up and requires only one cycle
In SampleDisposable, explain GC.SuppressFinalize -> tell the GC no finalizer queue work is needed here!
Open TripDownMemoryLane.sln
Show Demo02_Random
Open IL viewer tool window, show what happens in IL for each code sample
Explain IL viewer + hovering statements to see what they do
BoxingRing() – show boxing and unboxing statements in IL, explain they consume CPU and allocate an object
ParamsArray() – the call to ParamsArrayImpl() actually allocates a new string array! CPU + memory
AverageWithinBounds() – temporary class is created to capture state of all variables, then passed around
IL_0000: newobj instance void TripDownMemoryLane.Demo02.Demo02_Random/'<>c__DisplayClass3_0'::.ctor()
Lambdas() – same thing, temporary class to capture state in the loop
IL_001f: newobj instance void Allocatey.Talk.Demo02_Random/'<>c__DisplayClass4_0'::.ctor()
Show Demo02_ValidateArgumentsDemo – this one is fun!
Explain what we want to do: build a guard function – check a condition, show error
First one is the easy one, but it allocates a string and runs string.Format
Second one is better – does not allocate the string! But does allocate a function and a state capture...
Third one – allocates an array (params)
Fourth one – no allocations, yay! Using overloads...
Show heap allocations viewer!
Open TripDownMemoryLane.sln
Show BeersDemoUnoptimized (demo “3-1” and “3-2”)
Explain we’re building an application that shows all beers in the world and their ratings
Stored in beers.json (show document) with beer name, brewery, number of votes
For a view in our application, read this file into a multi-dimensional dictionary that contains breweries, beers, and their rating
Show BeerLoader and note the dictionary format
Show LoadBeersInsane and explain this is BAD BAD BAD because of the high memory usage
Show LoadBeersUnoptimized, explain what it does, optimized against the insane version as we’re streaming over our file
Load beers a number of times
Inspect snapshots
GC is very visible
Most memory in gen2 (we keep our beers around)
Compare two snapshots: high traffic on dictionary items
(Lots of string allocations - JSON.NET)
Show LoadBeersOptimized, explain what it does, re-using dictionary and updating items as we read the JSON
Load beers a number of times
Inspect snapshots
GC is almost invisible
Less allocations happening
Compare two snapshots: almost no traffic
Less work for GC, less pauses!
Measure and make it look good!
There is an old adage in IT that says “don’t do premature optimization”. In other words: maybe some allocations are okay to have, as the GC will take care of cleaning them up anyway. While some do not agree with this, I believe in the middle ground.
The garbage collector is optimized for high memory traffic in short-lived objects, and I think it’s okay to make use of what the .NET runtime has to offer us here. If it’s in a critical path of a production application, fewer allocations are better, but we can’t write software with zero allocations - it’s what our high-level programming language uses to make our developer life easier. It’s not okay to have objects go to gen2 and stay there when in fact they should be gone from memory.
Learn where allocations happen, using any of the above methods, and profile your production applications frequently to see if there are large objects in higher generations of the heap that don’t belong there.
Will print “true” twice.
Open our demo application in dotPeek
Explain PE headers
Show #US table
Open StringAllocationDemo class. Jump to IL code, show ldstr statement for strings that are in #US table
Code = trick question, what if we enter same value twice? String equals, reference not equals!
How many strings are stored
How many strings are stored
Open ClrMD.sln
Explain: two projects, one target application, one running ClrMD to analyze what we have
Open ClrMD.Explorer.Program, show attaching ClrMD
Get CLR version – gets info about the current CLR version
Get runtime – gets info about the actual runtime hosting our app
Show DumpClrInfo – get info, stress DAC data access components location – defines the runtime structures, used by ClrMD and VS Debugger etc to explore runtime while debugging/profiling/...
Explore DumpHeapObjects, stress the heap structure
Loop object addresses - foreach (var objectAddress in generation)
Get type of object at address - var type = heap.GetObjectType(objectAddress.Ptr);
Use type info to get value - type.GetValue(objectAddress.Ptr)
Explore type autocomplete – structure to get enum, method addresses, ...
Open TestsWithDMU.sln
Explain: similar Clock leak as in previous demo
Two unit tests that create the clock, and timer. Then run GC.Collect, then use dMU to check whether instances are left in memory.
Easy way to test, after investigation, when a memory leak comes back (or not)