D-Bus is a message bus system that allows applications to communicate locally within a single machine. It provides inter-process communication (IPC) and allows services to publish data to applications via method calls, signals or properties. Key aspects include objects, proxies, methods, signals and interfaces that define how processes connect and exchange messages through the D-Bus daemon. It is commonly used on desktop systems but is not well-suited for internet or distributed applications.
The TC Flower Classifier allows control of packets based on flows determined by matching of well-known packet fields and metadata. This is inspired by similar flow classification described by OpenFlow and implemented by Open vSwitch. Offload of the TC Flower classifier and related modules provides a powerful mechanism to both increase throughput and reduce CPU utilisation for users of such flow-based systems. This presentation will give an overview of the evolution of offload of the TC Flower classifier: where it came from, the current status and possible future directions.
Tutorial: Using GoBGP as an IXP connecting routerShu Sugimoto
- Show you how GoBGP can be used as a software router in conjunction with quagga
- (Tutorial) Walk through the setup of IXP connecting router using GoBGP
SOSCON 2019.10.17
What are the methods for packet processing on Linux? And how fast are each packet processing methods? In this presentation, we will learn how to handle packets on Linux (User space, socket filter, netfilter, tc), and compare performance with analysis of where each packet processing is done in the network stack (hook point). Also, we will discuss packet processing using XDP, an in-kernel fast-path recently added to the Linux kernel. eXpress Data Path (XDP) is a high-performance programmable network data-path within the Linux kernel. The XDP is located at the lowest level of access through SW in the network stack, the point at which driver receives the packet. By using the eBPF infrastructure at this hook point, the network stack can be expanded without modifying the kernel.
Daniel T. Lee (Hoyeon Lee)
@danieltimlee
Daniel T. Lee currently works as Software Engineer at Kosslab and contributing to Linux kernel BPF project. He has interest in cloud, Linux networking, and tracing technologies, and likes to analyze the kernel's internal using BPF technology.
Most file systems have methods to assign permissions or access rights to specific users and groups of users.
These system control the ability of the users to view, change, navigate, and execute the contents of the file system.
Permissions on the linux- systems are managed in three distinct scopes or classes. Theses scopes are known as users, groups or others.
The TC Flower Classifier allows control of packets based on flows determined by matching of well-known packet fields and metadata. This is inspired by similar flow classification described by OpenFlow and implemented by Open vSwitch. Offload of the TC Flower classifier and related modules provides a powerful mechanism to both increase throughput and reduce CPU utilisation for users of such flow-based systems. This presentation will give an overview of the evolution of offload of the TC Flower classifier: where it came from, the current status and possible future directions.
Tutorial: Using GoBGP as an IXP connecting routerShu Sugimoto
- Show you how GoBGP can be used as a software router in conjunction with quagga
- (Tutorial) Walk through the setup of IXP connecting router using GoBGP
SOSCON 2019.10.17
What are the methods for packet processing on Linux? And how fast are each packet processing methods? In this presentation, we will learn how to handle packets on Linux (User space, socket filter, netfilter, tc), and compare performance with analysis of where each packet processing is done in the network stack (hook point). Also, we will discuss packet processing using XDP, an in-kernel fast-path recently added to the Linux kernel. eXpress Data Path (XDP) is a high-performance programmable network data-path within the Linux kernel. The XDP is located at the lowest level of access through SW in the network stack, the point at which driver receives the packet. By using the eBPF infrastructure at this hook point, the network stack can be expanded without modifying the kernel.
Daniel T. Lee (Hoyeon Lee)
@danieltimlee
Daniel T. Lee currently works as Software Engineer at Kosslab and contributing to Linux kernel BPF project. He has interest in cloud, Linux networking, and tracing technologies, and likes to analyze the kernel's internal using BPF technology.
Most file systems have methods to assign permissions or access rights to specific users and groups of users.
These system control the ability of the users to view, change, navigate, and execute the contents of the file system.
Permissions on the linux- systems are managed in three distinct scopes or classes. Theses scopes are known as users, groups or others.
Linux offers an extensive selection of programmable and configurable networking components from traditional bridges, encryption, to container optimized layer 2/3 devices, link aggregation, tunneling, several classification and filtering languages all the way up to full SDN components. This talk will provide an overview of many Linux networking components covering the Linux bridge, IPVLAN, MACVLAN, MACVTAP, Bonding/Team, OVS, classification & queueing, tunnel types, hidden routing tricks, IPSec, VTI, VRF and many others.
Let's trace Linux Lernel with KGDB @ COSCUP 2021Jian-Hong Pan
https://coscup.org/2021/en/session/39M73K
https://www.youtube.com/watch?v=L_Gyvdl_d_k
Engineers have plenty of debug tools for user space programs development, code tracing, debugging and analyzing. Except “printk”, do we have any other debug tools for Linux kernel development? The “KGDB” mentioned in Linux kernel document provides another possibility.
Will share how to experiment with the KGDB in a virtual machine. And, use GDB + OpenOCD + JTAG + Raspberry Pi in the real environment as the demo in this talk.
開發 user space 軟體時,工程師們有方便的 debug 工具進行查找、分析、除錯。但在 Linux kernel 的開發,除了 printk 外,還可以有哪些工具可以使用呢?從 Linux kernel document 可以看到 KGDB 相關的資訊,提供了在 kernel 除錯時的另一個可能性。
本次將分享,從建立最簡單環境的虛擬機機開始,到實際使用 GDB + OpenOCD + JTAG + Raspberry Pi 當作展示範例。
Kubernetes is a solid leader among different cloud orchestration engines and its adoption rate is growing on a daily basis. Naturally people want to run both their applications and databases on the same infrastructure.
There are a lot of ways to deploy and run PostgreSQL on Kubernetes, but most of them are not cloud-native. Around one year ago Zalando started to run HA setup of PostgreSQL on Kubernetes managed by Patroni. Those experiments were quite successful and produced a Helm chart for Patroni. That chart was useful, albeit a single problem: Patroni depended on Etcd, ZooKeeper or Consul.
Few people look forward to deploy two applications instead of one and support them later on. In this talk I would like to introduce Kubernetes-native Patroni. I will explain how Patroni uses Kubernetes API to run a leader election and store the cluster state. I’m going to live-demo a deployment of HA PostgreSQL cluster on Minikube and share our own experience of running more than 130 clusters on Kubernetes.
Patroni is a Python open-source project developed by Zalando in cooperation with other contributors on GitHub: https://github.com/zalando/patroni
How to do a LIVE-demo with minikube:
1. git clone https://github.com/zalando/patroni
2. cd patroni
3. git checkout feature/demo
4. cd kubernetes
5. open demo.sh and edit line #4 (specify the minikube context )
6. docker build -t patroni .
7. may be docker push patroni
8. may be edit patroni_k8s.yaml line #22 and put the name of patroni image you build there
9. install tmux
10. run tmux in one terminal
11. run bash demo.sh in another terminal and press Enter from time to time
The Art of Database Experiments – PostgresConf Silicon Valley 2018 / San JoseNikolay Samokhvalov
Future database administration will be highly automated. Until then, we still live in a world where extensive manual interactions are required from a skilled DBA. This will change soon as more "autonomous databases" reach maturity and enter the production environment.
Postgres-specific monitoring tools and systems continue to improve, detecting and analyzing performance issues and bottlenecks in production databases. However, while these tools can detect current issues, they require highly-experienced DBAs to analyze and recommend mitigations.
In this session, the speaker will present the initial results of the POSTGRES.AI project – Nancy CLI, a unified way to manage automated database experiments. Nancy CLI is an automated database management framework based on well-known open-source projects and incorporating major open-source tools and Postgres modules: pgBadger, pg_stat_kcache, auto_explain, pgreplay, and others.
Originally developed with the goal to simulate various SQL query use cases in various environments and collect data to train ML models, Nancy CLI turned out to be very a universal framework that can play a crucial role in CI/CD pipelines in any company.
Using Nancy CLI, casual DBAs and any engineers can easily conduct automated experiments today, either on AWS EC2 Spot instances or on any other servers. All you need is to tell Nancy which database to use, specify workload (synthetic or "real", generated based on the Postgres logs), and what you want to test – say, check how a new index will affect all most expensive query groups from pg_stat_statements, or compare various values of "default_statistics_target". All the collected information with a very high level of confidence will give you understanding, how various queries and overall Postgres performance will be affected when you apply this change to production.
Title: Working Remotely (via SSH) Rocks!
Intro: Consistent & Persistent development environment from any location any client.
"SSH + TMUX + CLI" Rocks!
Nice material about "SSH Tunneling": http://www.slideshare.net/osoco/ssh-tunneling-recipes-10284950
In this session, we’ll review how previous efforts, including Netfilter, Berkley Packet Filter (BPF), Open vSwitch (OVS), and TC, approached the problem of extensibility. We’ll show you an open source solution available within the Red Hat Enterprise Linux kernel, where extending and merging some of the existing concepts leads to an extensible framework that satisfies the networking needs of datacenter and cloud virtualization.
Linux offers an extensive selection of programmable and configurable networking components from traditional bridges, encryption, to container optimized layer 2/3 devices, link aggregation, tunneling, several classification and filtering languages all the way up to full SDN components. This talk will provide an overview of many Linux networking components covering the Linux bridge, IPVLAN, MACVLAN, MACVTAP, Bonding/Team, OVS, classification & queueing, tunnel types, hidden routing tricks, IPSec, VTI, VRF and many others.
Let's trace Linux Lernel with KGDB @ COSCUP 2021Jian-Hong Pan
https://coscup.org/2021/en/session/39M73K
https://www.youtube.com/watch?v=L_Gyvdl_d_k
Engineers have plenty of debug tools for user space programs development, code tracing, debugging and analyzing. Except “printk”, do we have any other debug tools for Linux kernel development? The “KGDB” mentioned in Linux kernel document provides another possibility.
Will share how to experiment with the KGDB in a virtual machine. And, use GDB + OpenOCD + JTAG + Raspberry Pi in the real environment as the demo in this talk.
開發 user space 軟體時,工程師們有方便的 debug 工具進行查找、分析、除錯。但在 Linux kernel 的開發,除了 printk 外,還可以有哪些工具可以使用呢?從 Linux kernel document 可以看到 KGDB 相關的資訊,提供了在 kernel 除錯時的另一個可能性。
本次將分享,從建立最簡單環境的虛擬機機開始,到實際使用 GDB + OpenOCD + JTAG + Raspberry Pi 當作展示範例。
Kubernetes is a solid leader among different cloud orchestration engines and its adoption rate is growing on a daily basis. Naturally people want to run both their applications and databases on the same infrastructure.
There are a lot of ways to deploy and run PostgreSQL on Kubernetes, but most of them are not cloud-native. Around one year ago Zalando started to run HA setup of PostgreSQL on Kubernetes managed by Patroni. Those experiments were quite successful and produced a Helm chart for Patroni. That chart was useful, albeit a single problem: Patroni depended on Etcd, ZooKeeper or Consul.
Few people look forward to deploy two applications instead of one and support them later on. In this talk I would like to introduce Kubernetes-native Patroni. I will explain how Patroni uses Kubernetes API to run a leader election and store the cluster state. I’m going to live-demo a deployment of HA PostgreSQL cluster on Minikube and share our own experience of running more than 130 clusters on Kubernetes.
Patroni is a Python open-source project developed by Zalando in cooperation with other contributors on GitHub: https://github.com/zalando/patroni
How to do a LIVE-demo with minikube:
1. git clone https://github.com/zalando/patroni
2. cd patroni
3. git checkout feature/demo
4. cd kubernetes
5. open demo.sh and edit line #4 (specify the minikube context )
6. docker build -t patroni .
7. may be docker push patroni
8. may be edit patroni_k8s.yaml line #22 and put the name of patroni image you build there
9. install tmux
10. run tmux in one terminal
11. run bash demo.sh in another terminal and press Enter from time to time
The Art of Database Experiments – PostgresConf Silicon Valley 2018 / San JoseNikolay Samokhvalov
Future database administration will be highly automated. Until then, we still live in a world where extensive manual interactions are required from a skilled DBA. This will change soon as more "autonomous databases" reach maturity and enter the production environment.
Postgres-specific monitoring tools and systems continue to improve, detecting and analyzing performance issues and bottlenecks in production databases. However, while these tools can detect current issues, they require highly-experienced DBAs to analyze and recommend mitigations.
In this session, the speaker will present the initial results of the POSTGRES.AI project – Nancy CLI, a unified way to manage automated database experiments. Nancy CLI is an automated database management framework based on well-known open-source projects and incorporating major open-source tools and Postgres modules: pgBadger, pg_stat_kcache, auto_explain, pgreplay, and others.
Originally developed with the goal to simulate various SQL query use cases in various environments and collect data to train ML models, Nancy CLI turned out to be very a universal framework that can play a crucial role in CI/CD pipelines in any company.
Using Nancy CLI, casual DBAs and any engineers can easily conduct automated experiments today, either on AWS EC2 Spot instances or on any other servers. All you need is to tell Nancy which database to use, specify workload (synthetic or "real", generated based on the Postgres logs), and what you want to test – say, check how a new index will affect all most expensive query groups from pg_stat_statements, or compare various values of "default_statistics_target". All the collected information with a very high level of confidence will give you understanding, how various queries and overall Postgres performance will be affected when you apply this change to production.
Title: Working Remotely (via SSH) Rocks!
Intro: Consistent & Persistent development environment from any location any client.
"SSH + TMUX + CLI" Rocks!
Nice material about "SSH Tunneling": http://www.slideshare.net/osoco/ssh-tunneling-recipes-10284950
In this session, we’ll review how previous efforts, including Netfilter, Berkley Packet Filter (BPF), Open vSwitch (OVS), and TC, approached the problem of extensibility. We’ll show you an open source solution available within the Red Hat Enterprise Linux kernel, where extending and merging some of the existing concepts leads to an extensible framework that satisfies the networking needs of datacenter and cloud virtualization.
A brief introduction to task communication in real time operating system.It covers Inter-process communication like concepts of shared memory , message passing, remoteprocedure call .Interprocess communication (IPC) refers specifically to the mechanisms an operating system provides to allow the processes to manage shared data. Typically, applications can use IPC, categorized as clients and servers, where the client requests data and the server responds to client requests.Many applications are both clients and servers, as commonly seen in distributed computing.
Message Passing, Remote Procedure Calls and Distributed Shared Memory as Com...Sehrish Asif
Message Passing, Remote Procedure Calls and
Distributed Shared Memory as Communication Paradigms for Distributed Systems & Remote Procedure Call Implementation Using Distributed Algorithms
Inter-Process Communication in distributed systemsAya Mahmoud
Inter-Process Communication is at the heart of all distributed systems, so we need to know the ways that processes can exchange information.
Communication in distributed systems is based on Low-level message passing as offered by the underlying network.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
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See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
2. What is d-bus?
Desktop bus, IPC mechanism.
Medium for local communication between processes
running on the same host.
1:1 request-reply, 1:n publish-subscribe.
Structured view of the data.
messages can be validated and ill-formed messages rejected.
low-level C binding, also Java, Perl and Python.
2
3. Buses
Processes connect to the daemon
using the library.
p2p communication library:
used by any two processes in order to exchange
messages among themselves.
the daemon:
any number of processes may be connected at
any given time.
Multiple buses may be active
simultaneously.
system bus:
system-wide communication.
session bus:
single user's ongoing session.
● Addresses describes how to connect to bus such as "/tmp/.hiddensocket”. They completely
hidden from the client process by the dbus library.
3
4. Connections
When a connection is set up, the bus immediately assigns it an immutable bus
name that it will retain for as long as the bus exists.
Services under well-known names that are agreed upon by convention, like
org.freedesktop.DBus.
4
6. Objects
Created by a client process,
Exists within the context of that client's connection to the bus.
Message types carried by the bus:
Requests sent to objects by client processes.
Replies to requests, going from an object back to a requesting process.
One-way messages emanating from objects, broadcast to any connected clients
that have registered an interest in them.
6
7. Proxies
Local representation of an object that is really accessed through the bus, and
typically lives outside your program.
GLib binding’s proxies support failover.
7
8. Methods
When a client sends a request to an object, it sees this request as invoking a
method on the object.
Arguments can be passed and result back to the requester, along with either
result data or exception information.
Messages are encapsulated by d-bus library.
Both asynchronous & synchronous method invocation.
8
9. Signals
One-way communications come from an object and go client processes.
Client processes can register an interest in signals of a particular name
coming from a particular object.
There are no replies to signals.
No input and output parameters like methods do.
Allow clients to restrict their interest to cases where certain of the signal's
parameters match given values.
9
10. Interfaces
Every object supports particular methods and may emit particular signals.
These are specified in interfaces.
When a client invokes a method or listens for a signal, it must indicate the
object and the member {methods, signals} it is referring to.
10
13. furthermore; Activation
Bus daemon can be instructed to start clients automatically when needed.
To achieve that describe client in a service file.
Default path: /usr/share/dbus-1/services/*.service
For example: client program /usr/local/bin/bankcounter can be run to provide
well-known bus names com.bigmoneybank.Deposits and
com.bigmoneybank.Withdrawals.
# Sample bankcounter.service file
[D-BUS Service]
Names=com.bigmoneybank.Deposits;
com.bigmoneybank.Withdrawals
Exec=/usr/local/bin/bankcounter
13
14. Performance
One-to-one communication was about 2.5x slower than simply pushing the
data raw over a socket.
Bus daemon should be about twice as slow as one-to-one mode, because a
round trip involves four socket reads/writes rather than two socket
reads/writes.
Overhead comes from:
Abstraction penalty (marshalling)
Data validation (‘no validation’ mode exist, but not recommended)
Raw bandwidth isn't the only concern; D-Bus is designed to enable
asynchronous communication and avoid round trips. This is frequently a
more important performance issue than throughput.
14
15. Why D-Bus?
difference from other IPC protocols:
d-bus is also lifecycle tracking, service activation, security policy, and
other higher-level structure and assumptions.
not good for:
internet applications,
clustering, distributed swarms, peer-to-peer.
good for:
desktop application talks to other parts of the desktop session,
communications between system daemons and communications between
the desktop and system daemons.
15
17. Drawbacks
Used for control, not payload.
Inefficient (10 copies, 4 validations, 4 context switches per
duplex method call transaction)
No implicit timestamping.
Not available in boot time.
Security framework hooks happen in userspace.
retrieved from http://0pointer.de/public/lca.pdf
17
18. alternative: kdbus
Efficient (2 or fewer copies, 2 validations, 2 context switches per
duplex method call transaction).
Implicit timestamping.
Always available, from earliest boot to latest shutdown.
Security framework hooks happen in kernel space.
retrieved from http://0pointer.de/public/lca.pdf
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