Tag Archives: tracing

Integrating AWS X-Ray with AWS App Mesh

Post Syndicated from Ignacio Riesgo original https://aws.amazon.com/blogs/compute/integrating-aws-x-ray-with-aws-app-mesh/

This post is contributed by Lulu Zhao | Software Development Engineer II, AWS

 

AWS X-Ray helps developers and DevOps engineers quickly understand how an application and its underlying services are performing. When it’s integrated with AWS App Mesh, the combination makes for a powerful analytical tool.

X-Ray helps to identify and troubleshoot the root causes of errors and performance issues. It’s capable of analyzing and debugging distributed applications, including those based on a microservices architecture. It offers insights into the impact and reach of errors and performance problems.

In this post, I demonstrate how to integrate it with App Mesh.

Overview

App Mesh is a service mesh based on the Envoy proxy that makes it easy to monitor and control microservices. App Mesh standardizes how your microservices communicate, giving you end-to-end visibility and helping to ensure high application availability.

With App Mesh, it’s easy to maintain consistent visibility and network traffic control for services built across multiple types of compute infrastructure. App Mesh configures each service to export monitoring data and implements consistent communications control logic across your application.

A service mesh is like a communication layer for microservices. All communication between services happens through the mesh. Customers use App Mesh to configure a service mesh that contains virtual services, virtual nodes, virtual routes, and corresponding routes.

However, it’s challenging to visualize the way that request traffic flows through the service mesh while attempting to identify latency and other types of performance issues. This is particularly true as the number of microservices increases.

It’s in exactly this area where X-Ray excels. To show a detailed workflow inside a service mesh, I implemented a tracing extension called X-Ray tracer inside Envoy. With it, I ensure that I’m tracing all inbound and outbound calls that are routed through Envoy.

Traffic routing with color app

The following example shows how X-Ray works with App Mesh. I used the Color App, a simple demo application, to showcase traffic routing.

This app has two Go applications that are included in the AWS X-Ray Go SDK: color-gateway and color-teller. The color-gateway application is exposed to external clients and responds to http://service-name:port/color, which retrieves color from color-teller. I deployed color-app using Amazon ECS. This image illustrates how color-gateway routes traffic into a virtual router and then into separate nodes using color-teller.

 

The following image shows client interactions with App Mesh in an X-Ray service map after requests have been made to the color-gateway and to color-teller.

Integration

There are two types of service nodes:

  • AWS::AppMesh::Proxy is generated by the X-Ray tracing extension inside Envoy.
  • AWS::ECS::Container is generated by the AWS X-Ray Go SDK.

The service graph arrows show the request workflow, which you may find helpful as you try to understand the relationships between services.

To send Envoy-generated segments into X-Ray, install the X-Ray daemon. The following code example shows the ECS task definition used to install the daemon into the container.

{
    "name": "xray-daemon",

    "image": "amazon/aws-xray-daemon",

    "user": "1337",

    "essential": true,

    "cpu": 32,

    "memoryReservation": 256,

    "portMappings": [

        {

            "hostPort": 2000,

            "containerPort": 2000,

            "protocol": "udp"

         }

After the Color app successfully launched, I made a request to color-gateway to fetch a color.

  • First, the Envoy proxy appmesh/colorgateway-vn in front of default-gateway received the request and routed it to the server default-gateway.
  • Then, default-gateway made a request to server default-colorteller-white to retrieve the color.
  • Instead of directly calling the color-teller server, the request went to the default-gateway Envoy proxy and the proxy routed the call to color-teller.

That’s the advantage of using the Envoy proxy. Envoy is a self-contained process that is designed to run in parallel with all application servers. All of the Envoy proxies form a transparent communication mesh through which each application sends and receives messages to and from localhost while remaining unaware of the broader network topology.

For App Mesh integration, the X-Ray tracer records the mesh name and virtual node name values and injects them into the segment JSON document. Here is an example:

“aws”: {
	“app_mesh”: {
		“mesh_name”: “appmesh”,
		“virtual_node_name”: “colorgateway-vn”
	}
},

To enable X-Ray tracing through App Mesh inside Envoy, you must set two environment variable configurations:

  • ENABLE_ENVOY_XRAY_TRACING
  • XRAY_DAEMON_PORT

The first one enables X-Ray tracing using 127.0.0.1:2000 as the default daemon endpoint to which generated segments are sent. If the daemon you installed listens on a different port, you can specify a port value to override the default X-Ray daemon port by using the second configuration.

Conclusion

Currently, AWS X-Ray supports SDKs written in multiple languages (including Java, Python, Go, .NET, and .NET Core, Node.js, and Ruby) to help you implement your services. For more information, see Getting Started with AWS X-Ray.

Kernel 4.17 released

Post Syndicated from corbet original https://lwn.net/Articles/756373/rss

Linus has released the 4.17 kernel, which
will indeed be called “4.17”.
“No, I didn’t call it 5.0, even though all the git object count
numerology was in place for that. It will happen in the not _too_
distant future, and I’m told all the release scripts on kernel.org are
ready for it, but I didn’t feel there was any real reason for it.”

Headline features in this release include
improved load estimation in the CPU
scheduler,
raw
BPF tracepoints,
lazytime support in the XFS filesystem,
full in-kernel TLS protocol support,
histogram triggers for tracing,
mitigations for the latest Spectre variants,
and, of course, the removal of support for eight unloved processor
architectures.

ISP Questions Impartiality of Judges in Copyright Troll Cases

Post Syndicated from Andy original https://torrentfreak.com/isp-questions-impartiality-of-judges-in-copyright-troll-cases-180602/

Following in the footsteps of similar operations around the world, two years ago the copyright trolling movement landed on Swedish shores.

The pattern was a familiar one, with trolls harvesting IP addresses from BitTorrent swarms and tracing them back to Internet service providers. Then, after presenting evidence to a judge, the trolls obtained orders that compelled ISPs to hand over their customers’ details. From there, the trolls demanded cash payments to make supposed lawsuits disappear.

It’s a controversial business model that rarely receives outside praise. Many ISPs have tried to slow down the flood but most eventually grow tired of battling to protect their customers. The same cannot be said of Swedish ISP Bahnhof.

The ISP, which is also a strong defender of privacy, has become known for fighting back against copyright trolls. Indeed, to thwart them at the very first step, the company deletes IP address logs after just 24 hours, which prevents its customers from being targeted.

Bahnhof says that the copyright business appeared “dirty and corrupt” right from the get go, so it now operates Utpressningskollen.se, a web portal where the ISP publishes data on Swedish legal cases in which copyright owners demand customer data from ISPs through the Patent and Market Courts.

Over the past two years, Bahnhof says it has documented 76 cases of which six are still ongoing, 11 have been waived and a majority 59 have been decided in favor of mainly movie companies. Bahnhof says that when it discovered that 59 out of the 76 cases benefited one party, it felt a need to investigate.

In a detailed report compiled by Bahnhof Communicator Carolina Lindahl and sent to TF, the ISP reveals that it examined the individual decision-makers in the cases before the Courts and found five judges with “questionable impartiality.”

“One of the judges, we can call them Judge 1, has closed 12 of the cases, of which two have been waived and the other 10 have benefitted the copyright owner, mostly movie companies,” Lindahl notes.

“Judge 1 apparently has written several articles in the magazine NIR – Nordiskt Immateriellt Rättsskydd (Nordic Intellectual Property Protection) – which is mainly supported by Svenska Föreningen för Upphovsrätt, the Swedish Association for Copyright (SFU).

“SFU is a member-financed group centered around copyright that publishes articles, hands out scholarships, arranges symposiums, etc. On their website they have a public calendar where Judge 1 appears regularly.”

Bahnhof says that the financiers of the SFU are Sveriges Television AB (Sweden’s national public TV broadcaster), Filmproducenternas Rättsförening (a legally-oriented association for filmproducers), BMG Chrysalis Scandinavia (a media giant) and Fackförbundet för Film och Mediabranschen (a union for the movie and media industry).

“This means that Judge 1 is involved in a copyright association sponsored by the film and media industry, while also judging in copyright cases with the film industry as one of the parties,” the ISP says.

Bahnhof’s also has criticism for Judge 2, who participated as an event speaker for the Swedish Association for Copyright, and Judge 3 who has written for the SFU-supported magazine NIR. According to Lindahl, Judge 4 worked for a bureau that is partly owned by a board member of SFU, who also defended media companies in a “high-profile” Swedish piracy case.

That leaves Judge 5, who handled 10 of the copyright troll cases documented by Bahnhof, waiving one and deciding the remaining nine in favor of a movie company plaintiff.

“Judge 5 has been questioned before and even been accused of bias while judging a high-profile piracy case almost ten years ago. The accusations of bias were motivated by the judge’s membership of SFU and the Swedish Association for Intellectual Property Rights (SFIR), an association with several important individuals of the Swedish copyright community as members, who all defend, represent, or sympathize with the media industry,” Lindahl says.

Bahnhof hasn’t named any of the judges nor has it provided additional details on the “high-profile” case. However, anyone who remembers the infamous trial of ‘The Pirate Bay Four’ a decade ago might recall complaints from the defense (1,2,3) that several judges involved in the case were members of pro-copyright groups.

While there were plenty of calls to consider them biased, in May 2010 the Supreme Court ruled otherwise, a fact Bahnhof recognizes.

“Judge 5 was never sentenced for bias by the court, but regardless of the court’s decision this is still a judge who shares values and has personal connections with [the media industry], and as if that weren’t enough, the judge has induced an additional financial aspect by participating in events paid for by said party,” Lindahl writes.

“The judge has parties and interest holders in their personal network, a private engagement in the subject and a financial connection to one party – textbook characteristics of bias which would make anyone suspicious.”

The decision-makers of the Patent and Market Court and their relations.

The ISP notes that all five judges have connections to the media industry in the cases they judge, which isn’t a great starting point for returning “objective and impartial” results. In its summary, however, the ISP is scathing of the overall system, one in which court cases “almost looked rigged” and appear to be decided in favor of the movie company even before reaching court.

In general, however, Bahnhof says that the processes show a lack of individual attention, such as the court blindly accepting questionable IP address evidence supplied by infamous anti-piracy outfit MaverickEye.

“The court never bothers to control the media company’s only evidence (lists generated by MaverickMonitor, which has proven to be an unreliable software), the court documents contain several typos of varying severity, and the same standard texts are reused in several different cases,” the ISP says.

“The court documents show a lack of care and control, something that can easily be taken advantage of by individuals with shady motives. The findings and discoveries of this investigation are strengthened by the pure numbers mentioned in the beginning which clearly show how one party almost always wins.

“If this is caused by bias, cheating, partiality, bribes, political agenda, conspiracy or pure coincidence we can’t say for sure, but the fact that this process has mainly generated money for the film industry, while citizens have been robbed of their personal integrity and legal certainty, indicates what forces lie behind this machinery,” Bahnhof’s Lindahl concludes.

Source: TF, for the latest info on copyright, file-sharing, torrent sites and more. We also have VPN reviews, discounts, offers and coupons.

Monitoring for Everyone

Post Syndicated from Blogs on Grafana Labs Blog original https://grafana.com/blog/2018/05/23/monitoring-for-everyone/

Øredev – Carl Bergquist – Monitoring for Everyone What is monitoring?
What do the terms log, metric, and distributed tracing actually mean?
What makes a good alert?
Why should I care?
At a recent developer conference in Malmö, Sweden, I gave a presentation on monitoring and observability to discuss the high level concepts and common tools that are out there.
Monitoring and observability can easily become quite complex, but at the heart of it, we simply want to know how our systems are performing, and when performance drops – be able to find out why.

All Systems Go! 2018 CfP Open

Post Syndicated from Lennart Poettering original http://0pointer.net/blog/all-systems-go-2018-cfp-open.html

The All Systems Go! 2018 Call for Participation is Now Open!

The Call for Participation (CFP) for All Systems Go!
2018 is now open. We’d like to invite you
to submit your proposals for consideration to the CFP submission
site.

ASG image

The CFP will close on July 30th. Notification of acceptance and
non-acceptance will go out within 7 days of the closing of the CFP.

All topics relevant to foundational open-source Linux technologies are
welcome. In particular, however, we are looking for proposals
including, but not limited to, the following topics:

  • Low-level container executors and infrastructure
  • IoT and embedded OS infrastructure
  • BPF and eBPF filtering
  • OS, container, IoT image delivery and updating
  • Building Linux devices and applications
  • Low-level desktop technologies
  • Networking
  • System and service management
  • Tracing and performance measuring
  • IPC and RPC systems
  • Security and Sandboxing

While our focus is definitely more on the user-space side of things,
talks about kernel projects are welcome, as long as they have a clear
and direct relevance for user-space.

For more information please visit our conference
website!

[$] Using user-space tracepoints with BPF

Post Syndicated from corbet original https://lwn.net/Articles/753601/rss

Much has been written on LWN about dynamically instrumenting kernel
code. These features are also available to user-space code with a
special kind of probe known as a User Statically-Defined Tracing
(USDT) probe. These probes provide a low-overhead way of
instrumenting user-space code and provide a convenient way to debug applications
running in production. In this final article of the BPF and BCC series
we’ll look at where USDT probes come from and how you can use them to
understand the behavior of your own applications.

Tracing Stolen Bitcoin

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/03/tracing_stolen_.html

Ross Anderson has a really interesting paper on tracing stolen bitcoin. From a blog post:

Previous attempts to track tainted coins had used either the “poison” or the “haircut” method. Suppose I open a new address and pay into it three stolen bitcoin followed by seven freshly-mined ones. Then under poison, the output is ten stolen bitcoin, while under haircut it’s ten bitcoin that are marked 30% stolen. After thousands of blocks, poison tainting will blacklist millions of addresses, while with haircut the taint gets diffused, so neither is very effective at tracking stolen property. Bitcoin due-diligence services supplant haircut taint tracking with AI/ML, but the results are still not satisfactory.

We discovered that, back in 1816, the High Court had to tackle this problem in Clayton’s case, which involved the assets and liabilities of a bank that had gone bust. The court ruled that money must be tracked through accounts on the basis of first-in, first out (FIFO); the first penny into an account goes to satisfy the first withdrawal, and so on.

Ilia Shumailov has written software that applies FIFO tainting to the blockchain and the results are impressive, with a massive improvement in precision. What’s more, FIFO taint tracking is lossless, unlike haircut; so in addition to tracking a stolen coin forward to find where it’s gone, you can start with any UTXO and trace it backwards to see its entire ancestry. It’s not just good law; it’s good computer science too.