jm + docker   89

Nextflow - A DSL for parallel and scalable computational pipelines
Data-driven computational pipelines

Nextflow enables scalable and reproducible scientific workflows using software containers. It allows the adaptation of pipelines written in the most common scripting languages.

Its fluent DSL simplifies the implementation and the deployment of complex parallel and reactive workflows on clouds and clusters.


GPLv3 licensed, open source
computation  workflows  pipelines  batch  docker  ops  open-source 
11 days ago by jm
Kubernetes Best Practices // Speaker Deck
A lot of these are general Docker/containerisation best practices, too.

(via Devops Weekly)
k8s  kubernetes  devops  ops  containers  docker  best-practices  tips  packaging 
26 days ago by jm
How Did I “Hack” AWS Lambda to Run Docker Containers?
Running Docker containers in Lambda using a usermode-docker hack -- hacky as hell but fun ;) Lambda should really support native Docker though
docker  lambda  aws  serverless  ops  hacks  udocker 
7 weeks ago by jm
lambci/docker-lambda
A sandboxed local environment that replicates the live AWS Lambda environment almost identically – including installed software and libraries, file structure and permissions, environment variables, context objects and behaviors – even the user and running process are the same.


(via og-aws)
docker  lambda  images  testing  aws  serverless 
9 weeks ago by jm
Instead of containerization, give me strong config & deployment primitives
Reasonable list of things Docker does badly at the moment, and a call to fix them. I still think Docker/rkt are a solid approach, if not 100% there yet though
docker  containers  complaining  whinge  networking  swarm  deployment  architecture  build  packaging 
april 2017 by jm
Capturing all the flags in BSidesSF CTF by pwning Kubernetes/Google Cloud
good exploration of the issues with running a CTF challenge (or any other secure infrastructure!) atop Kubernetes and a cloud platform like GCE
gce  google-cloud  kubernetes  security  docker  containers  gke  ctf  hacking  exploits 
april 2017 by jm
Segment.com on cost savings using DynamoDB, autoscaling and ECS
great post.

1. DynamoDB hot shards were a big problem -- and it is terrible that diagnosing this requires a ticket to AWS support! This heat map should be a built-in feature.

2. ECS auto-scaling gets a solid thumbs-up.

3. Switching from ELB to ALB lets them set ports dynamically for individual ECS Docker containers, and then pack as many containers as will fit on a giant EC2 instance.

4. Terraform modules to automate setup and maintainance of ECS, autoscaling groups, and ALBs
terraform  segment  architecture  aws  dynamodb  alb  elb  asg  ecs  docker 
march 2017 by jm
ctop
Top for containers (ie Docker)
docker  containers  top  ops  go  monitoring  cpu 
march 2017 by jm
pachyderm
'Containerized Data Analytics':
There are two bold new ideas in Pachyderm:

Containers as the core processing primitive
Version Control for data

These ideas lead directly to a system that's much more powerful, flexible and easy to use.

To process data, you simply create a containerized program which reads and writes to the local filesystem. You can use any tools you want because it's all just going in a container! Pachyderm will take your container and inject data into it. We'll then automatically replicate your container, showing each copy a different chunk of data. With this technique, Pachyderm can scale any code you write to process up to petabytes of data (Example: distributed grep).

Pachyderm also version controls all data using a commit-based distributed filesystem (PFS), similar to what git does with code. Version control for data has far reaching consequences in a distributed filesystem. You get the full history of your data, can track changes and diffs, collaborate with teammates, and if anything goes wrong you can revert the entire cluster with one click!

Version control is also very synergistic with our containerized processing engine. Pachyderm understands how your data changes and thus, as new data is ingested, can run your workload on the diff of the data rather than the whole thing. This means that there's no difference between a batched job and a streaming job, the same code will work for both!
analytics  data  containers  golang  pachyderm  tools  data-science  docker  version-control 
february 2017 by jm
How-to Debug a Running Docker Container from a Separate Container
arguably this shouldn't be required -- building containers without /bin/sh, strace, gdb etc. is just silly
strace  docker  ops  debugging  containers 
february 2017 by jm
10 Most Common Reasons Kubernetes Deployments Fail
some real-world failure cases and how to fix them
kubernetes  docker  ops 
february 2017 by jm
Amazon EC2 Container Service Plugin - Jenkins - Jenkins Wiki
neat, relatively new plugin to use ECS as a autoscaling node fleet in Jenkins
ec2  ecs  aws  jenkins  docker  plugins 
february 2017 by jm
Julia Evans reverse engineers Skyliner.io
simple usage of Docker, blue/green deploys, and AWS ALBs
docker  alb  aws  ec2  blue-green-deploys  deployment  ops  tools  skyliner  via:jgilbert 
november 2016 by jm
Testing Docker multi-host network performance - Percona Database Performance Blog
wow, Docker Swarm looks like a turkey right now if performance is important. Only "host" gives reasonably perf numbers
docker  networking  performance  ops  benchmarks  testing  swarm  overlay  calico  weave  bridge 
november 2016 by jm
Measuring Docker IO overhead - Percona Database Performance Blog
See also https://www.percona.com/blog/2016/02/05/measuring-docker-cpu-network-overhead/ for the CPU/Network equivalent. The good news is that nowadays it's virtually 0 when the correct settings are used
docker  percona  overhead  mysql  deployment  performance  ops  containers 
november 2016 by jm
J1 2015 "Debugging Java Apps in Containers: No Heavy Welding Gear Required"
Some good slides with tips on running java apps in production in Docker
java  docker  ops  containers 
september 2016 by jm
Skyliner
Coda Hale's new gig on how they're using Docker, AWS, etc. I like this: "Use containers. Not too much. Mostly for packaging."
docker  aws  packaging  ops  devops  containers  skyliner 
september 2016 by jm
AWS Case Study: mytaxi
ECS, Docker, ELB, SQS, SNS, RDS, VPC, and spot instances. Pretty canonical setup these days...
The mytaxi app is also now able to predict daily and weekly spikes. In addition, it has gained the elasticity required to meet demand during special events. Herzberg describes a typical situation on New Year's Eve: “Shortly before midnight everyone needs a taxi to get to parties, and after midnight people want to go home. In past years we couldn't keep up with the demand this generated, which was around three and a half times as high as normal. In November 2015 we moved our Docker container architecture to Amazon ECS, and for the first time ever in December we were able to celebrate a new year in which our system could handle the huge number of requests without any crashes or interruptions—an accomplishment that we were extremely proud of. We had faced the biggest night on the calendar without any downtime.”
mytaxi  aws  ecs  docker  elb  sqs  sns  rds  vpc  spot-instances  ops  architecture 
august 2016 by jm
Some thoughts on operating containers
R.I.Pienaar talks about the conventions he uses when containerising; looks like a decent approach.
ops  containers  docker  ripienaar  packaging 
june 2016 by jm
grammarly/rocker
backward compatible replacement for Dockerfile. Yes, you can take any Dockerfile, rename it to Rockerfile and use rocker build instead of docker build. ... Rocker aims to solve the following use cases, which are painful with plain Docker:

Mount reusable volumes on build stage, so dependency management tools may use cache between builds.
Share ssh keys with build (for pulling private repos, etc.), while not leaving them in the resulting image.
Build and run application in different images, be able to easily pass an artifact from one image to another, ideally have this logic in a single Dockerfile.
Tag/Push images right from Dockerfiles.
Pass variables from shell build command so they can be substituted to a Dockerfile.
And more. These are the most critical issues that were blocking our adoption of Docker at Grammarly.

The most challenging part is caching. While implementing those features seems to be not a big deal, it's not trivial to do that just by utilising Docker’s image cache (the one that docker build does). Actually, it is the main reason why those features are still not in Docker. With Rocker we achieve this by introducing a set of trade-offs. Search this page for "trade-off" to find out more details.
docker  rocker  build  containers  dockerfiles 
may 2016 by jm
fiunchinho/dockerize-me
'Tired of copy/pasting Dockerfiles around? Not sure about best practices for Dockerfiles or Docker entry points? This tool lets you Dockerize your applications using best practices to define your Dockerfile and Docker entry point files.'

The best practices in question are defined here: https://github.com/docker-library/official-images#review-guidelines
docker  dockerfile  images  build  best-practices  alpine  containers 
may 2016 by jm
GitLab Container Registry
GitLab continue to out-innovate Github, which is just wanking around with breaking the UI these days
gitlab  github  git  ci  cd  containers  docker  deployment  coding 
may 2016 by jm
The Challenges of Container Configuration // Speaker Deck
Some good advice on Docker metadata/config from Gareth Rushgrove
docker  metadata  configuration  build  devops  dev  containers  slidfes 
may 2016 by jm
Linux kernel bug delivers corrupt TCP/IP data to Mesos, Kubernetes, Docker containers — Vijay Pandurangan
Bug in the "veth" driver skips TCP checksums. Reminder: app-level checksums are important
checksums  tcp  veth  ethernet  drivers  linux  kernel  bugs  docker 
april 2016 by jm
Running Docker on AWS from the ground up
Advantages/disavantages section right at the bottom is good.
ECS, believe it or not, is one of the simplest Schedulers out there. Most of the other alternatives I’ve tried offer all sorts of fancy bells & whistles, but they are either significantly more complicated to understand (lots of new concepts), take too much effort to set up (lots of new technologies to install and run), are too magical (and therefore impossible to debug), or some combination of all three. That said, ECS also leaves a lot to be desired.
aws  docker  ecs  ec2  schedulers 
april 2016 by jm
Ruby in Production: Lessons Learned — Medium
Based on the pain we've had trying to bring our Rails services up to the quality levels required, this looks pretty accurate in many respects. I'd augment this advice by saying: avoid RVM; use Docker.
rvm  docker  ruby  production  rails  ops 
march 2016 by jm
Argon2 code audits - part one - Infer
A pretty viable way to run Facebook's Infer dataflow static analysis tool (which is otherwise quite a bear to run).
infer  facebook  java  clang  errors  static-analysis  lint  dataflow  docker 
february 2016 by jm
About Microservices, Containers and their Underestimated Impact on Network Performance
shock horror, Docker-SDN layers have terrible performance. Still pretty lousy perf impacts from basic Docker containerization, presumably without "--net=host" (which is apparently vital)
docker  performance  network  containers  sdn  ops  networking  microservices 
january 2016 by jm
Amazon EC2 Container Registry
hooray, Docker registry here at last
ecs  docker  registry  ops  containers  aws 
december 2015 by jm
Why We Chose Kubernetes Over ECS
3 months ago when we, at nanit.com, came to evaluate which Docker orchestration framework to use, we gave ECS the first priority. We were already familiar with AWS services, and since we already had our whole infrastructure there, it was the default choice. After testing the service for a while we had the feeling it was not mature enough and missing some key features we needed (more on that later), so we went to test another orchestration framework: Kubernetes. We were glad to discover that Kubernetes is far more comprehensive and had almost all the features we required. For us, Kubernetes won ECS on ECS’s home court, which is AWS.
kubernetes  ecs  docker  containers  aws  ec2  ops 
december 2015 by jm
The impact of Docker containers on the performance of genomic pipelines [PeerJ]
In this paper, we have assessed the impact of Docker containers technology on the performance of genomic pipelines, showing that container “virtualization” has a negligible overhead on pipeline performance when it is composed of medium/long running tasks, which is the most common scenario in computational genomic pipelines.

Interestingly for these tasks the observed standard deviation is smaller when running with Docker. This suggests that the execution with containers is more “homogeneous,” presumably due to the isolation provided by the container environment.

The performance degradation is more significant for pipelines where most of the tasks have a fine or very fine granularity (a few seconds or milliseconds). In this case, the container instantiation time, though small, cannot be ignored and produces a perceptible loss of performance.
performance  docker  ops  genomics  papers 
november 2015 by jm
Amazon ECS CLI Tutorial - Amazon EC2 Container Service
super-basic ECS tutorial, using a docker-compose.yml to create a new ECS-managed service fleet
ecs  cli  linux  aws  ec2  hosting  docker  tutorials 
october 2015 by jm
AWS re:Invent 2015 | (CMP406) Amazon ECS at Coursera - YouTube
Coursera are running user-submitted code in ECS! interesting stuff about how they use Docker security/resource-limiting features, forking the ecs-agent code, to run user-submitted code. :O
coursera  user-submitted-code  sandboxing  docker  security  ecs  aws  resource-limits  ops 
october 2015 by jm
remind101/conveyor
'A fast build system for Docker images', open source, in Go, hooks into Github
build  ci  docker  github  go 
october 2015 by jm
How IFTTT develop with Docker
ugh, quite a bit of complexity here
docker  osx  dev  ops  building  coding  ifttt  dns  dnsmasq 
october 2015 by jm
Rebuilding Our Infrastructure with Docker, ECS, and Terraform
Good writeup of current best practices for a production AWS architecture
aws  ops  docker  ecs  ec2  prod  terraform  segment  via:marc 
october 2015 by jm
Anatomy of a Modern Production Stack
Interesting post, but I think it falls into a common trap for the xoogler or ex-Amazonian -- assuming that all the BigCo mod cons are required to operate, when some are luxuries than can be skipped for a few years to get some real products built
architecture  ops  stack  docker  containerization  deployment  containers  rkt  coreos  prod  monitoring  xooglers 
september 2015 by jm
Docker image creation, tagging and traceability in Shippable
this is starting to look quite impressive as a well-integrated Docker-meets-CI model; Shippable is basing its builds off Docker baselines and is automatically cutting Docker images of the post-CI stage. Must take another look
shippable  docker  ci  ops  dev  continuous-integration 
august 2015 by jm
buildfarm_deployment/cleanup_docker_images.py
Cleanup old/obsolete Docker images in a repo.
disk-space  ops  docker  cleanup  cron 
august 2015 by jm
Why Docker is Not Yet Succeeding Widely in Production
Spot-on points which Docker needs to address. It's still production-ready, and _should_ be used there, it just has significant rough edges...
docker  containers  devops  deployment  releases  linux  ops 
july 2015 by jm
From Zero to Docker: Migrating to the Whale
nicely detailed writeup of how New Relic are dockerizing
docker  ops  deployment  packaging  new-relic 
july 2015 by jm
Docker at Shopify: From This-Looks-Fun to Production
Pragmatic evolution story, adding Docker as a packaging/deploy format for an existing production Capistrano/Rails fleet
docker  ops  deployment  packaging  shopify  slides 
june 2015 by jm
Google Cloud Platform announces new Container Registry
Yay. Sensible Docker registry pricing at last. Given the high prices, rough edges and slow performance of the other registry offerings, I'm quite happy to see this.
Google Container Registry helps make it easy for you to store your container images in a private and encrypted registry, built on Cloud Platform. Pricing for storing images in Container Registry is simple: you only pay Google Cloud Storage costs. Pushing images is free, and pulling Docker images within a Google Cloud Platform region is free (Cloud Storage egress cost when outside of a region).

Container Registry is now ready for production use:

* Encrypted and Authenticated - Your container images are encrypted at rest, and access is authenticated using Cloud Platform OAuth and transmitted over SSL
* Fast - Container Registry is fast and can handle the demands of your application, because it is built on Cloud Storage and Cloud Networking.
* Simple - If you’re using Docker, just tag your image with a gcr.io tag and push it to the registry to get started.  Manage your images in the Google Developers Console.
* Local - If your cluster runs in Asia or Europe, you can now store your images in ASIA or EU specific repositories using asia.gcr.io and eu.gcr.io tags.
docker  registry  google  gcp  containers  cloud-storage  ops  deployment 
june 2015 by jm
Automated Nginx Reverse Proxy for Docker
Nice hack. An automated nginx reverse proxy which regenerates as the Docker containers update
nginx  reverse-proxy  proxies  web  http  ops  docker 
june 2015 by jm
etcd Clustering in AWS
'a fully-automated solution to build auto-scaling etcd clusters in AWS'
aws  cluster  docker  etcd  asg  autoscaling  ops 
june 2015 by jm
Dogestry
Simple CLI app for storing Docker image on Amazon S3.
dogestry  registry  docker  s3  github 
june 2015 by jm
Eric Brewer interview on Kubernetes
What is the relationship between Kubernetes, Borg and Omega (the two internal resource-orchestration systems Google has built)?

I would say, kind of by definition, there’s no shared code but there are shared people.

You can think of Kubernetes — especially some of the elements around pods and labels — as being lessons learned from Borg and Omega that are, frankly, significantly better in Kubernetes. There are things that are going to end up being the same as Borg — like the way we use IP addresses is very similar — but other things, like labels, are actually much better than what we did internally.

I would say that’s a lesson we learned the hard way.
google  architecture  kubernetes  docker  containers  borg  omega  deployment  ops 
may 2015 by jm
Red Hat on rkt vs Docker
This is like watching a train-wreck in slow motion on Groundhog Day. We, in the broader Linux and open source community, have been down this path multiple times over the past fifteen years, specifically with package formats. While there needs to be room for experimentation, having two incompatible specs driven by two startups trying to differentiate and in direct competition is *not* a good thing. It would be better for the community and for everyone who depends on our collective efforts if CoreOS and Docker collaborated on a standardized common spec, image format, and distribution protocol. To this end, we at Red Hat will continue to contribute to both initiatives with the goal of driving convergence.
rkt  docker  appc  coreos  red-hat  dpkg  rpm  linux  packaging  collaboration  open-source 
may 2015 by jm
Deploy a registry - Docker Documentation
Looks like it's pretty feasible to run a private Docker registry on every host, backed by S3 (according to the ECS team's AMA). SPOF-free -- handy
docker  registry  ops  deployment  s3 
may 2015 by jm
Kubernetes compared to Borg
'Here are four Kubernetes features that came from our experiences with Borg.'
google  ops  kubernetes  borg  containers  docker  networking 
april 2015 by jm
Cluster-Based Architectures Using Docker and Amazon EC2 Container Service
In this post, we’re going to take a deeper dive into the architectural concepts underlying cluster computing using container management frameworks such as ECS. We will show how these frameworks effectively abstract the low-level resources such as CPU, memory, and storage, allowing for highly efficient usage of the nodes in a compute cluster. Building on some of the concepts detailed in the earlier posts, we will discover why containers are such a good fit for this type of abstraction, and how the Amazon EC2 Container Service fits into the larger ecosystem of cluster management frameworks.
docker  aws  ecs  ec2  ops  hosting  containers  mesos  clusters 
april 2015 by jm
Amazon EC2 Container Service team AmA
a few answers here. Mostly people pointing out shortcomings and the team asking them to start a thread on their forum though :(
ec2  ecs  docker  aws  ops  ama  reddit 
april 2015 by jm
Microservices and elastic resource pools with Amazon EC2 Container Service
interesting approach to working around ECS' shortcomings -- bit specific to Hailo's microservices arch and IPC mechanism though.

aside: I like their version numbering scheme: ISO-8601, YYYYMMDDHHMMSS. keep it simple!
versioning  microservices  hailo  aws  ec2  ecs  docker  containers  scheduling  allocation  deployment  provisioning  qos 
april 2015 by jm
EC2 Container Service Hands On
Sounds like a good start, but this isn't great:
There is no native integration with Autoscaling or ELBs.
ec2  containers  docker  ecs  ops 
december 2014 by jm
Announcing Snappy Ubuntu
Awesome! I was completely unaware this was coming down the pipeline.
A new, transactionally updated Ubuntu for the cloud. Ubuntu Core is a new rendition of Ubuntu for the cloud with transactional updates. Ubuntu Core is a minimal server image with the same libraries as today’s Ubuntu, but applications are provided through a simpler mechanism. The snappy approach is faster, more reliable, and lets us provide stronger security guarantees for apps and users — that’s why we call them “snappy” applications.

Snappy apps and Ubuntu Core itself can be upgraded atomically and rolled back if needed — a bulletproof approach to systems management that is perfect for container deployments. It’s called “transactional” or “image-based” systems management, and we’re delighted to make it available on every Ubuntu certified cloud.
ubuntu  linux  packaging  snappy  ubuntu-core  transactional-updates  apt  docker  ops 
december 2014 by jm
CoreOS is building a container runtime, Rocket
Whoa, trouble at mill in Dockerland!
When Docker was first introduced to us in early 2013, the idea of a “standard container” was striking and immediately attractive: a simple component, a composable unit, that could be used in a variety of systems. The Docker repository included a manifesto of what a standard container should be. This was a rally cry to the industry, and we quickly followed. Brandon Philips, co-founder/CTO of CoreOS, became a top Docker contributor, and now serves on the Docker governance board. CoreOS is one of the most widely used platforms for Docker containers, and ships releases to the community hours after they happen upstream. We thought Docker would become a simple unit that we can all agree on.

Unfortunately, a simple re-usable component is not how things are playing out. Docker now is building tools for launching cloud servers, systems for clustering, and a wide range of functions: building images, running images, uploading, downloading, and eventually even overlay networking, all compiled into one monolithic binary running primarily as root on your server. The standard container manifesto was removed. We should stop talking about Docker containers, and start talking about the Docker Platform. It is not becoming the simple composable building block we had envisioned.
coreos  docker  linux  containers  open-source  politics  rocket 
december 2014 by jm
Day 1 - Docker in Production: Reality, Not Hype
Good Docker info from Bridget Kromhout, on their production and dev usage of Docker at DramaFever. lots of good real-world tips
docker  ops  boot2docker  tips  sysadvent 
december 2014 by jm
veggiemonk/awesome-docker
A curated list of Docker resources.
linux  sysadmin  docker  ops  devops  containers  hosting 
november 2014 by jm
Is Docker ready for production? Feedbacks of a 2 weeks hands on
I have to agree with this assessment -- there are a lot of loose ends still for production use of Docker in a SOA stack environment:
From my point of view, Docker is probably the best thing I’ve seen in ages to automate a build. It allows to pre build and reuse shared dependencies, ensuring they’re up to date and reducing your build time. It avoids you to either pollute your Jenkins environment or boot a costly and slow Virtualbox virtual machine using Vagrant. But I don’t feel like it’s production ready in a complex environment, because it adds too much complexity. And I’m not even sure that’s what it was designed for.
docker  complexity  devops  ops  production  deployment  soa  web-services  provisioning  networking  logging 
october 2014 by jm
"Linux Containers And The Future Cloud" [slides]
by Rami Rosen -- extremely detailed presentation into the state of Linux containers, LXC, Docker, namespaces, cgroups, and checkpoint/restore in userspace (via lusis)
lsx  docker  criu  namespaces  cgroups  linux  via:lusis  ops  containers  rami-rosen  presentations 
october 2014 by jm
Revisiting How We Put Together Linux Systems
Building a running OS out of layered btrfs filesystems. This sounds awesome.
Instantiating a new system or OS container (which is exactly the same in this scheme) just consists of creating a new appropriately named root sub-volume. Completely naturally you can share one vendor OS copy in one specific version with a multitude of container instances.

Everything is double-buffered (or actually, n-fold-buffered), because usr, runtime, framework, app sub-volumes can exist in multiple versions. Of course, by default the execution logic should always pick the newest release of each sub-volume, but it is up to the user keep multiple versions around, and possibly execute older versions, if he desires to do so. In fact, like on ChromeOS this could even be handled automatically: if a system fails to boot with a newer snapshot, the boot loader can automatically revert back to an older version of the OS.


(via Tony Finch)
via:fanf  linux  docker  btrfs  filesystems  unionfs  copy-on-write  os  hacking  unix 
september 2014 by jm
Building a Smarter Application Stack - DevOps Ireland
This sounds like a very interesting Dublin meetup -- Engine Yard on thursday night:
This month, we'll have Tomas Doran from Yelp talking about Docker, service discovery, and deployments. 'There are many advantages to a container based, microservices architecture - however, as always, there is no silver bullet. Any serious deployment will involve multiple host machines, and will have a pressing need to migrate containers between hosts at some point. In such a dynamic world hard coding IP addresses, or even host names is not a viable solution. This talk will take a journey through how Yelp has solved the discovery problems using Airbnb’s SmartStack to dynamically discover service dependencies, and how this is helping unify our architecture, from traditional metal to EC2 ‘immutable’ SOA images, to Docker containers.'
meetups  talks  dublin  deployment  smartstack  ec2  docker  yelp  service-discovery 
june 2014 by jm
Docker Plugin for Jenkins
The aim of the docker plugin is to be able to use a docker host to dynamically provision a slave, run a single build, then tear-down that slave. Optionally, the container can be committed, so that (for example) manual QA could be performed by the container being imported into a local docker provider, and run from there.


The holy grail of Jenkins/Docker integration. How cool is that...
jenkins  docker  ops  testing  ec2  hosting  scaling  elastic-scaling  system-testing 
may 2014 by jm
AWS Elastic Beanstalk for Docker
This is pretty amazing. nice work, Beanstalk team. not sure how well it integrates with the rest of AWS though
aws  amazon  docker  ec2  beanstalk  ops  containers  linux 
april 2014 by jm
Blockade
'Testing applications under slow or flaky network conditions can be difficult and time consuming. Blockade aims to make that easier. A config file defines a number of docker containers and a command line tool makes introducing controlled network problems simple.'

Open-source release from Dell's Cloud Manager team (ex-Enstratius), inspired by aphyr's Jepsen. Simulates packet loss using "tc netem", so no ability to e.g. drop packets on certain flows or certain ports. Still, looks very usable -- great stuff.
testing  docker  networking  distributed  distcomp  enstratius  jepsen  network  outages  partitions  cap  via:lusis 
february 2014 by jm
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