jm + ops   259

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 
7 days ago 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 
17 days ago by jm
Migration to, Expectations, and Advanced Tuning of G1GC
Bookmarking for future reference. recommended by one of the GC experts, I can't recall exactly who ;)
gc  g1gc  jvm  java  tuning  performance  ops  migration 
17 days ago by jm
Patterns for building a resilient and scalable microservices platform on AWS
Some good details from Boyan Dimitrov at Hailo, on their orchestration, deployment, provisioning infra they've built
deployment  ops  devops  hailo  microservices  platform  patterns  slides 
19 days ago by jm
Why Loggly loves Apache Kafka
Some good factoids about Loggly's Kafka usage and scales
scalability  logging  loggly  kafka  queueing  ops  reliabilty 
20 days ago by jm
Cassandra moving to using G1 as the default recommended GC implementation
This is a big indicator that G1 is ready for primetime. CMS has long been the go-to GC for production usage, but requires careful, complex hand-tuning -- if G1 is getting to a stage where it's just a case of giving it enough RAM, that'd be great.

Also, looks like it'll be the JDK9 default:
cassandra  tuning  ops  g1gc  cms  gc  java  jvm  production  performance  memory 
26 days ago by jm
a web-based SSH console that centrally manages administrative access to systems. Web-based administration is combined with management and distribution of user's public SSH keys. Key management and administration is based on profiles assigned to defined users.

Administrators can login using two-factor authentication with FreeOTP or Google Authenticator . From there they can create and manage public SSH keys or connect to their assigned systems through a web-shell. Commands can be shared across shells to make patching easier and eliminate redundant command execution.
keybox  owasp  security  ssh  tls  ssl  ops 
29 days ago by jm
'Discover and discuss the best dev tools and cloud infrastructure services' -- fun!
stackshare  architecture  stack  ops  software  ranking  open-source 
29 days ago 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 
4 weeks ago 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 
4 weeks ago 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 
4 weeks ago by jm
Etsy's Release Management process
Good info on how Etsy use their Deployinator tool, end-to-end.

Slide 11: git SHA is visible for each env, allowing easy verification of what code is deployed.

Slide 14: Code is deployed to "princess" staging env while CI tests are running; no need to wait for unit/CI tests to complete.

Slide 23: smoke tests of pre-prod "princess" (complete after 8 mins elapsed).

Slide 31: dashboard link for deployed code is posted during deploy; post-release prod smoke tests are run by Jenkins. (short ones! they complete in 42 seconds)
deployment  etsy  deploy  deployinator  princess  staging  ops  testing  devops  smoke-tests  production  jenkins 
4 weeks ago by jm
'Continuous Deployment: The Dirty Details'
Good slide deck from Etsy's Mike Brittain regarding their CD setup. Some interesting little-known details:

Slide 41: database schema changes are not CD'd -- they go out on "Schema change Thursdays".

Slide 44: only the webapp is CD'd -- PHP, Apache, memcache components (, support and back-office tools, developer API, gearman async worker queues). The external "services" are not -- databases, Solr/JVM search (rolling restarts), photo storage (filters, proxy cache, S3), payments (PCI-DSS, controlled access).

They avoid schema changes and breaking changes using an approach they call "non-breaking expansions" -- expose new version in a service interface; support multiple versions in the consumer. Example from slides 50-63, based around a database schema migration.

Slide 66: "dev flags" (rollout oriented) are promoted to "feature flags" (long lived degradation control).

Slide 71: some architectural philosophies: deploying is cheap; releasing is cheap; gathering data should be cheap too; treat first iterations as experiments.

Slide 102: "Canary pools". They have multiple pools of users for testing in production -- the staff pool, users who have opted in to see prototypes/beta stuff, 0-100% gradual phased rollout.
cd  deploy  etsy  slides  migrations  database  schema  ops  ci  version-control  feature-flags 
4 weeks ago by jm
Internet Scale Services Checklist
good aspirational checklist, inspired heavily by James Hamilton's seminal 2007 paper, "On Designing And Deploying Internet-Scale Services"
james-hamilton  checklists  ops  internet-scale  architecture  operability  monitoring  reliability  availability  uptime  aspirations 
5 weeks ago by jm
Pinterest's Hadoop workflow manager; 'scalable, reliable, simple, extensible' apparently. Hopefully it allows upgrades of a workflow component without breaking an existing run in progress, like LinkedIn's Azkaban does :(
python  pinterest  hadoop  workflows  ops  pinball  big-data  scheduling 
5 weeks ago by jm
'a secret management and distribution service [from Square] that is now available for everyone. Keywhiz helps us with infrastructure secrets, including TLS certificates and keys, GPG keyrings, symmetric keys, database credentials, API tokens, and SSH keys for external services — and even some non-secrets like TLS trust stores. Automation with Keywhiz allows us to seamlessly distribute and generate the necessary secrets for our services, which provides a consistent and secure environment, and ultimately helps us ship faster. [...]

Keywhiz has been extremely useful to Square. It’s supported both widespread internal use of cryptography and a dynamic microservice architecture. Initially, Keywhiz use decoupled many amalgamations of configuration from secret content, which made secrets more secure and configuration more accessible. Over time, improvements have led to engineers not even realizing Keywhiz is there. It just works. Please check it out.'
square  security  ops  keys  pki  key-distribution  key-rotation  fuse  linux  deployment  secrets  keywhiz 
5 weeks ago by jm
Yelp Product & Engineering Blog | True Zero Downtime HAProxy Reloads
Using tc and qdisc to delay SYNs while haproxy restarts. Definitely feels like on-host NAT between 2 haproxy processes would be cleaner and easier though!
linux  networking  hacks  yelp  haproxy  uptime  reliability  tcp  tc  qdisc  ops 
5 weeks ago by jm
Optimizing Java CMS garbage collections, its difficulties, and using JTune as a solution | LinkedIn Engineering
I like the sound of this -- automated Java CMS GC tuning, kind of like a free version of JClarity's Censum (via Miguel Ángel Pastor)
java  jvm  tuning  gc  cms  linkedin  performance  ops 
6 weeks ago by jm
an asynchronous Netty based graphite proxy. It protects Graphite from the herds of clients by minimizing context switches and interrupts; by batching and aggregating metrics. Gruffalo also allows you to replicate metrics between Graphite installations for DR scenarios, for example.

Gruffalo can easily handle a massive amount of traffic, and thus increase your metrics delivery system availability. At Outbrain, we currently handle over 1700 concurrent connections, and over 2M metrics per minute per instance.
graphite  backpressure  metrics  outbrain  netty  proxies  gruffalo  ops 
6 weeks ago by jm
Introducing Vector: Netflix's On-Host Performance Monitoring Tool
It gives pinpoint real-time performance metric visibility to engineers working on specific hosts -- basically sending back system-level performance data to their browser, where a client-side renderer turns it into a usable dashboard. Essentially the idea is to replace having to ssh onto instances, run "top", systat, iostat, and so on.
vector  netflix  performance  monitoring  sysstat  top  iostat  netstat  metrics  ops  dashboards  real-time  linux 
6 weeks ago by jm
Gil Tene's "usual suspects" to reduce system-level hiccups/latency jitters in a Linux system
Based on empirical evidence (across many tens of sites thus far) and note-comparing with others, I use a list of "usual suspects" that I blame whenever they are not set to my liking and system-level hiccups are detected. Getting these settings right from the start often saves a bunch of playing around (and no, there is no "priority" to this - you should set them all right before looking for more advice...).
performance  latency  hiccups  gil-tene  tuning  mechanical-sympathy  hyperthreading  linux  ops 
7 weeks ago by jm
Outages, PostMortems, and Human Error 101
Good basic pres from John Allspaw, covering the basics of tier-one tech incident response -- defining the 5 severity levels; root cause analysis techniques (to Five-Whys or not); and the importance of service metrics
devops  monitoring  ops  five-whys  allspaw  slides  etsy  codeascraft  incident-response  incidents  severity  root-cause  postmortems  outages  reliability  techops  tier-one-support 
7 weeks ago by jm
Cassandra remote code execution hole (CVE-2015-0225)
Ah now lads.
Under its default configuration, Cassandra binds an unauthenticated
JMX/RMI interface to all network interfaces. As RMI is an API for the
transport and remote execution of serialized Java, anyone with access
to this interface can execute arbitrary code as the running user.
cassandra  jmx  rmi  java  ops  security 
7 weeks ago by jm
How We Scale VividCortex's Backend Systems - High Scalability
Excellent post from Baron Schwartz about their large-scale, 1-second-granularity time series database storage system
time-series  tsd  storage  mysql  sql  baron-schwartz  ops  performance  scalability  scaling  go 
8 weeks ago by jm
The Four Month Bug: JVM statistics cause garbage collection pauses (
Ugh, tying GC safepoints to disk I/O? bad idea:
The JVM by default exports statistics by mmap-ing a file in /tmp (hsperfdata). On Linux, modifying a mmap-ed file can block until disk I/O completes, which can be hundreds of milliseconds. Since the JVM modifies these statistics during garbage collection and safepoints, this causes pauses that are hundreds of milliseconds long. To reduce worst-case pause latencies, add the -XX:+PerfDisableSharedMem JVM flag to disable this feature. This will break tools that read this file, like jstat.
bugs  gc  java  jvm  disk  mmap  latency  ops  jstat 
8 weeks ago by jm
Transparent huge pages implicated in Redis OOM
A nasty real-world prod error scenario worsened by THPs:
jemalloc(3) extensively uses madvise(2) to notify the operating system that it's done with a range of memory which it had previously malloc'ed. The page size on this machine is 2MB because transparent huge pages are in use. As such, a lot of the memory which is being marked with madvise(..., MADV_DONTNEED) is within substantially smaller ranges than 2MB. This means that the operating system never was able to evict pages which had ranges marked as MADV_DONTNEED because the entire page has to be unneeded to allow a page to be reused. Despite initially looking like a leak, the operating system itself was unable to free memory because of madvise(2) and transparent huge pages. This led to sustained memory pressure on the machine and redis-server eventually getting OOM killed.
oom-killer  oom  linux  ops  thp  jemalloc  huge-pages  madvise  redis  memory 
9 weeks ago by jm
"tees" all TCP traffic from one server to another. "widely used by companies in China"!
testing  benchmarking  performance  tcp  ip  tcpcopy  tee  china  regression-testing  stress-testing  ops 
9 weeks ago by jm
an open source stream processing software system developed by Mozilla. Heka is a “Swiss Army Knife” type tool for data processing, useful for a wide variety of different tasks, such as:

Loading and parsing log files from a file system.
Accepting statsd type metrics data for aggregation and forwarding to upstream time series data stores such as graphite or InfluxDB.
Launching external processes to gather operational data from the local system.
Performing real time analysis, graphing, and anomaly detection on any data flowing through the Heka pipeline.
Shipping data from one location to another via the use of an external transport (such as AMQP) or directly (via TCP).
Delivering processed data to one or more persistent data stores.

Via feylya on twitter. Looks potentially nifty
heka  mozilla  monitoring  metrics  via:feylya  ops  statsd  graphite  stream-processing 
10 weeks ago by jm
The Large Hadron Migrator is a tool to perform live database migrations in a Rails app without locking.

The basic idea is to perform the migration online while the system is live, without locking the table. In contrast to OAK and the facebook tool, we only use a copy table and triggers. The Large Hadron is a test driven Ruby solution which can easily be dropped into an ActiveRecord or DataMapper migration. It presumes a single auto incremented numerical primary key called id as per the Rails convention. Unlike the twitter solution, it does not require the presence of an indexed updated_at column.
migrations  database  sql  ops  mysql  rails  ruby  lhm  soundcloud  activerecord 
11 weeks ago by jm
A project to reduce systemd to a base initd, process supervisor and transactional dependency system, while minimizing intrusiveness and isolationism. Basically, it’s systemd with the superfluous stuff cut out, a (relatively) coherent idea of what it wants to be, support for non-glibc platforms and an approach that aims to minimize complicated design. uselessd is still in its early stages and it is not recommended for regular use or system integration.

This may be the best option to evade the horrors of systemd.
init  linux  systemd  unix  ops  uselessd 
11 weeks ago by jm
Ubuntu To Officially Switch To systemd Next Monday - Slashdot
Jesus. This is going to be the biggest shitfest in the history of Linux...
linux  slashdot  ubuntu  systemd  init  unix  ops 
11 weeks ago by jm
What Color Is Your Xen?
What a mess.
What's faster: PV, HVM, HVM with PV drivers, PVHVM, or PVH? Cloud computing providers using Xen can offer different virtualization "modes", based on paravirtualization (PV), hardware virtual machine (HVM), or a hybrid of them. As a customer, you may be required to choose one of these. So, which one?
ec2  linux  performance  aws  ops  pv  hvm  xen  virtualization 
february 2015 by jm
"Cheap SSL certs from $4.99/yr" -- apparently recommended for cheap, low-end SSL certs
ssl  certs  security  https  ops 
february 2015 by jm
Performance Co-Pilot
System performance metrics framework, plugged by Netflix, open-source for ages
open-source  pcp  performance  system  metrics  ops  red-hat  netflix 
february 2015 by jm
A gateway script, now included in PCP
pcp2graphite  pcp  graphite  ops  metrics  system 
february 2015 by jm
Duplicate SSH Keys Everywhere
Poor hardware imaging practices, basically:
It looks like all devices with the fingerprint are Dropbear SSH instances that have been deployed by Telefonica de Espana. It appears that some of their networking equipment comes setup with SSH by default, and the manufacturer decided to re-use the same operating system image across all devices.
crypto  ssh  security  telefonica  imaging  ops  shodan 
february 2015 by jm
A tool for managing Apache Kafka. It supports the following :

Manage multiple clusters;
Easy inspection of cluster state (topics, brokers, replica distribution, partition distribution);
Run preferred replica election;
Generate partition assignments (based on current state of cluster);
Run reassignment of partition (based on generated assignments)
yahoo  kafka  ops  tools 
february 2015 by jm
0x74696d | Falling In And Out Of Love with DynamoDB, Part II
Good DynamoDB real-world experience post, via Mitch Garnaat. We should write up ours, although it's pretty scary-stuff-free by comparison
aws  dynamodb  storage  databases  architecture  ops 
february 2015 by jm
TL;DR: Cassandra Java Huge Pages
Al Tobey does some trial runs of -XX:+AlwaysPreTouch and -XX:+UseHugePages
jvm  performance  tuning  huge-pages  vm  ops  cassandra  java 
february 2015 by jm
NA Server Roadmap Update: PoPs, Peering, and the North Bridge
League of Legends has set up private network links to a variety of major US ISPs to avoid internet weather (via Nelson)
via:nelson  peering  games  networks  internet  ops  networking 
january 2015 by jm
How TCP backlog works in Linux
good description of the process
ip  linux  tcp  networking  backlog  ops 
january 2015 by jm
Nice trick -- wrap servers with a libc wrapper to intercept bind(2) and accept(2) calls, so that transparent restarts becode possible
linux  ops  servers  uptime  restarting  libc  bind  accept  sockets 
january 2015 by jm
Maintaining performance in distributed systems [slides]
Great slide deck from Elasticsearch on JVM/dist-sys performance optimization
performance  elasticsearch  java  jvm  ops  tuning 
january 2015 by jm
A much better carbon-relay, written in C rather than Python. Linking as we've been using it in production for quite a while with no problems.
The main reason to build a replacement is performance and configurability. Carbon is single threaded, and sending metrics to multiple consistent-hash clusters requires chaining of relays. This project provides a multithreaded relay which can address multiple targets and clusters for each and every metric based on pattern matches.
graphite  carbon  c  python  ops  metrics 
january 2015 by jm
Really nice time series dashboarding app. Might consider replacing graphitus with this...
time-series  data  visualisation  graphs  ops  dashboards  facette 
january 2015 by jm
AWS Tips I Wish I'd Known Before I Started
Some good advice and guidelines (although some are just silly).
aws  ops  tips  advice  ec2  s3 
january 2015 by jm
Personalization at Spotify using Cassandra
Lots and lots of good detail into the Spotify C* setup (via Bill de hOra)
via:dehora  spotify  cassandra  replication  storage  ops 
january 2015 by jm
Why we don't use a CDN: A story about SPDY and SSL
All of our assets loaded via the CDN [to our client in Australia] in just under 5 seconds. It only took ~2.7s to get those same assets to our friends down under with SPDY. The performance with no CDN blew the CDN performance out of the water. It is just no comparison. In our case, it really seems that the advantages of SPDY greatly outweigh that of a CDN when it comes to speed.
cdn  spdy  nginx  performance  web  ssl  tls  optimization  multiplexing  tcp  ops 
january 2015 by jm
Secure Secure Shell
How to secure SSH, disabling insecure ciphers etc. (via Padraig)
via:pixelbeat  crypto  security  ssh  ops 
january 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
'Machine Learning: The High-Interest Credit Card of Technical Debt' [PDF]
Oh god yes. This is absolutely spot on, as you would expect from a Google paper -- at this stage they probably have accumulated more real-world ML-at-scale experience than anywhere else.

'Machine learning offers a fantastically powerful toolkit for building complex systems
quickly. This paper argues that it is dangerous to think of these quick wins
as coming for free. Using the framework of technical debt, we note that it is remarkably
easy to incur massive ongoing maintenance costs at the system level
when applying machine learning. The goal of this paper is highlight several machine
learning specific risk factors and design patterns to be avoided or refactored
where possible. These include boundary erosion, entanglement, hidden feedback
loops, undeclared consumers, data dependencies, changes in the external world,
and a variety of system-level anti-patterns.


'In this paper, we focus on the system-level interaction between machine learning code and larger systems
as an area where hidden technical debt may rapidly accumulate. At a system-level, a machine
learning model may subtly erode abstraction boundaries. It may be tempting to re-use input signals
in ways that create unintended tight coupling of otherwise disjoint systems. Machine learning
packages may often be treated as black boxes, resulting in large masses of “glue code” or calibration
layers that can lock in assumptions. Changes in the external world may make models or input
signals change behavior in unintended ways, ratcheting up maintenance cost and the burden of any
debt. Even monitoring that the system as a whole is operating as intended may be difficult without
careful design.

Indeed, a remarkable portion of real-world “machine learning” work is devoted to tackling issues
of this form. Paying down technical debt may initially appear less glamorous than research results
usually reported in academic ML conferences. But it is critical for long-term system health and
enables algorithmic advances and other cutting-edge improvements.'
machine-learning  ml  systems  ops  tech-debt  maintainance  google  papers  hidden-costs  development 
december 2014 by jm
Two recent systemd crashes
Hey look, PID 1 segfaulting! I haven't seen that happen since we managed to corrupt /bin/sh on Ultrix in 1992. Nice work Fedora
fedora  reliability  unix  linux  systemd  ops  bugs 
december 2014 by jm
Introducing Atlas: Netflix's Primary Telemetry Platform
This sounds really excellent -- the dimensionality problem it deals with is a familiar one, particularly with red/black deployments, autoscaling, and so on creating trees of metrics when new transient servers appear and disappear. Looking forward to Netflix open sourcing enough to make it usable for outsiders
netflix  metrics  service-metrics  atlas  telemetry  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
PDX DevOps Graphite replacement
Replacing graphite with InfluxDB, Riemann and Grafana. Not quite there yet, looks like
influxdb  graphite  ops  metrics  riemann  grafana  slides 
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
(SDD416) Amazon EBS Deep Dive | AWS re:Invent 2014
Excellent data on current EBS performance characteristics
ebs  ops  aws  reinvent  slides 
november 2014 by jm
AWS re:Invent 2014 Video & Slide Presentation Links
Nice work by Andrew Spyker -- this should be an official feature of the re:Invent website, really
reinvent  aws  conferences  talks  slides  ec2  s3  ops  presentations 
november 2014 by jm
Microsoft Azure 9-hour outage
'From 19 Nov, 2014 00:52 to 05:50 UTC a subset of customers using Storage, Virtual Machines, SQL Geo-Restore, SQL Import/export, Websites, Azure Search, Azure Cache, Management Portal, Service Bus, Event Hubs, Visual Studio, Machine Learning, HDInsights, Automation, Virtual Network, Stream Analytics, Active Directory, StorSimple and Azure Backup Services in West US and West Europe experienced connectivity issues. This incident has now been mitigated.'

There was knock-on impact until 11:00 UTC (storage in N Europe), 11:45 UTC (websites, West Europe), and 09:15 UTC (storage, West Europe), from the looks of things. Should be an interesting postmortem.
outages  azure  microsoft  ops 
november 2014 by jm
The Infinite Hows, instead of the Five Whys
John Allspaw with an interesting assertion that we need to ask "how", not "why" in five-whys postmortems:
“Why?” is the wrong question.

In order to learn (which should be the goal of any retrospective or post-hoc investigation) you want multiple and diverse perspectives. You get these by asking people for their own narratives. Effectively, you’re asking “how?“

Asking “why?” too easily gets you to an answer to the question “who?” (which in almost every case is irrelevant) or “takes you to the ‘mysterious’ incentives and motivations people bring into the workplace.”

Asking “how?” gets you to describe (at least some) of the conditions that allowed an event to take place, and provides rich operational data.
ops  five-whys  john-allspaw  questions  postmortems  analysis  root-causes 
november 2014 by jm
A curated list of Docker resources.
linux  sysadmin  docker  ops  devops  containers  hosting 
november 2014 by jm
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