My sincerest apology to Ali Haider Zaveri, author of the article Location-Aware Distribution: Configuring servers at scale. I originally miscredited the article to two folks, claiming they were from Facebook when in fact they work at Google.

As Grubhub built out their service-oriented architecture, they first developed “base frameworks for building highly available, distributed services”.

William Blackie — Grubhub

Cloudflare discusses an optimization that improves their p99 response time in the face of occasionally slow disk access. Today I learned: Linux does not allow for non-blocking disk reads.

Ka-Hing Cheung — Cloudflare

I include this article not just to warn you in case you depend on GeoTrust certificates, but also to highlight what’s involved in running a reliable and trustworthy CA.

Devon O’Brien, Ryan Sleevi, and Andrew Whalley — Google

They go over the 6 key constraints that influenced their design and describe the solution they came up with. Some of the constraints seem to involve preserving not just their own systems’ reliability, but that of their customers’ systems.

Simon Woolf — Ably

Given that we already knew in advance how to deal with each issue as it arose, it made sense to automate the work. Here’s how we did it.

James O’Keeffe — Google

In this article we will look at the various load balancing solutions available in Azure and which one should be used in which scenario.

Rahul Rajat Singh

In this blog post I will show you what a disaster recovery exercise is, how it can diagnose weak points in your infrastructure, and how it can be a learning experience for your on-call team.

Alexandra Johnson — SigOpt

This article showcases the Chaos Toolkit experiments these folks wrote to test their system’s resiliency.

Sylvain Hellegouarc — chaosiq

With millions of servers and thousands of configuration changes per day, distribution of configuration information becomes a huge scaling challenge. Here’s some insight (and pretty architecture diagrams) explaining how Facebook does it.

Ali Haider Zaveri — Facebook [NOTE: originally miscredited, sorry!]

Liftbridge is a system for lightweight, fault-tolerant (LIFT) message streams built on NATS and gRPC. Fundamentally, it extends NATS with a Kafka-like publish-subscribe log API that is highly available and horizontally scalable.

Tyler Treat

This pretty neat: Google Cloud Platform now exposes their SLIs directly to you, as they pertain to the requests you make of the platform. For example, if a given API call has increased latency, you’ll see it on their graph. This can be great for those “is it us or is it them?” incidents.

Jay Judkowitz — Google

What can I do to make sure that, when this system fails, it fails as effectively as possible?

Todd Conklin — Pre-Accident Podcast

Here’s a review of Google’s new SRE book. I’m a little miffed that now I have to say that, instead of just “Google’s SRE book” or just “the SRE book”. Ah well. This one appears to be more about practical use cases than theory.

Todd Hoff — High Scalability

Chaos engineering isn’t just for SREs.

everyone benefits from observing a failure. Even UI engineers, people from a UX background, product managers.

Patrick Higgins — Gremlin

I love the idea of using hobbies as a gauge for your overload level at work. Also, serious kudos to Alice for the firm stance against alcohol at work and especially in Ops.

Alice Goldfuss

If the Linux OOM killer gets involved, you’ve already lost. Facebook reckons they can do better.

We find that oomd can respond faster, is less rigid, and is more reliable than the traditional Linux kernel OOM killer. In practice, we have seen 30-minute livelocks completely disappear.

Daniel Xu — Facebook

This is radical transparency: Honeycomb has set up a sandbox copy of their app for you to play with and loaded it with data from a real outage on their platform! Tinker away. It’s super fun.

Honeycomb

It may not actually make sense to halt feature development if your team has exhausted the error budget. What do you do instead?

Adrian Hilton, Alec Warner and Alex Bramley — Google

Today, we’re excited to share the architecture for Centrifuge–Segment’s system for reliably sending billions of messages per day to hundreds of public APIs. This post explores the problems Centrifuge solves, as well as the data model we use to run it in production.

The parallels to the Plaid article a few weeks ago (scaling 9000+ heterogeneous bank integrations) are intriguing.

Calvin French-Owen — Segment

A solid definition of SLIs, SLOs, and SLAs (from someone other than Google!). Includes some interesting tidbits on defining and measuring availability, choosing a useful time quantum, etc.

Kevin Kamel — Circonus

Read about how Heroku deployed a security fix to their fleet of customer Redis instances. This is awesome:

Our fleet roll code only schedules replacement operations during the current on-call operator’s business hours. This limits burnout by reducing the risk of the fleet roll waking them up at night.

Camille Baldock — Heroku

In this article I’m going to explore how multi-level automated chaos experiments can be used to explore system weaknesses that cross the boundaries between the technical and people/process/practices levels.

Russ Miles — ChaosIQ

A comparison of 2 free and 6 paid tools for load testing, along with advice on how to use them.

Noah Heinrich — ButterCMS

One could even call this article, “Why having a single microservice that every other microservice depends on is a bad idea”.

Mark Henke — Rollout.io

Segment discovered the hard way that their move to a microservice architecture had brought far more problems than benefits. Here’s why they transitioned back and how they pulled it off. Awesome article!

Alexandra Noonan — Segment

Drawing on the work of Dr. David Woods and the rest of the SNAFU Catchers, this article discusses the concepts behind resiliency and how to measure and achieve it.

Beth Long — New Relic

Serverless is not the magical gateway to the land of NoOps. You still have to operate your system even if you’re not directly running the servers. This article does a great job of explaining why.

Bhanu Singh — Network World

New to me: Wireshark’s statistics view and how it can be useful.

Julia Evans

How do you define whether your system is available and healthy? This article uses an anology to medical health.

Claiming that our system is doing well means nothing if users can perceive an outage.

José Carlos Chávez — Typeform

These folks are experiencing mysterious latency with HTTP/2 traffic to their ALB and published this report on their investigation. There’s no happy ending here — ultimately they disabled HTTP/2 support. I hope they update if they do discover the culprit.

Peter Forsberg — ShopGun

I had some fun this week unearthing the cause for the chronic lockups in Rsyslog that we’ve experienced at work. I found the cause (overeager retries of socket writes) and put together a bug report and a pull request.

Full disclosure: Fastly, my employer, is mentioned.

I love science! Grab wrote a nifty tool to help them select cohorts of users and perform experiments on them.

Abeesh Thomas and Roman Atachiants — Grab

Titus is the container orchestration system that Netflix created and open sourced. Rather than building a new auto-scaling feature for Titus, they instead got Amazon to productize EC2’s auto-scaling engine as a generalized auto-scaling tool, which Netflix then integrated with Titus. Neat!

See Amazon’s Application Auto Scaling announcement, published this past week.

Andrew Leung, Amit Joshi, and the rest of the Titus team — Netflix

What do you do when your hosts have kernel crashes at random every day? It turns out that you don’t need to be a seasoned kernel programmer to find a solution.

Pavlos Parissis — Booking.com

This is my first introduction tcpconnect (part of BCC). Pretty nifty!

fREW Schmidt

At Facebook, […] It is simply too difficult to rewrite caching/admission/eviction policies and other manually tuned heuristics by hand. We have to fundamentally change how we think about software maintenance.

Vladimir Bychkovsky, Jim Cipar, Alvin Wen, Lili Hu, and Saurav Mohapatra — Facebook

A couple weeks back, I linked to a postmortem template. Here’s a gameday report template from the same author.

Michael Kehoe

I had a really hard time choosing whether to include this one. On the one hand, it’s a really interesting article about service discovery in franchises that has to work right every time. On the other hand, Chick-fil-A has a terrible track record on GLBT rights, and I can’t overlook that.

Ultimately, I’m choosing to link to this article for its educational content, but I urge you to join me as I continue to boycott Chick-fil-A.

Brian Chambers, Caleb Hurd, and Alex Crane — Chick-fil-A

At 9 years old, this may be the oldest article I’ve linked to, but it’s worth it. The analogy to a home mortage is spot on.

Eric Lee

Click through to read about an interesting monitoring challenge and an account of how they solved it. I appreciate the emphasis on the importance of educating engineers to spread the knowledge of how the new system works among more people.

Joy Zheng and Jeeyoung Kim — Plaid

Another chaos engineering introduction. Why should you read it? If nothing else, the architecture diagram with the skull and cobwebs on it is pretty great. It’s also well worth reading if you’re looking to create a chaos engineering game plan.

Benjamin Wilms — Codecentric

Sometimes, a reliability risk can come in the form of a bunch of angry customers.

Ben Kuchera — Ars Technica