Outsource Your O11y: Now Roll It Out And Keep Them Happy (part 3/3)

This is part three of a three-part series of guest posts:

  1. How To Be A Champion, on how to choose a third-party vendor and champion them successfully to your security team.  (George Chamales)
  2. Get Aligned With Security, how to work with your security team to find the best possible outcome for all sides (Lilly Ryan)
  3. Now Roll It Out And Keep Them Happy, on how to operationalize your service by rolling out the integration and maintaining it — and the relationship with your security team — over the long run (Andy Isaacson)

All this pain will someday be worth it.  🙏❤️  charity + friends


“Now Roll It Out And Keep Them Happy”

This is the third in a series of blog posts; previously we analyzed the security challenges of using a third party service, and we worked together with the security team to build empathy to deliver the project.  You might want to read those first, since we are going to build on a lot of the ideas there to ship and maintain this integration.

Ready for launch

You’ve convinced the security team and other stakeholders, you’ve gotten the integration running, you’re getting promising results from dev-test or staging environments… now it’s time to move from proof-of-concept to full implementation.  Depending on your situation this might be a transition from staging to production, or it might mean increasing a feature flipper flag from 5% to 100%, or it might mean increasing coverage of an integration from one API endpoint to cover your entire developer footprint.

Taking into account Murphy’s Law, we expect that some things will go wrong during the rollout.  Perhaps during coverage, a developer realizes that the schema designed to handle the app’s event mechanism can’t represent a scenario, requiring a redesign or a hacky solution.  Or perhaps the metrics dashboard shows elevated error rates from the API frontend, and while there’s no smoking gun, the ops oncall decides to rollback the integration Just In Case it’s causing the incident.

This gives us another chance to practice empathy — while it’s easy, wearing the champion hat, to dismiss any issues found by looking for someone to blame, ultimately this poisons trust within your organization and will hamper success.  It’s more effective, in the long run (and often even in the short run), to find common ground with your peers in other disciplines and teams, and work through to solutions that satisfy everybody.

Keeping the lights on

In all likelihood as integration succeeds, the team will rapidly develop experts and expertise, as well as idiomatic ways to use the product.  Let the experts surprise you; folks you might not expect can step up when given a chance.  Expertise flourishes when given guidance and goals; as the team becomes comfortable with the integration, explicitly recognize a leader or point person for each vendor relationship.  Having one person explicitly responsible for a relationship lets them pay attention to those vendor emails, updates, and avoid the tragedy of the “but I thought *you* were” commons.  This Integration Lead is also a center of knowledge transfer for your organization — they won’t know everything or help every user come up to speed, but they can help empower the local power users in each team to ramp up their teams on the integration.

As comfort grows you will start to consider ways to change your usage, for example growing into new kinds of data.  This is a good time to revisit that security checklist — does the change increase PII exposure to your vendor?  Would the new data lead to additional requirements such as per-field encryption?  Don’t let these security concerns block you from gaining valuable insight using the new tool, but do take the chance to talk it over with your security experts as appropriate.

Throughout this organic growth, the Integration Lead remains core to managing your changing profile of usage of the vendor they shepherd; as new categories of data are added to the integration, the Lead has responsibility to ensure that the vendor relationship and risk profile are well matched to the needs that the new usage (and presumably, business value) is placing on the relationship.

Documenting the Intergation Lead role and responsibilities is critical. The team should know when to check in, and writing it down helps it happen.  When new code has a security implication, or a new use case potentially amplifies the cost of an integration, bringing the domain expert in will avoid unhappy surprises.  Knowing how to find out who to bring in, and when to bring them in, will keep your team getting the right eyes on their changes.

Security threats and other challenges change over time, too.  Collaborating with your security team so that they know what systems are in use helps your team take note of new information that is relevant to your business. A simple example is noting when your vendors publish a breach announcement, but more complex examples happen too — your vendor transitions cloud providers from AWS to Azure and the security team gets an alert about unexpected data flows from your production cluster; with transparency and trust such events become part of a routine process rather than an emergency.

It’s all operational

Monitoring and alerting is a fact of operations life, and this has to include vendor integrations (even when the vendor integration is a monitoring product.)  All of your operations best practices are needed here — keep your alerts clean and actionable so that you don’t develop pager fatigue, and monitor performance of the integration so that you don’t get blindsided by a creeping latency monster in your APIs.

Authentication and authorization are changing as the threat landscape evolves and industry moves from SMS verification codes to U2F/WebAuthn.  Does your vendor support your SSO integration?  If they can’t support the same SSO that you use everywhere else and can’t add it — or worse, look confused when you mention SSO — that’s probably a sign you should consider a different vendor.

A beautiful sunset

Have a plan beforehand for what needs to be done should you stop using the service.  Got any mobile apps that depend on APIs that will go away or start returning permission errors?  Be sure to test these scenarios ahead of time.

What happens at contract termination to data stored on the service?  Do you need to explicitly delete data when ceasing use?

Do you need to remove integrations from your systems before ending the commercial relationship, or can the technical shutdown and business shutdown run in parallel?

In all likelihood these are contingency plans that will never be needed, and they don’t need to be fully fleshed out to start, but a little bit of forethought can avoid unpleasant surprises.

Year after year

Industry best practice and common sense dictate that you should revisit the security questionnaire annually (if not more frequently). Use this chance to take stock of the last year and check in — are you getting value from the service?  What has changed in your business needs and the competitive landscape? 

It’s entirely possible that a new year brings new challenges, which could make your current vendor even more valuable (time to negotiate a better contract rate!) or could mean you’d do better with a competing service.  Has the vendor gone through any major changes?  They might have new offerings that suit your needs well, or they may have pivoted away from the features you need. 

Check in with your friends on the security team as well; standards evolve, and last year’s sufficient solution might not be good enough for new requirements.

 

Andy thinks out loud about security, society, and the problems with computers on Twitter.


 

❤️ Thanks so much reading, folks.  Please feel free to drop any complaints, comments, or additional tips to us in the comments, or direct them to me on twitter.

Have fun!  Stay (a little bit) Paranoid!!

— charity

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Outsource Your O11y: Now Roll It Out And Keep Them Happy (part 3/3)

Outsource Your O11y: Get Aligned With Security (part 2/3)

This is part two of a three-part series of guest posts:

  1. How To Be A Champion, on how to choose a third-party vendor and champion them successfully to your security team.  (George Chamales)
  2. Get Aligned With Security, how to work with your security team to find the best possible outcome for all sides (Lilly Ryan)
  3. Now Roll It Out And Keep Them Happy, on how to operationalize your service by rolling out the integration and maintaining it — and the relationship with your security team — over the long run (Andy Isaacson)

All this pain will someday be worth it.  🙏❤️  charity + friends


“Get Aligned With Security”

by Lilly Ryan

If your team has decided on a third-party service to help you gather data and debug product issues, how do you convince an often overeager internal security team to help you adopt it?

When this service is something that provides a pathway for developers to access production data, as analytics tools often do, making the case for access to that data can screech to a halt at the mention of the word “production”. Progressing past that point will take time, empathy, and consideration.

I have been on both sides of the “adopting a new service” fence: as a developer hoping to introduce something new and useful to our stack, and now as a security professional who spends her days trying to bust holes in other people’s setups. I understand both sides of the sometimes-conflicting needs to both ship software and to keep systems safe.  

This guide has advice to help you solve the immediate problem of choosing and deploying a third-party service with the approval of your security team.  But it also has advice for how to strengthen the working relationship between your security and development teams over the longer term. No two companies are the same, so please adapt these ideas to fit your circumstances.

Understanding the security mindset

The biggest problems in technology are never really about technology, but about people. Seeing your security team as people and understanding where they are coming from will help you to establish empathy with them so that both of you want to help each other get what you want, not block each other.

First, understand where your security team is coming from. Development teams need to build features, improve the product, understand and ship good code. Security teams need to make sure you don’t end up on the cover of the NYT for data breaches, that your business isn’t halted by ransomware, and that you’re not building your product on a vulnerable stack.

This can be an unfamiliar frame of mind for developers.  Software development tends to attract positive-minded people who love creating things and are excited about the possibilities of new technology. Software security tends to attract negative thinkers who are skilled at finding all the flaws in a system.  These are very different mentalities, and the people who occupy them tend to have very different assumptions, vocabularies, and worldviews.   

But if you and your security team can’t share the same worldview, it will be hard to trust each other and come to agreement.  This is where practicing empathy can be helpful.

Before approaching your security team with your request to approve a new vendor, you may want to run some practice exercises for putting yourselves in their shoes and forcing yourselves to deliberately cultivate a negative thinking mindset to experience how they may react — not just in terms of the objective risk to the business, or the compliance headaches it might cause, but also what arguments might resonate with them and what emotional reactions they might have.

My favourite exercise for getting teams to think negatively is what I call the Land Astronaut approach.

The “Land Astronaut” Game

Imagine you are an astronaut on the International Space Station. Literally everything you do in space has death as a highly possible outcome. So astronauts spend a lot of time analysing, re-enacting, and optimizing their reactions to events, until it becomes muscle memory. By expecting and training for failure, astronauts use negative thinking to anticipate and mitigate flaws before they happen. It makes their chances of survival greater and their people ready for any crisis.

Your project may not be as high-stakes as a space mission, and your feet will most likely remain on the ground for the duration of your work, but you can bet your security team is regularly indulging in worst-case astronaut-type thinking. You and your team should try it, too.

The Game:

Pick a service for you and your team to game out.  Schedule an hour, book a room with a whiteboard, put on your Land Astronaut helmets.  Then tell your team to spend half an hour brainstorming about all the terrible things that can happen to that service, or to the rest of your stack when that service is introduced.  Negative thoughts only!

Start brainstorming together. Start out by being as outlandish as possible (what happens if their data centre is suddenly overrun by a stampede of elephants?). Eventually you will find that you’ll tire of the extreme worst case scenarios and come to consider more realistic outcomes — some of which which you may not have thought of outside of the structure of the activity.

After half an hour, or whenever you feel like you’re all done brainstorming, take off your Land Astronaut helmets, sift out the most plausible of the worst case scenarios, and try to come up with answers or strategies that will help you counteract them.  Which risks are plausible enough that you should mitigate them?  Which are you prepared to gamble on never happening?  How will this risk calculus change as your company grows and takes on more exposure?

Doing this with your team will allow you all to practice the negative thinking mindset together and get a feel for how your colleagues in the security team might approach this request. (While this may seem similar to threat modelling exercises you might have done in the past, the focus here is on learning to adopt a security mindset and gaining empathy for this thought process, rather than running through a technical checklist of common areas of concern.)

While you still have your helmets within reach, use your negative thinking mindset to fill out the spreadsheet from the first piece in this series.  This will help you anticipate most of the reasonable objections security might raise, and may help you include useful detail the security team might not have known to ask for.

Once you have prepared your list of answers to George’s worksheet and held a team Land Astronaut session together, you will have come most of the way to getting on board with the way your security team thinks.

Preparing for compromise

You’ve considered your options carefully, you’ve learned how to harness negative thinking to your advantage, and you’re ready to talk to your colleagues in security – but sometimes, even with all of these tools at your disposal, you may not walk away with all of the things you are hoping for.

Being willing to compromise and anticipating some of those compromises before you approach the security team will help you negotiate more successfully.

While your Land Astronaut helmets are still within reach, consider using your negative thinking mindset game to identify areas where you may be asked to compromise. If you’re asking for production access to this new service for observability and debugging purposes, think about what kinds of objections may be raised about this and how you might counter them or accommodate them. Consider continuing the activity with half of the team remaining in the Land Astronaut role while the other half advocates from a positive thinking standpoint. This dynamic will get you having conversations about compromise early on, so that when the security team inevitably raises eyebrows, you are ready with answers.

Be prepared to consider compromises you had not anticipated, and enter into discussions with the security team with as open a mind as possible. Remember the team is balancing priorities of not only your team, but other business and development teams as well.  If you and your security colleagues are doing the hard work to meet each other halfway then you are more likely to arrive at a solution that satisfies both parties.

Working together for the long term

While the previous strategies we’ve covered focus on short-term outcomes, in this continuous-deployment, shift-left world we now live in, the best way to convince your security team of the benefits of a third-party service – or any other decision – is to have them along from day one, as part of the team.

Roles and teams are increasingly fluid and boundary-crossing, yet security remains one of the roles least likely to be considered for inclusion on a software development team. Even in 2019, the task of ensuring that your product and stack are secure and well-defended is often left until the end of the development cycle.  This contributes a great deal to the combative atmosphere that is common.

Bringing security people into the development process much earlier builds rapport and prevents these adversarial, territorial dynamics. Consider working together to build Disaster Recovery plans and coordinating for shared production ownership.

If your organisation isn’t ready for that kind of structural shift, there are other ways to work together more closely with your security colleagues.

Try having members of your team spend a week or two embedded with the security team. You may even consider a rolling exchange – a developer for a security team member – so that developers build the security mindset, and the security team is able to understand the problems your team is facing (and why you are looking at introducing this new service).

At the very least, you should make regular time to meet with the security team, get to know them as people, and avoid springing things on them late in the project when change is hardest.

Riding off together into the sunset…?

If you’ve taken the time to get to know your security team and how they think, you’ll hopefully be able to get what you want from them – or perhaps you’ll understand why their objections were valid, and come up with a better solution that works well for both of you.

Investing in a strong relationship between your development and security teams will rarely lead to the apocalypse. Instead, you’ll end up with a better product, probably some new work friends, and maybe an exciting idea for a boundary-crossing new career in tech.

But this story isn’t over! Once you get the green light from security, you’ll need to think about how to roll your new service out safely, maintain it, and consider its full lifespan within your company.  Which leads us to part three of this series, on rolling it out and maintaining it … both your integration and your relationship with the security team.

 

Lilly Ryan is a pen tester, Python wrangler, and recovering historian from Melbourne. She writes and speaks internationally about ethical software, social identities after death, teamwork, and the telegraph. More recently she has researched the domestic use of arsenic in Victorian England, attempted urban camouflage, reverse engineered APIs, wielded the Oxford comma, and baked a really good lemon shortbread.

Outsource Your O11y: Get Aligned With Security (part 2/3)

Outsource Your O11y: How To Be A Champion (part 1/3)

I hear variations on this question constantly: “I’d really like to use a service like Honeycomb for my observability, but I’m told I can’t ship any data off site.  Do you have any advice on how to convince my security team to let me?”

I’ve given lots of answers, most of them unsatisfactory.  “Strip the PII/PHI from your operational data.”  “Validate server side.”  “Use our secure tenancy proxy.”  (I’m not bad at security from a technical perspective, but I am not fluent with the local lingo, and I’ve never actually worked with an in-house security team — i’ve always *been* the security team, de facto as it may be.) 

So I’ve invited three experts to share their wisdom in a three-part series of guest posts:

  1. How To Be A Champion, on how to choose a third-party vendor and champion them successfully to your security team.  (George Chamales)
  2. Get Aligned With Security, how to work with your security team to find the best possible outcome for all sides (Lilly Ryan)
  3. Now Roll It Out And Keep Them Happy, on how to operationalize your service by rolling out the integration and maintaining it — and the relationship with your security team — over the long run (Andy Isaacson)

My ✨first-ever guest posts✨!  Yippee.  I hope these are useful to you, wherever you are in the process of outsourcing your tools.  You are on the right path: outsourcing your observability to a vendor for whom it’s their One Job is almost always the right call, in terms of money and time and focus — and yes, even security. 

All this pain will someday be worth it.  🙏❤️  charity + friends


“How to be a Champion”

by George Chamales

You’ve found a third party service you want to bring into your company, hooray!

To you, it’s an opportunity to deploy new features in a flash, juice your team’s productivity, and save boatloads of money.

To your security and compliance teams, it’s a chance to lose your customers’ data, cause your applications to fall over, and do inordinate damage to your company’s reputation and bottom line.

The good news is, you’re absolutely right.  The bad news is, so are they.

Successfully championing a new service inside your organization will require you to convince people that the rewards of the new service are greater than the risks it will introduce (there’s a guide below to help you).  

You’re convinced the rewards are real. Let’s talk about the risks.

The past year has seen cases of hackers using third party services to target everything from government agencies, to activists, to Targetagain.  Not to be outdone, attention-seeking security companies have been actively hunting for companies exposing customer data then issuing splashy press releases as a means to flog their products and services.  

A key feature of these name-and-shame campaigns is to make sure that the headlines are rounded up to the most popular customer – the clickbait lead “MBM Inc. Loses Customer Data” is nowhere near as catchy as “Walmart Jewelry Partner Exposes Personal Data Of 1.3M Customers.”

While there are scary stories out there, in many, many cases the risks will be outweighed by the rewards. Telling the difference between those innumerable good calls and the one career-limiting move requires thoughtful consideration and some up-front risk mitigation.

When choosing a third party service, keep the following in mind:

    • The security risks of a service are highly dependent on how you use it.  
      You can adjust your usage to decrease your risk.  There’s a big difference between sending a third party your server metrics vs. your customer’s personal information.  Operational metrics are categorically less sensitive than, say, PII or PHI (if you have scrubbed them properly).
    • There’s no way to know how good a service’s security really is.  
      History is full of compromised companies who had very pretty security pages and certifications (here’s Equifax circa September 2017).  Security features are a stronger indicator, but there are a lot more moving parts that go into maintaining a service’s security.
    • Always weigh the risks vs. the rewards.

 

 

There’s risk no matter what you do – bringing in the service is risky, doing nothing is risky.  You can only mitigate risks up to a point. Beyond that point, it’s the rewards that make risks worthwhile.

Context is critical in understanding the risks and rewards of a new service.  

You can use the following guide to put things in context as you champion a new service through the gauntlet of management, security, and compliance teams.  That context becomes even more powerful when you can think about the approval process from the perspective of the folks you’ll need to win over to get the okay to move forward.

In the next part of this series Lilly Ryan shares a variety of techniques to take on the perspective of your management, security and compliance teams, enabling you to constructively work through responses that can include everything from “We have concerns…” to “No” to “Oh Helllllllll No.”

Championing a new service is hard – it can be equally worthwhile.  Good luck!

 

George Chamales is a useful person to have around. Please send critiques of this post to george@criticalsec.com

“A Security Guide for Third Party Services” Worksheet

Note to thoughtful service providers:  You may want to fill parts of this out ahead of time and give it to your prospective customers.  It will provide your champion with good fortune in the compliance wars to come.  (Also available as a nicely formatted spreadsheet.)

 

Our Reasons
Why this service? This is the justification for the service – the compelling rewards that will outweigh the inevitable risks.
What will be true once the service is online?
Good reasons are ones that a fifth grader would understand.
Our Data
Data it will / won’t collect? Describe the classes or types of data the service will access / store and why that’s necessary for the service to operate.
If there are specific types of sensitive data the service won’t collect (e.g. passwords, Personally Identifiable Information, Patient Health Information) explicitly call them out.
How is data be accessed? Describe the process for getting data to the service.  
Do you have to run their code on your servers, on your customer’s computers?
Our Costs
Costs of NOT doing it? This are the financial risks / liabilities of not going with this service. What’s the worst and average cost?
Have you had costly problems in the past that could have been avoided if you were using this service?
Costs of doing it? Include the cost for the service and, if possible, the amount of person-time it’s going to take to operate the service.  
Ideally less than the cost of not doing it.
Our Risk – how mad will important people be…
If it’s compromised. What would happen if hackers or attention-seeking security companies publicly released the data you sent the service?  Is it catastrophic or an annoyance?
When it goes down? When this service goes down (and it will go down), will it be a minor inconvenience or will it take out your primary application and infuriate your most valuable customers?
Their Security  – in order of importance
SSO & 2FA Support? This is a security smoke test:  If a service doesn’t support SSO or 2FA, it’s safe to assume that they don’t prioritize security.
Also a good idea to investigate SSO support up front since some vendors charge extra for it (which is a shame).
Fine-grained permissions? This is another key indicator of the service’s maturity level since it takes time and effort to build in.  It’s also something else they might make you pay extra for.
Security certifications? These aren’t guarantees of quality, but it does indicate that the company’s put in some effort and money into their processes.
Check their website for general security compliance merit badges such as SOC2, ISO27001 or industry-specific things like PCI or HIPAA.
Security & privacy pages? If there is, it means that they’re willing to publicly state that they do something about security.  The more specific and detailed, the better.
Vendor’s security history? Have there been any spectacular breaches that demonstrated a callous disregard for security, gross incompetence, or both?
BONUS Questions Want to really poke and prod the internal security of your vendor?  Ask if they can answer the following questions:

  • How many known vulnerabilities (CVEs) exist on your production infrastructure right now?
  • At what time (exactly) was the last successful backup of all your customer data completed?
  • What were the last three secrets accessed in the production environment?
Our Decision
Is it worth it? Look back through the previous sections and ask whether it makes sense to:

* Use the 3rd party service

* Build it yourself

* Not do it at all
Would a thoughtful person agree with you?

 

 

 

Outsource Your O11y: How To Be A Champion (part 1/3)

Logs vs Structured Events

I got an interesting tweet the other day from @evntdrvn in response to this thread of mine. Paraphrasing,

“So I’ve almost got our group at work up to Step 1 in your observability maturity model, but some of the devs that I work with want to turn OFF our lovely structured logging in prod for informational-level msgs due to their legacy philosophy (‘we only log errors in prod’). The reasons given are mostly philosophical (“I’m a dev and only interested when things error out, I don’t want any other noise in prod logs”, “I don’t want to slow my app down in prod”). Help?!?”

As I was reading this, I was itching to fly out and dive into battle with Eric. I know exactly where his opinionated devs are coming from. I used to say the same things! I even wrote a whole blog post about it.

These developers have internalized a set of rules and best practices for dealing with output data, in the context of “monolith application development in the early 2000s”.

Monolithic systems assumptions

Those systems had many common constraints and assumptions, such as:

  • We have a monolith service, or a very small number of services. We can model the system in our heads.
  • Logging is done to local disk, which can impact performance
  • Disks are expensive
  • Screen Shot 2019-02-05 at 7.02.43 AM
  • Log lines are spat out inline with execution.  A poorly placed printf can take the whole system down.
  • Investigation is rare, and usually means a human reading error logs.
  • Logging is of poor utility for understanding internal states or execution paths; you should just read the code or use a debugger.  (There are few or network hops between functions.)
  • Logging is mostly useful for detecting certain terminal crash states or connection errors.

Monolithic logging best practices

Therefore:

  • We should be very stingy in what we log
  • Debuggers should be used for understanding internal states of the code
  • Logs are a last resort and record of crash dumps.  We do not expect to use log data in the course of our daily work.  We assume log-related manual investigation will be infrequent and of limited utility.

These were exactly the right lessons to learn in the era of expensive hardware and monolithic repos/artifacts. Many people still work in environments like this, and follow logging best practices like these. God bless, more power to em.

Distributed systems assumptions

But more and more of us face systems that are very different.

  • We have many services, possibly many MANY services. A representative request will have “many” hops across “many” services and routers and proxies and meshes and storage systems.
  • We cannot model the system in our heads; it would be a mistake to try. We rely on tooling as the source of truth for those systems.
  • You may or may not have access to those services, or the systems your code runs on. There may or may not be a logging facility, or a centralized log aggregator. Your only view of the system is through the instrumentation of your code.
  • Disks and system resources are cheap, ephemeral, all but disposable.
  • Data services are similarly cheap.  We can almost entirely silo application performance off from the cost of writing perf data out.Screen Shot 2019-02-05 at 7.03.04 AM
  • Investigation is prohibitively slow and expensive for a human to do by hand. Many of the nodes or processes we need to inspect may no longer even exist, but their past states may still be relevant to us in understanding patterns to the present time.
  • Investigation should usually be done distributedly, across all instantiations of your code, however many there might be — and in real time
  • Investigation requires computation — not just string search. We need to ask on the fly involving math and percentiles and breakdowns and group by’s.  And we need access to the raw requests in order to run accurate computations — no pre-aggregates.
  • The hardest part isn’t usually debugging the code, it’s figuring out where is the code you need to debug. Or what the errors or outliers have in common from the perspective of the code.  Fixing the code itself is often comparatively trivial, once found.
  • What even is ‘logging’?
  • What even is ‘local disk’?

This isn’t optional: at some point of complexity or scale or distributedness, it becomes necessary if you want to work with these systems.

Logs can’t help you here.

And you aren’t going to get that kind of explorable data out of loglevel:ERROR, or by chopping up your telemetry into disconnected metrics devoid of context.

You are only going to get this kind of explorable, ad hoc, computation-friendly data if you take a radically new approach to how you output and aggregate telemetry.  You’re going to need to replace your log lines and log levels with a different sort of beast: arbitrarily wide structured events that describe the request and its context, one event per

sourceoftruth
Remember kids: you either have a single source of truth, or multiple sources of lies.

request per service.

If it helps, don’t think of them as log files any more. Think of them as events. Yes, you can stash this stream in a file, but why would you?  on what disk?  will that work for your serverless functions too?  Just stream them over the network to wherever you want to put them.

 

Log levels are another confusing and unnecessary artifact of yesteryear that you no longer really need. The more you think of structured events as logs, the more tempted you may be to apply the old set of best practices. So just don’t think of them as logs at all.

How to gather and structure your data

Instead of dribbling little pebbles of log effluvia throughout your code, do this.  (If you’re a honeycomb user, our beelines do it all automatically for you *and* pre-propagate the blobs with everything we know of your context.)

  1. Initialize an empty blob at the beginning, when the request first enters the service.
  2. Stuff any and all interesting detail about the request into that blob throughout the lifetime of the request.
    • Any unique id, any high-cardinality variable, any headers passed in, every full query, normalized query, and query execution time; every http call out to a remote service, every http execution time; any shopping cart id, first and last name, execution time — literally anything interesting, append to blob.
  3. Then, when the request is about to exit or error, write the blob off to honeycomb or another service or disk somewhere.

You can see immediately how this method has radically different performance Screen Shot 2019-02-05 at 7.02.57 AMimplications and risks than the earlier shotgun spray approach. No more “oops i accidentally put a print line INSIDE a for loop”. The write amplification profile is compressed. Most importantly, the incremental cost of capturing more detail about the request per service is nearly zero.

And now you have the kind of structured data that you can feed into something like a columnar store, or honeycomb, and run ad hoc queries to your heart’s delight.

Distributed systems logging events best practices:

Let’s sum up.  (I’m including links to other past rants on this topic):

Just think.

No more doing multi-line regexps trying to look for the same request ID or user ID doing five suspicious things in a row.

No more regexps at all, for fuck’s sake.

No more bullshit percentiles that were computed at write time by averaging over a bunch of other averages

No more having to jump around from dashboards to logs trying to vainly eyeball correlate one spike with another. No more wondering why no two tools can agree if anything even exists or not

Just gather the detail you need to ask the questions when you need them, and store it in a single source of truth.  It’s that simple.

No need to shame people from learning best practices that worked perfectly well for a long time.  You can either let them learn the hard way that this transformation is non optional, or you can help them learn the easy way that it’s simply much better and easier to invest in this telemetry up front.  You seem like a nice enough chap, which is probably why you chose door 2.  (If you wanted to get tougher about it, have a few reformed folks in to tell their horror stories.  Try some ex-twitter engineers.)

The hardest part seems to be getting people to unlearn all the best practices they once learned for dealing with logs.  So just don’t call it logs anymore, if that helps. Call it “structured events”.

– charity.

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Logs vs Structured Events

Software Sprawl, The Golden Path, and Scaling Teams With Agency

gplanis

Stop me if you’ve heard this one before.

The company is growing like crazy, your engineering team keeps rising to the challenge, and you are ferociously proud of them.  But some cracks are beginning to show, and frankly you’re a little worried.  You have always advocated for engineers to have broad latitude in technical decisions, including choosing languages and tools.  This autonomy and culture of ownership is part of how you have successfully hired and retained top talent despite the siren song of the Faceboogles.

But recently you saw something terrifying that you cannot unsee: your company is using all the languages, all the environments, all the databases, all the build tools.  Shit!!!  Your ops team is in full revolt and you can’t really blame them.  It’s grown into an unsupportable nightmare and something MUST be done, but you don’t know what or how — let alone how to solve it while retaining the autonomy and personal agency that you all value so highly.

gpredwedd

I hear a version of this everywhere I’ve gone for the past year or two.  It’s crazy how often.  I’ve been meaning to write my answer up for ages, and here it (finally) is.

gpathcartoon

First of all: you aren’t alone.  This is extremely common among high-performing teams, so congratulations.  Really!

There actually seems to be a direct link between teams that give engineers lots of leeway to own their technical decisions and that team’s ability to hire and retain top-tier talent, particularly senior talent.   Everything is a tradeoff, obviously, but accepting somewhat more chaos in exchange for a stronger sense of individual ownership is usually the right one, and leads to higher-performing teams in the long run.

Second, there is actually already a well-trod path out of this hole to a better place, and it doesn’t involve sacrificing developer agency.  It’s fairly simple!  Just five short steps, which I will describe to you now.

gpjava

How to build a golden path and reverse software sprawl

  1. Assemble a small council of trusted senior engineers.
  2. Task them with creating a recommended list of default components for developers to use when building out new services.  This will be your Golden Path, the path of convergence (and the path of least resistance).
  3. Tell all your engineers that going forward, the Golden Path will be fully supported by the org.  Upgrades, patches, security fixes; backups, monitoring, build pipeline; deploy tooling, artifact versioning, development environment, even tier 1 on call support.  Pave the path with gold.  Nobody HAS to use these components … but if they don’t, they’re on their own.  They will have to support it themselves.
  4. Work with team leads to draw up an umbrella plan for adopting the Golden Path for their current projects as well as older production services, as much as is reasonable or possible or desirable.  Come up with a timeline for the whole eng org to deprecate as many other tools as possible.  Allocate real engineering time to the effort.  Hell, make a party out of it!
  5. After the cutoff date (and once things have stabilized), establish a regular process for reviewing and incorporating feedback about the blessed Path and considering any proposed changes, additions or removals.

There you go.  That’s it.  Easy, right??

(It’s not easy.  I never said it was easy, I said it was simple.  👼🏼)

Your engineers are currently used to picking the best tool for the job by optimizing locally.  What data store has a data model that is easiest for them to fit to their needs?  Which language is fastest for I/O throughput?  What are they already proficient in?  What you need to do is start building your muscles for optimizing globally.  Not in isolation of other considerations, but in conjunction with them.  It will always be a balancing act between optimizing locally for the problem at hand and optimizing globally for operability and general sanity.

(Oh, incidentally, requiring an engineer to write up a proposal any time they want to use a non-standard component, and then defend their case while the council grills them in person — this will be nothing but good for them, guaran-fucking-teed.)

Let’s go into a bit more detail on each of the five points.  But quick disclaimer: this is not a prescription.  I don’t know your system, your team, your cultural land mines or technical interdependencies or anything else about your situation.  I am just telling stories here.

gpjon

1. Assemble your council

Three is a good number for a council.  More than that gets unwieldy, and may have trouble reaching consensus.  Less than three and you run into SPOFs.  You never want to have a single person making unilateral decisions because a) the decision-making process will be weaker, b) it sets that person up for too much interpersonal friction, and c) it denies your other engineers the opportunity to practice making these kinds of decisions.

  • Your council members need technical breadth more than depth, and should be widely respected by engineers.
  • gprain7At least one member should have a long history with the company so they know lots of stupid little details about what’s been tried before and why it failed.
  • At least one member should be deeply versed in practical data and operability concerns.
  • They should all have enough patience and political skill to drive consensus for their decisions.  Absolutely no bombthrowers.

If you’re super lucky, you just tap the three senior technologists who immediately come to mind … your mind and everyone else’s.  If you don’t have this kind of automatic consensus, you may want to let teams or orgs nominate their own representative so they feel they have some say.

gpcss

2.  Task the council with defining a Golden Path

gpsun2

Your council cannot vanish for a week and then descend from the mountain lugging lists engraved on stone tablets.  The process of discovery and consensus is what validates the result.

The process must include talking to and gathering feedback from your engineers, talking to experts outside the company, talking to teams at other companies who are farther along using that technology, coming up with detailed pro/con lists and reasons for their choices.  Maybe sometimes it includes prototyping something or investigating the technical depths … but yeah no mostly it’s just the talking.

You need your council members to have enough political skill to handle these conversations deftly, building support and driving consensus through the process.  Everybody doesn’t have to love the outcome, but it shouldn’t be a *surprise* to anyone by the end.

gphappy

3.  Know where you’re going

Your council should create a detailed written plan describing which technologies are going to be supported … and a stab at what “supported” means.  (Ask the experts in each component what the best practices are for backups, versioning, dependency management, etc.)

You might start with something like this:

* Backend lang: Go 1.11           ## we will no longer be supporting
backend scripting languages
* Frontend lang: ReactJS v 16.5
* Primary db: Aurora v 2.0        ## Yes, we know postgres is "better", 
but we have many mysql experts and 0 pg experts except the one guy 
who is going to complain about this.  You know who you are.
* Deploy pipeline: github -> jenkins + docker -> S3 -> custom k8s 
deploy tooling
* Message broker: kafka v 2.10, confluent build
* Mail: SES
* .... etc

Circulate the draft regularly for feedback, especially with eng managers.  Some team reorganization will probably be necessary to bear the new weight of your support specifications, and managers will need some lead time to wrangle this.

This is also a great time to reconceive of the way on call works at your company.  But I am not going to go into all that here.

gpbutt2

4. Set a date, draft a plan: go!

Get approval from leadership to devote a certain amount of time to consolidating your stack and paying down a lump sum of tech debt.  It depends on your stage of decay, gprainbut a reasonable amount of time might be “25% of engineering time for three months“.  Whatever you agree to, make sure it’s enough to make the world demonstrably better for the humans who run it; you don’t want to leave them with a tire fire or you’ll blow your credibility.

The council and team leads should come up with a rough outer estimate for how long it would take to rewrite everything and move the whole stack on to the Golden Stack.  (It’s probably impossible and/or would take years, but that’s okay.)  Next, look for the quick wins or swollen, inflamed pain points.

  • If you are running two pieces of functionally similar software, like postgres and mysql, can you eliminate one?
  • If you are managing something yourself that AWS could manage for you (e.g. postfix instead of SES, or kafka instead of kinesis), can you migrate that?
  • If you are managing anything yourself that is not core to your business value, in fact, you should try to not manage it.
  • If you are running any services by hand on an AWS instance somewhere, could you try using a service?
  • If you are running your own monitoring software, etc … can you not?
  • If you have multiple versions of a piece of software, can you upgrade or consolidate on one version?

gpdied

The hardest parts are always going to be the ones around migrating data or rewriting components.  Not everything is worth doing or can afford to be done in the time span of your project time, and that’s okay.

Next, brainstorm up some carrots.  Can you write templates so that anybody who writes a service using your approved library, magically gets monitoring checks without having to configure anything?  Can you write a wrapper so they get a bunch of end-to-end tests for free?  Anything you can do to delight people or save them time and effort by using your preferred components is worth considering.  gps8

(By the way, if you don’t have any engineers devoted to internal tooling, you’re probably way overdue at this point.)

Pay down as much debt as you can, but be pragmatic: it’s better to get rid of five small things than one large thing, from a support perspective.  Your main goal is to shrink the number of types of software your team has to support, particularly databases.

Do look for ways to make it fun, like … running a competition to see who can move the most tools to AWS in a week, or throwing a hack week party, or giving dorky prizes like trophies that entitle you to put your manager on call instead of you for a day, etc.

gpcersei

5. Make the process sustainable

After your target date has come and gone, you probably want to hold a post mortem retrospective and do lots of listening.  (Well — first might I recommend a bubble bath and a bottle of champagne?  But then a post mortem.)

Nothing is ever fixed forever.  The company’s needs are going to expand and contract, gpsrsand people will come and go, because change is the only constant.  So you need to bake some flex into your system.  How are you going to handle the need for changes to the Golden Path?  Monthly discussions?  An email list?  Quarterly meetings with a formal agenda?  I’ve seen people do all of these and more, it doesn’t really matter afaict.

Nobody likes a cabal, though, so the original council should gradually rotate out.  I recommend replacing one person at a time, one per quarter, and rotating in another senior engineer in their place.  This provides continuity while giving others a chance to learn these technical and political skills.

In the end, engineers are still free to use any tool or component at any time, just like before, only now they are solely responsible for it, which puts pressure on them not to do it unless REALLY necessary.  So if someone wants to propose adding a new tool to the default golden path, they can always add it themselves and gain some experience in it before bringing it to the council to discuss a formal place for it.

gplinux

That’s all folks

See, wasn’t that simple?

(It’s never simple.)

I dearly wish more people would write up their experiences with this sort of thing in detail.  I think engineering teams are too reluctant to show their warts and struggles to the world — or maybe it’s their executives who are afraid?  Dunno.

Regardless, I think it’s actually a highly effective recruiting tool when teams aren’t afraid to share their struggles.  The companies that brag about how awesome they are are the ones who come off looking weak and fragile.  Whereas you can always trust the ones gpwvwho are willing to laugh about all the ways they screwed up.  Right?

In conclusion, don’t feel like an asshole for insisting on some process here.  There should be friction around adding new components to your stack.  (Add in haste, repent at leisure, as they say.)  Anybody who argues with you probably needs to be exposed to way, way more of the support load for that software.  That’s my professional opinion.

Anyway.  You win or you die.  Good luck with your sprawl.

charity

IMG_2433

 

 

Software Sprawl, The Golden Path, and Scaling Teams With Agency

Shipping Software Should Not Be Scary

On twitter this week, @srhtcn noted that “Many incidents happen during or right after release” and asked for advice on ways to fix this.

And he’s right!  Rolling out new software is the proximate cause for the overwhelming majority of incidents, at companies of all sizes.  Upgrading software is both a necessity and a minor insanity, considering how often it breaks things.

Image result for deploy production memeI’m not going to recap the history of continuous integration and delivery, suffice it to say that we now know that smaller and more frequent changes are much safer than larger and less frequent changes.

But it’s still risky.  And most issues are still caused by humans and our pesky need for “improvements”.  So what can be done?

It’s not ok for software releases to be scary and hazardous

First of all: If releasing is risky for you, you need to fix that.  Make this a priority.  Track your failures, practice post mortems, evaluate your on call practices andImage result for test in production meme culture.  Know if you’re getting better or worse.  This is a project that will take weeks if not months until you can be confident in the results.

You have to fix it though, because these things are self-reinforcing.  If shipping changes is scary and fraught, people will do it less and it will get even MORE scary and treacherous.

Likewise, if you turn it into a non-cortisol inducing event and set expectations, engineers will ship their code more often in smaller diffs and therefore break the world less.

Fixing deploys isn’t about eliminating errors, it’s about making your pipeline resilient to errors.  It’s fundamentally about detecting common failures and recovering from them, without requiring human intervention.

Value your tools more

As an short term patch, you should run deploys in the mornings or whenever everyone is around and fresh.  Then take a hard look at your deploy pipeline.

In too many organizations, deploy code is a technical backwater, an accumulation of crufty scripts and glue code, forked gems and interns’ earnest attempts to hack up Capistrano.  It usually gives off a strong whiff of “sloppily evolved from many 2 am patches with no code review”.Image result for test in production meme

This is insane.  Deploy software is the most important software you have.  Treat it that way: recruit an owner, allocate real time for development and testing, bake in metrics and track them over time.

If it doesn’t have an owner, it will never improve.  And you will need to invest in frequent improvements even after you’re over this first hump.

  • Signal high organizational value by putting one of your best engineers on it.
  • Recruit help from the design side of the house as well.  The “right” thing to do must be the fastest, easiest thing to do, with friendly prompts and good docs.  No “shortcuts” for people to reach for at the worst possible time.  You need user research and design here.  Image result for deploy production meme
  • Track how often deploys fail and why.  Managers should pay close attention to this metric, just like the one for people getting interrupted or woken up, and allocate time to fixing this early whenever it sags.  Before it gets bad.
  • Allocate real time for development, testing, and training — don’t expect the work to get shoved into people’s “spare time” or post mortem cleanup time.  Make sure other managers understand the impact of this work and are on board.  Make this one of your KPIs.Image result for deploy production meme

In other words, make deploy tools a first class citizen of your technical toolset.  Make the work prestigious and valued — even aspirational.  If you do performance reviews, recognize the impact there.

(Btw, “how we hardened our deploys” is total Velocity-bait (&& other practitioner conferences) as well as being great for recruiting and general visibility in blog post form.  People love these stories; there definitely aren’t enough of them.)

Turn software engineers into software owners

The canonical CI/CD advice starts with “ship early, ship often, ship smaller change sets”.  That’s great advice: you should definitely do those things.  But they are covered plenty elsewhere.  What’s software ownership?

Software ownership is the natural end state of DevOps.  Software engineers, operations engineers, platform engineers, mobile engineers — everyone who writes code should be own the full lifecycle of their software.

Software owners are people who:

  1. Write codeImage result for deploy production meme
  2. Can deploy and roll back their own code
  3. Are able to debug their own issues in prod (via instrumentation, not ssh)

If you’re lacking any one of those three ingredients, you don’t have ownership.

Why ownership?  Because software ownership makes for better engineers, better software, and a better experience for customers.  It shortens feedback loops and means the person debugging is usually the person with the most context on what has recently changed.

Some engineers might balk at this, but you’ll be doing them a favor.  We are all distributed systems engineers now, and distributed systems require a much higher level of operational literacy.  May as well start today.

Fail fast, fix fast

This is about shifting your mindset from one of brittleness and a tight grip, to one of flexibility where failures are no big deal because they happen all the time, don’t impact users, and give everyone lots of practice at detecting and recovering from them.

Here are a few of the best practices you should adopt with this practice.

Make operability a high-value skill set.  Never promote someone to “senior engineer” if they can’t deploy and debug their Image result for test in production memeown code.

Software engineers don’t have to become operational experts.  They do need to know the bare basics of instrumentation, deploy/revert, and debugging.

Everyone who puts software in production needs to understand and feel responsible for the full lifecycle of their code, not just how it works in their IDE.

Baking: it’s not just for cookies

Shipping something to production is a process of incrementally gaining confidence, not a switch you can flip.

You can’t trust code until it’s been in prod a while, Image result for deploy production memeuntil you’ve seen it perform under a wide range of load and concurrency scenarios, in lots of partial failure modes.  Only over time can you develop confidence in it not being terrible.

Nothing is production except production.  Don’t rely on never failing; expect failure, embrace failure.  Practice failure!  Build guard rails around your production systems to help you find and fix problems quickly.

The changes you need to make your pipeline more resilient are roughly the same changes you need to safely test in production.  These are a few of your guard rails.

  • Use feature flags to switch new code paths on and offImage result for test in production meme
  • Build canaries for your deploy process, so you can promote releases gracefully and automatically to larger subsets of your traffic as you gain confidence in them
  • Create cohorts.  Deploy to internal users first, then any free tier, etc in order of ascending importance.  Don’t jump from 10% to 25% to 50% and then 100% — some changes are related to saturating backend resources, and the 50%-100% jump will kill you.
  • Have robots check the health of your software as it rolls out to decide whether to promote the canary.  Over time the robot checks will mature and eventually catch a ton of problems and regressions for you.

The quality of code is not knowable before it hits production.  You may able to spot some problems, but you can never guarantee a lack of then.  It takes time to bake a new release and gain incremental confidence in new code.

In summary.

  1. Get someone to own the deploy software
  2. Value the work
  3. Create a culture of software ownership
  4. LOOK at what you’ve done after you do it
  5. Be suspicious of new versions until they prove themselves

Image result for deploy production meme

Two blog posts in one weekend!  That’s definitely never happened before.  Thanks to Baron for asking me to draft this up following the weekend’s twitter thread: https://twitter.com/mipsytipsy/status/1030340072741064704.

 

 

Shipping Software Should Not Be Scary

On Engineers and Influence

(Based on yesterday’s tweetstorm and the ensuing conversation, https://twitter.com/mipsytipsy/status/1029608573217587201)

Let’s talk about influence. As an engineer, how do you get influence? What does influence look like, what is it rooted in, how do you wield it or lose it? How is it different from the power and influence you might have as a manager?[0]

This often comes up in the context of ICs who desperately want to become managers in order to have more access to information and influence over decisions. This is a bad signal, though it’s sadly very common.

When that happens, you need to do some soul-searching. Does your org make space for senior ICs to lead and own decisions? Do you have an IC track that runs parallel to the manager track at least as high as director level? Are they compensated equally? Do youImage result for engineer software meme individual contributorhave a career ladder? Are your decision-making processes mysterious to anyone who isn’t a manager? Don’t assume what’s obvious to you is obvious to others; you have to ask around.

If so, it’s probably their own personal baggage speaking. Maybe they don’t believe you. Maybe they’ve only worked in orgs where managers had all the power. Maybe they’ve even worked in lots of places that said the exact same things as you are saying about how ICs can have great impact, but it was all a lie and now they’re burned. Maybe they aren’t used to feeling powerful for all kinds of reasons.

Regardless, people who want to be managers in order to perpetuate a bad power structure are the last people you want to be managers.[1]

But what does engineering influence look like?  How do your powers manifest?

I am going to avoid discussing the overlapping and interconnected issues of gender, race and class, let’s just acknowledge that it’s much more structurally difficult for some to wield power than for others, ok?

The power to create

Doing is the engineering superpower. We create things with just a laptop and our brain! It’s incredible! We don’t have to constantly convince and cajole and coerce others into building on our behalf, we can just build.

This may seem basic, but it matters. Creation is the ur-power from which all our forms of power flow. Nothing gets built unless we agree to build it (which makes this an ethical issue, too).

Facebook had a poster that said “CODE WINS ARGUMENTS”. Problematic in many ways, absolutely. But how many times have you seen a technical dispute resolved by who wasImage result for code wins arguments facebook willing to do the work? Or “resolved” one way.. then reversed by doing? Doing ends debates. Doing proves theories. Doing is powerful. (And “doing” doesn’t only mean “write code”.)

Furthermore, building software is a creative activity, and doing it at scale is an intensely communal one. As a creative act, we are better builders when we are motivated and inspired and passionate about our work (as compared to say, chopping wood). And as a collaborative act, we do better work when we have high trust and social cohesion.

Engineering ability and judgment, autonomy and sense of purpose, social trust and cooperative behaviors: this is the raw stuff of great engineering. Everybody has a mode or two that they feel most comfortable and authoritative operating from: we can group these roughly into archetypes.

(Examples drawn from some of the stupendously awesome senior engineers I’ve gotten to work with over the years, as well as the ways I loved to fling my weight around as an engineer.)

Archetypes of influence

  • “Doing the work that is desperately hard and desperately needed — and often desperately dull.” SOC2 compliance, backups and restores, terrifying refactors, any auth integration ever: if it’s moving the business forward, they don’t give a shit how dull the work is. If you are this engineer, you have a deep well of respect and gratitude.
  • Debugger of last resort.” Often the engineer who has been there the longest or originally built the system. If you are helpful and cheerful with your history and context, this is a huge asset. (People tend to wildly overestimate this person’s indispensability, actually; please don’t encourage this.)Image result for engineer software meme manager
  • The “expert” archetype is closely related. If you are the deep subject matter expert in some technology component, you have a shit ton of influence over anything that uses or touches that component. (You should stay up on impending changes to retain your edge.)
  • There are people who deliver a bafflingly powerful firehose of sustained output, sometimes making headway on multiple fronts at once. Some work long hours, others just have an unerring instinct for how to maximize impact (this sometimes maps to junior/senior manifestations). Nobody wants to piss off those people. Their consent is critical for … everything. Their participation will often turbo charge a project or pull a foundering effort over the finish line.

Not all influence is rooted in raw technical strength or output.  Just a few of the wide variety of creative/collaborative/interpersonal strengths:

  • Some engineers are infinitely curious, and have a way of consistently sniffing a few steps ahead of the pack. They might seem to be playing around with something pointless, and you want to scold them; then they save your ass from total catastrophe. You learn to value their playing around.
  • Some engineers solve problems socially, by making friends and trading tips and fixes and favors in the industry. Don’t underestimate social debugging, it’s often the quickest path to the right answer.Image result for influence meme
  • Some are dazzlingly lazy and blow your mind with their elegant shortcuts and corners correctly cut.
  • Some are recruiting magnets, and it’s worth paying their salary just for all the people who want to work with them again.
  • Some are skilled at driving consensus among stakeholders.
  • Some are killer explainers and educators and storytellers.
  • Some are the senior engineer everyone silently wants to grow up to be.
  • Some can tell such an inspiring story of tomorrow that everyone will run off to make it so.
  • Some teach by turning code reviews into a pedagogical art form.
  • Some make everyone around them somehow more productive and effective. Some create relentless forward momentum. Some are good at saying no.

And there are a few special wells of power that bear calling out as such.

  • Engineers who have been managers are worth their weight in gold.  They can translate business goals for junior engineers in their native language with impeccable credibility (something managers never really have, esp in junior engineers’ eyes.). They make strong tech leads, they can carve up projects into components that challenge but do not overwhelm each contributor while hitting deadlines.
  • Some engineers are a royal pain in the ass because they questionImage result for engineer software meme individual contributor and challenge every system and hierarchy. But these are sharp, powerful rocks that can polish great teams. Though they do require a strong manager, to channel t
    heir energy towards productive dialogue and improvement and keep them from pissing off the whole team.
  • And let’s not forget engineers who are on call. If you have a healthy on call culture,your ownership over production creates a deep, deep well of power and moral authority — to make demands, drive change, to prioritize. On call should not be a shit salad served up to those who can’t refuse, it should be a badge of honor and seriousness shouldered by every engineer who ships code. (And it should not be miserable or regularly life-impacting.)

… I could go on all day. Engineering is such a powerful role and skill set. It’s definitely worth unpacking where your own influence comes from, and understanding how others perceive your strengths.

Most forms of power boil down to “influence, wielded”.

But just banging out code is not enough. You may have credibility, but having it is not the same as using it. To transform influence into power you have to use it.  And the way you use it is by communicating.

What’s locked up in your head has no impact on the rest of us.  You have to get it out.

You can do this in lots of ways: by writing, in 1x1s, conversations with small groups, openly recruiting allies, convincing someone with explicit authority, broadcasting inImage result for engineer software meme individual contributorpublic, etc.

Because engineering is a creative activity, authoritarian power is actually quite brittle and damaging. The only sustainable forms of power are so-called “soft powers” like influencing and inspiring, which is why good managers use their soft power freely and hard power sparingly/with great reluctance. If your leadership invokes authority on the regular, that’s an antipattern.[2]

If you don’t speak up, you don’t have the right to sit and fume over your lack of influence. And speaking up does mean being vulnerable — and sometimes wrong — in front of other people.

This is not a zero-sum game.

Most of you have far more latent power than you realize or are used to wielding, because you don’t feel powerful or don’t recognize what you do in those terms.

Managers may have hard power and authority, but the real meaty decisions about technical delivery and excellence are more properly made by the engineers closest to them. These belong properly to the doers, in large part because they are the ones who have to support the consequences of these decisions.Image result for engineer software meme individual contributor

Power tends to flow towards managers because they are privy to more information. That makes it important to hire managers who are aware of this and lean against it to push power back to others.

In the same way that submissives have ultimate power in healthy BDSM relationships, engineers actually have the ultimate power in healthy teams. You have the ultimate veto: you can refuse to create.  Demand is high for your skills.  You can usually afford to look for better conditions. Many of you probably should.

And when technical and managerial priorities collide, who wins? Ideally you work together to find the best solution for the business and the people. The teams that feel 🔥on fire🔥 always have tight alignment between the two.

Pick your battles.

One final thought. You can have a lot of say in what gets built and how it gets built, if you cultivate your influence and spend it wisely. But you can’t have a say in everything. It doesn’t work that way.

Think of it like @mcfunley’s famous “innovation tokens”, but for attention and fucks given.
Image result for engineer software meme
The more you use your influence for good outcomes, the more you build up over time, yes … but it’s a precision tool, not background noise. Imagine someone trying to give you a massage by laying down on your whole back instead of pushing their elbow or hand into knots and trigger points. A too-broad target will diffuse your force and limit your potential impact.

Spend your attention tokens wisely.

And once you have influence, don’t forget to use it on behalf of others. Pay attention to those who aren’t being heard, and amplify their voices. Give your time, lend your patronage and credibility, and most of all teach the skills that have made you powerful to others who need them.

charity

P.S. I owe a huge debt to all the awesome senior engineers i’ve gotten to work with.  Mad love to you all.  ❤
Image result for influence meme

  • [0] I successfully answered one (1) of these questions before running out of steam.  Later. 
  • [1] Sheepish confession: this is why I became a manager.
  • [2] It’s also a bad sign if they won’t grant any explicit authority to the people they hold responsible for outcomes. I’m talking about relatively healthy orgs here, not pathological ones where people (often women) are told they don’t need promotions or explicit authority, they should just use their “soft power” — esp when the hard forms of power aligned against with them. That’s setting you up for failure.
  • [3] Some people seem caught off guard by my use of “power” to signal anything other than explicit granted powers by the org. This doesn’t make any sense to me. I find it too depressing and disempowering to think of power as merely granted authority. It doesn’t map to how I experience the world, either. Individual clout is a thing that waxes and wanes and only exists in relation to others’. I’ve seen plenty of weak managers pushed around by strong personalities (which is terrible too).
On Engineers and Influence