Bottleneck #01: Tech Debt

In its early days, a startup searches for a superb product-market match. When
it finds one it appears to be like to develop quickly, a part referred to as a scaleup. At this
time it is rising quickly alongside many dimensions: revenues, buyer,
headcount. At Thoughtworks, we have labored with many such scaleups, and our
work has targeted on learn how to assist them overcome numerous bottlenecks that
impede this development.

As we have achieved this work, we have seen frequent
bottlenecks, and realized approaches to take care of them. This text is the
first in a collection that examines these bottlenecks. In every article we’ll look
at how startups get into the bottleneck, normally by way of doing the precise
issues which can be wanted early in a startup’s life, however are now not proper as
development modifications the context for methods of working. We’ll spotlight key indicators
that the startup is approaching or caught within the bottleneck. We’ll then discuss
about learn how to break by way of the bottleneck, describing the modifications we have seen
that enable scaleups to achieve their correct potential.

We begin this collection by taking a look at technical debt: how the instruments and
practices that facilitate fast experimentation of the product/market match
want to vary as soon as development kicks in.

How did you get into the bottleneck?

The most typical scaling bottleneck we encounter is technical debt —
startups commonly state that tech debt is their major obstacle to
development. The time period “tech debt” tends for use as a catch-all time period,
usually indicating that the technical platform and stack wants
enchancment. They’ve seen characteristic improvement decelerate, high quality points, or
engineering frustration. The startup crew attributes it to technical debt
incurred attributable to an absence of technical funding throughout their development part.
An evaluation is required to determine the kind and scale of the tech debt.
It could possibly be that the code high quality is dangerous, an older language or framework
is used, or the deployment and operation of the product isn’t absolutely
automated. The answer technique may be slight modifications to the groups’
course of or beginning an initiative to rebuild elements of the appliance.

It’s essential to say that prudent technical debt is wholesome and desired,
particularly within the preliminary phases of a startup’s journey. Startups ought to
commerce technical points corresponding to high quality or robustness for product supply
velocity. This can get the startup to its first objective – a viable enterprise
mannequin, a confirmed product and clients that love the product. However because the
firm appears to be like to scale up, now we have to handle the shortcuts taken, or it
will in a short time have an effect on the enterprise.

Let’s look at a few examples we’ve encountered.

Firm A – A startup has constructed an MVP that has proven sufficient
proof (person visitors, person sentiment, income) for traders and secured
the subsequent spherical of funding. Like most MVPs, it was constructed to generate person
suggestions moderately than high-quality technical structure. After the
funding, as an alternative of rebuilding that pilot, they construct upon it, preserving the
traction by specializing in options. This will not be an instantaneous drawback
because the startup has a small senior crew that is aware of the sharp edges and
can put in bandaid options to maintain the corporate afloat.

The problems begin to come up when the crew continues to concentrate on characteristic
improvement and the debt isn’t getting paid down. Over time, the
low-quality MVP turns into core elements, with no clear path to enhance or
substitute them. There may be friction to be taught, work, and assist the code. It
turns into more and more tough to develop the crew or the characteristic set
successfully. The engineering leaders are additionally very nervous concerning the
attrition of the unique engineers and dropping the information they’ve.

Ultimately, the shortage of technical funding involves a head. The crew
turns into paralyzed, measured in decrease velocity and crew frustration. The
startup has to rebuild considerably, which means characteristic improvement has to
decelerate, permitting rivals to catch up.

Firm B – The corporate was based by ex-engineers and so they
needed to do every part “proper.” It was constructed to scale out of the field.
They used the newest libraries and programming languages. It has a finely
grained structure, permitting every a part of the appliance to be
applied with totally different applied sciences, every optimized to scale
completely. In consequence, it can simply have the ability to deal with hyper development when
the corporate will get there.

The difficulty with this instance is that it took a very long time to create,
characteristic improvement was gradual, and lots of engineers frolicked engaged on the
platform moderately than the product. It was additionally onerous to experiment — the
finely grained structure meant concepts that didn’t match into an present
service structure had been difficult to do. The corporate didn’t understand
the worth of the extremely scalable structure as a result of it was not in a position to
discover a product-market match to achieve that scale of buyer base.

These are two excessive examples, primarily based on an amalgamation of varied
purchasers with whom the startup groups at Thoughtworks have labored. Firm A
acquired itself right into a technical debt bottleneck that paralyzed the corporate.
Firm B over-engineered an answer that slowed down improvement and
crippled its capacity to pivot shortly because it learnt extra.

The theme with each is an lack of ability to search out the precise steadiness of technical
funding vs. product supply. Ideally we need to leverage the usage of prudent technical debt to energy
fast characteristic improvement and experimentation. When the concepts are discovered to
be beneficial, we must always pay down that technical debt. Whereas that is very simply
said, it may be a problem to place into observe.

To discover learn how to create the precise steadiness, we’re going to look at the
various kinds of technical debt:

Typical kinds of debt:

Technical debt is an ambiguous time period, typically thought to be purely
code-related. For this dialogue, we’re going to make use of technical debt to imply
any technical shortcut, the place we’re buying and selling long-term funding right into a
technical platform for short-term characteristic improvement.

Code high quality
Code that’s brittle, onerous to check, onerous to grasp, or poorly
documented will make all improvement and upkeep duties slower and can
degrade the “enjoyment” of writing code whereas demotivating engineers.
One other instance is a website mannequin and related knowledge mannequin that doesn’t
match the present enterprise mannequin, leading to workarounds.

A scarcity of unit, integration, or E2E assessments, or the improper distribution
(see take a look at pyramid). The developer can’t shortly get confidence that
their code won’t break present performance and dependencies. This leads
to builders batching modifications and a discount of deployment frequency.
Bigger increments are tougher to check and can typically end in extra bugs.
Between modules (typically occurs in a monolith), groups probably
block one another, thus decreasing the deployment frequency and
rising lead time for modifications. One resolution is to drag out providers
into microservices, which comes with it’s personal
— there might be extra easy methods of setting
clear boundaries throughout the monolith.

Unused or low worth options
Not usually considered technical debt, however one of many signs of
tech debt is code that’s onerous to work with. Extra options creates
extra circumstances, extra edge instances that builders must design
round. This erodes the supply velocity. A startup is experimenting. We
ought to all the time be certain to return and re-evaluate if the experiment
(the characteristic) is working, and if not, delete it. Emotionally, it may be very
tough for groups to make a judgment name, but it surely turns into a lot simpler
when you have got goal knowledge quantifying the characteristic worth.

Old-fashioned libraries or frameworks
The crew might be unable to reap the benefits of new enhancements and
stay weak to safety issues. It’ll end in a abilities
drawback, slowing down the onboarding of latest hires and irritating
present builders who’re pressured to work with older variations. Moreover, these
legacy frameworks are inclined to restrict additional upgrades and innovation.

Sub-optimum third-party merchandise or instruments that require a number of
upkeep. The panorama is ever-changing, and extra environment friendly
tooling could have entered the market. Builders additionally naturally need to
work with essentially the most environment friendly instruments. The steadiness between shopping for vs.
constructing is advanced and wishes reassessment with the remaining debt in

Reliability and efficiency engineering issues
This could have an effect on the shopper expertise and the flexibility to scale. We
must watch out, as now we have seen wasted effort in untimely
optimization when scaling for a hypothetical future state of affairs. It’s higher to
have a product confirmed to be beneficial with customers than an unproven product
that may scale. We’ll describe this in additional element within the piece on
“Scaling Bottleneck: Constructed with out reliability and observability in thoughts”.

Guide processes
A part of the product supply workflow isn’t automated. This might
be steps within the developer workflow or issues associated to managing the
manufacturing system. A warning: this will additionally go the opposite method once you
spend a number of time automating one thing that’s not used sufficient to be
definitely worth the funding.

Automated deployments
Early stage startups can get away with a easy setup, however this could
be addressed very quickly — small incremental deployments energy experimental
software program supply. Use the 4 key metrics as your information put up. You need to
have the flexibility to deploy at will, normally a minimum of as soon as a day.

Information sharing
Lack of helpful data is a type of technical debt. It makes
it tough for brand spanking new workers and dependent groups to stand up to hurry.
As commonplace observe, improvement groups ought to produce concisely
written technical documentation, API Specs, and architectural
determination information. It also needs to be discoverable through a developer
portal or search engine. An anti-pattern is not any moderation and
deprecation course of to make sure high quality.

Is that actually technical debt or performance?

Startups typically inform us about being swamped with technical debt, however
beneath examination they’re actually referring to the restricted performance
of the technical platform, which wants its personal correct therapy with
planning, requirement gathering, and devoted sources.

For instance, Thoughtworks’ startup groups typically work with purchasers on
automating buyer onboarding. They may have a single-tenant resolution
with little automation. This begins off properly sufficient — the builders can
manually arrange the accounts and monitor the variations between installs.
However, as you add extra purchasers, it turns into too time-consuming for the
builders. So the startup may rent devoted operations employees to set
up the shopper accounts. Because the person base and performance grows, it
turns into more and more tough to handle the totally different installs —
buyer onboarding time will increase, and high quality issues enhance. At
this level automating the deployment and configuration or shifting to a
multi-tenant setup will instantly impression KPIs — that is

Different types of technical debt are tougher to identify and tougher to level
to a direct impression, corresponding to code that’s tough to work with or brief
repeated handbook processes. The easiest way to establish them is with
suggestions from the groups that have them day-to-day. A crew’s
steady enchancment course of can deal with it and shouldn’t require a
devoted initiative to repair it.

How do you get out of the bottleneck?

The strategy that groups are taking to technical debt ought to come from
its technical technique, set by its leaders. It needs to be intentional,
clear, and re-evaluated over time. Sadly, we regularly see groups
working off historic instructions, creating future issues with out
realizing it. For a corporation on this circumstance, a couple of alternatives
generally set off when to re-evaluate their present technique:

  • New funding means extra options and extra sources — this may compound
    present issues. Addressing present technical debt needs to be a part of the
    funding plan.
  • New product course can invalidate earlier assumptions and put
    stress on new elements of the programs.
  • A very good governance course of includes reevaluating the state of the
    know-how on an everyday cadence.
  • New opinions will help keep away from “boiling frog” issues. Outdoors assist, crew
    rotations and new workers will convey a recent perspective.

The slippery slope

How did you find yourself with a number of technical debt? It may be very onerous to
pinpoint. Sometimes it isn’t attributable to only one occasion or determination, however
moderately a collection of choices and trade-offs made beneath stress.

Satirically, on reflection, if one considers every determination on the level
in time at which it was made, primarily based on what was identified on the
time, it’s unlikely to be thought of a mistake. Nevertheless, one
concession results in one other and so forth, till you have got a major problem
with high quality. There may be generally a tipping level at which resolving the
tech debt takes extra time than creating incremental worth.

It’s onerous to recuperate and the state of affairs tends to snowball. It’s
pure for builders to make use of the present state as an indicator of what
is suitable. In these circumstances, creating the brand new options will
end in much more debt. That is the slippery slope, a vicious cycle
that sadly results in a cliff as the trouble to implement the subsequent
characteristic will increase non-linearly.

Set a high quality bar

Many organizations discover it helpful to have a set of requirements and
practices to which the corporate is dedicated that information technical
evolution. Remember the fact that some technical practices are fairly
tough to attain, for instance steady supply; deploying
commonly with out affecting customers is technically difficult. Groups
typically have preliminary issues, and in response management could deprioritize
the observe. As an alternative we advocate the other, do it extra typically and
your groups will grasp the practices and type robust habits. When the
robust time comes, moderately than dropping the observe, use the suggestions to
information future funding in crew functionality.

Blast Radius

We settle for that taking shortcuts is a essential a part of scaling the
enterprise. How can we restrict the blast radius, understanding that these shortcuts
will have to be resolved, and even completely rebuilt? Clearly, we’d like a
technique that limits the impression to the enterprise. A method is to decouple
groups and programs, which permits a crew to introduce tech debt that’s
remoted and received’t essentially snowball as described above.

Prime quality literature about decoupling is plentiful, so we received’t
try to clarify right here. We advocate focusing consideration on
microservices and area pushed design methods. Nevertheless, watch out
doing an excessive amount of too early, decoupling provides latency and complexity to your
programs, and selecting poor area boundaries between groups can add
communication friction. We might be writing about anti-patterns associated
to overcomplicated distributed architectures in future articles.

Product and Engineering Collaboration

If commerce off conversations aren’t balanced between enterprise technique,
product and engineering, technical high quality mostly degrades first,
and because of this product high quality finally suffers as properly. While you
search for the basis explanation for this bottleneck, it almost all the time comes down
to the steadiness throughout the firm between enterprise, product and
engineering objectives. Lack of collaboration usually results in brief
sighted selections made in a vacuum. This could go each methods, chopping
corners in important areas or gold plating one thing that isn’t beneficial
are equally possible.

  • The enterprise technique at any cut-off date needs to be clear and clear.
  • We empower crew leaders to make selections which profit the enterprise.
  • Product and Engineering ought to have an equal footing, belief in one another, and
    be keen to make commerce off selections primarily based on lengthy and brief time period impression to the enterprise.
  • Selections are made with knowledge – e.g. the present state of the technical platform,
    estimates, evaluation of anticipated worth and KPI enchancment, person analysis, A/B take a look at outcomes.
  • Selections are revisited when knowledge is refined or new learnings are found.

A tech technique to restrict technical debt impression

When considering of methods for a startup, and the way it scales, we like
to make use of a four-phase mannequin to grasp the totally different phases of a
startup’s improvement.

Part 1


Prototypes – semi-functional software program to display product,
shifting to useful with rising curiosity

Part 2

Getting Traction

Ecosystem selections – cloud vendor, language decisions, service
integration type

Exchange prototype software program for core programs

Setup preliminary foundations – experimentation, CI/CD, API,
observability, analytics

Set up the broad domains, set preliminary tender boundaries (in

Part 3

(Hyper) Development

Create decoupled product groups managing their very own providers

Set up SLAs and high quality bar, linked to alerts round buyer
expertise of product

Set up platform groups targeted on the effectiveness of product

Part 4


Reassess SLA and high quality bar targeted on long run productiveness
and upkeep

Audit state of technical platform, sponsor initiatives in product
groups and create non permanent tiger groups to repair largest technical debt

Rebuild or purchase capabilities for improved effectivity

Prepare groups on good technical high quality practices

How do you deal with the tech debt

It begins with clear data sharing how the
enterprise is doing, the present product course, metrics on the present
scaling capability, what clients are saying concerning the product and what
buyer assist and ops are seeing. This data will enable
technologists to make knowledgeable selections. Sharing the information of the
present problem helps technologists to know why issues are being
addressed and measure their success.

There needs to be clear end-to-end possession of all merchandise and
their associated programs. As groups develop and take duty for his or her
respective areas, there’s typically no clear possession for an end-to-end
journey, which leaves technical gaps that usually develop into crammed with
technical debt. As groups develop and tackle new duties, it turns into
more and more tough to search out an proprietor for older code. Moreover,
with out possession, groups are much less incentivized to repair issues.

We’ve to empower groups to repair issues — resolving technical debt ought to
be a part of the pure stream of product improvement. Engineers and product
managers want to barter the wholesome steadiness between tech debt vs.
performance with the precise pragmatic mentality. It’s a part of a product
crew’s job to keep up and maintain technically wholesome merchandise, not one thing
achieved as an after-thought. There needs to be an agreed course of to sort out and
monitor technical debt frequently. This requires onerous trade-offs amongst
engineering and product leaders to maintain a steady steadiness.

Designing your crew topology the precise
method will also be an element. For instance, suppose we frequently see
technical debt created in sure areas. In that case, it would point out
that the crew design is improper, and there may be a platform or enterprise
functionality that wants robust possession and a spotlight.

Some metrics are highly effective — for instance, scanning for frequent
errors or measuring construct and deployment instances. The engineering
group ought to present self-service tooling into which groups
can shortly combine their programs. Metrics needs to be used as guides
for the crew to make selections about tech-debt moderately than for managers
to watch or incentivize. Skilled builders present worth by
deciphering the accessible knowledge and grounding their intution in fact-based
qualitative data.

Whereas we consider in autonomous groups, an excessive amount of autonomy is usually a drawback
and can lead to a chaotic technical panorama. There needs to be light-weight checks and balances such
as automated checks or architectural peer overview, which will help implement
insurance policies and support builders.

How your group chooses to handle its tech debt is determined by your
context. One frequent theme now we have seen throughout many organizations is the need
to “simply do one thing,” typically leading to a band-aid which quickly creates its
personal set of frictions. As an alternative, we’ve discovered that taking an iterative strategy
and letting the metrics mixed with present improvement exercise information the funding in resolving tech debt ends in
higher outcomes.


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