Software Development

Bottleneck #01: Tech Debt

In its early days, a startup searches for a very good product-market match. When
it finds one it appears to be like to develop quickly, a section generally known 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 centered on tips on how to assist them overcome numerous bottlenecks that
impede this progress.

As we have executed 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, often via doing the proper
issues which can be wanted early in a startup’s life, however are not proper as
progress adjustments the context for tactics of working. We’ll spotlight key indicators
that the startup is approaching or caught within the bottleneck. We’ll then speak
about tips on how to break via the bottleneck, describing the adjustments we have seen
that permit 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 alter as soon as progress kicks in.

How did you get into the bottleneck?

The commonest scaling bottleneck we encounter is technical debt —
startups often state that tech debt is their most important obstacle to
progress. 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 because of an absence of technical funding throughout their progress section.
An evaluation is required to determine the sort and scale of the tech debt.
It could possibly be that the code high quality is unhealthy, an older language or framework
is used, or the deployment and operation of the product isn’t totally
automated. The answer technique is perhaps slight adjustments 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 elements akin to high quality or robustness for product supply
velocity. This can get the startup to its first purpose – a viable enterprise
mannequin, a confirmed product and clients that love the product. However because the
firm appears to be like to scale up, we have now 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 (consumer visitors, consumer sentiment, income) for buyers and secured
the following spherical of funding. Like most MVPs, it was constructed to generate consumer
suggestions moderately than high-quality technical structure. After the
funding, as a substitute of rebuilding that pilot, they construct upon it, maintaining 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
change them. There may be friction to study, 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 in regards to the
attrition of the unique engineers and shedding the information they’ve.

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

Firm B – The corporate was based by ex-engineers they usually
wished 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’s going to simply be capable of deal with hyper progress when
the corporate will get there.

The difficulty with this instance is that it took a very long time to create,
characteristic improvement was sluggish, and plenty of engineers hung out engaged on the
platform moderately than the product. It was additionally laborious to experiment — the
finely grained structure meant concepts that didn’t match into an current
service structure have been difficult to do. The corporate didn’t notice
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, based mostly on an amalgamation of assorted
purchasers with whom the startup groups at Thoughtworks have labored. Firm A
received itself right into a technical debt bottleneck that paralyzed the corporate.
Firm B over-engineered an answer that slowed down improvement and
crippled its means to pivot rapidly because it learnt extra.

The theme with each is an incapacity to search out the proper steadiness of technical
funding vs. product supply. Ideally we wish to leverage using prudent technical debt to energy
fast characteristic improvement and experimentation. When the concepts are discovered to
be precious, we must always pay down that technical debt. Whereas that is very simply
acknowledged, it may be a problem to place into apply.

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

Typical sorts of debt:

Technical debt is an ambiguous time period, usually 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, laborious to check, laborious 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 information mannequin that doesn’t
match the present enterprise mannequin, leading to workarounds.

A scarcity of unit, integration, or E2E assessments, or the mistaken distribution
(see take a look at pyramid). The developer can’t rapidly get confidence that
their code won’t break current performance and dependencies. This leads
to builders batching adjustments and a discount of deployment frequency.
Bigger increments are more durable to check and can usually end in extra bugs.
Between modules (usually occurs in a monolith), groups doubtlessly
block one another, thus decreasing the deployment frequency and
growing lead time for adjustments. One resolution is to drag out providers
into microservices, which comes with it’s personal
— there could be extra simple methods of setting
clear boundaries inside the monolith.

Unused or low worth options
Not usually considered technical debt, however one of many signs of
tech debt is code that’s laborious to work with. Extra options creates
extra situations, extra edge instances that builders must design
round. This erodes the supply velocity. A startup is experimenting. We
ought to at all times be sure 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 will have goal information quantifying the characteristic worth.

Outdated libraries or frameworks
The crew will likely be unable to make the most of new enhancements and
stay weak to safety issues. It’s going to end in a abilities
drawback, slowing down the onboarding of recent hires and irritating
present builders who’re pressured to work with older variations. Moreover, these
legacy frameworks are likely to restrict additional upgrades and innovation.

Sub-optimum third-party merchandise or instruments that require a whole lot of
upkeep. The panorama is ever-changing, and extra environment friendly
tooling could have entered the market. Builders additionally naturally wish to
work with probably 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 may have an effect on the shopper expertise and the power to scale. We
must watch out, as we have now seen wasted effort in untimely
optimization when scaling for a hypothetical future scenario. It’s higher to
have a product confirmed to be precious 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 manner while you
spend a whole lot of time automating one thing that isn’t 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 submit. You need to
have the power to deploy at will, often not less than as soon as a day.

Data sharing
Lack of helpful info is a type of technical debt. It makes
it tough for brand new staff and dependent groups to stand up to hurry.
As commonplace apply, improvement groups ought to produce concisely
written technical documentation, API Specs, and architectural
resolution information. It also needs to be discoverable through a developer
portal or search engine. An anti-pattern isn’t any moderation and
deprecation course of to make sure high quality.

Is that basically technical debt or performance?

Startups usually 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 remedy with
planning, requirement gathering, and devoted assets.

For instance, Thoughtworks’ startup groups usually work with purchasers on
automating buyer onboarding. They could have a single-tenant resolution
with little automation. This begins off nicely 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 would possibly rent devoted operations workers to set
up the shopper accounts. Because the consumer 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 improve. 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 more durable to identify and more durable to level
to a direct impression, akin to code that’s tough to work with or quick
repeated handbook processes. One of the best ways 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 method 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 frequently see groups
working off historic instructions, creating future issues with out
realizing it. For a corporation on this circumstance, just a few alternatives
generally set off when to re-evaluate their present technique:

  • New funding means extra options and extra assets — this can compound
    present issues. Addressing present technical debt needs to be a part of the
    funding plan.
  • New product path can invalidate earlier assumptions and put
    stress on new elements of the methods.
  • A very good governance course of includes reevaluating the state of the
    expertise on a daily cadence.
  • New opinions will help keep away from “boiling frog” issues. Exterior assist, crew
    rotations and new staff will carry a recent perspective.

The slippery slope

How did you find yourself with a whole lot of technical debt? It may be very laborious to
pinpoint. Sometimes it isn’t because of only one occasion or resolution, however
moderately a collection of choices and trade-offs made beneath strain.

Sarcastically, looking back, if one considers every resolution on the level
in time at which it was made, based mostly on what was recognized on the
time, it’s unlikely to be thought of a mistake. Nonetheless, one
concession results in one other and so forth, till you will have a significant issue
with high quality. There may be generally a tipping level at which resolving the
tech debt takes extra time than growing incremental worth.

It’s laborious to get better and the scenario tends to snowball. It’s
pure for builders to make use of the present state as an indicator of what
is appropriate. In these situations, growing 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 following
characteristic will increase non-linearly.

Set a high quality bar

Many organizations discover it useful to have a set of requirements and
practices to which the corporate is dedicated that information technical
evolution. Take into account that some technical practices are fairly
tough to realize, for instance steady supply; deploying
often with out affecting customers is technically difficult. Groups
usually have preliminary issues, and in response management could deprioritize
the apply. As a substitute we suggest the alternative, do it extra usually and
your groups will grasp the practices and kind sturdy habits. When the
robust time comes, moderately than dropping the apply, 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 will we restrict the blast radius, realizing that these shortcuts
will should be resolved, and even completely rebuilt? Clearly, we want a
technique that limits the impression to the enterprise. A method is to decouple
groups and methods, which permits a crew to introduce tech debt that’s
remoted and gained’t essentially snowball as described above.

Top quality literature about decoupling is plentiful, so we gained’t
try to clarify right here. We suggest focusing consideration on
microservices and area pushed design methods. Nonetheless, watch out
doing an excessive amount of too early, decoupling provides latency and complexity to your
methods, and selecting poor area boundaries between groups can add
communication friction. We will likely 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 ultimately suffers as nicely. Whenever you
search for the foundation reason for this bottleneck, it practically at all times comes down
to the steadiness inside the firm between enterprise, product and
engineering objectives. Lack of collaboration usually results in quick
sighted selections made in a vacuum. This may go each methods, reducing
corners in essential areas or gold plating one thing that isn’t precious
are equally seemingly.

  • 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 based mostly on lengthy and quick time period impression to the enterprise.
  • Choices are made with information – e.g. the present state of the technical platform,
    estimates, evaluation of anticipated worth and KPI enchancment, consumer analysis, A/B take a look at outcomes.
  • Choices are revisited when information is refined or new learnings are found.

A tech technique to restrict technical debt impression

When pondering 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 reveal product,
shifting to useful with growing curiosity

Part 2

Getting Traction

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

Change prototype software program for core methods

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

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

Part 3

(Hyper) Progress

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 centered on the effectiveness of product

Part 4


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

Audit state of technical platform, sponsor initiatives in product
groups and create momentary tiger groups to repair greatest technical debt

Rebuild or purchase capabilities for improved effectivity

Practice groups on good technical high quality practices

How do you handle the tech debt

It begins with clear info sharing how the
enterprise is doing, the present product path, metrics on the present
scaling capability, what clients are saying in regards to the product and what
buyer assist and ops are seeing. This info will permit
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 methods. As groups develop and take accountability for his or her
respective areas, there’s usually no clear possession for an end-to-end
journey, which leaves technical gaps that always change into stuffed 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 now have to empower groups to repair issues — resolving technical debt ought to
be a part of the pure circulation of product improvement. Engineers and product
managers want to barter the wholesome steadiness between tech debt vs.
performance with the proper pragmatic mentality. It’s a part of a product
crew’s job to keep up and maintain technically wholesome merchandise, not one thing
executed as an after-thought. There needs to be an agreed course of to deal with and
monitor technical debt frequently. This requires laborious trade-offs amongst
engineering and product leaders to maintain a steady steadiness.

Designing your crew topology the proper
manner can 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 mistaken, and there is perhaps a platform or enterprise
functionality that wants sturdy possession and a focus.

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 rapidly combine their methods. Metrics needs to be used as guides
for the crew to make selections about tech-debt moderately than for managers
to observe or incentivize. Skilled builders present worth by
decoding the out there information and grounding their intution in fact-based
qualitative info.

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

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

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