The American Journal of Engineering and Technology
96
https://www.theamericanjournals.com/index.php/tajet
TYPE
Original Research
PAGE NO.
96-101
10.37547/tajet/Volume07Issue07-11
OPEN ACCESS
SUBMITED
07 June 2025
ACCEPTED
29 June 2025
PUBLISHED
24 July 2025
VOLUME
Vol.07 Issue 07 2025
CITATION
Markushin, V. (2025). Inside Blockchain Startups: Precision Strategies to
Sidestep Technical Pitfalls. The American Journal of Engineering and
Technology, 7(07), 96
–
101.
https://doi.org/10.37547/tajet/Volume07Issue07-11
COPYRIGHT
© 2025 Original content from this work may be used under the terms
of the creative commons attributes 4.0 License.
Inside Blockchain Startups:
Precision Strategies to
Sidestep Technical Pitfalls
Vladislav Markushin
Team Lead, Rust Developer at Composable Foundation, Argentina
Abstract:
This paper presents a structured analysis of
common engineering failures in early-stage blockchain
startups. Drawing on practical experience within the
Ethereum, Solana, Polkadot, and Cosmos SDK
ecosystems, it identifies five recurrent categories of
technical pitfalls: inadequate system design, fragile or
overly coupled architectures, improper use of cross-
chain protocols, insufficient build and release
automation, and limited observability and runtime
diagnostics. The study employs a case-based
methodology across five representative projects,
covering a wide range of protocol layers and
architectural patterns
—
from decentralized messengers
to cross-chain bridge infrastructure.
Findings demonstrate that the adoption of mature
engineering practices
—
such as Command
–
Query
Responsibility Segregation (CQRS), event sourcing, finite
state machines, proxy contract standards (EIP-1967, EIP-
2535), and type safety in Rust
—
substantially improves
system resilience and extensibility. Particular emphasis
is placed on Inter-Blockchain Communication (IBC) as a
robust standard for secure interoperability across
heterogeneous chains. The paper also highlights how
automated CI/CD pipelines, multi-layer telemetry, and
centralized alerting frameworks support early fault
detection and operational responsiveness. The study
concludes
that
minimizing
custom
low-level
implementations in favor of standardized, modular
approaches is critical for building secure, auditable, and
scalable decentralized systems.
Keywords:
blockchain, cross-chain, Ethereum, Solana,
Polkadot, IBC, development
Introduction
Blockchain systems, characterized by decentralized
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consensus and tamper-resistant data structures, impose
a distinct set of design constraints on early-stage
technology ventures. These constraints frequently
surface in the form of technical missteps, such as
premature optimization, custom protocol development,
or the absence of robust architectural frameworks.
Collectively, such missteps can delay system rollouts,
introduce vulnerabilities, and erode a project’s
operational viability.
This study draws on my applied experience as a Rust
engineer working within the Ethereum, Solana,
Polkadot, and Cosmos SDK ecosystems. Projects
analyzed span multiple blockchain domains, including
messaging systems (Paymon Inc.), protocol-level
consensus (Soramitsu), and cross-chain bridge
architecture (Composable Foundation).
The analysis identifies five recurrent categories of
technical pitfalls in blockchain startups: (1) Inadequate
system design strategies; (2) Fragile or monolithic
software
architecture;
(3)
Misapplication
or
underutilization
of
cross-chain
communication
protocols; (4) Deficient build automation and release
orchestration; (5) Limited observability and runtime
introspection mechanisms. Each category is examined
through a case study methodology grounded in real-
world deployments, with the goal of offering practical
mitigations informed by both general software
engineering
principles
and
blockchain-specific
requirements. This work aims to inform practitioners
and researchers invested in advancing the resilience and
scalability of decentralized systems.
Methodology
This study adopts a qualitative, case-based research
approach to examine recurring technical challenges in
the development of blockchain infrastructure. The
analysis is grounded in direct engineering experience
across five representative projects, selected for their
diversity in architectural scope, consensus mechanisms,
and protocol layers.
●
Crypto Messenger (Paymon Inc., 2017
–
2019):
A
messaging
platform
incorporating
integrated
cryptocurrency transfers. The project encountered
issues related to architectural over-engineering and
nonstandard protocol design.
●
Iroha Blockchain (Soramitsu, 2020
–
2021):
standalone
Blockchain distributed ledger system. This case
illustrates the challenges of managing protocol
complexity and developing a secure smart contract
environment.
●
Decentralized Loyalty System (Bitfury, 2019
–
2020):
A
modular architecture implementing GOST cryptographic
standards. The focus here is on system modularity and
the implications of cryptographic design constraints on
infrastructure extensibility.
●
Ethereum
–
Internet Computer Bridge (InfinitySwap,
2021
–
2022):
A cross-chain bridge protocol emphasizing
system-level optimization and secure interoperability
across heterogeneous chains.
●
IBC Bridges and Solana Rollup (Composable
Foundation, 2022
–
present):
A multi-chain integration
effort featuring Inter-Blockchain Communication (IBC)
and rollup technologies. Particular attention is given to
governance-aware architecture and formal state
verification mechanisms.
Results and Discussion
System Design Pitfalls
A recurring design failure observed across early-stage
blockchain
projects
involves
the
unnecessary
reinvention of foundational infrastructure. In one case
study, the development team elected to construct the
entire network stack from first principles, bypassing
established remote procedure call (RPC) protocols and
serialization libraries. Instead, a custom binary protocol
was developed in C++. While this approach was
intended to offer greater control, it significantly
impeded debugging, delayed feature delivery, and
ultimately necessitated a complete architectural
reimplementation.
This tendency
—
favoring bespoke solutions over
standardized tooling
—
is prevalent among blockchain
startups. In pursuit of performance optimization or
architectural purity, teams frequently forgo widely
adopted technologies such as JSON-RPC, WebSockets,
or serialization libraries like borsh and scale-codec. In
practice, however, these decisions often fragment
development efforts, hinder interoperability, and result
in the accumulation of long-term technical debt.
These findings reinforce a broader principle: in the initial
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phases of system development, engineering priorities
should be weighted toward observability, verifiability,
and maintainability rather than micro-optimizations.
Architectures based on robust, well-supported
components are less prone to critical failure modes and
reduce the operational overhead associated with long-
term maintenance.
Architectural Practices and Change Resilience
Although architectural shortcomings may appear benign
in the early stages of distributed system development,
they often become major obstacles to scalability and
evolvability as the system matures. Across the examined
case studies, several architectural anti-patterns
emerged repeatedly. These included reliance on
mutable global state, insufficient modularization, tight
coupling between functional components, and frequent
violations of established object-oriented design
principles
—
particularly those articulated by the SOLID
framework. These deficiencies collectively increased the
cognitive load required for refactoring, impeded the
integration of new features, and elevated the risk of
regressions and latent defects.
Several design strategies consistently proved effective
in mitigating these issues:
●
CQRS
(Command
–
Query
Responsibility
Segregation):
Partitioning read and write operations
enabled clearer separation of concerns. In the
context of cross-chain bridges, this approach
allowed transaction submission and status queries
to be processed through distinct layers, enhancing
both performance and reliability.
●
Event Sourcing:
Persisting system state transitions
as a stream of immutable events facilitated reliable
state reconstruction and provided a natural
integration point for downstream services through
event subscription mechanisms.
●
Finite State Machines (FSMs):
Formalizing system
behavior via FSMs provided a rigorous framework
for managing operation lifecycles. This was
particularly critical in cross-chain workflows, where
strict sequencing constraints are required to
prevent invalid or premature transitions.
●
Proxy Contract Patterns (EIP-1967) and the
Diamond Standard (EIP-2535):
These upgradeability
techniques enabled safe replacement of contract
logic without jeopardizing the integrity of stored
state
—
an essential requirement in financial systems
handling on-chain assets.
●
Type safety in Rust:
The use of Rust’s type system,
including generics, traits, and algebraic data types,
played a central role in enforcing invariants at
compile time. This improved both modular
reasoning and overall system reliability by catching
potential logic errors prior to runtime.
The application of these patterns significantly improved
maintainability, facilitated the addition of new features
without architectural compromise, and enhanced
testability. Collectively, these practices promote
software systems that are resilient to change and robust
against failure, which are key attributes in the rapidly
evolving landscape of blockchain infrastructure.
Cross-Chain Protocols and IBC
Cross-chain integration presents stringent requirements
in terms of data consistency, synchronization
guarantees, and fault tolerance. Ensuring secure and
reliable
inter-network
communication
in
a
heterogeneous blockchain environment remains one of
the
most
technically
demanding
aspects
of
decentralized systems engineering. Across multiple
projects, implementation deficiencies in cross-chain
bridge protocols frequently resulted in state divergence
between participating networks, exposing users to loss
of funds and undermining trust in protocol correctness.
The most reliable solution in this context was the Inter-
Blockchain
Communication
(IBC)
protocol.
IBC
formalizes inter-chain message passing through the
Interchain Standards (ICS) specification suite, offering a
rigorously defined interface for verifying remote states
and coordinating cross-chain operations.
Key architectural modules include:
●
ICS-02: Light Clients
Responsible for verifying the state of remote
blockchains through cryptographic validation of
Merkle proofs and consensus headers. These clients
play a central role in maintaining data integrity and
detecting protocol violations such as equivocation
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(double-signing) or timestamp manipulation.
●
ICS-03: Connection Handshake
Specifies a four-phase handshake protocol
—
ConnOpenInit, ConnOpenTry, ConnOpenAck, and
ConnOpenConfirm
—
used
to
establish
authenticated
and
validated
communication
channels between two chains. The handshake
protocol relies on trusted client state for
bidirectional agreement.
●
ICS-26: Middleware Routing
Provides a modular routing layer that enables
protocol extensibility without modifying core
application logic. This facilitates the seamless
integration of optional features such as fee
abstraction, on-chain routing policies, or interchain
account management via custom middleware.
●
ICS-08: WASM Clients
Implements client-side verification logic using
WebAssembly (WASM), allowing for more flexible
upgrades and cross-language development. Smart
contracts are deployed using MsgStoreCode and
upgraded
via
MsgMigrateContract,
enabling
governance-based evolution of interchain clients
without requiring network forks.
In practice, successful IBC deployment necessitates the
development of chain-specific light client adapters to
accommodate
varying
consensus
mechanisms.
Furthermore, strict typing of interchain state data and
routine protocol audits are essential to ensuring
correctness, resilience, and auditability.
Adherence to the IBC framework significantly reduces
the likelihood of inconsistent state transitions or
unexpected asset behavior, supporting the construction
of secure and scalable cross-chain communication
protocols.
Build Automation and Release Processes
Blockchain
startups
frequently
operate
under
compressed development timelines, requiring rapid
iteration,
support
for
multiple
deployment
environments (such as development, testnet, and
production), and strict reproducibility guarantees across
heterogeneous platforms. In the absence of robust
continuous
integration
and
delivery
(CI/CD)
infrastructure, these operational pressures often result
in unreliable builds, delayed release cycles, and elevated
operational burden on engineering teams.
To address these challenges and enhance build
reliability, the projects examined in this study adopted a
fully automated approach to the software delivery
lifecycle. Docker-based containerization was employed
to
ensure
environmental
consistency
across
development and production systems, with image
publishing managed via the docker/build-push-action.
This setup enabled reproducible builds and significantly
accelerated the delivery of new releases. Build times
were further optimized through the use of dependency
caching in GitHub Actions; in particular, caching the
Cargo and target directories with the rust-cache action
proved highly effective for Rust-based systems with
complex dependency graphs.
Automated enforcement of code quality standards was
integrated into every CI stage. Static analysis was
performed using cargo clippy, formatting compliance
was verified via cargo fmt -- --check, and test coverage
metrics were collected using cargo-llvm-cov. These tools
ensured that potential issues were identified early in the
development cycle
—
prior to code integration
—
thereby
improving consistency and maintainability across the
codebase.
Deployment workflows were managed through Amazon
Web Services (AWS), with orchestration pipelines
issuing commands such as aws ecs update-service and
aws eks update-kubeconfig to perform seamless
updates of containerized services and Kubernetes
clusters. To prevent configuration drift across
environments, deployment logic was isolated using
github.ref conditions in conjunction with scoped
environment variables.
Release processes were governed by semantic
versioning, with Git tags in the v*.*.* format triggering
automated deployment and rollback mechanisms. This
workflow reduced the risk of human error, minimized
manual intervention, and significantly tightened the
feedback loop between development and production
environments.
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Monitoring and Observability Systems
In the early stages of one project, the absence of a
structured observability framework significantly delayed
the detection and resolution of critical production
issues. Latency spikes in API responses, inconsistencies
in transaction processing, and instances of CPU
exhaustion were only recognized post hoc
—
typically
following user reports or service disruptions. The lack of
centralized monitoring and alerting mechanisms led to
prolonged recovery times and diminished operational
responsiveness.
To mitigate these challenges, observability practices
were extended across the full system stack. At the
infrastructure level, telemetry was collected for key
resource indicators, including CPU utilization, memory
allocation, disk input/output operations, and network
throughput. These metrics were monitored both at the
host and container levels to enable fine-grained
resource tracking in containerized deployments.
At the application layer, operational telemetry
encompassed API latency distributions, request
throughput, error rates (HTTP 4xx/5xx), and transaction
queue depth. These indicators were instrumental in
assessing the health and responsiveness of core
business logic components under varying load
conditions.
In addition, blockchain-specific metrics were captured
to provide insight into protocol-layer behavior.
Monitored signals included current block height,
reorganization frequency, mempool congestion, and gas
consumption patterns. These metrics supported early
detection of chain instabilities and facilitated
preemptive remediation of network-level anomalies.
Centralized log aggregation was performed using the
ELK stack and Grafana Loki, enabling efficient log
retrieval and correlation during incident response. For
deeper performance diagnostics, distributed tracing
—
implemented via OpenTelemetry and Jaeger
—
enabled
end-to-end request flow analysis across microservices,
facilitating root cause identification for latency and
reliability regressions.
Complementing passive monitoring, synthetic blackbox
checks were deployed to continuously verify the
availability and responsiveness of critical endpoints,
including RPC interfaces. Alerting workflows were
managed through Alertmanager, with notification
routing to operational communication platforms such as
Slack and Telegram. Alerting logic was governed by
service-level
indicators
(SLIs)
and
service-level
objectives (SLOs), combining static thresholds with
anomaly detection techniques to minimize false
positives and prioritize events requiring immediate
intervention.
Conclusion
Engineering failures in blockchain startups extend
beyond project delays; they erode user trust, complicate
maintainability, and in many cases, introduce
vulnerabilities that compromise asset security. The root
causes of such failures are varied, encompassing the
unnecessary development of custom protocols, the
absence of well-defined architectural patterns, and the
lack of systematic observability and operational
visibility.
The case studies presented in this paper highlight that
resilience in blockchain infrastructure is not a product of
novelty but of disciplined engineering. Systems that rely
on mature, standardized protocols and libraries
—
rather
than bespoke, low-level implementations
—
tend to
exhibit greater maintainability and fault tolerance.
Modular architectural designs with strict separation of
concerns support adaptability and scalability, while
formalized inter-chain communication via protocols
such as IBC introduces robustness in cross-network
interactions. Additionally, automation of build,
deployment, and monitoring pipelines enhances
reproducibility
and
operational
responsiveness,
minimizing downtime and human error.
Together, these practices offer a pragmatic foundation
for the development of secure, auditable, and scalable
blockchain systems. As the ecosystem continues to
mature, adopting these engineering principles will be
essential not only for technical excellence but also for
maintaining
long-term
trust
in
decentralized
technologies.
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