Why blockchains mark a new era for debugging and monitoring services

The application error monitoring market, estimated to be worth over USD 29 billion, is on the cusp of a significant transformation. As we transition from the Cloud era to the Blockchain era, the landscape of debugging and monitoring services is set to change dramatically. Historically, each major shift in computing platforms has brought new challenges and opportunities, reshaping the monitoring market and introducing new key players.

Big companies like Microsoft and Apple, along with indie developers and game studios, rely heavily on real-time application monitoring systems to ensure reliability and meet user requirements. However, as we stand at the threshold of a new era of computation—blockchain technology—the current monitoring solutions are poised to face unprecedented disruptions.

This article delves into the reasons behind this anticipated shift and explores the new opportunities that blockchain technology offers. We will journey through the history of computing over the past 70 years, highlighting how each era—from the early days of computing to the cloud and mobile era—reshaped the application monitoring landscape. We will then contrast the current cloud-based era with the emerging blockchain era, illustrating why traditional monitoring tools may fall short in this new environment.

Finally, we will analyse the current state of blockchain-specific monitoring tools and assess the burgeoning market opportunities for new players poised to address the unique challenges introduced by blockchain technology. At Walnut, we are excited about these opportunities and are actively exploring multiple solutions across various blockchain ecosystems. Join us as we explore why blockchains mark a new era for debugging and monitoring services.

History of computation and changes to the monitoring market

Let's start by briefly looking at the history of computing platforms and how each change caused new players in the application monitoring market.

Early Days of Computing (1940s-1960s)

The earliest computers were rudimentary, with programming done via punched cards and machine code. Debugging was mostly a manual process, often involving physical inspection of the hardware and simple printouts.

Interesting fact: The term “debugging” became widely known in this era due to an incident in 1947 when Grace Hopper's team found a moth causing a problem in the Harvard Mark II computer. Removing the moth fixed the problem, coining the term “debugging” for fixing software and hardware issues.

Key players in the application monitoring market during the Early Days of Computing era:

• IBM: provided mainframe computers and basic debugging tools.

Personal Computing Era (1970s-1990s)

As computers became more accessible to the general public and more performant, this led to the development of new, more complex applications. More complex applications opened up new challenges in finding computer bugs and ensuring they worked as intended 100% of the time, leading to the rise of new players in the monitoring market. New debuggers and monitoring services were introduced, including paid integrated development environments (IDEs), graphical debuggers, and advanced error reporting systems.

Key players in the application monitoring market during the Personal Computing era:

• Borland: Turbo Pascal, a paid IDE with integrated debugging tools.
• Microsoft: Early versions of Visual Studio offered powerful debugging features. Visual Studio later became a leading paid IDE with comprehensive debugging capabilities, and still exists today.

Mobile and Cloud Computing Era (2000s-2010s)

Apps running in the cloud and users connecting to them from their mobile devices dramatically changed how programs were written and run, leading to a new disruption in monitoring systems.

Turbo Pascal was no longer the main language. Instead, we saw the rise of new, web-native languages like PHP and JavaScript.

This shift in the monitoring market brought (yet again) new solutions offering advanced tools for real-time error monitoring and comprehensive performance profiling.

Key players in the debugging and monitoring market during the Mobile and Cloud Computing era included:

• Sentry: Offered paid plans for advanced error monitoring and diagnostics.
• Datadog: Provided comprehensive monitoring solutions with paid plans.
• New Relic: Known for application monitoring tools that optimize performance.

All of these players are still dominant today and are worth billions of dollars. Sentry is valued at $3 billion, Datadog at $39.42 billion, and New Relic is in the process of being acquired by Francisco Partners and TPG for $6.5 billion.

However, a new era is just around the corner, which might significantly disrupt today's dominant monitoring service players and lead to the emergence of new solutions, similar to what we saw in the past.

Blockchain Era (2020s and beyond)

Blockchain technology is a radical shift in computation. More and more companies are moving on chain. Brian Armstrong, the CEO of Coinbase, claims that on-chain is the new online, implying that blockchains are a similar shift to how Cloud Era advanced the Personal Computing Era. Today, we already see applications in Healthcare, Logistics, Finance, Social Media, Gaming and more, exploring the blockchain technology.

Whether blockchains actually become the next computing platform is yet to be seen. But if they do, and we firmly believe they will, it will mark another revolution in application monitoring systems and present a large opportunity for new solutions to emerge.

New Challenges in Computation introduced by the Blockchains Era

In this section, we compare the Blockchain era with the Mobile and Cloud era and offer key differences that lead to the requirement of new specialised monitoring services. For more condensed insights please refer to the overview table at the end of this section.

Execution environment

The execution environment refers to where application code runs, which significantly impacts the requirements for monitoring and debugging systems.

Cloud: Cloud systems and mobile applications typically involve executing programs on UNIX-based machines. These machines are well-understood by the existing monitoring services and have been established for a long time, providing a familiar environment for developers.

Blockchain: Blockchain applications do not run on existing operating systems like UNIX. Instead, they typically run in specialised virtual machines, such as the Ethereum Virtual Machine (EVM). Programs are invoked through transactions, and the execution is irreversible and permanent. Programs are encoded as smart contracts, deployed to the blockchain in the form of bytecode.

There is a need for a specialised monitoring system that understands the specifics of blockchain Virtual Machines such as the EVM or Cairo VM or Solana VM.

Data Storage

Data storage involves how data is managed and stored and in what format it is encoded, which affects how monitoring services deal with the data for later processing.

Cloud: Traditional databases such as PostgreSQL, MySQL, and SQL Server are used. These systems are centralised and well-understood by existing monitoring tools.

Blockchain: Data is stored in a distributed manner using structures like Merkle trees and other cryptographic methods. This storage format approach is unfamiliar to many traditional monitoring systems, requiring a different approach for decoding and understanding the data.

Monitoring systems built for Cloud and Mobile applications do not understand the specifics of blockchain data format.

Runtime Context and Logs

Existing solutions like Sentry and DataDog rely on runtime logs created by applications running on mobile devices or in the cloud. Blockchains, due to their decentralised style, have a very different approach to logging.

Cloud: Programs usually generate logs about their execution, which are utilised by monitoring services like DataDog or Sentry to provide insights into problems and potential fixes.

Blockchain: Logs generated by blockchain nodes are very scarce and almost non-existent. This is due to the nature of blockchains, where every program is re-executed by thousands of validators, making it impractical and expensive to generate extensive logs.

Blockchains do not generate logs and runtime context about program execution because it would be too expensive. There is a need for a radically different approach that involves re-running, or simulating blockchain programs in a controlled environment, to generate the extra logging and analytics required.

Programming Languages

Programming languages used to write programs significantly affect the tools and methods required for monitoring.

Cloud: The most popular programming languages include Python, JavaScript, C#, Java, and Go. These languages are well-supported by existing debugging and monitoring tools.

Blockchain: Blockchain development requires new and specialised languages. Examples include Solidity for Ethereum and all EVM chains, Cairo for Starknet, Noir for Aztec, and Rust for Solana.

Blockchains need monitoring software tailored to the specific languages they use.

Program Source Code

The way Blockchains function brings new problems to how the program source code is bundled, which causes challenges to monitoring previously unseen.

Cloud: The program's source code is fully created and owned by the program creator, making it straightforward to debug and monitor. If the program has dependencies to other libraries, those will be compiled with the program to generate a single, self-containing bundle.

Blockchain: Blockchain applications coexist and interact with other apps on the same chain, forming a super-app. Developers often rely on other apps’ functionality without having access to their source code, posing unique challenges for debuggers.

An example: The lending application zkLend can call another application Ekubo to perform swaps of tokens in the case of liquidation. The zkLend team only has access to the zkLend's source code, and the zkLend's app bundle only contains code related to zkLend. Even though the zkLend app relies on Ekubo’s code, it doesn’t contain any Ekubo app’s code in its app bundle. In Solana, this is called Cross Program Invocation, and you can read more about it here.

The fact that blockchain apps often rely on other apps, but at the same time do not have other app’s code in their bundle, poses unique challenges for debuggers, which need to understand the full context of all of the apps on the blockchain in order to correctly present issues caused by dependencies.

Cost of Running Applications

Performance monitoring is a subcategory of application monitoring services. It focuses on tracking and managing the performance and availability of software applications to detect and diagnose complex performance issues, ensuring optimal user experiences and system reliability.

Cloud: Users are billed based on the resources they consume, such as compute power, storage, and bandwidth. Pricing models are typically transparent and predictable.

Blockchain: The cost structure is more complex and is based on GAS, which price is dynamic and varies all the time. Costs include transaction fees, smart contract deployment, storage, and validator incentives. These factors can fluctuate based on network demand and other variables.

Blockchain apps handle application performance and cost very differently. This requires specialised performance monitoring tools that understand the concept of gas and the role it plays in blockchain applications.

Aspect Comparison Table

Current state of monitoring tools for blockchains

In the previous section, we explained differences between blockchains and Cloud systems, and presented concrete examples why existing web2 monitoring systems (like Sentry or DataDog) fall short in the new blockchain era. We provided concrete examples of why blockchains present an opportunity for new monitoring systems to emerge, purpose built for the challenges introduced by blockchains.

In this section, we will explore some of the emerging tools specifically built for monitoring and debugging blockchain applications.

Tenderly

Tenderly is one of the most comprehensive tools for solving the problems discussed in this article. Tenderly started around 7 years ago with a debugger service for Ethereum and EVM, and is now used by many Ethereum and EVM developers.

Over time, Tenderly added more advanced features like transaction simulations, testnets for users who need to develop applications privately, real time alerts and detailed gas visualisation of transaction traces. Today, Tenderly supports over 60 EVM chains. The company raised almost $60M over three rounds (the last one was series B where they raised $40M).

Pros

• Tools focused on debugging and error monitoring.
• Real-time monitoring and alerting.
• Comprehensive debugging and performance analytics.

Cons

• Support for EVM chains only.

Foundry, Hardhat, Truffle

Besides Tenderly, there is a set of open-source tools for developing and testing smart contracts on Ethereum and EVM chains.

The tools, due to their open source nature, lack any more advanced features for real-time application monitoring.

Pros

Cons

Opportunity for New Players to Enter the Market

Tenderly has been a prominent player in advancing a comprehensive blockchain monitoring system.

However, the blockchain monitoring market still faces significant challenges. Tenderly's focus on EVM chains leaves many other chains without solutions. Numerous non-EVM chains, including many recent ZK-based validity rollups, lack support. Even zkSync and Scroll, validity rollups that claim EVM compatibility, are unsupported by Tenderly due to differences in their underlying VMs. Additionally, smaller fully EVM-compatible rollups also often lack Tenderly support, likely due to cost considerations.

It's not just about Tenderly; there's substantial room for improvement. More options are needed within the EVM ecosystem, and non-EVM chains currently lack solutions for real-time monitoring and debugging.

Market Opportunity for Blockchain Monitoring Services

To provide an estimate of the market opportunity for blockchain monitoring, we will first analyse the size of monitoring in Web 2.0 and calculate the ratio between monitoring services and the total market cap of Web 2.0. We will then estimate the blockchain market and its potential growth. Finally, we will use the same ratio of monitoring services market cap to the total Web 2.0 market cap and apply it to the blockchain market cap to estimate the potential of blockchain monitoring.

The total market size of Web 2.0, which includes companies involved in social media, content creation, e-commerce, and other internet-based services, is valued at around $14.8 trillion (reference).

The combined market capitalization of key debugging and monitoring services players — DataDog, Sentry, and New Relic — is approximately $50 billion. Other companies offering monitoring and application performance management (APM) services include:

1. Microsoft: Application Insights for real-time monitoring.
2. Oracle: OCI Monitoring and Oracle Management Cloud.
3. IBM: Instana and IBM Cloud Monitoring.
4. Cisco (AppDynamics): Real-time performance monitoring.
5. SolarWinds: Infrastructure and application monitoring solutions.

The global blockchain market was valued at $17.21 billion in 2023 and is projected to grow to $29.35 billion in 2024, with a compound annual growth rate (CAGR) of 70.6%. (reference) Another projection estimates the market will reach $1.4 trillion by 2030, growing at a CAGR of 87.7% (reference). This growth spans industries such as finance, supply chain, healthcare, gaming, and AI, driven by promises of increased transparency, security, and efficiency.

The total market capitalization of debugging and monitoring services for Web 2.0 is not explicitly available as a single aggregated figure. However, combining the valuations above, we estimate the application monitoring market is worth ~ $100 billion, or approximately 1% of the total $14.8 trillion Web 2.0 market. Given the same estimation, the opportunity for blockchain monitoring services is projected to be $9.52 billion.

Significant gaps exist in blockchain debugging and monitoring tools. Financial impacts of blockchain-related errors are substantial, with vulnerabilities and bugs in smart contracts leading to losses exceeding $1 billion over the past three years (reference). As financial institutions like JPMorgan and HSBC move more activities to blockchain, the potential for significant financial losses due to errors increases. Robust debugging and monitoring tools are critical to mitigating these risks and ensuring the security of financial operations (reference).

In conclusion, the substantial financial impact of blockchain-related errors underscores the critical need for advanced debugging and monitoring solutions. As blockchain technology continues to integrate deeper into existing systems like finance, healthcare, logistics, gaming, and social, these tools are essential to safeguard against risks.

Conclusion

We are at the beginning of a new era of computation: Blockchain. This era presents unique opportunities for new debugging and monitoring services, requiring specialised tools compared to the existing monitoring leaders like Datadog or Sentry, which are focused on monitoring applications of the current Cloud era.

While some specialised tools like Tenderly or Foundry have already been developed, there is still a growing need for new solutions and players. This is because we see an expansion of new blockchain technologies with varying virtual machines like EVM, Solana, Starknet, Aptos, and more.

The rapidly growing blockchain market underscores the importance of robust tools, especially as financial institutions adopt this technology. Significant financial losses from smart contract errors highlight the need for comprehensive solutions.

At Walnut, we are excited about the opportunities in monitoring tools for the Blockchains and are exploring multiple solutions across various blockchain ecosystems to meet these emerging needs.