This is a microservices dataset. For an exclusive explanation, please take a look at the paper and at the online appendix: https://github.com/darioamorosodaragona-tuni/Microservices-DatasetIn particular, this file contains all the projects labeled as:- Is it a microservices?: Yes | Uknown- Archived: Yes | NoCopyright:Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). MSR ’24, April 15–16, 2024, Lisbon, Portugal © 2024 Copyright held by the owner/author(s). ACM ISBN 979-8-4007-0587-8/24/04 https://doi.org/10.1145/3643991.3644890

The dataset titled "Greedy Multi-Cloud Selection Approach to Deploy an Application Based on Microservices" consists of 400,000 rows and 11 columns, capturing various parameters essential for deploying microservices-based applications across multiple cloud environments. This dataset is designed to simulate and analyze the deployment decisions and outcomes when using a greedy algorithm approach for cloud provider selection.

Columns Overview: Application ID: Unique identifier for each application instance. Microservice Name: Name of the microservice within the application. Cloud Provider: Chosen cloud provider for deploying the microservice (e.g., AWS, Azure, Google Cloud, IBM Cloud). Region: Geographic region where the cloud provider's data center is located (e.g., US-East, EU-West, Asia-Pacific). Resource Utilization (%): Percentage of allocated resources utilized by the microservice. Latency (ms): Average latency experienced by the microservice in milliseconds. Cost ($): Deployment cost in US dollars incurred by the microservice. Deployment Time (hrs): Time taken to deploy the microservice in hours. Success Rate (%): Percentage of successful deployments for the microservice. Data Transfer (GB): Amount of data transferred by the microservice in gigabytes. Environment: Deployment environment phase (e.g., Development, Testing, Production). Dataset Usage: This dataset facilitates research and analysis into the efficacy of a greedy algorithm for selecting optimal cloud providers based on various performance and cost metrics. Researchers and practitioners can use this dataset to:

Evaluate the impact of cloud provider choice on resource utilization and deployment costs. Analyze latency variations across different geographic regions and cloud providers. Assess the success rate of deployments and its correlation with selected cloud providers and deployment environments. Model and optimize deployment strategies for microservices-based applications in diverse cloud environments. Data Characteristics: The data ranges were simulated to reflect realistic scenarios encountered in multi-cloud deployments, ensuring variability in cloud provider performance and deployment outcomes. Random generation methods such as uniform distributions for costs and deployment times, normal distributions for latency, and categorical choices for cloud providers and deployment environments provide a diverse yet controlled dataset suitable for comprehensive analysis.

Potential Applications: This dataset is valuable for researchers, data scientists, and cloud architects involved in optimizing cloud resource utilization, minimizing deployment costs, and enhancing application performance through effective cloud provider selection strategies. It can also serve as a benchmark for comparing different algorithms and methodologies in the field of multi-cloud deployment and management.

The global microservices architecture market size reached USD 4.2 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 13.1 Billion by 2033, exhibiting a growth rate (CAGR) of 12.7% during 2025-2033. The increased demand for scalability, digital transformation initiatives, expanding e-commerce industry, and ongoing technological advancements are primarily driving the market's growth.

IMARC Group provides an analysis of the key trends in each segment of the global microservices architecture market report, along with forecasts at the global, regional, and country levels from 2025-2033. Our report has categorized the market based on component, deployment type, organization size, and industry vertical.

The Microservices market was valued at $7.42 billion in 2025 and is projected to reach $34.18 billion by 2034, growing at 18.5% CAGR.

Dataset used by the paper MADE: Learning to Detect and Explain Chaos in Microservice Architectures Include the raw dataset of 10 chaos

According to Market Research Intellect, the microservices architecture market stood at USD 4.06 Billion in 2025 and is forecast to reach USD 18.08 Billion by 2035, progressing at a CAGR of 16.1.

Microservices Platform Market Outlook

According to our latest research, the global microservices platform market size reached USD 7.35 billion in 2024, reflecting robust adoption across industries. The market is expected to expand at a remarkable CAGR of 19.8% from 2025 to 2033, with the forecasted market size projected to hit USD 37.7 billion by 2033. This significant growth trajectory is driven by the increasing demand for scalable, agile, and resilient IT architectures, as organizations modernize their application development and deployment strategies to meet evolving business needs.

The primary growth factor fueling the expansion of the microservices platform market is the ongoing digital transformation initiatives undertaken by enterprises worldwide. As businesses seek to enhance customer experiences and accelerate time-to-market for new products and services, the limitations of monolithic application architectures have become increasingly apparent. Microservices platforms offer a modular approach, enabling organizations to break down complex applications into smaller, independently deployable services. This architectural shift not only improves scalability and fault isolation but also fosters continuous integration and continuous delivery (CI/CD) practices, which are essential for maintaining a competitive edge in today’s fast-paced digital economy.

Another major driver is the proliferation of cloud-native technologies and the widespread adoption of DevOps methodologies. Cloud service providers and platform vendors are integrating advanced tools for container orchestration, service mesh, and API management, making it easier for enterprises to implement and manage microservices at scale. The integration of microservices with emerging technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) is further propelling market growth. Organizations in sectors like BFSI, healthcare, and retail are leveraging microservices to build flexible, resilient, and highly available systems that can respond swiftly to changing customer demands and regulatory requirements.

The rise of remote work and the need for robust digital infrastructure during and after the COVID-19 pandemic has also accelerated the adoption of microservices platforms. Enterprises are increasingly investing in IT modernization to support distributed teams, hybrid cloud environments, and omnichannel customer engagement. Microservices facilitate these initiatives by enabling seamless integration with legacy systems and third-party services, thus supporting business continuity and operational agility. Furthermore, the growing ecosystem of open-source tools and frameworks around microservices is lowering the barriers to entry, allowing small and medium enterprises to benefit from the same architectural advantages as large corporations.

From a regional perspective, North America continues to dominate the microservices platform market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The United States, in particular, is at the forefront due to its mature IT infrastructure, high concentration of technology companies, and early adoption of cloud-native solutions. Meanwhile, Asia Pacific is experiencing the fastest growth, driven by rapid digitalization in countries such as China, India, and Japan. These regions are witnessing increased investments in cloud computing, smart manufacturing, and fintech, all of which are fueling the demand for microservices platforms. Europe remains a strong market as well, with significant uptake in sectors such as banking, healthcare, and retail, supported by stringent data protection regulations and a focus on innovation.

Component Analysis

The microservices platform market is segmented by component into platform and services, each playing a vital role in the overall adoption and implementation of microservices architectures. The platform segment encompasses the core software frameworks, orchestration tools,

Microservices is a popular architectural style for the development of distributed software, with an emphasis on modularity, scalability, and flexibility. Indeed, in microservice systems, functionalities are provided by loosely coupled, small services, each focusing on a specific business capability. Building a system according to the microservices architectural style brings a number of challenges, mainly related to how the different microservices are deployed and coordinated and how they interact. In this paper, we provide a survey about how techniques in the area of Artificial Intelligence have been used to tackle these challenges.

In 2022, ** percent of microservice developers indicated using Java. Other prominent programming languages among microservice developers were Python and Go. Microservice architecture refers to an approach in software development where applications are built in independent pieces that work together.

Microservices architecture decomposes a monolith into independently deployable services, each owning a bounded domain. This enables independent scaling, technology heterogeneity, and faster deployments — but introduces distributed systems complexity: network failures, data

Market Research Database containing comprehensive market size analysis, growth drivers, industry trends, market opportunities, key player analysis, country-level insights, market segmentation, PESTEL analysis, and strategic consulting.

Dataset

This dataset was created by Papa Moussa Sanogo

Released under Apache 2.0

Contents

The size of the Microservices Architecture Market was valued at USD 7.7 Billion in 2024 and is projected to reach USD 25.26 Billion by 2033, with an expected CAGR of 18.5% during the forecast period. Recent developments include: In September 2022, Microsoft released.NET Microservices: Architecture for Containerized.NET Applications, which innovates for Windows and Linux. These technologies provide container solutions that enable businesses to create and deploy applications at cloud speed and scale, regardless of platform or tool., In June 2022, Cognizant was given an agreement by National Insurance Company Limited (NICL) to accelerate and manage its digital transformation via the use of digital technologies such as artificial intelligence, machine learning, automation, and microservices-based architecture.. Key drivers for this market are: Increased demand for agility and innovation: Microservices enable faster development and deployment cycles, allowing businesses to respond quickly to changing market demands.

Adoption of cloud computing: Cloud platforms offer the infrastructure and tools necessary to easily develop and manage microservices architectures.

Rise of DevOps and CI/CD practices: DevOps and continuous integration/continuous delivery (CI/CD) practices streamline the development and deployment of microservices applications.. Potential restraints include: Complexity of management: Managing a large number of microservices can be complex, requiring specialized tools and expertise.

Data consistency challenges: Ensuring data consistency across multiple microservices can be challenging, especially in distributed environments.

Security concerns: Microservices architectures can introduce new security risks, requiring robust security measures.. Notable trends are: Microservices mesh: Service meshes provide a unified layer for managing communication, security, and observability between microservices.

Data mesh architecture: Data mesh architectures enable decentralized data management and access in microservices environments.

Serverless computing: Serverless platforms further simplify the development and deployment of microservices by eliminating the need for server management..

According to our latest research, the global Microservices API Gateway market size reached USD 2.47 billion in 2024, demonstrating robust growth supported by the increasing adoption of microservices architecture across industries.

Introduction

According to Market.us, The global 6G-Enabled Industrial Microservices Market earned USD 3.2 billion in 2024 and is expected to grow from USD 4.7 billion in 2025 to around USD 124.2 billion by 2034. This growth reflects a compound annual growth rate (CAGR) of 44% over the forecast period. In 2024, North America held a leading market position with a share of over 35.5%, generating revenue of USD 1.1 billion.

The 6G-Enabled Industrial Microservices Market embodies the fusion of next-generation 6G wireless connectivity with modular microservices architectures tailored for industrial applications. This integration empowers industries to break down complex software into scalable, independent services that can be deployed and updated swiftly. With 6G networks delivering ultra-low latency, terabit-level speeds, and AI-driven networking, these microservices support real-time automation, autonomous operations, and digital twin simulations.

https://market.us/wp-content/uploads/2025/10/6G-Enabled-Industrial-Microservices-Market-Size.png" alt="6G-Enabled Industrial Microservices Market Size" width="1216" height="706">

Demographic, psychographic, geographic and brand-affinity data for the Microservices audience in Germany, sourced from Rascasse's panel of 12+ social and digital signals.

This data set contains the rapid review results and tool inspection details for the study "Tools for Refactoring to Microservices:
A Preliminary Usability Report"

Parse measures the brands and sources AI systems cite when answering "We have "sprawl" in our microservices architecture. What is the best service catalog tool for tracking ownership and dependencies of hundreds of services?".

Complete dataset included in the full report. Detailed tables, regional splits, forecasts, and methodologies are available with purchase.

Cloud Microservices Market Size And Forecast

The Cloud Microservices Market size was valued at USD 1.16 Billion in 2024 and is projected to reach USD 5.56 Billion by 2031, growing at a CAGR of 21.70% from 2024 to 2031.

Global Cloud Microservices Market Drivers

Increased agility and scalability: Microservices architecture allows for faster development, deployment, and scaling of applications, enabling businesses to respond quickly to changing market conditions.

Improved fault isolation: In a microservices architecture, failures are isolated to individual services, minimizing disruptions to the overall application.

Reduced time to market: Microservices can be developed and deployed independently, reducing the time it takes to bring new products and features to market.

Global Cloud Microservices Market Restraints

Complexity: Designing and managing microservices architectures can be complex, requiring specialized skills and tools.

Increased operational overhead: Microservices architectures can increase operational overhead due to the need to manage multiple services, networks, and dependencies.