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This report investigates how developers use artificial intelligence (AI)-assisted development tools. We start by looking at how many developers use these AI tools to help them with their projects and exploring the tasks they use them for. This report also covers the main reasons why developers use AI-assisted development tools and their effectiveness. Finally, we investigate the challenges developers face when using these tools in their projects. To better understand the current state of AI-assisted development tools, we also break down AI usage information by developer demographics such as experience and use cases throughout the report. All Insights How developers use AI-assisted development tools Exploring adoption, effectiveness and challenges for AI-assisted tools. Access the Full Preview About this Report This report investigates how developers use artificial intelligence (AI)-assisted development tools. We start by looking at how many developers use these AI tools to help them with their projects and exploring the tasks they use them for. This report also covers the main reasons why developers use AI-assisted development tools and their effectiveness. Finally, we investigate the challenges developers face when using these tools in their projects. To better understand the current state of AI-assisted development tools, we also break down AI usage information by developer demographics such as experience and use cases throughout the report. Key Questions Answered How does the likelihood of using AI tools vary across developers with differing experience levels? What are the common use cases for AI-assisted development tools? How effective do developers perceive AI to be in accomplishing various tasks? What are the key drivers and barriers that motivate and impede developers when incorporating AI tools into their workflow? Click to expand ACCESS THE FULL PREVIEW Methodology The 26th edition of the Developer Nation survey reached more than 10,000 respondents from 135 countries around the world, which ran between December 2023 and February 2024. This research report delves into key developer trends for Q1 2024 and beyond. Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT

Key Questions Answered What percentage of developers add AI functionality to their applications? How does the usage of AI functionality in applications differ based on company size? What types of models do developers use to add AI functionality to their applications? Click to expand ACCESS THE FULL REPORT Methodology The 27th edition of the Developer Nation survey reached more than 9,000 respondents from 130+ countries around the world. This research report delves into key developer trends for Q3 2024 and beyond. Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT All Reports Questions? Let's talk! Fill the form. Natasa and Petro will help you drive developer adoption: Name Email I have read and agree to SlashData's Privacy Policy and I want to be contacted. GET IN TOUCH WITH ME How developers build AI-enabled applications Types of models developers incorporate in AI-powered applications Access the Full Report About this Report This report explores how software developers add artificial intelligence (AI) functionality to their applications. We start by looking at the percentage of developers who add AI functionality to their applications, breaking it down by professional status and company size. Following this, we focus on the types of models that these developers use in their applications.

As the use of artificial intelligence (AI) increases, so do concerns regarding security, risk management, and trustworthiness in AI-powered applications. This report explores the various security practices organisations employ to protect their AI-enabled applications against AI-specific security and privacy threats. It also looks at the various challenges facing these companies when it comes to the explainability of AI-powered applications, as well as how they ensure compliance with relevant regulations. All Insights Trust, risk, and security management in AI Current practices and challenges Access the Full Preview About this Report As the use of artificial intelligence (AI) increases, so do concerns regarding security, risk management, and trustworthiness in AI-powered applications. This report explores the various security practices organisations employ to protect their AI-enabled applications against AI-specific security and privacy threats. It also looks at the various challenges facing these companies when it comes to the explainability of AI-powered applications, as well as how they ensure compliance with relevant regulations. Key Questions Answered What are the most common AI-specific risk mitigation practices that organisations employ? How does the implementation of AI-specific risk mitigation practices change based on organisation size and region? What are the main challenges that organisations face in maintaining transparency in the use of AI while ensuring security and privacy? How do these challenges differ based on organisation size and the types of models they use to add AI functionality to their applications? What are the main compliance measures that organisations have when it comes to AI regulations? How do the main compliance measures differ based on organisations in different regions? Click to expand ACCESS THE FULL PREVIEW Methodology The report is based on data collected in the 27th edition of SlashData's Developer Nation survey, which was fielded between June and July 2024. In this survey, more than 1,500 professional developers who build AI-enabled applications answered questions about trust, risk, and security management in AI-enabled applications. Questions? Let's talk! Fill the form. Natasa and Petro will help you drive developer adoption: Name Email I have read and agree to SlashData's Privacy Policy and I want to be contacted. GET IN TOUCH WITH ME Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT

How SlashData helped a client gain insights and recommendations for targeted improvements to their developer program. All Case Studies Mapping developer engagement patterns and program needs The challenge One of the major silicon vendor companies engaged SlashData to gain insights and recommendations for targeted improvements to their developer program. Their goal was to enhance developer satisfaction and engagement with their resources. Additionally, they sought to identify competing developer programs to benchmark their satisfaction and engagement levels against those of other competitors and industry leaders. The approach SlashData leveraged existing data from its 2024 Q1 Developer Nation survey, which reached over 3,500 professional developers across Western Europe, Eastern Europe, North America, South Asia, and the Greater China area. These developers shared insights into their experiences with various developer programs. Respondents were recruited through SlashData’s developer community and verified third-party survey panels, ensuring a robust and representative sample. In addition to using existing quantitative data to answer the client’s questions, we conducted desk research. This was done in order to provide a deeper dive into the user experience with the client’s developer documentation and sample code. Through this analysis, the client was able to receive first-hand feedback and recommendations on how to improve their developer support. The result The data gathered from SlashData’s survey helped the client understand the drivers of engagement and satisfaction amongst professional developers. The analysis answered the client’s core questions, including: Which types of developers are the most engaged with the client’s developer program? Which developer program resources are most important to highly engaged developers? Which types of technologies are associated with high engagement? Which developer profiles does the client attract, and how well does the client engage these developers compared to other vendors? Which of the client’s technology resources are associated with the highest engagement and satisfaction? Which types of developers should the client focus on to raise engagement and satisfaction? What are best-in-class examples of vendors with high engagement and satisfaction scores? These insights helped the client gain a deeper understanding of developer engagement patterns and program needs. In turn, this enables them to tailor their offerings to align with developer profiles and preferences, enhance satisfaction, and drive engagement with key resources and technologies across targeted developer segments. Why SlashData For the client, SlashData’s robust methodology and established global community of developers provided a unique advantage. Leveraging a deep understanding of the developer landscape, SlashData tapped into its extensive developer community and a curated network of third-party providers to reach precisely the right audience for our client's research objectives. Our proprietary survey platform hosted the survey, ensuring robust data integrity through advanced metadata analysis and sophisticated dynamic question logic, so the client received accurate, reliable insights on developer engagement and satisfaction with its technology resources. Do you have a developer program you would like to offer more support to your developer audience? Let’s see together what they need. Contact us. You can find all our data & free reports in our Research Space . Related services Developer Program Benchmarking Quantitative research Previous Case Next Case Get all the new insights in your inbox JOIN NEWSLETTER Talk to our analysts TALK TO US

Discover how the DevRelX community can help you elevate the way you engage with developers. Marketing to developers is tricky. Learning from each other should not be. SlashData powers DevRelX and the community behind it . A place for all developer-facing professionals to access resources and peer-to-peer learning to elevate their professional performance. Want it? APPLY HERE Be part of something bigger Why Join Through participating in community-led events and programs Learning & Training Exclusive access to numerous resources and data to elevate your understanding of developers Data & Resources A place to create meaningful connections with peers and make the most out of learning opportunities with field experts Connect Lead towards the future by sharing ideas and taking an active role within the DevRelX community Contribute The benefits for the members of the community: Who’s in? Developer Marketing professionals Developer Relations professionals Developer Advocates Developer Evangelists Program Managers VPs / CxOs …and more are already members of the community. How about you? APPLY HERE

Track adoption, market share and satisfaction All Reports AI-assisted coding tools Competitive Technology Landscape Report Q3 2025 Track adoption, market share and satisfaction Access the Full Report About this Report What is the AI-assisted coding tools Competitive Technology Landscape? In our AI-assisted coding tools Competitive Technology Landscape report, we benchmark the main competing AI-assisted coding tools based on the responses of over 1,700 developers who used these tools in the last year. We look at which vendor products and technologies developers are currently using, and we measure developer satisfaction across 20 different attributes. Our analysis provides deep insights into the criteria developers use to select products and how likely they are to recommend Key Questions Answered Which AI-assisted coding tools are developers aware of, which are they currently using and which have they abandoned? Which attributes do developers consider most important when they select an AI-assisted coding tool? Do developers rely on a single AI-assisted coding tool, or do they use multiple? Why do developers stop using AI-assisted coding tools? How satisfied are developers with each AI-assisted coding tool? How do they score the tools they use across the attributes they consider most important? How likely are developers to recommend the AI-assisted coding tools products they are currently using? How do the user bases of the most popular AI-assisted coding tools compare to one another? Click to expand ACCESS THE FULL REPORT Methodology The report is based on data collected from the 30th edition of the Developer Nation survey edition of the Developer Nation survey, a large-scale, online developer survey that was designed, hosted, and fielded by SlashData over a period of six and a half weeks between June 2025 and July 2025. Questions? Let's talk! Fill the form. Natasa and Petro will help you drive developer adoption: Name Email I have read and agree to SlashData's Privacy Policy and I want to be contacted. GET IN TOUCH WITH ME Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT

Key Questions Answered Which AI inferencing tools do cloud native developers consider mature and reliable enough for production deployment? How do ML orchestration technologies compare in terms of developer satisfaction and recommendation likelihood? What are the emerging adoption patterns for agentic AI platforms and frameworks? Can technologies that span multiple use cases (like BentoML) achieve market leadership across all categories, or do specialized tools maintain advantages? Click to expand ACCESS THE FULL REPORT Methodology In our research, we employed Likert scales to capture developers' opinions on the maturity and usefulness, from 1 to 5 stars, of the various multicluster application management and batch computing technologies surveyed. While these ratings are inherently subjective, reflecting individual perceptions and experiences, they provide valuable insights into the developer community's views. The nature of our research is centered on investigating developer perceptions of these aspects, making the subjective nature of the ratings not only acceptable but also valuable for our analysis. Although the subjective nature of Likert scales may influence the interpretation of results, as different respondents may have varying standards for rating, this variability enriches our understanding of the developer experience. Respondents were initially asked about where their projects ran or were deployed, to identify their position as a ‘cloud developer.’ Following this, they were asked which technologies they were currently using that we associate with cloud native development approaches, including technologies such as Infrastructure as Code, service meshes, and serverless computing. Respondents were recruited from third-party panels. For privacy and data minimization purposes, exclusion is based on internal consistency and survey-taking behavior metrics. As such, information on the organization the respondent works for is not carried through to any analysis. This privacy also helps encourage greater honesty from respondents, who do not have concerns that their expressed opinion will be associated with them. Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT All Reports Questions? Let's talk! Fill the form. Natasa and Petro will help you drive developer adoption: Name Email I have read and agree to SlashData's Privacy Policy and I want to be contacted. GET IN TOUCH WITH ME CNCF Technology Radar Q3 2025 AI Inferencing, ML Orchestration, and Agentic AI Tools and Platforms Access the Full Report About this Report As AI and machine learning workloads increasingly converge with cloud native infrastructure, understanding which tools developers trust and recommend becomes critical for technology strategy. This Technology Radar report surveys over 300 professional developers working with cloud native technologies to assess their experiences with AI inferencing engines, ML orchestration tools, and agentic AI platforms. The research categorises technologies into four adoption tiers — adopt, trial, assess, and hold — based on developer ratings of maturity, usefulness, and likelihood to recommend. For AI inferencing, NVIDIA Triton, DeepSpeed, TensorFlow Serving, and BentoML emerge as adoption leaders. In ML orchestration, Airflow and Metaflow achieve adopt status, while BentoML demonstrates cross-category versatility. For the rapidly evolving agentic AI space, Model Context Protocol (MCP) and Llama Stack show strong developer confidence. The findings reveal important patterns: technologies can excel in maturity while struggling with usefulness for specific use cases, high recommendation rates don't always correlate with top maturity scores, and cross-functional tools like BentoML can succeed in multiple domains without dominating any single category. With 41% of ML/AI developers now classified as cloud native—a proportion expected to grow — this research provides actionable intelligence for organisations building AI/ML infrastructure strategies. The report also highlights the CNCF ecosystem's crucial role in cultivating technologies from experimental innovations to production-ready infrastructure.

Track adoption, market share and satisfaction All Reports Application Security Testing Market Landscape Report Q1 2023 Track adoption, market share and satisfaction Access the Full Report About this Report In our Application Security Testing (AST) Competitive Technology Landscape, we discuss developers’ usage and awareness of different AST tools, their reasons for adopting and rejecting different AST tools, and how satisfied they are with their experience. We benchmark the main competing Application Security Testing products, we look at which vendor products and technologies developers are currently using and we measure developer satisfaction across 18 different attributes. Our analysis provides deep insights on the criteria developers use to select products and how likely they are to recommend them. Key Questions Answered Which technologies have DevOps developers used as part of their development in the past 12 months? Which AST products are DevOps developers aware of, which are they currently using and which have they abandoned? Which attributes do developers consider most important when they select an AST product? Why do developers adopt and why do they reject each AST product? How satisfied are developers with each AST product? How do they score the offerings they use across the attributes they consider most important? How likely are developers to recommend the AST products they are currently using? Click to expand ACCESS THE FULL REPORT Methodology The data for this report comes from the 24th edition of our Developer Nation survey, which ran between December 2022 and February 2023 and reached nearly 26,000 developers from 166 countries. Of these respondents, over 5,500 developers answered survey questions regarding their usage and opinions of AST tools. Questions? Let's talk! Fill the form. Natasa and Petro will help you drive developer adoption: Name Email I have read and agree to SlashData's Privacy Policy and I want to be contacted. GET IN TOUCH WITH ME Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT

Data for the report comes from the 23rd edition of our Developer Nation survey, which ran between June 2022 and August 2022. Emerging practices in MLops / DataOps An overview of current and emerging trends in MLOps/DataOps Access the Full Preview All Insights About this Report Data for the report comes from the 23rd edition of our Developer Nation survey, which ran between June 2022 and August 2022. Key Questions Answered What MLOps/DataOps practices are developers using, and using in combination? What are the differences in MLOps/DataOps practices between developers in different sectors? What impact does how the data is stored have on MLOps/DataOps practices? How does the amount of data ML/data scientists use for training their models have on their choice and use of MLOps/DataOps practices? How does the motivation of those involved in ML/AI have on their choice and use of MLOps/DataOps practices? Click to expand ACCESS THE FULL PREVIEW Methodology In this report, we will explore the different practices and approaches used by developers involved in data and machine learning (ML) operations (DataOps/MLOps), and how these practices are used together. We will also look at how differentDataOps/MLOp practices dictate the use of different backend and ML technologies, as well as ways of storing data. Finally, we will show how developers' motivations and target audiences are impacted bytheirDataOps/MLOp practices. Questions? Let's talk! Fill the form. Natasa and Petro will help you drive developer adoption: Name Email I have read and agree to SlashData's Privacy Policy and I want to be contacted. GET IN TOUCH WITH ME Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT

Key Questions Answered What is the current adoption of DevOps practices? What is the current adoption of DevOps technologies? Which industries are most involved in DevOps? How has the industry’s performance on DORA metrics changed over the last three and a half years? What is the impact of using multiple DevOps technologies on DORA performance? What is the impact of CI/CD tools on DORA performance? What is the impact of using multiple CI/CD tools simultaneously? Click to expand ACCESS THE FULL REPORT Methodology The findings in this report are based on data from SlashData’spast six Developer Nation surveys, which reached more than 125,000 respondents worldwide over two and half years, from Q3 2020 to Q1 2023 Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT All Reports Questions? Let's talk! Fill the form. Natasa and Petro will help you drive developer adoption: Name Email I have read and agree to SlashData's Privacy Policy and I want to be contacted. GET IN TOUCH WITH ME State of Continuous Delivery Report 2023 The Evolution of Software Delivery Performance Access the Full Report About this Report In this report, commissioned by the Continuous Delivery Foundation (CDF) and authored by SlashData, we explore the current state of the CD developer ecosystem and how this has evolved over the past two and half years. We will look at what proportion of developers are involved in the broader DevOps space and how many work with CD technologies in particular. Moreover, we will see how developers’ software delivery performance has changed over time. Finally, we will explore how developers’ usage of multiple continuous integration and continuous delivery (CI/CD) tools contribute to software delivery performance, as well as how approaches to application security testing change delivery performance.

Data Dashboards are the most straightforward way to give everyone access to our market research data. Users can access a series of graphs and filters, each delivering the latest data to key industry questions. Filter through the data with interactive dashboards Try it The 360 view of developers dashboard is free to access and explore. ACCESS HERE Boost productivity Focus on the tech data you need Data Dashboards are the most straightforward way to give you access to our data. Access a series of graphs, each delivering the latest data to key industry questions. It’s up to you to customise your view. Use filters to narrow down the data, such as experience, professional status, region and more. One licence | Unlimited seats Access to dashboards is enterprise-wide. With one subscription, everyone in your organisation can access the dashboards Steve from Marketing can explore regional distribution, while Jen from Product can filter for adoption preferences. Contact us to explore your options LET'S TALK Explore our available dashboards 30 September 2025 Global Developer Population Sizing (Q3 2025) MORE 26 September 2025 Decoding AI: How developers are leveraging AI today (Q3 2025) MORE 23 September 2025 The 360 View of Developers (Q3 2025) MORE 19 September 2025 Consumer Electronics (CE) Key Developer Metrics (Q3 2025) MORE 17 September 2025 Web Key Developer Metrics (Q3 2025) MORE 16 September 2025 Industrial Internet of Things (IIoT) Key Developer Metrics (Q3 2025) MORE 16 September 2025 Global Developer Population Sizing Trends (Q3 2025) MORE 4 September 2025 Mobile Developer Segmentation (Q3 2025) MORE 3 September 2025 Mobile Key Developer Metrics (Q3 2025) MORE 2 September 2025 Games Key Developer Metrics (Q3 2025) MORE 31 August 2025 Developer Program Benchmarking (Q3 2025) MORE 28 August 2025 How and Where to Reach Developers (Q3 2025) MORE 27 August 2025 AI-assisted coding tools Competitive Technology Landscape (Q3 2025) MORE 26 August 2025 DevOps Platforms Adoption Trends (Q3 2025) MORE 25 August 2025 Augmented & Virtual Reality (AR/VR) Key Developer & Non-Developer Metrics (Q3 2025) MORE 20 August 2025 Enterprise App Ecosystems Key Developer Metrics (Q3 2025) MORE 19 August 2025 3rd-party App Ecosystems Key Developer Metrics (Q3 2025) MORE 18 August 2025 Embedded Software Key Developer Metrics (Q3 2025) MORE 18 August 2025 Data Science & Machine Learning / AI Key Developer Metrics (Q3 2025) MORE 14 August 2025 Desktop Key Developer Metrics (Q3 2025) MORE 14 August 2025 Desktop Developer Segmentation (Q3 2025) MORE 11 August 2025 Container Orchestration Technology Adoption Tracker (Q3 2025) MORE 11 August 2025 Cloud Developer Segmentation (Q3 2025) MORE 8 August 2025 Cloud Key Developer Metrics (Q3 2025) MORE 6 August 2025 PaaS Technology Adoption Tracker (Q3 2025) MORE 11 March 2025 Consumer Electronics (CE) Key Developer Metrics (Q1 2025) MORE 11 March 2025 Embedded Software Key Developer Metrics (Q1 2025) MORE 11 March 2025 Enterprise App Ecosystems Key Developer Metrics (Q1 2025) MORE 11 March 2025 Industrial Internet of Things (IIoT) Key Developer Metrics (Q1 2025) MORE 19 February 2025 How and Where to Reach Developers (Q1 2025) MORE 23 January 2025 Augmented & Virtual Reality (AR/VR) Key Developer & Non-Developer Metrics (Q1 2025) MORE 23 January 2025 Developer Program Benchmarking (Q1 2025) MORE 23 January 2025 Global Developer Population Sizing (Q1 2025) MORE 23 January 2025 Global Developer Population Sizing Trends MORE 23 January 2025 AI-assisted coding tools Competitive Technology Landscape (Q1 2025) MORE 7 November 2024 Mobile Key Developer Metrics (Q4 2024) MORE 7 November 2024 Mobile Developer Segmentation (Q4 2024) MORE 17 October 2024 Games Key Developer Metrics (Q4 2024) MORE 17 October 2024 Decoding AI: How developers are leveraging AI today (Q4 2024) MORE 17 October 2024 Desktop Key Developer Metrics (Q4 2024) MORE 17 October 2024 Desktop Developer Segmentation (Q4 2024) MORE 10 September 2024 3rd-party App Ecosystems Key Developer Metrics MORE 10 September 2024 The 360 View of Developers (Q3 2024) MORE 10 September 2024 Industrial Internet of Things (IIoT) Key Developer Metrics MORE 10 September 2024 The 360 View of Developers (Free Edition) (Q3 2024) MORE 10 September 2024 Enterprise App Ecosystems Key Developer Metrics MORE 10 September 2024 Embedded Software Key Developer Metrics MORE 21 August 2024 Q3 2024 - Developer Program Benchmarking MORE 21 August 2024 Container Orchestration Technology Adoption Tracker MORE 21 August 2024 IaaS Technology Adoption Tracker MORE 21 August 2024 Q3 2024 - Cloud-based development environments Competitive Technology Landscape MORE 21 August 2024 Cloud Developer Segmentation MORE 21 August 2024 PaaS Technology Adoption Tracker MORE 21 August 2024 Serverless Technology Adoption Tracker MORE 9 April 2024 Q1 2024 - The 360 View of Developers (Free Edition) MORE What SlashData Dashboards deliver Flexibility The same reliable data, same thorough methodology. Tailored your way, with the filters you choose. Always up-to-date Each dashboard gets at least 1 annual update. Some key dashboards get 2 data updates per subscription period. DIY Analysis A focus on self-service data that enables a flexible analysis on what you are most interested in. The “plus” in add-ons Dashboards can work as your standalone data source or as an add-on tied to one of your Developer Ecosystem Insights. SlashData Dashboard types Key Developer Metrics Focus: Web, cloud, ML/AI and all 13 development areas. Uncover trends in the adoption of development tools, technologies, and practices across different development areas. Developer Segmentation Focus: Cloud, Mobile and Desktop. A goals-based segmentation approach. Compare developer segments: Hobbyists, Explorers, Hunters, Guns for Hire, Product Extenders, Digital Content Publishers, Gold Seekers, and Optimizers. Analyze their key attributes, technology adoption patterns, and tool usage trends. Developer Program Benchmarking Focus: Cross-sector, including Backend, IoT, embedded systems, and AR/VR. Comparing the performance of more than 20 distinct developer programs. With interactive graphs and over 40 customizable filters, compare programs, analyze developer profiles, identify emerging trends, and export charts or data tables for in-depth insights. Technology Adoption Tracker Focus: The most broadly used cloud technologies, including IaaS, DBaaS, Serverless, and Orchestration. Apply product usage filters to create tailored views of developer preferences and analyze the adoption trends for each product. Competitive Technology Landscape Focus: Application Performance Monitoring, Test Automation/ Management, Application Security Testing, Cloud-based Development Environments and all developer tooling areas Product & market landscapes based on custom questions which allow us to collect unique insights on key topics. Global Developer Population Sizing Trends Explore the evolution of the global developer population and filter by region, age, company size, industry, and more. Are you looking for insights tailored to your exact needs? Contact us and we can design your survey together. CONTACT US

Application security is critical as it serves to protect against a variety of threats, including malicious attacks that compromise application functionality, unauthorised access to sensitive information, the injection of malicious code, and/or data-leaks. The shift-left approach to application security is a strategy that aims to encourage security checks from the early stages of the software development process. In our analysis we examine how and when – during the software development process – security measures are implemented. We additionally examine what factors contribute to developers implementing various types of security and the amount of security checks they take. All Insights Applications and shift-left security Exploring the application security landscape Access the Full Preview About this Report Application security is critical as it serves to protect against a variety of threats, including malicious attacks that compromise application functionality, unauthorised access to sensitive information, the injection of malicious code, and/or data-leaks. The shift-left approach to application security is a strategy that aims to encourage security checks from the early stages of the software development process. In our analysis we examine how and when – during the software development process – security measures are implemented. We additionally examine what factors contribute to developers implementing various types of security and the amount of security checks they take. Key Questions Answered When and how security measures are being implemented? What type of developers are implementing them? Click to expand ACCESS THE FULL PREVIEW Questions? Let's talk! Fill the form. Natasa and Petro will help you drive developer adoption: Name Email I have read and agree to SlashData's Privacy Policy and I want to be contacted. GET IN TOUCH WITH ME Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT Methodology The report is based on data collected from 14,000+ developers involved in DevOps-related activities who told us about the approaches they use to secure their applications in the 23rd edition of our Developer Nation survey, which was fielded between June and August 2022.

Key Questions Answered How do professionals working in startups differ from their counterparts working in established companies? Click to expand ACCESS THE FULL REPORT Methodology The 27th edition of the Developer Nation survey reached more than 9,000 respondents from 130+ countries around the world. This research report delves into key developer trends for Q3 2024 and beyond. Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT All Reports Questions? Let's talk! Fill the form. Natasa and Petro will help you drive developer adoption: Name Email I have read and agree to SlashData's Privacy Policy and I want to be contacted. GET IN TOUCH WITH ME Profiling of technology professionals working at startups How startups differ from other technology companies in their revenue models and the projects they work on Access the Full Report About this Report In this report, we specifically explore developers working in startups. We first examine their profile and then assess how their revenue generation models and involvement in technological spaces distinguish them from their established counterparts.

In this report, we look into the underlying trends behind the growth of the mobile developer population across the world. We start by exploring the global population of mobile developers over the years and break it down by geographical location. Then, we look at the breakdown of the total mobile developer population by professional status and categories of applications built. Finally, we discuss the platforms and technologies that mobile developers use, and we estimate the size of the addressable market-specific tools used to create mobile applications, such as programming languages and frameworks. All Insights Mobile developers population forecast How many mobile developers are there? Access the Full Preview About this Report In this report, we look into the underlying trends behind the growth of the mobile developer population across the world. We start by exploring the global population of mobile developers over the years and break it down by geographical location. Then, we look at the breakdown of the total mobile developer population by professional status and categories of applications built. Finally, we discuss the platforms and technologies that mobile developers use, and we estimate the size of the addressable market-specific tools used to create mobile applications, such as programming languages and frameworks. Key Questions Answered How many mobile developers are there across the globe? What is the breakdown of these backend developers by professional status, geographical region, and experience? What types of tools and technologies are mobile developers using? Who are mobile developers primarily targeting with their software? Click to expand ACCESS THE FULL PREVIEW Methodology To count developers, we use an independent, bottom-up methodology. The data we use to arrive at the estimates in this report comes from: 1. Reliably measured numbers of developers or direct indicators of their activity: GitHub accounts and repositories, Stack Overflow accounts, and employment statistics from the USA and the European Union. 2. Our proprietary developer survey data, i.e., measured developer behaviour. For this report, we used data from 44,000+ mobile developers across six consecutive surveys. Questions? Let's talk! Fill the form. Natasa and Petro will help you drive developer adoption: Name Email I have read and agree to SlashData's Privacy Policy and I want to be contacted. GET IN TOUCH WITH ME Contact us First name* Last name* Work Email* Company * Role* Message I agree to SlashData's Privacy Policy and I want to be contacted * SUBMIT