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Key Questions Answered What share of professional developers use AI-assisted coding tools, and which ones are the most popular? How do AI-assisted coding tools rank in terms of satisfaction? How does satisfaction vary based on developers’ experience? What are the key strengths of the top AI-assisted coding tools? Click to expand ACCESS THE FULL REPORT Methodology The 30th edition of the Developer Nation survey reached more than 12,000 respondents from 128 countries around the world. This research report series delves into key developer trends for Q3 2025 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 Choosing the right AI coding tools for your team Usage, satisfaction, and trust among professional developers Access the Full Report About this Report The rapid rise of AI-assisted coding tools marks a pivotal moment in software development. What began as experimental add-ons has quickly evolved into a crowded market of products, each claiming to boost productivity and transform workflows. Yet with so many options and so much noise, it can be difficult to know which tools are truly delivering value. By examining adoption, satisfaction, and trust-related attributes such as accuracy, support, and security, this report provides a data-driven benchmark of which AI coding tools developers are embracing and which they rate most highly. The analysis reveals where usage aligns with satisfaction, where trust is earned through consistent delivery, and where gaps remain between expectations and reality. For engineering leaders making decisions about which tools to integrate and scale across their teams, the insights in this report help distinguish the coding tools that enable productivity from those that are still struggling to meet developer needs.

Key Questions Answered To what extent are developers building AI-powered applications? Which regions are leading in AI integration? Have developers begun deploying agentic AI architectures to production? How does the implementation of agentic AI vary by company size? How does the implementation of agentic AI vary by project type? What types of agentic architectures are being deployed in production? What use cases are developers targeting with agentic architectures? Click to expand ACCESS THE FULL REPORT Methodology The 30th edition of the Developer Nation survey reached more than 12,000 respondents from 128 countries around the world. This research report series delves into key developer trends for Q3 2025 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 The state of agentic AI adoption in software projects The architectures developers use, and the use cases they target Access the Full Report About this Report Agentic AI is emerging as one of the most transformative shifts in how companies design and deploy intelligent systems. This mini-report analyses insights from over 8,400 professional developers to help CTOs and engineering leaders navigate the rapidly evolving agentic AI landscape and make informed architecture and use case decisions. We’ll explore how the implementation of agentic AI varies by company size and project type as well as looking at the types of agentic architectures that are being deployed to production, along with the use cases developers are targeting.

Key Questions Answered What are the main barriers preventing developers from integrating generative AI into their applications? What can software engineering leaders focus on to prepare for challenges that slow the adoption of generative AI? Click to expand ACCESS THE FULL REPORT Methodology The 30th edition of the Developer Nation survey reached more than 12,000 respondents from 128 countries around the world. This research report series delves into key developer trends for Q3 2025 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 Barriers to integrating generative AI in applications Understanding what prevents developers from building generative AI features across different company types Access the Full Report About this Report Generative artificial intelligence (AI) is rapidly becoming an integral part of the modern software ecosystem, significantly transforming how developers innovate and deliver value in their applications. In fact, this technology has already begun redefining software capabilities and introducing new technical considerations around model selection, integration methods, and user experience design. As of Q3 2025, a quarter (25%) of professional developers are adding generative AI features to their applications. However, this means that a large share of the developer population is still not building applications that utilise this technology. To understand this from the perspective of developers, we asked over 7,000 professional developers about the main barriers preventing them from integrating generative AI into their applications. For software engineering leaders, these insights provide a benchmark against peers and industries, helping them prioritise technology investments and prepare mitigation strategies for the challenges most likely to slow adoption.

Industry and technology market reports that are free to access and download and share key insights on the trending technology and software development trends. Research is not a privilege. It’s a necessity for decision-making. Giving back is in our DNA, so we always serve the world through our strength: insights. You can find all the insights we are happy to share with everyone- no strings attached. Pick the topic that resonates best and dive into a world of data. Explore our latest research 14 November 2025 Barriers to integrating generative AI in applications MORE 14 November 2025 The state of agentic AI adoption in software projects MORE 14 November 2025 Choosing the right AI coding tools for your team MORE 11 November 2025 CNCF Technology Radar Q3 2025 MORE 10 November 2025 State of Cloud Native Development Q3 2025 MORE 21 October 2025 The State of FinOps in 2025 MORE 21 October 2025 Sizing programming language communities MORE 21 October 2025 Benchmarking backend and cloud technology strategies MORE 12 September 2025 2025 Cloud Landscape in Europe and the US MORE 7 May 2025 Usage of AI assistance between DORA performance groups MORE 7 May 2025 Challenges organisations face in software development projects MORE 6 May 2025 The developers behind generative AI applications MORE 6 May 2025 Sizing programming language communities MORE 6 May 2025 How and why developers engage with emerging technologies MORE 6 May 2025 How technology practitioners use social media MORE 16 April 2025 The state of cloud operations and management in 2025 and the impact of AI MORE 4 April 2025 CNCF Technology Radar MORE 10 March 2025 Generative AI for Business: Success, Challenges and the Future MORE 11 February 2025 State of Development Environments MORE 1 December 2024 Profiling of technology professionals working at startups MORE 29 November 2024 CNCF Technology Landscape Radar MORE 1 November 2024 The rise of AI-chatbots for problem-solving MORE 1 November 2024 Network APIs: The new oil in the 5G economy MORE 1 November 2024 Sizing programming language communities Q3 2024 MORE 1 November 2024 What developers think about their teams MORE 1 November 2024 How developers build AI-enabled applications MORE 1 May 2024 How and why developers engage with emerging technologies MORE 1 May 2024 Threats in software supply chain management MORE 1 May 2024 How happy are developers with their jobs? MORE 1 May 2024 How developers interact with AI technologies MORE 1 May 2024 Profiling of new ML/AI developers MORE 1 May 2024 Sizing programming language communities Q1 2024 MORE 1 April 2024 State of Continuous Integration and Continuous Delivery Report 2024 MORE 13 March 2024 How Silicon Developers help developers build AI solutions MORE 1 February 2024 Maturity of Software Supply Chain Security Practices 2024 MORE 1 November 2023 25th edition - State of the Developer Nation MORE 1 September 2023 Developer Perceptions of Distributed Cloud MORE 1 September 2023 The State of WebAssembly 2023 MORE 1 July 2023 Designing for success MORE 1 June 2023 2023 state of data management solutions for digital natives MORE 1 June 2023 The state of developer happiness MORE 1 May 2023 24th edition - State of the Developer Nation MORE 1 May 2023 State of Continuous Delivery Report 2023 MORE 1 May 2023 Building and Developing on Salesforce Report 2023 MORE 1 February 2023 Securing the enterprise MORE 1 November 2022 NGINX State of App and API Delivery Report MORE 1 November 2022 Developers & Shift-left Security MORE 1 October 2022 23rd edition - State of the Developer Nation MORE Can’t find what you are looking for? Get in touch and we will be happy to help LET'S TALK Case Studies Explore real life scenarios, and how we helped our clients access key market information. We include the process, what SlashData brought to the table and the results they achieved. CASE STUDIES

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Key Questions Answered How many cloud native developers are there in Q3 2025? How many cloud native backend developers are there in Q3 2025? How many ML/AI developers are cloud native in Q3 2025? What are the most popular cloud deployment options in Q3 2025, and how has this changed over time? What are the most common cloud native technologies backend developers use? What are the most common cloud technologies in use? 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 ten weeks between June 2025 and July 2025. 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 State of Cloud Native Development Q3 2025 Access the Full Report About this Report This report, based on the 30th edition of SlashData’s Developer National survey, explores the current state and scale of cloud native development in Q3 2025. The report provides approximations of the cloud-native developer population in backend services, machine learning or AI, and throughout the entire developer population. The report also provides information on the popularity of different cloud native technologies or approaches among backend developers, to reveal the sophistication path organisations often go through. In addition, the report explores the trends in cloud deployment approaches, as well as the technologies that developers are using in their backend or cloud development processes and services. We also provide estimates for the proportion of cloud nativeness throughout the range of types of development (e.g. mobile, desktop, DevOps, etc.).

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 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.

Explore how we help our clients and the industry. These are anonymised, real problems we have sold and shared insights that shed light on our clients' challenges. Explore real-life case studies Exploring the European cloud: How UpCloud used data to lead the data sovereignty conversation UpCloud partnered with SlashData to survey 300 cloud decision-makers in Europe/US, uncovering security, compliance and data-sovereignty drivers—shaping European cloud positioning and product bets. MORE Enhancing web developer experience by addressing key challenges See how SlashData helped a global tech giant address developer challenges, optimise web offerings, and boost engagement with data-driven insights. MORE What drives or prevents Web2 developers to jump to blockchain? Profiling developers who already made the leap How SlashData helped a leading Web3 company uncover barriers, motivators, and trends in blockchain adoption among Web2 developers. MORE Developers’ preferences in Cloud Development Environments (CDEs) adoption Enterprise developers’ preferences and decision-making and how it helped a SlashData client refine their CDE offerings to gain a competitive edge MORE Using SlashData custom questions to understand AI software developers How one of our clients, worked with us to understand the needs and preferences of software developers working with AI. MORE Mapping developer engagement patterns and program needs How SlashData helped a client gain insights and recommendations for targeted improvements to their developer program. MORE Using SlashData Deep Dives to boost Developer Experience Let’s see how a household name we’ll call “Client”, one of the largest companies in the world, worked with us to improve their Developer Experience. MORE How Okta is Broadening Their Developer Network with SlashData’s Developer Program Benchmarking Here’s how one of them –Okta– is using SlashData’s Developer Program Benchmarking to stand out and unlock more developer opportunities. MORE Understanding how developers engage with authentication services In this case study, we look at how SlashData worked with a client product team to answer their questions on developer authentication needs. MORE Assessing satisfaction, tool usage, and workflow challenges in a complex cloud developer ecosystem A case study focusing on a CRM platform that wanted to better understand developers in their ecosystem. MORE How Akamai identified key opportunities to shape distributed cloud computing strategies How we helped Akamai uncover developer insights on distributed cloud computing and identify key improvements for industry adoption. MORE Tracking brand awareness among enterprise developers: gaps and opportunities How we provided a client with critical insights into the network API landscape, addressing the questions that will guide the future. MORE Insights on DevOps: How SlashData helped the CD Foundation understand CI/CD adoption and performance How SlashData helped the CD Foundation uncover DevOps adoption trends, performance impacts, and the value of CI/CD tools. MORE Aligning product strategy with user needs: How we helped an e-commerce leader navigate the headless space A leading e-commerce provider gained insights into developer needs and technologies in headless e-commerce, shaping their product strategy. MORE Estimating the total addressable market for a silicon vendor How we helped a silicon vendor estimate their total addressable market for their products targeted at software developers. MORE Shaping the future of network APIs How we provided a client with critical insights into the network API landscape, addressing the questions that will guide the future. MORE Understanding the maturity of organisations' software supply chain security practices with Red Hat A case study on how SlashData worked closely with Red Hat to understand and assess software supply chain maturity. MORE Exploring developer happiness and productivity with Sentry A case study on how SlashData worked with Sentry to measure if developer happiness affects their productivity. MORE Measuring the effectiveness of machine translations A case study on how we helped a client's localisation team determine if machine translation was sufficient for optimal user experience. MORE Assessing and Benchmarking Developer Satisfaction with Cloud Service Provider Support In this case study we look at how a developer marketing team from a leading cloud service provider wanted to understand user satisfaction. MORE Exploring developer preferences for API programs and no-code/low-code solutions A case study about a cloud communication company working on understanding the needs of professional developers integrating 3rd party APIs. MORE Let’s focus on you What insights can make a difference for you? LET'S TALK How the industry uses our market insights Explore real-life scenarios on how we helped our clients access key market information and reach their goals. Though anonymised, all scenarios are 100% true. We include the process, what SlashData brought to the table and the results they achieved.

UpCloud partnered with SlashData to survey 300 cloud decision-makers in Europe/US, uncovering security, compliance and data-sovereignty drivers—shaping European cloud positioning and product bets. All Case Studies Exploring the European cloud: How UpCloud used data to lead the data sovereignty conversation The challenge UpCloud, a European cloud service provider, sought to publish a thought leadership report on the rapidly evolving cloud landscape, particularly around security, compliance, and data sovereignty. With increasing global attention on where data resides and how it is protected, UpCloud wanted to uncover how organisations across Europe and the US perceive these issues, and how such perceptions might drive the adoption of European cloud vendors. The company also aimed to use this data internally to guide product decisions and refine its messaging. The approach SlashData designed and fielded a custom survey reaching 300 cloud decision-makers in Europe and the US (professionals involved in the selection and management of cloud services within organisations of at least five employees). The study explored, among other things, organisations’ current and planned usage of European and US cloud service providers (CSPs), key selection factors, challenges organisations face in managing their cloud environments, motivations and barriers for adopting European CSPs, and their top priorities around cloud services and infrastructure in the next two years. The survey was hosted on SlashData’s proprietary research platform, ensuring high-quality responses through advanced data cleaning and fraud detection processes. The result The resulting report ( 2025 Cloud Landscape in Europe and the US ) provided UpCloud with a clear, data-backed narrative for both external and internal use. Key findings from the report included: More organisations across Europe and North America are looking to include European providers in their cloud strategies in the next two years Security, performance, and data privacy and residency are the top factors when considering cloud service providers. Free add-on services, trials, or credits are not enough to attract cloud decision-makers. Integrating AI into cloud infrastructure and processes is a key priority for one-third of cloud decision-makers over the next 1–2 years. The vast majority of organisations have already taken action or are preparing to support AI workloads on cloud infrastructure. Are you looking to publish a thought leadership report for your industry? Let’s work together. "SlashData was an amazing partner to work with. They really helped us shape our project from scratch, and showed a genuine commitment to helping us get the most value out of it. Running a survey is not as easy as some may think. It takes a lot of thought and expertise to get it right and to make it interesting, engaging and useful. In this regard, SlashData's expertise was invaluable to us. Their team was always reachable and willing to advise, and they went through several iterations of the project with us, helping us really mature our ideas and improve the survey. I look forward to further joint collaboration opportunities in the future." Why SlashData SlashData specialises in understanding tech leaders and developers - their needs, preferences, and behaviours - making us the ideal partner for studies targeting the technology ecosystem. We serve as a comprehensive market research partner, guiding clients from an initial high-level research brief to actionable data from their target audience, addressing key business questions. Previous Case Next Case Get all the new insights in your inbox JOIN NEWSLETTER Access more insights tailored to your needs TALK TO US

Gain competitive advantage with SlashData’s Competitive Market Intelligence: compare offerings, refine go‑to‑market, map industry landscape & empower sales teams. Decode your market through actionable intelligence Get the insights you need to win more deals, seize market gaps, and stay ahead of disruption. Competitive market intelligence for a future-proof strategy What’s the next step to become the market leader? Gain a sharper understanding of where you stand in the market and where you could go next Our rigorous research approach helps technology firms Refine positioning Identify whitespace opportunities Understand emerging threats Empower customer-facing teams with intelligence that drives results. How Competitive market intelligence can power your strategy Competitive benchmarking Side-by-side comparisons of product features, pricing models, go-to-market strategies, and more, giving you a clear view of how your offerings stack up. Where do you stand out? Sales enablement Actionable insights for your sales team with competitive talking points, and objection-handling strategies, to win deals and drive revenue growth in crowded markets. What can your sales team use to stand out? Landscape reports A comprehensive view of a given technology sector or niche. A map of key players, trends, market forces, and potential disruptors. This is essential for strategic planning, investment decisions, or entry to new markets. What does your market landscape look like? Strategic hypotheses generation A dig into available evidence to form well-grounded hypotheses about market behavior, competitor advantages, and customer preferences - fueling your internal analysis, product development, and strategic discussions. What else should you explore? What insights does your team need? Let’s get you the data you need TALK TO US BOOK A CALL Explore all our services Audience Insights ➜ Product Development & Improvement ➜ Brand Research ➜ Customer Segmentation & Persona Insights ➜ Product Configuration & Optimisation ➜ Competitive Market Intelligence ➜

This report investigates the state of integration of open and fully open-source artificial intelligence (AI) models by developers who add AI functionality to their applications. While focusing on the broader picture, we explore the types of functionalities developers use these models for, why they choose them over their proprietary alternatives, and the challenges they face. In addition to this, we also take a brief look at the reason why developers might avoid using open or open-source models in their applications. All Insights Developers’ experience with integrating AI functionality A focus on open and open-source AI models Access the Full Preview About this Report This report investigates the state of integration of open and fully open-source artificial intelligence (AI) models by developers who add AI functionality to their applications. While focusing on the broader picture, we explore the types of functionalities developers use these models for, why they choose them over their proprietary alternatives, and the challenges they face. In addition to this, we also take a brief look at the reason why developers might avoid using open or open-source models in their applications. Key Questions Answered Where are developers using network APIs located? What type of projects are network API users building? What types of network APIs are developers using? How do professional involvement and company size influence the implementation of network APIs? What challenges do developers face when using network APIs? How do developers prefer to pay for network APIs? How do pricing preferences differ between regions and companies of different sizes? Click to expand ACCESS THE FULL PREVIEW 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 in the 27th edition of SlashData’s global Developer Nation survey, which was fielded between June and July 2024. This survey reached over 2,000 developers who add AI functionality to their applications and answered questions about their experiences with open and open-source models.

Sustainable software engineering (SSE) is the practice of minimisingthe environmental cost of software. It is an emerging discipline at the intersection of climate science, software practices and architecture, electricity markets, hardware, and data centre design. In this report, we’ll look at which developers are involved in building sustainable software and which SSE principles are most commonly utilised. We’ll investigate how developers’ experience levels, location, and the size of the organisation they work for –amongst other factors –affect the rate at which they utilise SSE and which principles they most often adopt. Later, we’ll take a closer look at what motivates developers to utilise SSE principles, as well as which challenges they face in doing so. We’ll demonstrate how developers’ motivations and challenges change based on several different factors, such as their experience levels. All Insights Who's integrating sustainable software engineering principles? Developers’ approaches, motivations, and challenges around building green software Access the Full Preview About this Report Sustainable software engineering (SSE) is the practice of minimisingthe environmental cost of software. It is an emerging discipline at the intersection of climate science, software practices and architecture, electricity markets, hardware, and data centre design. In this report, we’ll look at which developers are involved in building sustainable software and which SSE principles are most commonly utilised. We’ll investigate how developers’ experience levels, location, and the size of the organisation they work for –amongst other factors –affect the rate at which they utilise SSE and which principles they most often adopt. Later, we’ll take a closer look at what motivates developers to utilise SSE principles, as well as which challenges they face in doing so. We’ll demonstrate how developers’ motivations and challenges change based on several different factors, such as their experience levels. Key Questions Answered What percentage of developers have added generative AI features to their applications, and how many are interested? Do developers need to be AI or machine learning experts to create generative AI experiences? How does company size influence the choice of incorporation methods of generative AI functionality? What are the biggest challenges developers face when integrating generative AI functionality into their applications? Which cloud services do developers use the most for integrating generative AI into their applications? Click to expand ACCESS THE FULL PREVIEW Methodology Data for this report comes from the 24th edition of our Developer Nation survey, which was fielded in Q1 2023, between December 2022 and February 2023. Around 17,000 developers told us about their experiences with integrating SSE principles into their development projects. 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

The aim of this report is to investigate the current state of the MLDS landscape through the exploration of key practices amongst MLDS developers. We begin by examining how developers engage with MLDS projects and where MLDS developers execute their code. Following this, we take a close look at the programming languages and algorithms that MLDS developers use. Finally, we discuss the types of data that developers use in their MLDS projects and where that data comes from. All Insights The state of machine learning and data science Examining code execution, algorithms, and data practices Access the Full Preview About this Report The aim of this report is to investigate the current state of the MLDS landscape through the exploration of key practices amongst MLDS developers. We begin by examining how developers engage with MLDS projects and where MLDS developers execute their code. Following this, we take a close look at the programming languages and algorithms that MLDS developers use. Finally, we discuss the types of data that developers use in their MLDS projects and where that data comes from. Key Questions Answered How are developers involved in data science, machine learning, and artificial intelligence (AI)? Where does the code of MLDS developers run? Which programming languages are used in MLDS projects? Which algorithms and approaches are used in MLDS projects? What types of data do MLDS developers work with? Where does the data used in MLDS projects come from? Click to expand ACCESS THE FULL PREVIEW Methodology The report is based on data collected from the 28th 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 five weeks between September and October 2024. 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

This report is based on data collected from over 15,000 professional developers who indicated that they use DevOps technologies in the 23rd edition of our Developer Nation survey, which was fielded in Q3 2022. Observability in software development and the challenges developers face in observability projects Access the Full Preview All Insights About this Report This report is based on data collected from over 15,000 professional developers who indicated that they use DevOps technologies in the 23rd edition of our Developer Nation survey, which was fielded in Q3 2022. Key Questions Answered Which regions are the hotspots for blockchain development? Which revenue models are used by professional developers involved in blockchain projects? Where do blockchain developers go to get information about software development? Which types of content do blockchain developers prefer when solving problems? Which types of content do developers interested in blockchain prefer when doing research? Which blockchain platforms are the most popular? Which blockchain platforms do the most and least experienced developers use? Click to expand ACCESS THE FULL PREVIEW Methodology The aim of this report is to provide an overview of the current state of observability through the eyes of DevOps professionals. We will begin by investigating the adoption of application performance monitoring and observability technologies, and discuss how this is affected by region, company size, and experience levels of the developers. Following this, we will take a deep dive into the most prominent challenges that developers face when setting up and maintaining observability projects. 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