Performance
observability, performance and monitoring, aiops, slo
Data Engineering
Enriching Data Pipelines, Expanding AI, and Expediting Analytics
Over a decade ago, DZone welcomed the arrival of its first ever data-centric publication. Since then, the trends surrounding the data movement have held many titles — big data, data science, advanced analytics, business intelligence, data analytics, and quite a few more. Despite its varying vernacular, the purpose has remained the same: to build intelligent, data-driven systems. The industry has come a long way from organizing unstructured data and driving cultural acceptance to adopting today's modern data pipelines and embracing business intelligence capabilities.
This year's Data Engineering Trend Report draws all former terminology, advancements, and discoveries into the larger picture, illustrating where we stand today along our unique, evolving data journeys. Within these pages, readers will find the keys to successfully build a foundation for fast and vast data intelligence across their organization. Our goal is for the contents of this report to help guide individual contributors and businesses alike as they strive for mastery of their data environments.
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Big Data
data engineering, data pipelines, ai, analytics and metadata
Kubernetes in the Enterprise
Once Decade-Defining, Now Forging a Future Beyond Containerization
In 2014, Kubernetes' first commit was pushed to production. And 10 years later, it is now one of the most prolific open-source systems in the software development space. So what made Kubernetes so deeply entrenched within organizations' systems architectures? Its promise of scale, speed, and delivery, that is — and Kubernetes isn't going anywhere any time soon.
DZone's fifth annual Kubernetes in the Enterprise Trend Report dives further into the nuances and evolving requirements for the now 10-year-old platform. Our original research explored topics like architectural evolutions in Kubernetes, emerging cloud security threats, advancements in Kubernetes monitoring and observability, the impact and influence of AI, and more, results from which are featured in the research findings.
As we celebrate a decade of Kubernetes, we also look toward ushering in its future, discovering how developers and other Kubernetes practitioners are guiding the industry toward a new era. In the report, you'll find insights like these from several of our community experts; these practitioners guide essential discussions around mitigating the Kubernetes threat landscape, observability lessons learned from running Kubernetes, considerations for effective AI/ML Kubernetes deployments, and much more.
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Cloud
kubernetes
Enterprise Security
Reinforcing Enterprise Application Defense
Security is everywhere: Behind every highly performant application, or even detected threat, there is a powerful security system and set of processes implemented. And in the off chance there are NOT such systems in place, that fact will quickly make itself known. We are living in an entirely new world, where bad actors are growing more and more sophisticated the moment we make ourselves "comfortable." So how do you remain hypervigilant in this ever so treacherous environment?
DZone's annual Enterprise Security Trend Report has you covered. The research and expert articles explore the fastest emerging techniques and nuances in the security space, diving into key topics like CSPM, full-stack security practices and challenges, SBOMs and DevSecOps for secure software supply chains, threat hunting, secrets management, zero-trust security, and more. It's time to expand your organization's tactics and put any future attackers in their place as you hear from industry leaders and experts on how they are facing these challenges in everyday scenarios — because if there is one thing we know about the cyberspace, any vulnerabilities left to chance will always be exposed.
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Security
security
Database Systems
Modernization for Data-Driven Architectures
In 2024, the focus around databases is on their ability to scale and perform in modern data architectures. It's not just centered on distributed, cloud-centric data environments anymore, but rather on databases built and managed in a way that allows them to be used optimally in advanced applications. This modernization of database architectures allows for developers and organizations to be more flexible with their data. With the advancements in automation and the proliferation of artificial intelligence, the way data capabilities and databases are built, managed, and scaled has evolved at an exponential rate.
This Trend Report explores database adoption and advancements, including how to leverage time series databases for analytics, why developers should use PostgreSQL, modern, real-time streaming architectures, database automation techniques for DevOps, how to take an AI-focused pivot within database systems practices, and more. The goal of this Trend Report is to equip developers and IT professionals with tried-and-true practices alongside forward-looking industry insights to allow them to modernize and future-proof their database architectures.
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Database
databases
Low-Code Development
Elevating the Engineering Experience With No and Low Code
Low code, no code, citizen development, AI automation, scalability — if you work in the tech world, it's likely that you have been encouraged to use tools in at least one of these spaces. And it's for a good reason as Gartner has projected that by 2025, 70% of applications developed within organizations will have been built using low- and/or no-code technologies. So does the practice live up to the hype?
Year over year, the answer is a resounding "yes" as the industry continues to evolve. Organizations have an increased demand for more frequent application releases and updates, and with that comes the need for increased efficiencies. And this is where low-code and no-code development practices shine. Sprinkle AI automation into low- and no-code development, and the scalability opportunities are endless.
This Trend Report covers the evolving landscape of low- and no-code development by providing a technical exploration of integration techniques into current development processes, the role AI plays in relation to low- and no-code development, governance, intelligent automated testing, and adoption challenges. In addition to findings from our original research, technical experts from the DZone Community contributed articles addressing important topics in the low code space, including scalability, citizen development, process automation, and much more. To ensure that you, the developer, can focus on higher priorities, this Trend Report aims to provide all the tools needed to successfully leverage low code in your tech stack.
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Web Dev
low code, no code, automation, low code development
Cloud Native
Championing Cloud Development Across the SDLC
Cloud native has been deeply entrenched in organizations for years now, yet it remains an evolving and innovative solution across the software development industry. Organizations rely on a cloud-centric state of development that allows their applications to remain resilient and scalable in this ever-changing landscape. Amidst market concerns, tool sprawl, and the increased need for cost optimization, there are few conversations more important today than those around cloud-native efficacy at organizations.
Google Cloud breaks down "cloud native" into five primary pillars: containers and orchestration, microservices, DevOps, and CI/CD. For DZone's 2024 Cloud Native Trend Report, we further explored these pillars, focusing our research on learning how nuanced technology and methodologies are driving the vision for what cloud native means and entails today. The articles, contributed by experts in the DZone Community, bring the pillars into conversation via topics such as automating the cloud through orchestration and AI, using shift left to improve delivery and strengthen security, surviving observability challenges, and strategizing cost optimizations.
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Cloud
cloud native
Modern API Management
Connecting Data-Driven Architectures Alongside AI, Automation, and Microservices
When assessing prominent topics across DZone — and the software engineering space more broadly — it simply felt incomplete to conduct research on the larger impacts of data and the cloud without talking about such a crucial component of modern software architectures: APIs . Communication is key in an era when applications and data capabilities are growing increasingly complex. Therefore, we set our sights on investigating the emerging ways in which data that would otherwise be isolated can better integrate with and work alongside other app components and across systems.
For DZone's 2024 Modern API Management Trend Report, we focused our research specifically on APIs' growing influence across domains, prevalent paradigms and implementation techniques, security strategies, AI, and automation. Alongside observations from our original research, practicing tech professionals from the DZone Community contributed articles addressing key topics in the API space, including automated API generation via no and low code; communication architecture design among systems, APIs, and microservices; GraphQL vs. REST; and the role of APIs in the modern cloud-native landscape.
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Integration
api
Enterprise AI
The Emerging Landscape of Knowledge Engineering
Artificial intelligence (AI) has continued to change the way the world views what is technologically possible. Moving from theoretical to implementable, the emergence of technologies like ChatGPT allowed users of all backgrounds to leverage the power of AI. Now, companies across the globe are taking a deeper dive into their own AI and machine learning (ML) capabilities; they’re measuring the modes of success needed to become truly AI-driven, moving beyond baseline business intelligence goals and expanding to more innovative uses in areas such as security, automation, and performance.
In DZone’s Enterprise AI Trend Report, we take a pulse on the industry nearly a year after the ChatGPT phenomenon and evaluate where individuals and their organizations stand today. Through our original research that forms the “Key Research Findings” and articles written by technical experts in the DZone Community, readers will find insights on topics like ethical AI, MLOps, generative AI, large language models, and much more.
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AI
ai
The Modern DevOps Lifecycle
Shifting CI/CD and Application Architectures
While DevOps is here to stay, as the years pass, we must continuously assess and seek improvements to our existing software processes, systems, and culture — and DevOps is no exception to that rule. With business needs and customer demands constantly shifting, so must our technology, mindsets, and architecture in order to keep pace.
Now is the time for this movement that's all about "shifting left" to essentially shift.
In our annual DevOps Trend Report, we explore both its fundamental principles as well as the emerging topics, methodologies, and challenges surrounding the engineering ecosystem. Within our "Key Research Findings" and featured articles from our expert community members, readers will find information on core DevOps topics as well as new insights on what's next for DevOps in 2024 and beyond. Join us to learn about the state of CI/CD pipelines, the impact of technical debt, patterns for supply chain management<>DevOps, the rise of platform engineering, and even more!
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DevOps
devops
Security
security
Observability and Application Performance
Building Resilient Systems
Making data-driven decisions, as well as business-critical and technical considerations, first comes down to the accuracy, depth, and usability of the data itself. To build the most performant and resilient applications, teams must stretch beyond monitoring into the world of data, telemetry, and observability. And as a result, you'll gain a far deeper understanding of system performance, enabling you to tackle key challenges that arise from the distributed, modular, and complex nature of modern technical environments.
Today, and moving into the future, it's no longer about monitoring logs, metrics, and traces alone — instead, it’s more deeply rooted in a performance-centric team culture, end-to-end monitoring and observability, and the thoughtful usage of data analytics.
In DZone's 2023 Observability and Application Performance Trend Report, we delve into emerging trends, covering everything from site reliability and app performance monitoring to observability maturity and AIOps, in our original research. Readers will also find insights from members of the DZone Community, who cover a selection of hand-picked topics, including the benefits and challenges of managing modern application performance, distributed cloud architecture considerations and design patterns for resiliency, observability vs. monitoring and how to practice both effectively, SRE team scalability, and more.
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Performance
performance, observability
Kubernetes in the Enterprise
Redefining the Container Ecosystem
Kubernetes: it’s everywhere . To fully capture or articulate the prevalence and far-reaching impacts of this monumental platform is no small task — from its initial aims to manage and orchestrate containers to the more nuanced techniques to scale deployments, leverage data and AI/ML capabilities, and manage observability and performance — it’s no wonder we, DZone, research and cover the Kubernetes ecosystem at great lengths each year.
In our 2023 Kubernetes in the Enterprise Trend Report, we further dive into Kubernetes over the last year, its core usages as well as emerging trends (and challenges), and what these all mean for our developer and tech community. Featured in this report are actionable observations from our original research, expert content written by members of the DZone Community, and other helpful resources to help you go forth in your organizations, projects, and repos with deeper knowledge of and skills for using Kubernetes.
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Cloud
kubernetes
Data Pipelines
Investigating the Modern Data Stack
Enter the modern data stack: a technology stack designed and equipped with cutting-edge tools and services to ingest, store, and process data. No longer are we using data only to drive business decisions; we are entering a new era where cloud-based systems and tools are at the heart of data processing and analytics. Data-centric tools and techniques — like warehouses and lakes, ETL/ELT, observability, and real-time analytics — are democratizing the data we collect. The proliferation of and growing emphasis on data democratization results in increased and nuanced ways in which data platforms can be used. And of course, by extension, they also empower users to make data-driven decisions with confidence.
In our 2023 Data Pipelines Trend Report, we further explore these shifts and improved capabilities, featuring findings from DZone-original research and expert articles written by practitioners from the DZone Community. Our contributors cover hand-picked topics like data-driven design and architecture, data observability, and data integration models and techniques.
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Big Data
data pipelines
Database Systems
Architecture Advancements and Data Storage Reimagined
This data-forward, analytics-driven world would be lost without its database and data storage solutions. As more organizations continue to transition their software to cloud-based systems, the growing demand for database innovation and enhancements has climbed to novel heights. We are upon a new era of the "Modern Database," where databases must both store data and ensure that data is prepped and primed securely for insights and analytics, integrity and quality, and microservices and cloud-based architectures.
In our 2023 Database Systems Trend Report, we explore these database trends, assess current strategies and challenges, and provide forward-looking assessments of the database technologies most commonly used today. Further, readers will find insightful articles — written by several of our very own DZone Community experts — that cover hand-selected topics, including what "good" database design is, database monitoring and observability, and how to navigate the realm of cloud databases.
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Database
databases
DevOps
automated testing, test automation
Web Dev
web dev, low code, automation, java, javascript, web app development, mobile app development, no code, workflow automation, technical debt
Cloud
container adoption, containers, containerization, microservices, container management, container security, containerized applications
Integration
integration, api, api integration, microservices apis, integration architecture, cloud integration, microservice integration
DevOps
CI/CD, Application Delivery, and Release Orchestration
The DevOps movement has paved the way for CI/CD and streamlined application delivery and release orchestration. These nuanced methodologies have not only increased the scale and speed at which we release software, but also redistributed responsibilities onto the developer and led to innovation and automation throughout the SDLC.
DZone's 2023 DevOps: CI/CD, Application Delivery, and Release Orchestration Trend Report explores these derivatives of DevOps by diving into how AIOps and MLOps practices affect CI/CD, the proper way to build an effective CI/CD pipeline, strategies for source code management and branching for GitOps and CI/CD, and more. Our research builds on previous years with its focus on the challenges of CI/CD, a responsibility assessment, and the impact of release strategies, to name a few. The goal of this Trend Report is to provide developers with the information they need to further innovate on their integration and delivery pipelines.
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DevOps
devops, ci/cd, application release orchestration, application release automation, continuous delivery, continuous deployment, continuous integration, aiops, gitops, iac
Enterprise Application Security
Building Secure and Resilient Applications
Data breaches, ransomware attacks, and other security vulnerabilities have become the norm in recent years. Hackers have become shrewder. And with that, development teams bear the responsibility of ensuring that all stages of the SDLC have strong security.
DZone's 2022 Trend Report, Enterprise Application Security: Building Secure and Resilient Applications , focuses on key factors of security practices including supply chain security, principles of zero-trust security, how to secure mobile applications, common DevSecOps practices, and what to do after your organization experiences a security breach. Our research dives into sentiments on perceived application security risks, development techniques for securing applications, and where the role of security lies for teams within today's organizational structures. The goal of this Trend Report is to equip developers with the tools, best practices, and advice they need to help implement security at every stage of the SDLC.
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Security
application security, security, zero trust, microservices security, security breaches, mobile security, cloud security, security and defense, security challenges, secrets management
Performance and Site Reliability
Observability for Distributed Systems
The concept of observability was first leveraged over 110 years ago. It was initially known as telemetry, and in 1912, it used the city of Chicago’s telephone lines to transmit data from the electric power plants to a central control station. Today, modern observability is still very much focused on the interplay of data to yield informed inputs and outputs of systems. Sprinkle in site reliability engineering (SRE), and there should be little to no performance issues in distributed systems, right? In an ideal world, yes, but in reality, there is still work to be done.
DZone’s 2022 Trend Report, Performance and Site Reliability: Observability for Distributed Systems , takes a holistic view of where developers stand in their observability practices. Through the research and expert-contributed articles, it offers a primer on distributed systems observability, including how to build an open-source observability toolchain, dives into distributed tracing, and takes a look at prospective performance degradation patterns. It also provides insight into how to create an SRE practice, as well as tactics to conduct an effective incident retrospective. The goal of this Trend Report is to offer a developer-focused assessment of what the current state of observability is and how it fits in with modern performance practices.
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Performance
application performance, monitoring, site reliability, observability, distributed tracing, performance degradation, site reliability engineering, performance management, performance analysis, distributed systems
Cloud
kubernetes, kubernetes architecture, kubernetes deployments, kubernetes environment, kubernetes implementation, kubernetes infrastructure, kubernetes monitoring, kubernetes performance, kubernetes patterns, kubernetes scaling
Database Systems
Strategies for Migration, Management, and Data Quality
Every modern application and organization collects data. With that, there is a constant demand for database systems to expand, scale, and take on more responsibilities. Database architectures have become more complex, and as a result, there are more implementation choices. An effective database management system allows for quick access to database queries, and an organization can efficiently make informed decisions. So how does one effectively scale a database system and not sacrifice its quality?
Our Database Systems Trend Report offers answers to this question by providing industry insights into database management selection and evaluation criteria. It also explores database management patterns for microservices, relational database migration strategies, time series compression algorithms and their applications, advice for the best data governing practices, and more. The goal of this report is to set up organizations for scaling success.
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Database
databases, database systems, data management, cloud database, data consistency, data quality, dbms, database migration, database trends, relational database
Microservices
microservice architecture, containerization, container environments, container orchestration, microservice adoption, microservice design, distributed applications, microservices performance, container security, microservices communication
Web Dev
low code, no code, low code automation, low code development, release automation, low code programming, low code challenges
Data Pipelines
Ingestion, Warehousing, and Processing
Data is at the center of everything we do. As each day passes, more and more of it is collected. With that, there’s a need to improve how we accept, store, and interpret it. What role do data pipelines play in the software profession? How are data pipelines designed? What are some common data pipeline challenges? These are just a few of the questions we address in our research.
In DZone’s 2022 Trend Report, "Data Pipelines: Ingestion, Warehousing, and Processing," we review the key components of a data pipeline, explore the differences between ETL, ELT, and reverse ETL, propose solutions to common data pipeline design challenges, dive into engineered decision intelligence, and provide an assessment on the best way to modernize testing with data synthesis. The goal of this Trend Report is to provide insights into and recommendations for the best ways to accept, store, and interpret data.
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Big Data
big data, data pipelines, data warehouse, data analytics, data architecture, data security, data lake, etl, elt, data storage
Integration
integration, application integration, enterprise application, api, apis, graphql, rest api
DevOps
devops, ci/cd, ci/cd pipeline, application release orchestration, application release automation, continuous delivery, continuous deployment, continuous development, continuous integration, continuous integration and deployment
Enterprise AI
Machine Learning, Design Paradigms, and Operational Impact
In recent years, artificial intelligence has become less of a buzzword and more of an adopted process across the enterprise. With that, there is a growing need to increase operational efficiency as customer demands arise. AI platforms have become increasingly more sophisticated, and there has become the need to establish guidelines and ownership.
In DZone's 2022 Enterprise AI Trend Report, we explore MLOps, explainability, and how to select the best AI platform for your business. We also share a tutorial on how to create a machine learning service using Spring Boot, and how to deploy AI with an event-driven platform. The goal of this Trend Report is to better inform the developer audience on practical tools and design paradigms, new technologies, and the overall operational impact of AI within the business.
This is a technology space that's constantly shifting and evolving. As part of our December 2022 re-launch, we've added new articles pertaining to knowledge graphs, a solutions directory for popular AI tools, and more.
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AI
ai, machine learning, artificial intelligence, explainability, mlops
Application Performance Management
As enterprise applications increasingly adopt distributed systems and cloud-based architectures, the complexity of application performance management (APM) has grown accordingly. To address this new set of challenges, traditional APM is making a push towards intelligent automation (AIOps), self-healing applications, and a convergence of ITOps and DevOps.
DZone’s 2021 Application Performance Management Trend Report dives deeper into the management of application performance in distributed systems, including observability, intelligent monitoring, and rapid, automated remediation. It also provides an overview of how to choose an APM tool provider, common practices for self-healing, and how to manage pain points that distributed cloud-based architectures cause. Through research and thoughtfully curated articles, this Trend Report offers a current assessment of where real enterprises are in their journey to design APM approaches for modern architectures.
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Performance
application performance management, apm, application performance, distributed systems, observability, monitoring
Cloud
kubernetes, enterprise kubernetes
Security
application security, appsec
Low-Code Development
Empowering Business Users, Enabling Developers
Development speed, engineering capacity, and technical skills are among the most prevalent bottlenecks for teams tasked with modernizing legacy codebases and innovating new solutions. In response, an explosion of “low-code” solutions has promised to mitigate such challenges by abstracting software development to a high-level visual or scripting language used to build integrations, automate processes, construct UI, and more. While many tools aim to democratize development by reducing the required skills, others seek to enhance developer productivity by eliminating needs such as custom code for boilerplate app components.
Over the last decade, the concept of low code has matured into a category of viable solutions that are expected to be incorporated within mainstream application development. In this Trend Report, DZone examines advances in the low-code space, including developers' perceptions of low-code solutions, various use cases and adoption trends, and strategies for successful integration of these tools into existing development processes.
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Web Dev
low code development, low-code, no-code and low-code options, no code development, application development
DevOps
ci cd, continuous integration, continuous delivery, continuous deployment, devops, devsecops, pipeline management, automation
Cloud
containers, container adoption, containerized applications, container configuration, container challenges, container implementation, container management, container performance, container monitoring, container platform
Web Dev
web development
Integration
api, api management, api design, rest api
Data Persistence
At the core of every modern application is an endless, diverse stream of data and with it, an inherent demand for scalability, increased speed, higher performance, and strengthened security. Although data management tools and strategies have matured rapidly in recent years, the complexity of architectural and implementation choices has intensified as well, creating unique challenges — and opportunities — for those who are designing data-intensive applications.
DZone’s 2021 Data Persistence Trend Report examines the current state of the industry, with a specific focus on effective tools and strategies for data storage and persistence. Featured in this report are observations and analyses of survey results from our research, as well as an interview with industry leader Jenny Tsai-Smith. Readers will also find contributor insights written by DZone community members, who cover topics ranging from microservice polyglot persistence scenarios to data storage solutions and the Materialized Path pattern. Read on to learn more!
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Database
data persistence, database management system, dbms, database tools, data management, polyglot persistence, relational databases, tree structure, database research, database trends
IoT
edge computing, edge architecture, internet of things, edge data collection, cloud computing, trend report, survey findings
Cloud
kubernetes, containers, k8s, docker
Data Warehousing
Data warehousing has become an absolute must in today’s fast-paced, data-driven, modern business landscape. As the demand for informed business decisions and analytics continues to skyrocket, data warehouses are gaining in popularity, especially as more and more businesses adopt cloud-based data warehouses.
DZone’s 2020 Data Warehousing Trend Report explores data warehouse adoption across industries, including key challenges, cloud storage, and common data tools such as data lakes, data virtualization, and ETL/ELT. In this report, readers will find original research, an exclusive interview with "the father of data warehousing," and additional resources with helpful tips, best practices, and more.
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Big Data
data warehousing, big data, analytics, cloud, hybrid
Database
database, sql, nosql, big data, trends, graph database
DevOps
continuous testing, testing automation, automated testing, testing trends, test automation, test automation framework, test data management, test data management strategy, testing best practices
Performance
apm, application performance monitoring, site reliability engineering, aiops, performance engineering, performance trends
DevOps
ci/cd, continuous integration, devops, pipeline management, continuous delivery
Big Data
big data, analytics, dashboards, data visualization, machine learning
Database
database security, sql server, data security breach, cloud
Cloud
cloud (add topic), cloud native, microservices, serverless architecture, container management
Cloud
kubernetes, continuous integration, continuous delivery, container orchestration, cloud computing
DevOps
devops, devsecops, appsec, open source security, security automation
Web Dev
web developement
AI
ai, machine learning, python machine learning, what is machine learning
Microservices
microservices adoption, microservices
Cloud
kubernetes, container orchestration
DevOps
devops at scale, devops maturity
Integration
api management, integration
Security
security, application security