DZone Trend Reports and Guides provide expert thought leadership and survey insights into recent advancements in technology, how adoption of new tools or methodologies has grown over time, the challenges that exist in executing on the promises of these technologies, and what new advancements are on the horizon.
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.
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.
In 2022, Kubernetes has become a central component for containerized applications. And it is nowhere near its peak. In fact, based on our research, 94 percent of survey respondents believe that Kubernetes will be a bigger part of their system design over the next two to three years. With the expectations of Kubernetes becoming more entrenched into systems, what do the adoption and deployment methods look like compared to previous years?
DZone's Kubernetes in the Enterprise Trend Report provides insights into how developers are leveraging Kubernetes in their organizations. It focuses on the evolution of Kubernetes beyond container orchestration, advancements in Kubernetes observability, Kubernetes in AI and ML, and more. Our goal for this Trend Report is to help inspire developers to leverage Kubernetes in their own organizations.
Security | application security, security, zero trust, microservices security, security breaches, mobile security, cloud security, security and defense, security challenges, secrets management | |
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 | 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 | |
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 | |
AI | ai, machine learning, artificial intelligence, explainability, mlops | |
Performance | application performance management, apm, application performance, distributed systems, observability, monitoring | |
Cloud | kubernetes, enterprise kubernetes | |
Security | application security, appsec | |
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 | |
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 | |
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 |