Latest news with #Java-based
Techday NZ
a day ago
- Business
- Techday NZ
Java Independence is now a board-level priority - Driving cost savings, cloud efficiency and strategic agility
Chances are every time you stream content, buy something online or check your bank balance, you're interacting with Java-based systems. Java powers mission-critical systems across industries. Netflix runs its entire streaming infrastructure on Java-based microservices, processing millions of concurrent viewers. Global payment networks validate credit card transactions in milliseconds across hundreds of countries using Java applications. While the Java community has expanded to over 10 million developers worldwide, enterprises face mounting cost pressures from multiple directions. For the enterprises powering these essential services, 2025 represents a critical decision point: continue paying escalating costs for Oracle Java, potentially impacting profit margins or customer pricing as well as the potential for future price hikes, or seek alternatives. Java independence gives businesses control, choice, and confidence in how they build and run Java applications. Azul's recent 2025 State of Java Survey & Report reveals an enterprise Java ecosystem in transition, driven by mounting cost concerns, market preference for open-source solutions, and ongoing uncertainty around Oracle's licensing policies. This watershed moment stems from Oracle's shift to employee-based pricing in January 2023, which fundamentally disrupted enterprise Java strategy. Oracle's licensing practices have significantly increased Java-related expenditures, with the company generating billions annually from Java licensing and support. This shift isn't just about cost savings, it's about mitigating risk and enhancing agility. Java independence has become a board-level priority in an era where digital transformation drives market leadership. The oracle Java challenge The new Oracle pricing model detaches Java costs from actual usage, creating an unsustainable scenario: a 10,000-employee company running a handful of Java applications pays the same as a similarly sized organisation running thousands of Java-based services. For global businesses, this represents both a financial challenge and a strategic imperative to maintain competitive advantage. Our research reveals that two-thirds of organisations found Oracle's licensing model more expensive than alternatives, and an overwhelming majority reported successful migrations away from Oracle Java. With 25% of companies citing audit risk as a key migration driver, the urgency to transition has become a business priority rather than just an IT concern. The OpenJDK success story The success of OpenJDK adoption has shattered Oracle Java migration concerns. The data tells a compelling story: 84% of companies found the transition easier than expected or as planned, with three-quarters completing migrations within 12 months. This rapid timeline reflects both the maturity of available solutions and the robust support ecosystem around OpenJDK migrations. OpenJDK distributions have emerged as preferred alternatives to Oracle Java. These enterprise-ready solutions match Oracle Java SE's core capabilities while offering enhanced support and performance options. Successful migration hinges on three key components: Organisational momentum - Technical expertise, discovery & inventory tools and project planning assistance from a commercial OpenJDK provider can significantly help secure and maintain executive support, ultimately impacting a successful transition. Comprehensive Java mapping - Identifying all Java deployments across an organisation is essential. With 83% of organisations requiring commercially supported Java in production, this mapping phase is critical. Governance and compliance - Maintaining independence from Oracle Java licensing requires robust governance. Success means partnering with OpenJDK providers offering comprehensive protection, from IP safeguards to indemnification. The immediate financial benefits are substantial — most organisations report a 50-70% reduction in Oracle Java-related costs. Perhaps even more compelling, additional value lies in regaining control over Java technology strategy. Cloud cost optimisation Organisations are grappling with rapidly escalating cloud infrastructure costs, as annual global cloud spending is nearing a trillion dollars and continues to grow at double-digit rates. Our research reveals that 71% of organisations overpay for cloud compute capacity, highlighting an opportunity to reduce costs while improving application performance. Companies that select non-Oracle optimised Java platforms can save 20%+ on cloud computing costs. This is because high-performance Java runtimes deliver more stable Java applications and infrastructure while consuming fewer computing resources, creating compelling advantages beyond just licensing considerations. Powering AI innovation with Java Emerging technology demands amplify the need for change, particularly in AI and cloud computing. Half of the surveyed companies from our State of Java report already build AI functionality using Java — from financial institutions developing fraud detection systems to retailers leveraging machine learning for customer personalisation and inventory management. As computational demands grow, organisations require Java platforms that can deliver both performance and efficiency. These advanced workloads highlight the need for solutions that provide more scalable and stable applications while consuming fewer computing resources, enabling AI initiatives to be deployed successfully without excessive infrastructure investments. Oracle Java independence is not just a technical evolution — it's a strategic imperative that gives organisations the freedom to innovate, control costs, and build their technology future on their own terms.
Arabian Post
17-06-2025
- Arabian Post
LeetCode Java Solutions Gain Traction with Cleaner, Smarter Code
LeetCode's Java ecosystem is evolving beyond mere algorithmic correctness, with a growing emphasis on code quality metrics such as readability, maintainability, and performance profiling. Practitioners are advancing from writing bare-bones solutions to refining their work through rigorous complexity analysis and structured refactoring. LeetCode-in-Java, a prominent community resource hosting over 300 Java-based interview questions, lists the time complexity and space usage for each problem, aiding developers in benchmarking their approaches. But coding interviews today demand more than just a correct answer—they require holistic software design skills. A Medium feature on refactoring emphasises this shift, urging developers to assess time‑space complexity and then improve code clarity and structure post-solution. Industry voices critique LeetCode's environment for fostering overly optimized single‑run code that fails to reflect real‑world requirements. On Reddit, one experienced engineer noted many 'optimal' solutions are impractical for evolving specifications, urging a focus on maintainability over micro‑optimisation. As a result, echoing best practices from Java development, many practitioners now systematically refactor LeetCode solutions—using meaningful naming, extracting methods, avoiding magic constants, and de‑duplicating code, in line with recognized Java refactoring strategies. ADVERTISEMENT Empirical software‑engineering research reinforces the importance of such practices. A 2022 study tracking 785,000 Java methods found that maintaining routines under 24 lines significantly reduced maintenance effort. Similarly, classes named with suffixes like 'Utils' or 'Handler' were shown to harbour disproportionately high complexity—underlining the need for careful class design in production code. While LeetCode solutions may be small in scale, imbuing them with production‑grade discipline reflects professional development standards. When evaluating complexity, runtime benchmarks on LeetCode can mislead. As one software engineer commented via LinkedIn, the same code submission often records drastically different performance results—sometimes varying from top 9% to bottom 49%—making single-run statistics unreliable. The consensus is that complexity analysis should rely on theoretical Big‑O calculations and profiling tools, rather than on platform‑dependent runtime rankings. Leading Java‑centric LeetCode repositories, such as Stas Levin's 'LeetCode‑refactored,' offer annotated solutions that juxtapose common community code with clean‑code versions enhanced for readability and maintainability. These repositories emphasise abstractions that separate concerns and reflect developers' mental models—crucial traits for collaborative engineering. Comparing different practitioners' approaches highlights notable contrasts. Algorithm‑centric contributions typically deliver maximum efficiency but often sacrifice clarity. By contrast, clean‑code variants—extracted into discrete helper methods, elegantly named, and trimmed of magic numbers—raise maintainability, occasionally at the cost of some performance headroom. Experts recommend a balanced trade‑off: start with a correct algorithm, validate its complexity, then refactor iteratively, keeping an eye on time/space costs. Several improvement areas still persist. Developers often overlook test coverage when practising LeetCode, missing opportunities to adopt red‑green‑refactor cycles anchored in unit tests—best practice in professional Java work. In addition, object‑oriented design in LeetCode is rarely leveraged: functions are frequently static, bypassing opportunities to modularise logic into cohesive classes. Shared repository conventions like 'Utils' classes frequently miss cohesion standards, a warning echoed by empirical studies. Despite limitations in performance metrics, industry feedback indicates LeetCode remains valuable for demonstrating disciplined problem solving. Profiles of hiring managers show that, while they value clean and explainable code, technical interviews still often triage via algorithmic performance under time pressure, so balancing both dimensions is essential.
Technical.ly
15-02-2025
- Business
- Technical.ly
Big Data and Hadoop Developer Certification Training in Dover
Event Description Hadoop is an open-source, Java-based programming framework that continues the processing of large data sets in a distributed computing environment. It is based on the Google File System or GFS and Hadoop runs a few applications on distributed systems with thousands of nodes involving petabytes of information. Big Data Hadoop Developer Certification course is designed to prepare you for your next assignment in the world of Big Data. Hadoop is the market leader among Big Data Technologies and it is an important skill for every professional in this field. Big Data course also prepares you for the Cloudera CCA175 certification with simulation exams and real-life projects on CloudLabs. The Cloudera certification is the most sought-after Big Data certification in the industry. After completing the Reform Skills Hadoop training, you will be exam ready for the Cloudera certification and job-ready for your next Big Data Assignment. Key Features: 32 hours of instructor-led training 5 real-life industry projects in banking, telecom, insurance, and e-commerce domains 40 hours of Hands-on practice with CloudLabs 60 hours of project work Includes training on Yarn, MapReduce, Pig, Hive, Impala, HBase, and Apache Spark Exams fee included What is Big Data and Hadoop? Hadoop is an open-source, Java-based framework used for storing and processing big data. The data is stored on inexpensive commodity servers that run as clusters. Its distributed file system enables concurrent processing and fault tolerance. What is Big Data? It does not refer to a specific amount of data, but rather describes a dataset that cannot be stored or processed using traditional database software. Examples of big data include the Google search index, the database of Facebook user profiles, and product list. What is Hadoop? Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power, and the ability to handle virtually limitless concurrent tasks or jobs. Who needs to attend? Big Data career opportunities are on the rise, and Hadoop is quickly becoming a Must-know technology for the following professionals: Software Developers and Architects Analytics Professionals Data Management Professionals Business Intelligence Professionals Project Managers Aspiring Data Scientists Graduates looking to build a career in Big Data Analytics Anyone interested in Big Data Analytics What is this course about? After completing this course, you will be able to: Master the concepts of the Hadoop framework and its deployment in a cluster environment Understand how the Hadoop ecosystem fits in with the data processing lifecycle Learn to write complex MapReduce programs Describe how to ingest data using Sqoop and Flume Explain the process of distributing data using Spark Learn about Spark SQL, Graphx, MLlib List the best practices for data storage Explain how to model structured data as tables with Impala and Hive How to choose a data storage format for your data usage patterns WHY GLOBAL CORPORATES PREFER LEARNING ZONE INC AS THEIR TRAINING PARTNER A provider of Enterprise Learning Solutions (ELS), Learning Zone Inc creates industry-fit talents through training, coaching, and consulting by globally-acclaimed trainers. Much of Learning Zone's repute in co-creating business value stems from: Training delivered in 45+ countries. 250+ industry-relevant courses. Consulting and coaching to transform organizations. Trainers with experience in Retail, E-commerce, Energy & Utilities, etc. We stand out because Best value for time & money invested. Get trained at the best fee compared to other vendors Discounted fee offered for 5 and more attendees Training delivered by the industry expert Name: Debbie Riel
