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What Is Static Sentiment Analysis?

The third edition of UL 4600 was released in 2023 to add specific requirements for the use case of autonomous trucking and to address changing industry trends.

Here, we explain what’s happening in the autonomous trucking industry, why UL 4600 is important for autonomous trucking specifically, and how static analysis helps to overcome challenges for this evolving technology.

Read on or jump ahead to the section that interests you most:

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While some just dream of fleets of autonomous trucks efficiently delivering goods across the country, others are already at work to ensure they can do so safely and resiliently. With the update to ANSI/UL 4600, the Standards for Safety for the Evaluation of Autonomous Products, Edition 3, in play, embedded software teams now have better safety guidance just as self-driving technology is ramping up to make shipping faster, more cost-effective, and more efficient in the face of driver shortages and rising transportation costs.

Autonomous trucking software is on the cusp of widespread adoption. To prepare for the inevitable transition from closed-course testing to widespread deployment, OEMs need to understand the current state of trucking automation and how to effectively implement software safety practices.

What Is Autonomous Trucking?

Autonomous or driverless trucks operate with minimal to no human input. Instead, autonomous trucks or autonomous tractor-trailers rely on sensors — usually combinations of cameras, LiDAR, and radar — to feed environmental data into algorithms and actuators that control the vehicle.

The Society of Automotive Engineers (SAE) have defined levels of driving automation that are adopted across the industry, which range from Level 0 (completely manual) to Level 5 (completely autonomous). While the lower levels with an automated driving system (ADAS) are already in play for autonomous trucks, software development teams will need to ensure functional safety for the higher autonomy levels, ideally Levels 4 (High Automation) and 5 (Full Automation) for the freight industry to benefit from autonomous trucking.

Autonomous Trucking Development Today

Trucking is the dominant mode of inland freight transportation in many countries, with several trucking companies competing to be the first to operationalize autonomous driving. Driverless technologies offer significant potential value for fleet operators: They can reduce operating costs, overcome driver shortages, and improve efficiency.

For example, driverless semi trucks (or lorries) can employ truck platooning more effectively than human drivers, where vehicles follow each other at the same speed to improve fuel economy and reduce their impact on traffic.

While there have been a few setbacks in recent years — for example, TuSimple, Navistar and UPS shut down their “Driver-out” self-driving truck system in 2023 and Waymo, Embark and Locomation are no longer actively developing autonomous trucks — there are many more new entrants working toward wide-scale deployment:

Traditional OEMs are nearing full operationalization, with trucks already being tested in North America. In partnership with Aurora, Volvo revealed its first production-ready autonomous truck in May, and Daimler Truck reported that its Freightliner Cascadia semi-trucks are meeting closed-course acceptance tests in October of 2024.

These announcements indicate that the automotive industry is driving autonomous trucking plans forward — so software development teams in automotive manufacturing will need to get familiar with the challenges, solutions, best practices, and compliance with UL 4600 to ensure they are prepared for these exciting advancements.

Trucking Automation Software Challenges

There are five main challenges for teams developing autonomous trucking software:

It’s hard to reuse autonomous software built for cars.

The development and testing of self-driving cars focus on short, low-speed routes with stop-and-go traffic. In contrast, autonomous trucks will operate on long-haul highway routes at higher speeds and will encounter less traffic, more variable terrain, and transitions between urban and rural roads.

More critically, a Class 8 driverless semi-truck has a gross vehicle weight eight times that of the average passenger vehicle — before loading its cargo. This means autonomous driving software has to account for a larger turn radius, longer stopping distances, and the presence of a trailer that can weigh as much as 14,000 U.S. pounds unloaded.

Software has to handle many use cases.

Trucking automation software must accommodate different vehicle classes, cargo conditions, and route types. While some fleets deliver consumer packaged goods within cities, most autonomous trucks are particularly good for long distances, which will need to be accounted for in the software. Still others transport hazardous, refrigerated, or liquid materials across international borders.

There is also the scalability factor: To build and test multiple branches of software to handle various scenarios at scale, developers should design systems to accommodate a wide range of input and control conditions before deploying them into real-world trucking environments.

Verification and validation require long highway driving.

Once acceptance tests are performed on closed-loop circuits, autonomous trucks must conduct road tests on highways, ideally for hundreds of miles across the country. That way, developers can ensure their autonomous trucks can cover the distances, runtime, and road conditions necessary for the long haul. The U.S. Department of Energy reports that the average semi-truck travels over 62,000 miles annually.

Security must be a top priority.

Similar to their automotive counterparts, driverless trucks must address the following security concerns:

  • Protect connected infrastructure and endpoints such that there is acommon baseline of trust between nodes.
  • Track and adapt to vulnerabilities that will continue to grow as malicious actors realize new opportunities to attack and destabilize critical trucking networks.
  • Secure the manufacturing supply chain with vendors who may not have had to deal with software security before.
  • Comply with cybersecurity regulations and best practices, such as ISO/SAE 21434.

Safety compliance must be accounted for.

Safety will be the key differentiator between manufacturers that make it to market and those stuck in verification and validation activities. Fully unmanned trucks operating at highway speeds present real concerns, including difficulty in handling unexpected situations and decision-making capabilities, in addition to more typical concerns about undefined behaviors and software malfunctions.

The challenges of developing safe trucking automation systems lie in their components. Everything from sensors to decision-making algorithms to vehicle motion control must be scrutinized. Given this complexity, manufacturers will find themselves relying on automated tools, like Perforce Static Analysis, to help with UL 4600 compliance.

Understanding UL 4600: Safety Principles and Processes for Autonomous Trucking

UL 4600 is the first safety standard designed specifically for autonomous and connected vehicles. Unlike a traditional UL satefy standard, UL 4600 takes a “safety case” approach with real-world applications in a specific environment — and the inclusion of autonomous trucks in UL 4600 Edition 3 includes trucking-specific examples. The standard helps developers build a safety case for carious aspects of system development and maintenance:

“It offers framework that leads designers of autonomous systems through the required thought process to ensure all possible complications have been considered. What are the safety questions that need to be considered in design? How do you think beyond design and for the lifecycle of the vehicle? Can quality and consistency be assured across manufacturers?

— Dr. David Steel, Executive Director of UL Standards & Engagement, ULSE, Inc.

The UL 4600 Edition 3 standard requires developers to follow a three-step approach for assessing and validating driverless truck safety:

  1. Make a measurable safety claim, where developers state how the autonomous truck should operate.
  2. Make an argument that proves the claim is true by describing the perception technologies and the systems that are triggered by them.
  3. Provide evidence that the system will perform as expected by providing simulation results, road test outcomes, and other proof that the autonomous truck will perform as stated.

The end result is a safety case arguing that an exceptionally robust combination of analysis, simulation, closed course testing, and public road testing have been performed — with evidence given — to ensure an appropriate level of system safety.

How Static Analysis Helps Achieve Autonomous Truck Safety

There is a specific requirement in UL 4600 for coding standard compliance, as the development process should be similar to that of IEC 61508 or ISO 26262, so developers should use static analysis to some degree and produce the results of source code analysis. Static code analyzers — like Perforce Helix QAC and Klocwork — support these goals by ensuring comprehensive code coverage and sufficient supporting evidence in these areas:

Amid the pressure of getting driverless trucks to market, these tools enable developers to focus on feature development rather than compliance activities.

About Perforce
The best run DevOps teams in the world choose Perforce. Perforce products are purpose-built to develop, build and maintain high-stakes applications. Companies can finally manage complexity, achieve speed without compromise, improve security and compliance, and run their DevOps toolchains with full integrity. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce is trusted by the world’s leading brands to deliver solutions to even the toughest challenges. Accelerate technology delivery, with no shortcuts.

About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.

Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.

What Is Static Sentiment Analysis?

What Is Sentiment Analysis?

Sentiment analysis takes large volumes of data and uses natural language processing (NLP) to determine whether a body of text has a positive, negative, or neutral sentiment.

There are three main approaches to sentiment analysis:

  • Rules-based techniques: A group of words (lexicons) are classified in terms of tone. For example, a positive lexicon might include “secure” and “compliant,” while a negative lexicon might contain “insecure” and “non-compliant.”
  • Machine learning (ML)-based techniques: These techniques use algorithms trained to determine sentiment based on words appearing in blocks of text and the order in which they appear. The ML learns and improves as more data is ingested.
  • Hybrid techniques: This combines rules-based and ML approaches to balance speed and accuracy based on the use case.

In a talk by Perforce Principal Software Engineer Alex Celeste at Embedded World, Celeste introduced the concept of static sentiment analysis, which combines sentiment analysis and static analysis.

What Is Static Sentiment Analysis?

Static sentiment analysis takes the concept of sentiment analysis and combines it with static analysis. Static sentiment analysis uses machine learning (a small-language model) to analyze code and determine developer intent.

In other words, static sentiment analysis could determine whether the code does what a developer meant for it to do.

As artificial intelligence and machine learning technologies advance, they can help automate the software development process by adding a new dimension to testing and save development teams time and effort.

More on Static Sentiment Analysis 

Explore how static sentiment analysis works, its benefits, and how static sentiment analysis complements static analysis best practices in our new eBook.

Challenges of Traditional Testing in Software Development

Traditional software testing isn’t enough in today’s complex digital landscape, especially with the introduction of AI and ML.

Manual testing and manual code reviews slow down the development cycle and introduce a higher risk of human error. Currently, teams using static analysis tools — like Perforce Helix QAC and Klocwork — are automating the process by detecting bugs, code vulnerabilities, and compliance issues early in development.

But while traditional techniques like static analysis perform well against “hard” criteria like syntax errors, buffer overflows, and quantifiable rules in coding standards, they can miss “soft” criteria like developer intent. That’s where static sentiment analysis comes in.

Developers may soon be able to bridge the gap between intent and implementation by taking a static sentiment analysis approach.

How Does Static Sentiment Analysis Work?

Static sentiment analysis analyzes an abstract representation of code to determine if a test section is significantly different from a reference sample in the same code base. These differences could be changes in a developer’s style, code clarity, or misapplied design patterns.

A successful static sentiment analysis would not just detect the pattern of the structure — it would need to identify instances where the test section is sufficiently different from a reference sample and raise a flag.

To break it down further, static sentiment analysis determines the mathematical distance between the entropy of a test feature and a reference sample. The distance measures the similarity between features, and entropy evaluates the feature’s information. A significant increase in the distance between features indicates an unexpected change in style, which may require further investigation.

How Static Analysis and Machine Learning Level Up DevOps Workflows

The promise of static sentiment analysis allows developers to identify where developer intent went amiss in code and better fulfill the needs of customers and industry standards.

While static sentiment analysis is still in the research phase, static analysis is currently helping DevOps teams shift left and increase developer productivity.

Static code analyzers Helix QAC and Klocwork help reduce technical debt by:

  • Finding and fixing coding issues earlier
  • Improving overall software quality
  • Quickly inspecting millions of lines of source code (legacy and new code)
  • Enforcing coding standards compliance
  • Prioritizing risk and analysis results.

With the introduction of static sentiment analysis, DevOps teams could even further level up their workflows by also automatically checking for instances where developer intent may have been missed — greatly reducing the time and effort required for exhaustive functional testing.

In the meantime, there’s a lot you can do to level up now. See for yourself how Perforce Static Analysis helps accelerate development. Sign up for your free 7-day trial today.

About Perforce
The best run DevOps teams in the world choose Perforce. Perforce products are purpose-built to develop, build and maintain high-stakes applications. Companies can finally manage complexity, achieve speed without compromise, improve security and compliance, and run their DevOps toolchains with full integrity. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce is trusted by the world’s leading brands to deliver solutions to even the toughest challenges. Accelerate technology delivery, with no shortcuts.

About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.

Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.

Perforce’s Helix Core Now ISO 26262 Certified for Functional Safety in Automotive Development

Perforce matches functional safety with the software and design driven world of automotive today. 

MINNEAPOLIS, OCTOBER 29, 2024 — Perforce Software, a global provider of enterprise DevOps solutions, today announced its version control platform Helix Core has achieved ISO 26262 Functional Safety Process Certification by internationally-accredited certification body TÜV SÜD. With this certification, Perforce ensures its platform meets the strict safety and reliability standards required for developing automotive systems and reinforces its commitment to supporting innovation within the automotive industry.

Perforce Helix Core is the version control platform trusted by leading automotive OEMs and suppliers – as well as the world’s largest semiconductor firms, embedded systems developers, and top gaming and media studios – for limitless scalability, fine-grained security, and rapid file access from anywhere in the world.

ISO 26262 is an international functional safety standard for the development of electrical and electronic systems, including hardware and software components, for road vehicles. By certifying its version control platform is ISO 26262 compliant, Perforce now makes this critical solution available to all organizations that need to prove compliance with the highest safety, quality, and reliability standards.

“With the transition to software-defined vehicles and the rise of autonomy, automotive OEMs and suppliers are revolutionizing their development pipeline with modern tools that accelerate innovation, yet safety remains paramount,” said Brad Hart, CTO and VP of Product Management at Perforce. “Helix Core offers a modern alternative to legacy tools that can no longer meet the demands of today’s fast-paced software- and design-driven automotive development. For large, cross-functional, globally distributed teams, Helix Core is the only version control solution that can deliver the speed, scale, and security necessary to manage all digital assets, including binary code and large game engine/3D files.”

Perforce’s 2024 State of Game Technology survey found that 50% of respondents are now using game engines outside of traditional game development, such as in the creation of digital twins of vehicles. These digital twins can enhance vehicle safety in many ways, from virtual crash tests to using simulated driving scenarios to more efficiently train Advanced Driver Assistance Systems (ADAS). With Helix Core serving as an essential foundation to effectively leverage this technology, achieving the ISO 26262 Functional Safety Process Certification allows Perforce to offer a platform that drives innovation while ensuring the highest level of automotive safety.

About Perforce
The best run DevOps teams in the world choose Perforce. Perforce products are purpose-built to develop, build and maintain high-stakes applications. Companies can finally manage complexity, achieve speed without compromise, improve security and compliance, and run their DevOps toolchains with full integrity. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce is trusted by the world’s leading brands to deliver solutions to even the toughest challenges. Accelerate technology delivery, with no shortcuts.

About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.

Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.

Perforce Announces Hadoop Service Bundle – a New Open Source Big Data Management Offering

AUSTIN, Texas, October 15, 2024 —Perforce Software, the DevOps company for global teams requiring speed, quality, security and compliance at scale along the development lifecycle, announced its AI-driven strategy during the DevOps + Data Impact event. The strategy covers four AI-driven pillars across the testing lifecycle: test creation, execution, analysis and maintenance, across all main environments: web, mobile and packaged applications. The result would remove traditional testing barriers to help testing teams achieve new levels of agility, reliability, and breakthrough advancements.

The amount of talent in the testing space as well as the overall continued practice of manual testing — according to Forrester’s Developer Survey, 2023, 43% of testing is still done with manual practices — cannot keep pace with the quality and security needed in the testing space. To compound this, by 2028 IDC predicts that there will be over one billion new logical applications*.

“Test maintenance continues to be a huge burden for organizations and can lead to outdated tests and slower releases,” said Melinda-Carol Ballou, Research Director at IDC. “Building on earlier investments within the testing industry, we’ve seen a great uptick in AI and Machine Learning as key technologies that can greatly improve this area of development, including potential for increased efficiency, time and cost savings and business execution.”

Perforce’s vision for AI in software testing aims to democratize software testing by enabling testers of every skill level on every team. It will lead to simplified test creation, faster debugging, enhanced collaboration, and the elimination of test maintenance.

“What we aim to deliver is not just leveraging AI to augment and improve the way testers work today, but we are implementing AI testing that completely changes the way testing works within a business,” said Stephen Feloney, Vice President of Product Management at Perforce. “There are two core areas that we are revolutionizing in testing that we know teams will find immediate value in. First, is the reduction of the traditional tools and elimination of frameworks to make testing infinitely more flexible. Secondly, we want to create full automation of test maintenance, which continues to be a blocker to efficient testing and faster releases. Testers should focus on developing test cases instead of worrying about creating and maintaining automated scripts.”

This vision for continuous testing by Perforce will be comprised of four key pillars:

  1. AI-Driven Testing Creation: Eliminates the need for traditional testing frameworks and empowers every team member to contribute seamlessly, accelerating test creation timelines.
  2. AI-Driven Test Execution: AI autonomously adapts to real-time changes, ensuring resilience and consistency across all platforms without manual intervention.
  3. AI-Driven Test Analysis: Provides immediate insights into test failures, pinpointing the root cause to enable faster resolution and continuous optimization.
  4. AI-Driven Test Maintenance: Eliminates manual test maintenance by continuously adapting to UI, data, or logic changes, ensuring your testing suite is resilient and future-proof.

Perforce’s continuous testing suite offers AI currently with Test Data Pro, which provides test data generation powered by AI.

Source:*IDC, 1 Billion New Logical Applications: More Background, doc #US51953724, April 2024

Resources

About Perforce
The best run DevOps teams in the world choose Perforce. Perforce products are purpose-built to develop, build and maintain high-stakes applications. Companies can finally manage complexity, achieve speed without compromise, improve security and compliance, and run their DevOps toolchains with full integrity. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce is trusted by the world’s leading brands to deliver solutions to even the toughest challenges. Accelerate technology delivery, with no shortcuts.

About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.

Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.

Weighing the Value of Apache Hadoop vs. Cloudera

As the Big Data landscape has changed, comparing Apache Hadoop vs. Cloudera and their commercial platform is a worthwhile exercise. Do enterprise teams still need Cloudera for their Big Data stack management or can they save by independently managing their Apache Hadoop implementation?

In this blog, we’ll take a close look at the value of the Cloudera platform’s software bundle, proprietary tools, and cloud-hosting services. We’ll also explore Cloudera alternativesfor organizations that would prefer to not migrate to the cloud and want the freedom to decide where and how to manage their data infrastructure. 

Note: In this blog, references to the Cloudera platform are meant to encompass both the Cloudera Data Platform (CDP) and the legacy product, Cloudera Distribution of Hadoop (CDH).

Apache Hadoop vs. Cloudera: What’s the Difference?

Apache Hadoop is a free, open source data-processing technology that uses a network of computers to solve large data computation via the MapReduce programming model. Cloudera offers a commercial, Hadoop-based platform that is available via paid subscription.

The Cloudera platform is based on Apache Hadoop and various other software packages that, by and large, are part of the broader Apache Hadoop ecosystem. Therefore, many of the features and functions of Cloudera’s platform are available for free via the collection of those foundational open source software packages. 

When customers pay for a Cloudera subscription, they are essentially paying for:

  • A curated bundle of the open source software packages and specific versions that have been validated and proven to work together.
  • A couple of proprietary (not open source) applications that provide conveniences intended to help adopters manage an implementation of these disparate open source software packages.
  • A hosted managed services provider that unites it all in a controlled environment with the promise of stability, availability, and carefree maintenance.

While valuable for some enterprise use cases, these benefits come at a price — particularly the last one, as cloud migrations can be expensive. Because the Big Data landscape is continuously evolving with new solutions coming on the market all the time, it is a good practice to regularly evaluate the return on investment of those features against the cost of managing an equivalent open source stack. 

In the next few sections, we’ll dig deeper into the three bullets mentioned above and compare them to the free equivalents in Apache Hadoop.

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1. Cloudera’s Curated Bundle of OSS

When the Hadoop Ecosystem was an emerging technology, it was beneficial to have a leader in the space like Cloudera piecing together and testing a set of immature open source technologies that were under active development. Cloudera made it so individual companies did not have to dedicate development resources to keep pace with many independently evolving software releases and ensure there were no breaking changes at all the integration points. This can be particularly painful for early adopters, as there are rarely standards or best practices in place to allow product features to evolve independently. Without standards, the products are more tightly coupled and implementations must be more closely managed. 

The situation today, however, is very different. For example, many products now rely on JSON or YAML as the agreed-upon data exchange formats, but those were not in place 20 years ago. Data formats like Parquet and Avro take this a step further. Likewise, there are best practices around RESTful API versioning that many products now implement — and the list goes on. So what would have been very burdensome and resource-draining when Hadoop first emerged is considerably more feasible these days because standards and best practices have caught up. 

This is not to say a controlled and validated environment isn’t a good thing. It just might not deliver as much ROI for organizations as it once did. Furthermore, one must reevaluate being locked into a bundle vs. having flexibility now that more innovative and impactful technologies are available. Specifically, there are a couple of foundational areas where Apache Hadoop has made considerable advancements compared to what you get with the Cloudera implementation of Hadoop, and that’s what we will cover next. 

Execution Services: Oozie vs. Airflow

At a time when more modern organizations are moving toward Apache Airflow for workflow, Cloudera is still shipping with, and relying on, Apache Oozie. Apache Oozie workflows are tied to the Hadoop ecosystem and require unwieldy XML-based definitions. In contrast, Apache Airflow is a more modern, flexible, and scalable workflow and data pipeline management tool that integrates well with cloud services and various systems beyond Hadoop. It has a friendly user interface, a strong community, and advanced error handling. 

Security Services: Navigator & Sentry vs. Atlas & Ranger 

Modern Apache Hadoop implementations use a combination of Apache Atlas and Apache Ranger. Both of these products achieve significant improvements over the legacy Navigator and Sentry. Atlas will be covered again later when highlighting data governance. Apache Ranger has a more user-friendly web-based interface that makes it easier to create and manage security policies. Unlike Sentry, Ranger includes built-in robust auditing capabilities for tracking events and activities across the platform, even outside of Hadoop proper.

To be fair, Cloudera is migrating to these improved options as well, but they are not there yet — leaving CDP implementers saddled with the complexity of a combined solution but unable to benefit from the full set of new features.

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2. Cloudera’s Proprietary Tools for Cluster Management, Cluster Administration, and Data Governance

Cloudera ships two proprietary applications, Cloudera Manager and Cloudera Navigator, to provide implementors with a toolkit for managing and administering their Hadoop Cluster. These applications are essential in offering a cohesive, professional, and useful Hadoop-based Big Data platform. 

However, there are open source alternatives that meet or beat the features available in these proprietary tools. In fact, the most predominant open source versions of these tools were originally developed in the open and handed over to the Apache Foundation by Hortonworks — a company that was purchased by Cloudera in 2019. 

Cloudera Manager vs. Ambari

Cloudera Manager is an administrative application for the Cloudera Data Platform (CDP). It has a web-based user interface and a programmatic API, and is used to provision, configure, manage, and monitor CDP-based Hadoop clusters and associated services.

Apache Hadoop implementors use Apache Ambari (a project with Hortonworks origins) to accomplish what is offered through Cloudera Manager on CDP Hadoop implementations. Apache Ambari has a web-based user interface and a programmatic REST API that allows organizations to provision, manage, and administer Hadoop clusters and associated services.

To take a deeper dive and learn more about the nuanced differences between these tools, see my previous blog: Apache Ambari vs Cloudera Manager. 

Cloudera Navigator vs. Apache Atlas

Cloudera Navigator handles data governance. It offers a wide range of features for auditing and compliance, from organization policy creation and tracking to regulatory requirements like GDPR and HIPPA. It also includes data lineage tracking to look back upon data transformation and evolution, as well as metadata management for tagging and categorizing data to assist in searching and filtering.

Apache Hadoop implementors use Apache Atlas (also originally developed by Hortonworks) to implement data governance and metadata management. Cloudera Navigator is only applicable to CDP, whereas Apache Atlas works across a broad range of Hadoop distributions and data ecosystems. It is extensible and integrates with other packages, like Apache Hive and Apache HBase.

Apache Atlas logs creation, modification, access, and lineage information about each data asset. It tracks who has accessed or modified data to provide an audit trail for compliance and monitoring purposes. Policies can be defined in Atlas to manage role-based access control (RBAC), attribute-based access control (ABAC), and data masking. To enforce these policies, Atlas integrates with Apache Ranger (another open source package in the Hadoop ecosystem).

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3. Cloudera’s Cloud-Hosting Environment and Managed Services

Measuring the value of where the infrastructure resides will likely be more of a policy question for most organizations. Most organizations have a preference or a requirement that dictates whether they host services in public, private, on-premises, or hybrid clouds. So the real assessment here lies more in the value aligned with the managed services offered by Cloudera. For organizations that are not required to manage and own their own infrastructure, and don’t mind paying for these managed services, this may tip the scales in Cloudera’s favor. 

However, organizations that don’t want to be forced to the cloud should consider whether they have the talent, motivation, and capacity to own and maintain an Apache Hadoop implementation. The maturity of the Hadoop ecosystem and the availability of standardized cloud resources make this a viable alternative to Cloudera — but only if you have the internal resources or a partner like OpenLogic with deep Apache Hadoop expertise.

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Other Considerations 

We outlined some key differences in cluster execution services, cluster security, cluster administration, and data governance between Apache Hadoop and CDP. However, there are a number of other features and functions that are nearly identical for both of these platforms that will require installation, configuration, care, and feeding. These include products like Zookeeper for cluster coordination, and a number of data services that can be applied to meet various needs of an organization. These include, but are not limited to, HDFS, MapReduce, Yarn, Apache Spark, Apache Kafka, HBase, Hive, and Hue.

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Final Thoughts

There was a time when it was easier to associate a clear value for the dollar spend on Cloudera. They were pioneers in Big Data and offered the first commercial bundle of Hadoop. They were the Hadoop provider for many of the Fortune 500 firms. The Cloudera Platform could speed time to market, providing a clear path to a stable Big Data environment that allowed implementers to focus on creating domain-specific applications that leveraged their data — rather than juggling between managing a data platform and making use of their data.

However, nearly two decades have passed since the first incarnation of Hadoop. Cloudera has been involved for over 15 years, and a lot has changed. Hadoop has matured dramatically, and the supporting ecosystem has grown. New open source solutions are being developed all the time, as well as new commercial offerings around Big Data services and support. While there is still an appetite for hands-off, fully managed Big Data platforms like the one that Cloudera offers, the price has driven demand for lower-cost alternatives. For some organizations, using Apache Hadoop and avoiding a costly cloud migration is priceless.  

About Perforce
The best run DevOps teams in the world choose Perforce. Perforce products are purpose-built to develop, build and maintain high-stakes applications. Companies can finally manage complexity, achieve speed without compromise, improve security and compliance, and run their DevOps toolchains with full integrity. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce is trusted by the world’s leading brands to deliver solutions to even the toughest challenges. Accelerate technology delivery, with no shortcuts.

About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.

Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.

What’s Coming in CentOS Stream 10

Information about CentOS Stream 10 has been trickling in since ISOs first became available in June. CentOS Stream 10 will be based on Fedora 40 and released sometime ahead of RHEL 10, but the current images are still in testing/development and could very well change between now and the actual release. 

So what do we know about CentOS Stream 10? Our expert weighs in and offers considerations for enterprise teams considering CentOS Stream for production workloads.

CentOS Stream Project Update 

CentOS Stream has an interesting history, with some notable developments in the past few years. After announcing in 2020 that CentOS Linux would be discontinued in favor of focusing on CentOS Stream, last year Red Hat ruffled more feathers by announcing that CentOS Stream would become the sole repository for RHEL source code. CentOS Stream 8, the first release, reached end of life in May 2024; CentOS Stream 9 has been out since 2021. 

On June 6, 2024, the CentOS Project posted links to the CentOS Stream 10 compose images, install ISOs, and container images with the following message: “Please note the compose is still taking shape. Packages are still being added and even removed at this point. Not all packages are fully onboarded to gating, so just some updates are landing. Packages are being moved between repositories. Comps groups are being updated…” Developers were encouraged to test and share feedback.

In other words, much is still to be determined. New ISOs have been made available periodically since the June announcement (as of this writing, the last batch dropped on October 22, 2024). 

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CentOS Stream vs. CentOS Linux

The main difference between CentOS Stream and CentOS Linux is that CentOS Stream is upstream of RHEL, with packages planned for upcoming releases, and CentOS Linux is a rebuild of the current RHEL release.

Another key difference is how updates are made in the two distributions. For CentOS Linux, new minor versions consist of large batches of updates, with smaller updates between versions. Rather than batch updates, packages in CentOS Stream are updated as they are ready, in a continuous stream, and there are no minor versions. 

Before all versions reached end of life, CentOS Linux had a community support lifecycle of ten years, like RHEL and many other Enterprise Linux distributions. CentOS Stream has a shorter lifecycle of five years, with EOL based on when the corresponding RHEL release leaves Full Support and enters its Maintenance Phase (security updates only). 

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How Long Will CentOS Stream 9 Be Supported?

CentOS Stream 9 will be supported until May 31, 2027, when RHEL 9 leaves Full Support.  

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CentOS Stream 10 Release Date

CentOS Stream is upstream of RHEL and all signs point to the RHEL 10 GA release sometime in the first half of 2025, so the CentOS Stream 10 release is anticipated in late 2024 or early 2025. 

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Notable Changes in CentOS Stream 10 

  • Kernel: CentOS Stream 10 will be using a 6.11-based kernel, rather than 5.14 that CentOS Stream 9 used.
  • Programming language support/compilers: CentOS Stream 10 has GCC 14.2.1 (instead of GCC 11.5), and Python 3.12 (instead of Python 3.9).
  • CPU compatibility and capabilities: one user encountered a warning message that that x86_64-v3 will be required at a minimum in the future, but as of now it is just a deprecation warning.
  • Performance: Phoronix ran some benchmarks, and a thorough comparison of performance is available here. That is for Arm64 instead of x86_64, but should still be comparable.

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Using CentOS Stream in Production

There is some debate over whether enterprises should use CentOS Stream in production. Some say the rolling release model makes it too unstable and that it’s more of a ” beta testing ground” for features, or a preview of the next version of RHEL (though not everything in Stream may make it into RHEL). Red Hat explicitly says that CentOS Stream “is not designed for production use in enterprise environments” and recommends using RHEL as a CentOS alternative.

However, depending on your use case, using CentOS Stream for production workloads may not present any issues. Some teams like that Stream gives them access to bug fixes and new features before they become available in RHEL. The notion that CentOS Stream is fundamentally less stable or reliable than RHEL is not really accurate, as everything in Stream undergoes QA and testing, and has been accepted for the next minor RHEL release before being merged into Stream.  

The main difference between RHEL and CentOS Stream comes down to commercial support and services that RHEL provides to its paying subscribers.  

Still, a lot depends on your particular use case and infrastructure to determine whether or not CentOS Stream is the right fit. 

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CentOS Stream 10 Migration and Upgrade Considerations

As usual, you will want to test thoroughly before upgrading important systems. The new kernel version may not support older hardware, and with x86_64-v3 coming in the future, some older hardware may not work at all. Information about glibc-hwcaps can be found here. RHEL 9 did the same with x86_64-v2 and a simple test under Proxmox using x86-64-v2-AES produced a kernel panic during just an install, but x86-64-v3 succeeded.

With a new kernel, glibc, gcc, Python, and other changes, some existing software may not have library versions available to run the older version. Containers or VMs could mitigate the problem, however.

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What to Expect from Future CentOS Stream Releases

In future CentOS Stream releases, you can expect continuous upgrades of packages, with new versions, security patches, and performance improvements. Future releases may introduce new features, such as updated kernels, newer versions of programming languages, and support for emerging hardware or software trends.

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Final Thoughts 

CentOS Stream 10 gives us insight into what is likely to be included in the next version of RHEL — the first major release in four years. As to whether CentOS Stream 10 is a viable alternative to CentOS Linux or the best Linux distro for your organization, I recommend checking out this CentOS Stream checklist for guidance. 

It’s always a good idea to have technical support for your mission-critical workloads, and ideally, to work with experts who have full stack expertise to troubleshoot issues with updates and integrations. If you decide to use a FOSS Linux OS, it’s wise to pair it with commercial support from OpenLogic so you always have immediate access to Enterprise Architects. 

About Perforce
The best run DevOps teams in the world choose Perforce. Perforce products are purpose-built to develop, build and maintain high-stakes applications. Companies can finally manage complexity, achieve speed without compromise, improve security and compliance, and run their DevOps toolchains with full integrity. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce is trusted by the world’s leading brands to deliver solutions to even the toughest challenges. Accelerate technology delivery, with no shortcuts.

About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.

Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.

Solving Complex Kafka Issues: Enterprise Case Studies

Apache Kafka issues, especially for enterprises running Kafka at scale, can escalate quickly and bring operations to a halt. The open source community may be able to offer assistance, but in some situations, you need a resolution fast. 

While some organizations partner with OpenLogic for ongoing, SLA-backed Kafka support, our Professional Services team gets involved when a customer who does not have a support contract needs a consultation or help troubleshooting an issue with their Kafka deployments. These engagements can last anywhere from a few days to a few weeks, depending on the scope and complexity of the project. 

In this blog, we present four Kafka case studies with details on what the Kafka issue was and how OpenLogic solved it. 

Case Study #1: Large Internet Marketing Firm

Background: This customer was tracking clickstream events to measure ad campaign success. Their large bare metal implementation contained 48 nodes, and was processing roughly 5.8 million messages per second with 1-2 second end-to-end latency.

The Issue: LeaderAndIsr requests were failing during rolling restarts, resulting in multiple leader epochs with stale zkVersions.

The Solution: OpenLogic identified an existing bug that had not been fixed in the version of Kafka they were using, which had a higher likelihood of occurring during resource contention on the Zookeeper instance co-located on five of the Kafka nodes. They recommended upgrading the Kafka cluster and running Kafka on Zookeeper on independent nodes, which fixed the issue. 

Length of Engagement: 5 days 

 

Case Study #2: Large South American Bank

Background: This customer was currently utilizing IBM MQ and not hitting the performance metrics they desired. They were having to deal with large messages at high volume.

The Issue: Due to slow response times with end-to-end latency and total throughput with large messages, the customer wanted to move to Kafka to have a streaming-focused messaging bus.

The Solution: OpenLogic provided architecture using the Saga pattern with Apache Kafka and Apache Camel for managing long-running actions, such as crediting a payment on a loan from cash deposited at a branch. They also provided architecture for using Kafka with log shipping and the ELK stack, as well as for bridging events from IBM API Connect Cloud to Elasticsearch index behind the firewall using Apache Kafka. Finally, OpenLogic led a 5-day Apache Camel training to a team of 15 people so they could learn how to create Kafka consumers and producers.

Length of Engagement: 27 days 

Related Video: Apache Kafka Best Practices 

 

Case Study #3: U.S. Aerospace Firm

Background: Originally this customer wanted help with Rancher and moving from a VM-based Kafka cluster. They were utilizing a web socket server that was responsible for collecting satellite location data in real time. The web socket server could not talk directly with Kafka, and so they had developed a Camel-based system for their original Kafka cluster. They did not have any metrics collected on the existing cluster and could not identify the root cause for message delays and lag. 

The Issue: Performance issues with pub/sub relay application that consumed from websockets from domain-specific appliance and published to Kafka queues.

The Solution: OpenLogic implemented Rancher clusters dedicated to running the Strimzi operator and serving Kafka clusters. They were also able to improve throughput dramatically by moving existing Java code to Apache Camel with vertx driver. 

OpenLogic created metrics with Prometheus and Grafana in both the Camel websocket relay application and the Kafka brokers to determine replication and processing lag, and put monitoring in place to alert on topics that didn’t meet SLAs. Once metrics collection with Grafana and Prometheus were put in place, existing bottlenecks became identifiable and addressing them drastically improved end-to-end performance.

Length of Engagement: 3 days 

Case Study #4: Global Financial Services Company

Background: Customer came to OpenLogic with a security concern with Kafka Connect that violated PCI compliance as well as internal security standards.

The Issue: Sensitive information was included in stack traces with Kafka Connect.

The Solution: OpenLogic created a test harness, which was sanitized so that customer information was not present, that reproduced the bug. They filed a bug against the project and attached the test harness – and wrote the code that resolved the bug. OpenLogic then submitted the code to the community and worked with community to modify the PR to meet the community’s standards. Finally, they informed the customer when the bug was accepted and estimated which release was likely to include the fix for it. As a result, this K.I.P. was produced from the engagement.

Length of Engagement: 20 days 

Final Thoughts

Apache Kafka is an extremely powerful event streaming platform, but when things go wrong, they go wrong at scale. These Kafka case studies illustrate the benefits of having direct access to Enterprise Architects with deep Kafka expertise in those moments when every minute counts. 

About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.

Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.

About Perforce
The best run DevOps teams in the world choose Perforce. Perforce products are purpose-built to develop, build and maintain high-stakes applications. Companies can finally manage complexity, achieve speed without compromise, improve security and compliance, and run their DevOps toolchains with full integrity. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce is trusted by the world’s leading brands to deliver solutions to even the toughest challenges. Accelerate technology delivery, with no shortcuts.

Perforce Announces Same-Day Support for iOS 18

Perfecto by Perforce provides same-day support for iOS 18 mobile application testing –helping customers prepare their applications for the major release.

 

MINNEAPOLIS, Monday, September 16, 2024 – Perforce Software, a global leader in DevOps solutions, announces that its mobile application testing platform, Perfecto, will support Apple’s latest iOS version, iOS 18, on Monday, September 16, 2024. 

By enabling same-day mobile application testing support for iOS 18 and the new iPhone 16 series—scheduled for release on September 20, 2024—Perfecto encourages app developers and testing teams to prepare their applications to handle the latest iOS version and iPhone devices as soon as they become available. Since most iPhone users upgrade their devices immediately upon release, apps must be ready to handle the change. 

Research from Cambridge Judge Business School has shown that software failures cost enterprise organizations $61 billion annually.

“It is critical that testing and development teams prepare their applications for the latest release on day one,” says Clinton Sprauve, Director of Product Marketing at Perforce. “We are proud to offer day-one support for both the iOS 18 release and the iPhone 16 series in our device cloud.” 

With both beta testing and day-one testing support for the latest operating systems and devices, Perfecto has always enabled customers to prepare their applications ahead of time, keeping them free from bugs or glitches and saving resources and reputation. 

Developers and testing teams will need to test their applications against a host of new features arriving with the release of iOS 18 and the iPhone 16 series, including new customizable home screens, a redesigned photos app, email and note transcription services, message scheduling, and AI-powered features like Image Playground, Genmojis, and the upcoming Apple Intelligence, a beta version of which will be released with the iOS 18.1 update in October. 

Perfecto has consistently been ahead of the curve when it comes to same-day support for new releases—going back to 2007 with the first iPhone release—and continues that trajectory of innovation with the release of iOS 18. The iOS 18 release marks the seventeenth year that Perfecto is supporting a release on day one.

Perfecto’s cloud-based testing lab supports thousands of devices (real and virtual), operating systems, and browsers across the globe. To see the comprehensive list of supported platforms, visit http://www.perfecto.io/supported-devices. 

About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.

Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.

About Perforce
The best run DevOps teams in the world choose Perforce. Perforce products are purpose-built to develop, build and maintain high-stakes applications. Companies can finally manage complexity, achieve speed without compromise, improve security and compliance, and run their DevOps toolchains with full integrity. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce is trusted by the world’s leading brands to deliver solutions to even the toughest challenges. Accelerate technology delivery, with no shortcuts.

Exploring the Differences Between Community FOSS, Open Core, and Commercial OSS

Understanding the differences between community open source, open core, and commercial open source software is important when making choices that lay the foundation for systems and applications, as these decisions can have cascading effects on costs and flexibility for internal users and/or downstream customers.

In this blog, we break down the key differences between these three categories of open source software, and we’ll share some important considerations for teams deploying OSS both internal and external to the enterprise.

Editor’s Note: This blog was originally published in 2019 and was substantially updated and revised in 2024.

What Is Community Open Source Software?

Community open source software, also known as Free and Open Source Software (FOSS), is source code owned by a group of volunteers that have organized around a shared problem. Community open source projects are free and open to the public, and they’re bound by a permissive or restrictive license.

Related resource:How Does Open Source Licensing Work?

Open source communities bring people with shared interests together to collaboratively build something. Some of the most popular and widely used community open source projects are backed by nonprofit foundations such as the Apache Foundation, Linux Foundation, or Cloud Native Computing Foundation. Foundations add an air of legitimacy and garner inherent trust among users who might otherwise worry about adopting software built by a disparate cohort of individual contributors.

There are millions of FOSS projects but in the 2024 State of Open Source Report, respondents mentioned Linux, Jakarta EE, Apache Server, Docker, Kubernetes, PHP, WordPress, Python, PostgreSQL, MySQL, Kafka, and Eclipse IDE as among the most business-critical for enterprise. 

FOSS logos

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What Is Open Core Software?

Open core is a commercial model of software delivery where a company creates (or contributes heavily) to a “core” version of open source software, allowing users to freely adopt, adapt, and distribute it under an open source license, and then wraps that core version with advanced features, extensions, or enterprise-level scaling and availability under a proprietary license.  

This approach allows a company to leverage the collaborative nature of open source to build a community around the free version, which benefits from diverse contributions and widespread adoption. At the same time, they generate revenue by monetizing premium features aimed at larger organizations. This sometimes quickens time-to-market for a more commercially sustainable product.

Examples of open core software include Cloudera Data Platform, Oracle Linux, SUSE Linux, Redis, Grafana, Confluent Kafka, MongoDB, and GitLab.

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What Is Commercial Open Source Software?

Commercial open source vendors provide professional services for fully open source software. All features and functionality of that software remain open and freely available, and the company generates revenue through consulting, hosting, and support. 

Like open core, the commercial open source software approach benefits from the community-built software as a foundation. Although COSS companies likely contribute to the software, they don’t license their contributions separately. Instead, they provide value to their customers by professionalizing the implementation and adoption phases. 

RHEL and Rancher by SUSE are examples of COSS.

Get the Latest State of Open Source Report

The State of Open Source Report includes insights, analysis, and trends from a global survey of OSS users working in industries like finance, technology, retail, manufacturing, government, and more.

Download

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A Note About Open Source Definitions

The above definitions draw clean lines for the purposes of comparing and contrasting open source models; however, some companies employ multiple models across their portfolio. As companies grow and add products, this gets more prolific. In some cases, the lines drawn between these models (particularly COSS and open core) become progressively more gray.

A good example would be Red Hat Enterprise Linux, which is sold under a proprietary license; however, it is made up of code from two upstream open source products (Fedora and CentOS Stream). In this case, it borrows from the open core model, but there isn’t a true single free version that it extends.

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How to Choose Between Community Open Source, Open Core, and COSS 

All these options are based on the open source model, so they all have the potential to benefit from the power of a collaborative and transparent development process. When compared to proprietary internal development or purchased vendor software, all these OSS models can fundamentally reduce cost and time-to-market, while increasing security, stability, and innovation.

With each of these open models, there are costs. The cost of commercial options, either open core or COSS, are more obvious, and come in the form of license fees, maintenance contracts, hosting costs, support subscriptions, and consulting services. However, Free and Open Source Software (FOSS) also has associated costs that are more hidden. Adopting FOSS requires organizations to dedicate internal staff and infrastructure to hiring, acquiring, and maintaining the skills necessary to install, configure, upgrade, and contribute to sustainable development of the free-to-use software. It’s important to not forget about these shadow costs when considering FOSS for enterprise use cases.

The “F” in FOSS stands for free as in freedom, not absence of cost.

Knowing there are costs associated with all options may help organizations focus on the value and predictability of each of those costs. 

Here are some questions that can help steer an organization toward a defensible return on the investment:

  • What features are included in the commercial edition? Do I need those features? Are there alternatives that can achieve the same result?
  • What license(s) are associated with the software? Are they permissive, restrictive, or proprietary?
  • Does my organization have the skill and bandwidth to implement, maintain, and support the product?
  • How mature is the product and the backing community or commercial support vendor?
  • Is there a single commercial vendor that can serve all my open source software needs?

The table below illustrates, at a high level, some of the benefits and drawbacks worth considering: 

Type of Software

Benefits

Drawbacks

FOSS

  • Ability to try various solutions without vendor lock-in, thus a low-stakes entry
  • Information is shared readily within the community
  • Responsiveness of the community for patches and potential vulnerabilities
  • OSS can lack funding to maintain the software and fix security vulnerabilities
  • It may only provide a partial solution for your requirements
  • Integrating multiple OSS products can be challenging

Open Core

  • Often more regular updates and patches
  • SLA-backed support options, up to 24/7 for mission-critical services
  • Legal indemnification and liability during crises
  • Vendor lock-in can happen based on reliance on enterprise features
  • License changes could restrict your use
  • Restricted contribution models can diminish the value of the community
  • Could encounter a liability risk if the product is not upgraded
  • Enterprise features, hosting, and monitoring can be costly

COSS

  • SLA-backed support options, up to 24/7 for mission-critical services
  • Legal indemnification and liability during crises
  • Maintain full value of the community model
  • Value of expert knowledge when you need it, without the associated cost when you don’t
  • Adoption of additional complimentary FOSS packages may be required to achieve Open Core equivalent feature sets

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Final Thoughts

The decision to choose community open source software vs. open core or commercial open source software comes down to the depth and breadth of the projects, budgets, and use cases, as well as the scale of the environment(s).  There are situations where it makes sense to invest in commercial backing for open source development and other times when it might be better to implement a community-based solution. The three models outlined in this article layout a spectrum options that cover most needs.

Perhaps the most fundamental consideration is whether to:

  1. Spend valuable internal staff time on the installation, configuration, troubleshooting, training, maintenance, and support of the OSS that lays the foundation for the applications needed to deliver value to the business or downstream customers
    or
  2. Engage a vendor to ensure the organization has a secure, stable, and performant platform that enables internal staff to focus their time and energy on developing and maintaining domain expertise in delivering top quality applications needed to drive value for the business or downstream customers.

About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.

Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.

About Perforce
The best run DevOps teams in the world choose Perforce. Perforce products are purpose-built to develop, build and maintain high-stakes applications. Companies can finally manage complexity, achieve speed without compromise, improve security and compliance, and run their DevOps toolchains with full integrity. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce is trusted by the world’s leading brands to deliver solutions to even the toughest challenges. Accelerate technology delivery, with no shortcuts.

Perforce Announces Hadoop Service Bundle – a New Open Source Big Data Management Offering

MINNEAPOLIS, OCTOBER 1, 2024 – Perforce Software, the DevOps company for global teams requiring speed, quality, security and compliance at scale along the development lifecycle, today announced the Hadoop Service Bundle, a new professional services and support offering from OpenLogic by Perforce. 

This new solution offers enterprises a way to reduce Big Data management costs up to 60% by deploying an open source software-based Big Data stack and storing their data on-premises, in a public cloud, or a hybrid environment instead of in Cloudera’s Hadoop-based, public cloud platform.

“The Hadoop Service Bundle unlocks more options for enterprise organizations that want to own their Big Data infrastructure,” said Matthew Weier O’Phinney, Senior Product Manager at Perforce Software. “The Hadoop ecosystem has matured to the point where we can build a completely open source stack that is equivalent to the platform that Cloudera sells.”

In light of the fact that many Hadoop teams have invested in commercial, private cloud options to keep their most sensitive data secure, the Hadoop Service Bundle offers flexibility around where data is hosted. “No one should be forced to migrate to the public cloud if they don’t want to,” said Weier O’Phinney.

As part of the Hadoop Service Bundle, OpenLogic will oversee the base installation, data migration, and reference installation of customers’ Hadoop instances. For those organizations without the internal expertise required to fully manage a Hadoop implementation, technical support and administration is also included in the Hadoop Service Bundle.

Whereas the Cloudera Data Platform comes with a preset suite of software, the Hadoop Service Bundle allows teams to decide which tools and technologies to include in their Big Data stack based on their use case, potentially reducing deployment overhead.

“The Big Data landscape has evolved dramatically in recent years and the demand for more customizable, cost-effective solutions is what led us to develop the Hadoop Service Bundle,” said Rod Cope, Chief Technology Officer at Perforce Software. “For organizations that want to avoid vendor lock-in and keep costs low by storing their data in-house, in an open source stack built to accommodate their business needs, the Hadoop Service Bundle will be an appealing alternative.”

About Version 2 Limited
Version 2 Digital is one of the most dynamic IT companies in Asia. The company distributes a wide range of IT products across various areas including cyber security, cloud, data protection, end points, infrastructures, system monitoring, storage, networking, business productivity and communication products.

Through an extensive network of channels, point of sales, resellers, and partnership companies, Version 2 offers quality products and services which are highly acclaimed in the market. Its customers cover a wide spectrum which include Global 1000 enterprises, regional listed companies, different vertical industries, public utilities, Government, a vast number of successful SMEs, and consumers in various Asian cities.

About Perforce
The best run DevOps teams in the world choose Perforce. Perforce products are purpose-built to develop, build and maintain high-stakes applications. Companies can finally manage complexity, achieve speed without compromise, improve security and compliance, and run their DevOps toolchains with full integrity. With a global footprint spanning more than 80 countries and including over 75% of the Fortune 100, Perforce is trusted by the world’s leading brands to deliver solutions to even the toughest challenges. Accelerate technology delivery, with no shortcuts.