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Exam Number : PCCET
Exam Name : Palo Alto Networks Certified Cybersecurity Entry-level Technician
Vendor Name : Palo-Alto
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PCCET Exam Format | PCCET Course Contents | PCCET Course Outline | PCCET Exam Syllabus | PCCET Exam Objectives


EXAM CODE: PCCET

EXAM NAME: Palo Alto Networks Certified Cybersecurity Entry Level Technician (PCCET)



The PCCET certification is the first of its kind. It is aligned with the NIST/NICE (National Institute of Standards and Technology/National Initiative for Cybersecurity Education) workforce framework, designed to cover foundational knowledge of industry-recognized cybersecurity and network security concepts as well as various cutting-edge advancements across all Palo Alto Networks technologies.



Main Areas covered by Questions;

Fundamentals of Cybersecurity 30%

Network Security Components 30%

Cloud Technologies 20%

Elements of Security Operations 20%



Domain 1 Fundamentals of Cybersecurity 30%

Topic 1.1 Distinguish between Web 2.0 and 3.0 applications and services

Topic 1.2 Describe port-scanning methodologies and their impact

1.2.1 Nonstandard ports

1.2.2 Identify applications by their port number

Topic 1.3 Recognize applications used to circumvent port-based firewalls

Topic 1.4 Differentiate between common cloud computing service models

1.4.1 SaaS

1.4.2 PaaS

1.4.3 IaaS

Topic 1.5 Describe the business processes of supply-chain management

Topic 1.6 Describe the vulnerabilities associated with data being stored in the SaaS environment

1.6.1 Describe roles within a SaaS environment

1.6.2 Describe security controls for SaaS applications

Topic 1.7 Describe the impact of governance, regulation, and compliance

1.7.1 Differentiate between compliance and security

1.7.2 Identify major cybersecurity laws and their implications

Topic 1.8 Describe the tactics of the MITRE ATT&CK framework

1.8.1 Identify a leading indicator of a compromise

1.8.2 Describe how to use CVE

1.8.3 Describe how to use CVS

Topic 1.9 Identify the different attacker profiles and motivations

1.9.1 Describe the different value levels of the information that needs to be protected (political, financial, etc.)

Topic 1.10 Describe the different phases and events of the cyberattack lifecycle

1.10.1 Describe the purpose of command and control (C2)

Topic 1.11 Identify the characteristics, capabilities, and appropriate actions for different types of malware and ransomware

Topic 1.12 Differentiate between vulnerabilities and exploits

1.12.1 Differentiate between various business email compromise attacks

1.12.2 Identify different methodologies for social engineering

1.12.3 Identify the chain of events that result from social engineering

Topic 1.13 Identify what chain of events follows an attack

Topic 1.14 Differentiate between the functional aspects of bots and botnets

1.14.1 Describe the type of IoT devices that are part of a botnet attack

Topic 1.15 Differentiate the TCP/IP roles in DDoS attacks

1.15.1 Differentiate between DoS and DDoS

Topic 1.16 Describe advanced persistent threats

Topic 1.17 Describe risks with Wi-Fi networks

1.17.1 Differentiate between common types of Wi-Fi attacks

1.17.2 Describe how to monitor your Wi-Fi network

Topic 1.18 Describe perimeter-based network security

1.18.1 Identify the types of devices used in perimeter defense

Topic 1.19 Describe the Demilitarized Zone (DMZ)

Topic 1.20 Describe the transition from a trusted network to an untrusted network

1.20.1 Differentiate between North-South and East-West zones

Topic 1.21 Describe Zero Trust

1.21.1 Identify the benefits of the Zero Trust model

1.21.2 Identify the design principles for Zero Trust

1.21.3 Describe a microperimeter

1.21.4 Differentiate between Trust and Untrust zones

Topic 1.22 Describe the integration of services for network, endpoint, and cloud

Topic 1.23 Identify the capabilities of an effective Security Operating Platform

1.23.1 Describe the components of the Security Operating Platform

Domain 2 Network Security Components 30%

Topic 2.1 Differentiate between hubs, switches, and routers

2.1.1 Given a network diagram, Identify the icons for hubs, switches, and routers

Topic 2.2 Describe the use of VLANs

Topic 2.3 Differentiate between routed and routing protocols

Topic 2.4 Differentiate between static and dynamic routing protocols

2.4.1 Differentiate between link state and distance vector

Topic 2.5 Identify the borders of collision and broadcast domains

Topic 2.6 Differentiate between different types of area networks

2.6.1 WAN

2.6.2 LAN

Topic 2.7 Describe the advantages of SD-WAN

Topic 2.8 Describe the purpose of the Domain Name System (DNS)

2.8.1 Describe how DNS record types are used

2.8.2 Identify a fully qualified domain name (FQDN)

2.8.3 Describe the DNS hierarchy

Topic 2.9 Differentiate between categories of IoT devices

2.9.1 Identify the known security risks and solutions associated with IoT

Topic 2.10 Identify IoT connectivity technologies

Topic 2.11 Differentiate between IPv4 and IPv6 addresses

2.11.1 Describe binary-to-decimal conversion

2.11.2 Describe IPv4 CIDR notation

2.11.3 Describe IPv4 classful subnetting

2.11.4 Given a scenario, identify the proper subnet mask

2.11.5 Describe the purpose of subnetting

2.11.6 Describe the structure of IPv4 and IPv6

2.11.7 Describe the purpose of IPv4 and IPv6 addressing

Topic 2.12 Describe the purpose of a default gateway

Topic 2.13 Describe the role of NAT

Topic 2.14 Describe OSI and TCP/IP models

2.14.1 Identify the order of the layers of both OSI and TCP/IP models

2.14.2 Compare the similarities of some OSI and TCP/IP layers

2.14.3 Identify the protocols and functions of each OSI layer

Topic 2.15 Describe the data-encapsulation process

2.15.1 Describe the PDU format used at different layers

Topic 2.16 Identify the characteristics of various types of network firewalls

2.16.1 Traditional firewalls

2.16.2 Next-generation firewalls

2.16.3 Differentiate between NGFWs and traditional firewalls

Topic 2.17 Describe the application of NGFW deployment options (i.e., PA-, VM- and CN-Series)

Topic 2.18 Differentiate between intrusion detection systems and intrusion prevention systems

2.18.1 Differentiate between knowledge-based and behavior-based systems

Topic 2.19 Describe virtual private networks

2.19.1 Describe when to use VPNs

Topic 2.20 Differentiate between the different tunneling protocols

Topic 2.21 Describe the purpose of data loss prevention

2.21.1 Classify different types of data (e.g., sensitive, inappropriate)

Topic 2.22 Differentiate the various types of security functions from those that are integrated into UTM devices

Topic 2.23 Describe endpoint security standards

2.23.1 Describe the advantages of endpoint security

2.23.2 Describe host-based intrusion detection/prevention systems

2.23.3 Differentiate between signature-based and behavioral-based malware protection

2.23.4 Describe application block and allow listing

2.23.5 Describe the concepts of false-positive and false-negative alerts

2.23.6 Describe the purpose of anti-spyware software

Topic 2.24 Identify differences in managing wireless devices compared to other endpoint devices

Topic 2.25 Describe the purpose of identity and access management

2.25.1 Single- and multi-factor Authentication

2.25.2 Separation of duties and impact on privileges

2.25.3 RBAC, ABAC, DAC, and MAC

2.25.4 User profiles

Topic 2.26 Describe the integration of NGFWs with the cloud, networks, and endpoints

Topic 2.27 Describe App-ID, User-ID, and Content-ID

Topic 2.28 Describe Palo Alto Networks firewall subscription services

2.28.1 WildFire

2.28.2 URL Filtering

2.28.3 Threat Prevention

2.28.4 DNS Security

2.28.5 IoT Security

2.28.6 SD-WAN

2.28.7 Advanced Threat Prevention

2.28.8 Advanced URL Filtering

2.28.9 GlobalProtect

2.28.10 Enterprise DLP

2.28.11 SaaS Security Inline

2.28.12 Virtual Systems

Topic 2.29 Describe network security management

2.29.1 Identify the deployment modes of Panorama

2.29.2 Describe the three components of Best Practice Assessment (BPA)

Domain 3 Cloud Technologies 20%

Topic 3.1 Describe the NIST cloud service and deployment models

Topic 3.2 Recognize and list cloud security challenges

3.2.1 Describe the vulnerabilities in a shared community environment

3.2.2 Describe cloud security responsibilities

3.2.3 Describe cloud multitenancy

3.2.4 Differentiate between security tools in various cloud environments

3.2.5 Describe identity and access management controls for cloud resources

3.2.6 Describe different types of cloud security alerts and notifications

Topic 3.3 Identify the 4 Cs of cloud native security

Topic 3.4 Describe the purpose of virtualization in cloud computing

3.4.1 Describe the types of hypervisors

3.4.2 Describe characteristics of various cloud providers

3.4.3 Describe economic benefits of cloud computing and virtualization

3.4.4 Describe the security implications of virtualization

Topic 3.5 Explain the purpose of containers in application deployment

3.5.1 Differentiate containers versus virtual machines

3.5.2 Describe Container as a Service

3.5.3 Differentiate a hypervisor from a Docker Container

Topic 3.6 Describe how serverless computing is used

Topic 3.7 Describe DevOps

Topic 3.8 Describe DevSecOps

Topic 3.9 Illustrate the continuous integration/continuous delivery pipeline

Topic 3.10 Explain governance and compliance related to deployment of SaaS applications

3.10.1 Describe security compliance to protect data

3.10.2 Describe privacy regulations globally

3.10.3 Describe security compliance between local policies and SaaS applications

Topic 3.11 Describe the cost of maintaining a physical data center

Topic 3.12 Differentiate between data-center security weaknesses of traditional solutions versus cloud environments

Topic 3.13 Differentiate between east-west and north-south traffic patterns

Topic 3.14 Describe the four phases of hybrid data-center security

Topic 3.15 Describe how data centers can transform their operations incrementally

Topic 3.16 Describe the cloud-native security platform

Topic 3.17 Identify the four pillars of Prisma Cloud application security

Topic 3.18 Describe the concept of SASE

Topic 3.19 Describe the SASE layer

3.19.1 Describe sanctioned, tolerated, and unsanctioned SaaS applications

3.19.2 List how to control sanctioned SaaS usage

Topic 3.20 Describe the network-as-a-service layer

Topic 3.21 Describe how Prisma Access provides traffic protection

Topic 3.22 Describe Prisma Cloud Security Posture Management (CSPM)

Domain 4 Elements of Security Operations 20%

Topic 4.1 Describe the main elements included in the development of SOC business objectives

Topic 4.2 Describe the components of SOC business management and operations

Topic 4.3 List the six essential elements of effective security operations

Topic 4.4 Describe the four SecOps functions

4.4.1 Identify

4.4.2 Investigate

4.4.3 Mitigate

4.4.4 Improve

Topic 4.5 Describe SIEM

Topic 4.6 Describe the purpose of security orchestration, automation, and response (SOAR)

Topic 4.7 Describe the analysis tools used to detect evidence of a security compromise

Topic 4.8 Describe how to collect security data for analysis

Topic 4.9 Describe the use of analysis tools within a security operations environment

Topic 4.10 Describe the responsibilities of a security operations engineering team

Topic 4.11 Describe the Cortex platform in a security operations environment and the purpose of Cortex XDR for various endpoints

Topic 4.12 Describe how Cortex XSOAR improves security operations efficiency

Topic 4.13 Describe how Cortex Data Lake improves security operations visibility

Topic 4.14 Describe how XSIAM can be used to accelerate SOC threat response



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Palo-Alto Networks answers

 

VAST Data Continues To Expand Its Reach Through Partnerships

There has never been a better time to be a data management company. Digital transformation initiatives, the rise of AI thrown into hyperdrive by ChatGPT and the vast expansion of edge computing all make data—and the transformation and analysis of data—critical for modern business. To that end, it seems like there is a new AI, analytics or other data-adjacent company launching every day trying to catch this wave. And all of these workloads need highly performant storage. More concretely, there is certainly a lot of VC money pouring into this part of the tech industry.

So, how does one discern between the winners and losers in a tech market that feels like 2000 all over again? Well, Yogi Berra once said, "You can observe a lot just by watching," and as painful as it is for this Red Sox fan to admit, he was right. And carefully watching a company like VAST Data certainly makes it seem like this is a company built for long-term success.

VAST Data has experienced a meteoric rise in the market.

VAST Data

In a market brimming with both established companies and exciting startups, why VAST Data? I'll share my thoughts on that in this piece.

VAST has a killer product

The first rule of establishing long-term success is to truly solve the challenges that customers face, and to do it compellingly. What's the challenge in enterprise storage? Well, there are a few things. The first is summed up in one word: silos. Any company that's been around for a while has multiple storage environments deployed to serve different functions. For example, AI's latency requirements, not to mention its cost sensitivity, differ from those of a departmental database. Deploying multiple storage environments to support these disparate (and sometimes conflicting) requirements implies different storage architectures with different storage administrators and different protocols (e.g., NFS, SMB) across various cloud services (AWS S3, Azure Blob Storage, and so on).

The other challenge is complexity. It only takes a little imagination to see the complexity that’s introduced into an enterprise when deploying and maintaining file, block and object stores, whether we’re talking about resiliency or simply using the data within these stores. Life is difficult for administrators, developers and business users.

But complexity is not just about different storage types for different workloads. There’s also the locality issue. Data is generated, stored and used everywhere—in the datacenter, on the edge, on the far edge, on the industrial edge, in the cloud. Maintaining this distributed storage environment isn’t just challenging—it’s seemingly impossible.

Finally, the cost of maintaining these different data stores can be prohibitive, if you haven’t hit that point yet, you should probably recheck your IT spend. This is so because of all the challenges outlined above.

But what if I could eliminate the siloes and simplify my storage architecture using a universal platform that accounted for performance, scale, complexity and existing silos? Wouldn't that make life easier and lower my cost? The answer is yes, and VAST Data has delivered just such a solution.

The VAST Data Platform manages enterprise storage needs.

VAST Data

Regardless of data type, data location or function, VAST has a single platform to manage the needs of the enterprise. And it does this with a design focus on openness, scalability and cost.

So, considering the first rule of long-term success—having a killer product—VAST Data earns a check mark.

VAST meets the needs of many

Here’s what I like about what VAST has designed. Its product sits at the foundational level for multiple technology inflection points—analytics, AI, generative AI—that all rely on data. Likewise, any database or data store type (SQL, graph, key-value, document, column-oriented etc.) requires a performant back-end storage layer. And finally, regardless of data locality, the performant foundational storage platform underlying it will dictate how well workloads perform.

Winning across verticals, workloads, functions

VAST Data

I’ve seen a lot of companies come and go trying to meet the very specific needs of the market. In fact, I’ve been an employee at a few of these companies. Their lifespan is often limited due to the narrow focus or applicability of their offering, which means that their innovation might work only for one point in time in a market’s trajectory. By contrast, the VAST Data platform is engineered to be universal in terms of the functions it supports both today and in the long term.

VAST has won in the most competitive market segments

If you want to see a company's potential, look at its customer base's diversity, in terms of both segmentation and vertical industry. While a diverse customer base doesn't guarantee success, a limited customer base certainly limits growth potential.

VAST has done an excellent job of winning in the markets where performance matters, across various customer types.

VAST is winning across the market

VAST Data

As you can see from this sampling of customers, VAST is winning across segments with widely divergent purchase criteria. Whether a customer is focused on performance, scale or TCO, VAST seems to have an answer. And this is happening across verticals, from education to life sciences to content management. Again, this universal appeal says a lot about the long-term prospects for VAST.

Partnerships validate VAST’s solution and drive its TAM expansion

Finally, when considering whether a company has the technology and appeal for the long term, look to its validation in the market. In the case of VAST, we can look at two of the technology partnerships it has formed.

In April, HPE announced a partnership with VAST for file storage. In this partnership, VAST will be the brains (i.e., software) behind the GreenLake for file storage solution (you can read my coverage of that here). And just a couple of weeks ago, Nvidia certified VAST as the first NAS solution for its DGX SuperPOD (learn more about that here).

These partnerships are essential for a couple of reasons. First, they validate VAST's architecture and technology. When innovators select your company as a foundational part of their solutions, that's a big deal.

Second, these partnerships expand VAST's access to new markets. The company has already done quite well in the high-end storage market, but these partnerships should expand VAST's total addressable market (TAM). I believe the HPE partnership will immediately impact VAST's appeal "downstream," while the Nvidia certification will raise awareness of VAST in the higher-performance market segments.

Closing thoughts

The data management and storage market is full of strong players and compelling solutions. I've been in the technology field for a long time as an IT executive, consultant, marketer and now analyst, but I've never experienced so much growth and dynamism. In the current market, we will definitely see winners and losers shake out. The winners will include established tech companies that have responded to the market's needs as well as new entrants. And the losers will also include well-established companies along with newer entrants that fail to generate broad enough appeal.

From my vantage point of “observing by watching,” I’m putting VAST in the winner’s column. Is it still early in the game? Yes—but all the telltale signs are there.

Moor Insights & Strategy provides or has provided paid services to technology companies like all research and tech industry analyst firms. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and video and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Ampere Computing, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Cadence Systems, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cohesity, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex, Foundries.io, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, HYCU, IBM, Infinidat, Infoblox, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Juniper Networks, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, LoRa Alliance, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, Multefire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA, Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), NXP, onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler. Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Fivestone Partners, Frore Systems, Groq, MemryX, Movandi, and Ventana Micro., MemryX, Movandi, and Ventana Micro.


Ford Positions Business Segments To Tackle Digital Transformation

Ford

Looking across the past twenty years of technology, I can confidently say that 2008 brought the most monumental shift because of the rise of the smartphone—which changed everything we do, from work and play to communication and productivity. Looking ahead, there are two rising technologies that I believe will have an impact as dramatic as the smartphone. These changes are the rise of artificial intelligence in all our digital interactions and the rise of the digital automobile.

The iPhone is given the most credit for the rise of the smartphone, and rightly so. But remember that the iPhone came into an existing phone market that had mature players including Blackberry, Nokia and Microsoft. Yet iPhone changed the entire landscape for mobile devices and quickly became the market leader—leadership we still see today.

While many differences make the comparison far from perfect, we are seeing a similar story play out in real time with the rise of software-defined vehicles. The interest in electric vehicles as an efficient alternative to internal combustion engines (ICEs), along with the increasing capabilities of autonomous driving (AD) and advanced driver assistance system (ADAS) technologies, are accelerating the digital transformation of the automotive market.

The benefits of these technologies include better energy efficiency, better safety, better in-cabin experiences and new use cases that have not yet been realized, like using a car as a home sentry when it’s parked in a house’s driveway. While automotive companies are already focusing on energy efficiency, safety and in-cabin experiences, the true digital transformation of vehicles will shift their value away from their physical capabilities and toward their digital offerings.

For mature car and truck makers like Ford, the external verdict has been, as CEO Jim Farley said during Ford's recent Capital Markets Day, "Too many legacy issues—Ford can't win." Sure, legacy carmakers like Ford are great at building solid, reliable vehicles, but they are totally lacking in answers when it comes to the digital side of things. Or at least that’s the widespread assumption.

Ford, then, has reached a fight-or-flight moment where it needs to either step out of the way so digitally transforming technologies can take center stage, or it needs to become digitally transformed through innovation beyond its own efforts. Looking back at the comparison to the rise of the smartphone, is Ford going to be a Blackberry or Nokia of the market, where it once held a mature position until the market was changed by the rise of new technology, then fizzled out? Or is Ford going to embrace new technologies and be the change in the market, like Apple was with the iPhone?

Based on my view of the market and what I saw at Ford’s investor day, I want to give my analysis of how Ford is embracing these digital changes in spite of industry doubt. Let’s dive in.

Ford+, embracing digital change

Two years ago Ford announced Ford+, its new strategy to segment its business into Ford Blue, Model e and Ford Pro. Ford Blue is its portfolio of traditional ICE and hybrid-electric vehicles plus manufacturing capability, Model e is its portfolio of electric vehicles and includes responsibility for advanced technical development and Ford Pro is its portfolio of commercial vehicles and services.

I like Ford's strategy to differentiate its bread-and-butter vehicles like the Ford F-150, Ranger and Bronco from its next-generation electric vehicles. This segmentation gives Ford room to digitally transform its product portfolio without having to dramatically change its iconic gas-powered and hybrid lineup. Any successes that the company reaps from new technologies in the Model e segment can then be introduced and proved out in the Blue and Pro segments. Likewise, the decades of innovation, manufacturing and engineering that Ford has put into its traditional vehicles can be utilized in product development for Model e vehicles. It’s a smart strategy.

Positioning the Model e business segment is critical

As a tech industry analyst, I am most interested in the Model e segment and Ford's strategy to strengthen its digital transformation and differentiation while maintaining its traditional installed base.

The Model e segment is positioned as a lean startup within Ford, developing next-generation electric vehicle innovations and autonomous and ADAS technologies. The next-generation technologies that start in the Model e camp can then become differentiators for Ford in all three segments.

As an example of this, the Ford F-150 Lightning electric pickup is, in my opinion, an optimal mix of new technologies like the BlueCruise hands-free highway driving system with a familiar Ford look and feel. I think this is exactly what Ford was looking for: a new model differentiated from other EV trucks on the market that also retains what people know and love about the iconic F-150.

Interestingly, I think Ford introduced another compelling differentiator with the Mustang Mach-E and Lightning: the front trunk or "frunk." Without a gasoline engine under the hood, Ford was able to engineer a spacious front trunk—the largest one I have seen on the market. I hope Ford makes this a common feature for Ford EVs and includes it in the forthcoming all-electric Ford Explorer and other models.

Ford also mentioned Project T3, Ford's next electric truck. The mystery behind Project T3 makes it seem as though it will be a complete redesign of the Ford Lightning. However, Ford has communicated that the project will combine “a century of truck know-how with world-class electric vehicle, software and aerodynamics talent." The focus for Project T3 is not to make an electric truck that is completely unrecognizable for the Ford brand, but to initiate a platform shift toward a software-first design, even if it makes that aspect of the truck a big departure.

During its Capital Markets Day, Ford’s Chief Advanced Product Development & Technology Officer Doug Field – who moved over from Apple, and Tesla before that – spoke at length about how Ford is currently managing software development despite some limitations its facing and its ambitions for its next generation software platform.

According to Field, the current software platform is a challenge because it is “supplier-controlled’ based on a network of components that each need updating. This challenge means Ford engineers needs to work with suppliers to update their individual components in order to make wholesale changes to the vehicle. Despite that, this week, Ford announced it surpassed delivery of 13-million over-the-air software updates to both ICE and electric vehicles, noting about half of the updates enable customer facing improvements, such as improved BlueCruise capability.

Field also talked about the next-gen software platform, which will launch in 2025 starting with Ford’s second-gen EVs. On this platform, Ford will control the software – with a stated focus on developing customer features in the categories of autonomy, productivity, safety and security, and connectivity. And when that level of control happens, like Field stated in the keynote, “A new world of possibilities opens.”

I think a crucial part of executing this platform shift will be establishing a community of outside developers who create software for Ford vehicles. If Ford does not cultivate that to build on top of its software platform, I believe it could have a hard time following through with the digital transformation of its vehicles. In various areas of the tech world, I have seen many developer platforms succeed and many flop, and the difference is often in how well a company enables outsiders to build on its platform. Partnering with developers and building healthy relationships with outside software companies will be key if Ford wants to maximize software and services opportunities that will broaden sources of company revenue.

Here is where it is important to understand the difference between building the software-defined platform by itself and letting someone else build its software-defined vehicle platform for them. The benefits of Ford building its software defined vehicle platform is that Ford has total control over the platform. However, the benefits of partnering with companies that enable software-defined platforms is that it enables a wider range of developer integration. Nobody wants to develop for a platform that has a small reach. I have seen many platforms that have cultivated thriving developer ecosystems through developer enablement, and there have been many that I have seen flop.

Lastly, I think Ford Pro will continue to be an anchor for Ford. Commercial vehicles require reliability, functionality and practicality. In the Capital Markets Day presentation, Farley mentioned that great software and service experiences mean a lot to users, and that experience is a differentiating factor for customer loyalty.

Wrapping up

If we do make a direct comparison between the rise of the smartphone and the rise of the software-defined vehicle, I think many companies want to be the Apple in that story. However, I don’t want to see the Apple of the software-defined vehicle; I want to see the Ford of the software-defined vehicle.

The choices that Ford makes in the next couple of years are going to have a huge impact on its success for the next couple of decades. I believe Ford is heading in the right direction, but it cannot execute the digital transformation alone. The Ford+ plan puts Ford in a great position to embrace new technologies without compromising its breadwinners; in particular, the company has many exciting new offerings coming from its startup-like Model e team. I appreciate that Ford has recognized that software will be a defining factor in its future. It just can’t do it alone.

Note: Moor Insights & Strategy co-op Jacob Freyman contributed to this article.

Follow me on Twitter or LinkedIn. Check out my website or some of my other work here. 

Moor Insights & Strategy provides or has provided paid services to technology companies like all research and tech industry analyst firms. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and video and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Ampere Computing, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Cadence Systems, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cohesity, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex, Foundries.io, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, HYCU, IBM, Infinidat, Infoblox, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Juniper Networks, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, LoRa Alliance, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, Multefire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA, Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), NXP, onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler. Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Fivestone Partners, Frore Systems, Groq, MemryX, Movandi, and Ventana Micro., MemryX, Movandi, and Ventana Micro.


 


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