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S90-03A - SOA Design & Architecture - Dump Information

Vendor : SOA
Exam Code : S90-03A
Exam Name : SOA Design & Architecture
Questions and Answers : 100 Q & A
Updated On : April 23, 2019
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S90-03A Questions and Answers

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S90-03A SOA Design & Architecture

Study Guide Prepared by Killexams.com SOA Dumps Experts

Exam Questions Updated On :



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S90-03A exam Dumps Source : SOA Design & Architecture

Test Code : S90-03A
Test Name : SOA Design & Architecture
Vendor Name : SOA
Q&A : 100 Real Questions

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SOA SOA Design

A CTO's suggestions For Getting Stuff done | killexams.com Real Questions and Pass4sure dumps

As a globe-touring application govt, London-based mostly Luis Augusto Weir has seen carrier-oriented architectures (SOAs) evolve from complexity to ubiquity. The ancient SOA mannequin has been reborn by means of several strategies to middleware and APIs—and he’s chuffed to be a part of the booming API economic system.

Luis Weir, chief technology officer for Capgemini’s Oracle practice Cloud solutions team, says the main approach to encourage is by using example.

Oracle/Matt Lever

Weir has penned a number of books on middleware, together with the impending business API management (Packt Publishing, July 2019), thanks to his experience with building SOA, middleware, and API solutions for Fortune 500 agencies. And he began younger, building one of the country’s first social media websites in his native Venezuela in addition to starting a small building firm before he graduated from faculty. How does he dwell so productive whereas protecting current with altering technology?

Set the course

“I’m the CTO, so I control every person however I don’t manage any individual,” laughs Weir. As chief know-how officer for Capgemini’s Oracle practice Cloud options group, “I have four projects happening right now, so I’m indirectly managing a couple of americans.” His function is to set the expertise direction, defining where his apply may still invest, in response to market understanding and then engaging the technology team results in make certain that team of workers is educated and enabled. He does this by way of getting his arms dirty, to be able to talk.

“I consider the period of utility architects who just do PowerPoint is gone. i exploit it to sell an idea or a concept and to attract diagrams,” Weir says. however the main approach to inspire is by using illustration, he believes. “further and further I see CTOs who are like me. an excellent example is Lucas Jellema @lucasjellema, CTO of Amis, who's much more hands-on than i am.”

be aware Digital Natives

Getting hands-on is also key to managing the next technology of builders, in line with Weir. “What we get from institution is younger ability who are looking to get impressed and play with cool tech. they are digital-born; they’ve under no circumstances accepted the rest.” although, he feels it’s also vital to e-book developers towards not trying to reinvent the wheel. “for a lot of, chiefly when you are inexperienced, you are trying to remedy an issue from scratch devoid of investigating even if others have solved the problem already,” he says.

although “managing battle is a whole other theme,” he says, “one issue i am at all times scuffling with with is design selections. I hate unintended selections.” He misses the focal point on application structure that he says was extra commonplace.

“builders nowadays tend to forget about architecture a little bit. i love establishing, but making the right decisions can keep loads of time and energy down the line,” Weir says. That’s why he has what he calls a “red-tape method for design decisions,” where he asks questions corresponding to “Why are you the usage of JavaScript as adversarial to Java?” or “Why did you select relaxation APIs over GraphQL APIs?” the important thing, he says, is to retain an open mind and make choices which are justified for the purpose you try to obtain.

Use Your knowledgeable network

Staying abreast of the altering technology panorama and the way other executives are managing trade is important for a CTO. “You need to go obtainable and meet individuals at conferences such as Oracle OpenWorld Europe,” says Weir. As a longstanding Oracle ACE director and now an Oracle Groundbreaker Ambassador, he appreciates the alternatives that having an in depth relationship with a application dealer similar to Oracle brings and the chances to engage with peer Oracle ACEs and Groundbreakers.

“Groundbreakers is a brilliant community for studying and taking part,” Weir says. He additionally reads magazines online and is a Slack and Twitter enthusiast—but like most of us, he admits to struggling to close off those tips sources at times.

Don’t Exhaust yourself

indeed, for people reminiscent of Weir, understanding when he's able to focus and when to lower back off is essential. “Mornings are top-rated. I’m extra inventive, I’m rested, and that i don’t have 100 things in my head,” Weir says. That focus has a restrict, besides the fact that children: “every so often at the conclusion of the day, my wife complains that I don’t wish to speak. I find it elaborate to suppose, as a result of I’m mentally exhausted. I couldn’t do anything creative at evening.”

His favorite technique to find flow is to isolate himself from office distractions. “If, for example, I need to deliver a hard-core demo, like a pattern pattern to demonstrate my developers how to enforce anything the appropriate way, I stay domestic, isolate myself in my domestic studio, shut off e mail, and just focal point,” he says.

in the event you put your head down, time flies, Weir finds—but that, too, has hazards. He’s discovered it vital to take breaks for nutrition and “to disconnect a bit and are available lower back sparkling. Your creativity can be affected in case you don’t look after yourself a bit. That’s a standard difficulty. you could exhaust your self without realizing it.”


warding off Double payments in a disbursed funds system | killexams.com Real Questions and Pass4sure dumps

background

Airbnb has been migrating its infrastructure to a carrier Oriented structure (“SOA”). SOA offers many upsides, similar to enabling developer specialization and the capability to iterate sooner. youngsters, it also poses challenges for billing and funds purposes since it makes it extra problematic to keep statistics integrity. An API name to a provider that makes extra API calls to downstream services, the place each carrier adjustments state and doubtlessly has aspect results, is similar to executing a posh distributed transaction.

To be certain consistency among all features, protocols akin to two-part commit could be used. without this kind of protocol, distributed transactions present challenges to holding information integrity, permitting swish degradation, and reaching consistency. Requests also inevitably fail within distributed programs — connections will drop and timeout at some factor, specially for transactions that consist of varied network requests.

There are three different ordinary options utilized in allotted techniques to obtain eventual consistency: read fix, write restoration, and asynchronous restoration. There are advantages and change-offs to each strategy. Our payments system uses all three in a lot of functions.

Asynchronous repair comprises the server being chargeable for operating facts consistency checks, similar to desk scans, lambda services, and cron jobs. additionally, asynchronous notifications from the server to the client are conventional within the payments trade to drive consistency on the client aspect. Asynchronous fix, along with notifications, can be used in-conjunction with examine and write repair recommendations, offering a second line of defense with trade-offs in answer complexity.

Our answer in this particular publish utilizes write restoration, where each write name from the customer to the server makes an attempt to restoration an inconsistent, damaged state. Write fix requires clients to be smarter (we’ll expand on this later), and allows for them to many times fire the same request and under no circumstances need to hold state (other than retries). customers can thus request eventual consistency on-demand, giving them handle over the user adventure. Idempotency is an incredibly crucial property when enforcing write restoration.

what's idempotency?

For an API request to be idempotent, customers could make the equal name time and again and the influence will be the identical. In different phrases, making dissimilar similar requests may still have the same impact as making a single request.

This technique is common in billing and fee techniques involving money circulation — it is critical a funds request gets processed fully exactly once (also referred to as “exactly-as soon as delivery”). Importantly, if a single operation to circulate cash is called assorted instances, the underlying equipment should still circulation funds at most as soon as. here is critical for Airbnb payments APIs in order to stay away from numerous payouts to the host, and even worse, numerous fees to the guest.

by means of design, idempotency safely enables assorted similar calls from purchasers the usage of an auto-retry mechanism for an API to achieve eventual consistency. This method is normal among customer-server relationships with idempotency, and some thing that we use in our dispensed programs these days.

At a excessive stage, the beneath diagram illustrates some primary, instance scenarios with duplicate requests and highest quality idempotent habits. No be counted how many cost requests are made, the visitor will at all times be charged at most once.

An idempotent request is a request this is made with similar parameters and the effect will always be the identical, invariably (the guest is charged at most once). The issue remark

Guaranteeing eventual consistency for our payments gadget is of the utmost importance. Idempotency is a attractive mechanism to achieve this in a allotted device. In an SOA world, we will inevitably run into complications. for instance, how would customers recover if it did not devour the response? What if the response turned into misplaced or the customer timed out? What about race-circumstances leading to a user clicking “ebook” twice? Our requirements covered right here:

  • in its place of implementing a single, custom answer certain for a given use case, we vital a regularly occurring yet configurable idempotency answer to be used across Airbnb’s numerous funds SOA capabilities.
  • whereas SOA-based mostly charge items were being iterated on, we couldn’t compromise on data consistency considering the fact that this would affect our community at once.
  • We vital ultra low latency, so constructing a separate, stand-alone idempotency service wouldn’t be adequate. most importantly, the carrier would undergo from the identical problems it become at first meant to remedy.
  • As Airbnb is scaling its engineering organization the use of SOA, it would be tremendously inefficient to have each developer specialize on data integrity and eventual consistency challenges. We wanted to shield product developers from these nuisances to allow them to center of attention on product development and iterate faster.
  • additionally, considerable alternate-offs with code readability, testability and means to troubleshoot had been all considered non-starters.

    answer explained

    We desired to be capable of identify each and every incoming request uniquely. moreover, we mandatory to precisely tune and control where a selected request turned into in its lifecycle.

    We implemented and utilized “Orpheus”, a standard-goal idempotency library, throughout varied payments capabilities. Orpheus is the legendary Greek mythological hero who became in a position to orchestrate and appeal all dwelling things.

    We selected a library as an answer because it offers low latency whereas nevertheless presenting clean separation between excessive-speed product code and low-velocity equipment administration code. At a high level, it includes the following simple ideas:

  • An idempotency key's handed into the framework, representing a single idempotent request
  • Tables of idempotency counsel, always examine and written from a sharded master database (for consistency)
  • Database transactions are combined in distinctive parts of the codebase to ensure atomicity, the use of Java lambdas
  • Error responses are labeled as “retryable” or “non-retryable”
  • We’ll element how a fancy, disbursed device with idempotency guarantees can turn into self-curative and eventually constant. We’ll also stroll through one of the vital exchange-offs and further complexities from our answer that one may still remember of.

    hold database commits to a minimal

    probably the most key necessities in an idempotent equipment is to provide handiest two results, success or failure, with consistency. in any other case, deviations in facts can result in hours of investigation and incorrect payments. as a result of databases present ACID properties, database transactions may also be readily used to atomically write facts while making certain consistency. A database commit can also be certain to be successful or fail as a unit.

    Orpheus is headquartered around the assumption that basically every standard API request can also be separated into three distinctive phases: Pre-RPC, RPC, and submit-RPC.

    An “RPC”, or remote Procedural call(s), is when a shopper makes a request to a faraway server and waits for that server to conclude the requested manner(s) before resuming its procedure. in the context of funds APIs, we discuss with an RPC as a request to a downstream provider over a network, that could consist of external payments processors and acquiring banks. In short, here is what occurs in each section:

  • Pre-RPC: particulars of the fee request are recorded within the database.
  • RPC: The request is made live to the external processor and the response is obtained. this is a spot to do one or greater idempotent computations or RPCs (for example, query service for the fame of a transaction first if it’s a retry-effort).
  • post-RPC: particulars of the response from the external carrier are recorded in the database, including its successfulness and even if a nasty request is retryable or now not.
  • To keep data integrity, we adhere to two basic floor guidelines:

  • No carrier interaction over networks in Pre and post-RPC phases
  • No database interactions in the RPC phases
  • We essentially want to stay away from mixing network conversation with database work. We’ve realized the tough manner that community calls (RPCs) throughout the Pre and put up-RPC phases are prone and can effect in dangerous things like rapid connection pool exhaustion and efficiency degradation. without difficulty put, network calls are inherently unreliable. on account of this, we wrapped Pre and publish-RPC phases in enclosing database transactions initiated by means of the library itself.

    We additionally need to call out that a single API request may encompass varied RPCs. Orpheus does assist multi-RPC requests, however during this put up we desired to illustrate our notion technique with simplest the essential single-RPC case.

    As proven in the illustration diagram below, every database commit in every of the Pre-RPC and post-RPC phases is mixed right into a single database transaction. This ensures atomicity — total gadgets of work (here the Pre-RPC and put up-RPC phases) can fail or succeed as a unit constantly. The intent is that the equipment should still fail in a fashion it may get better from. as an instance, if a number of API requests failed within the center of an extended sequence of database commits, it could be extremely problematic to systematically hold music of where every failure befell. notice that the all network communique, the RPC, are explicitly separated from all database transactions.

    network communique is strictly saved break free database transactions

    A database commit right here includes an idempotency library commit and utility layer database commits, all combined within the identical code block. with out being careful, this may in fact begin to look in fact messy in real code (spaghetti, any person?). We also felt that it shouldn’t be the accountability of the product developer to call definite idempotency routines.

    Java Lambdas to the Rescue

    fortuitously, Java lambda expressions can also be used to mix assorted sentences into a single database transaction seamlessly, with out a influence to testability and code readability.

    here is an instance, simplified utilization of Orpheus, with Java lambdas in action:

    At a deeper stage, here's a simplified excerpt from the supply code:

    We didn't put in force nested database transactions, however as an alternative mixed database instructions from Orpheus and the utility right into a single database commit, strictly passing Java purposeful interfaces (lambdas).

    The separation of these issues does offer some change-offs. developers should use forethought to ensure code readability and maintainability as different new ones constantly make contributions. They additionally need to continually evaluate that correct dependencies and information get passed along. API calls are actually required to be refactored into three smaller chunks, which may arguably be restrictive on the style builders write code. It may in reality be basically complex for some advanced API calls to without problems be damaged down into a 3-step strategy. certainly one of our services has carried out a Finite State machine with every transition as an idempotent step the use of StatefulJ, where you might safely multiplex idempotent calls in an API call.

    coping with Exceptions — To Retry or not to Retry?

    With a framework like Orpheus, the server should recognize when a request is secure to retry and when it isn’t. For this to occur, exceptions should still be handled with meticulous intention — they should be categorised as both “retryable” or “non-retryable”. This most likely provides a layer of complexity for developers and will create unhealthy aspect-effects if they are not considered and prudent.

    for example, consider a downstream provider turned into offline briefly, however the exception raised changed into mistakenly labeled as “non-retryable” when it basically should still had been “retryable”. The request can be “failed” indefinitely, and subsequent retry requests would perpetually return the incorrect non-retryable error. Conversely, double payments may occur if an exception turned into labeled “retryable” when it in reality may still were “non-retryable” and requires guide intervention.

    In accepted, we agree with unexpected runtime exceptions because of community and infrastructure considerations (5XX HTTP statuses) are retryable. We expect these blunders to be transient, and we predict that a later retry of the same request may additionally ultimately be a hit.

    We categorize validation blunders, comparable to invalid enter and states (for example, that you can’t refund a refund), as non-retryable (4XX HTTP statuses) — we predict all subsequent retries of the same request to fail within the identical manner. We created a customized, usual exception type that handled these situations, defaulting to “non-retryable”, and for certain different cases, classified as “retryable”.

    it is elementary that request payloads for every request continue to be the same and are by no means mutated, otherwise it could ruin the definition of an idempotent request.

    Categorizing “retryable” and “non-retryable” exceptions

    There are of path more indistinct part situations that need to be dealt with with care, reminiscent of dealing with a NullPointerException correctly in diverse contexts. for example, a null value again from the database due to a connectivity blip is distinctive from an misguided null field in a request from a client or from a 3rd birthday celebration response.

    shoppers Play a a must have function

    As alluded to in the beginning of this submit, the customer must be smarter in a write fix gadget. It need to personal a few key obligations when interacting with a carrier that makes use of an idempotency library like Orpheus:

  • move in a special idempotency key for each new request; reuse the same idempotency key for retries.
  • Persist these idempotency keys to the database before calling the carrier (to later use for retries).
  • safely consume successful responses and in consequence unassign (or nullify) idempotency keys.
  • make certain mutation of the request payload between retry makes an attempt isn't allowed.
  • cautiously devise and configure auto-retry ideas in accordance with enterprise needs (the use of exponential backoff or randomized wait instances (“jitter”) to steer clear of the thundering herd issue).
  • a way to choose an Idempotency Key?

    picking an idempotency secret's important — the client can opt for both to have request-level idempotency or entity-stage idempotency in accordance with what key to make use of. This choice to use one over the different would rely on different business use-situations, but request-degree idempotency is essentially the most simple and customary.

    For request-stage idempotency, a random and interesting key may still be chosen from the client to be able to ensure idempotency for the complete entity assortment stage. as an instance, if we desired to allow numerous, distinctive funds for a reservation booking (corresponding to Pay less Upfront), we just deserve to make sure the idempotency keys are diverse. UUID is a good example structure to make use of for this.

    Entity-stage idempotency is far more stringent and restrictive than request-degree idempotency. Say we want to ensure that a given $10 payment with identification 1234 would simplest be refunded $5 once, on the grounds that we can technically make $5 refund requests twice. we'd then are looking to use a deterministic idempotency key in accordance with the entity mannequin to be sure entity-level idempotency. An illustration layout would be “charge-1234-refund”. every refund request for a unique fee would due to this fact be idempotent on the entity-degree (charge 1234).

    each API Request Has an Expiring lease

    numerous similar requests can be fired due to varied user-clicks or if the client has an aggressive retry coverage. This may potentially create race conditions on the server or double payments for our community. To evade these, API calls, with the assist of the framework, every deserve to acquire a database row-level lock on an idempotency key. This grants a lease, or a permission, for a given request to proceed extra.

    A hire comes with an expiration to cowl the state of affairs the place there are timeouts on the server side. If there isn't any response, then an API request can be retryable simplest after the latest rent has expired. The software can configure the rent expiration and RPC timeouts in line with their wants. a pretty good rule of thumb is to have a higher lease expiration than the RPC timeout.

    Orpheus moreover offers a highest retryable window for an idempotency key to give a safety net to be able to prevent rogue retries from sudden equipment habits.

    Recording the Response

    We additionally listing responses, to keep and video display idempotent conduct. When a consumer makes the same request for a transaction that has reached a deterministic conclusion-state, reminiscent of a non-retryable error (validation error, as an example) or a successful response, the response is recorded within the database.

    Persisting responses does have a performance exchange-off — valued clientele are capable of acquire quick responses on subsequent retries, but this desk will have growth proportional to the increase of the application’s throughput. This desk can rapidly turn into bloated the table if we’re not careful. One competencies answer is to periodically remove rows older than a definite timeframe, but doing away with an idempotent response too early has terrible implications, too. builders may still even be cautious not to make backwards-incompatible adjustments to the response entities and structure.

    prevent duplicate Databases — stick with grasp

    When analyzing and writing idempotency assistance with Orpheus, we selected to do that directly from the grasp database. In a gadget of disbursed databases, there's a tradeoff between consistency and latency. because we couldn’t tolerate excessive latency or analyzing uncommitted statistics, the use of master for these tables mades essentially the most sense for us. In doing so, there is not any need for the use of a cache or a database duplicate. If a database gadget isn't configured for effective examine-consistency (our methods are backed by means of MySQL), the usage of replicas for these operations may basically create adverse consequences from an idempotency perspective.

    as an instance, believe a payments provider saved its idempotency advice on a copy database. a consumer submits a charge request to the carrier, which finally ends up being a success downstream, but the customer doesn’t obtain a response due to a community concern. The response, at present stored on the provider’s grasp database, will finally be written to the duplicate. although, in the experience of reproduction lag, the customer might as it should be hearth an idempotent retry to the carrier and the response would now not be recorded to the replica yet. since the response “does not exist” (on the replica), the provider may mistakenly execute the price once more, resulting in replica funds. The below example illustrates how simply a number of seconds of replica lag could trigger colossal fiscal have an impact on to Airbnb’s neighborhood.

    a duplicate payment created because of this from duplicate lag Response 1 is not found on the reproduction within the retry attempt (Request 2) reproduction fee avoided via storing idempotency advice simplest on master Response 1 found immediately on master and lower back within the retry attempt (Request 2)

    When the use of a single master database for idempotency, it became fairly clear that scaling would definitely and without delay turns into an issue. We alleviated this via sharding the database by idempotency key. The idempotency keys we use have high cardinality and even distribution, making them helpful shard keys.

    last concepts

    reaching eventual consistency doesn't come with out introducing some complexity. consumers should save and address idempotency keys and implement automated retry-mechanisms. builders require additional context and ought to be surgically specific when enforcing and troubleshooting Java lambdas. They ought to be deliberate when coping with exceptions. moreover, because the latest edition of Orpheus is fight-established, we're continually discovering issues to enhance on: request-payload matching for retries, more desirable support for schema alterations and nested migrations, actively limiting database access during RPC phases, etc.

    whereas these are concerns at proper of intellect, the place has Orpheus gotten Airbnb funds up to now? on the grounds that the launch of the framework, we now have done five nines in consistency for our funds, while our annual fee volume has simultaneously doubled (examine this in case you’d like to gain knowledge of extra on how we measure information integrity at scale). in case you’re drawn to engaged on the intricacies of a disbursed funds platform and assisting travelers all over the world belong anywhere, the Airbnb funds team is hiring! Shoutout to Michel Weksler and Derek Wang for their thought leadership and architectural philosophy on this project!


    Syracuse architecture Thesis reports, competition and Exhibition Mark conclusion of 12 months | killexams.com Real Questions and Pass4sure dumps

    Campus & community Syracuse structure Thesis studies, competition and Exhibition Mark conclusion of year Tuesday, April sixteen, 2019, through Julie Sharkey Share
  • college of architecture

    Poster depicting times and dates of Syracuse Architecure eventsThe faculty of architecture will cap off an exciting educational year with thesis reports, the Thesis Prize Jury competition and an exhibition of scholar work.

    Thesis reviews

    On Monday and Tuesday, April 22-23, the faculty will host its annual final thesis reviews. students, school and group of workers are invited to Slocum corridor to watch as Bachelor of structure (BArch) and master of architecture (MArch) degree candidates existing their remaining thesis projects to a group of Syracuse structure faculty reviewers.

    each the BArch and MArch expert degree courses culminate with thesis tasks. Working as individuals or in collaborative teams, college students pursue analysis and design with an advisory neighborhood of faculty on themes regarding their expertise.

    The thesis yr is an opportunity for college kids to synthesize the dissimilar features of the curriculum in ways in which center of attention on specific issues or opportunities within the container, enabling them to explore architectural abilities and apply in a deeper and more advanced way than occurs of their prior design studios or different courses.

    “As emerging architects and ordinary design experts, (thesis is a) rite of passage for discovering our own voice inside the professional world and in our initiatives to come,” says Nathalie Brock, 2019 MArch candidate.

    For nearly 4 decades, a whole lot of theses had been offered at Syracuse architecture protecting topics that are as distinctive because the hobbies of the students and the school, and that have interaction the most compelling ideas at that time. students are inspired to focus on concerns they’re enthusiastic about, that nourish them intellectually and that situate them to make interesting contributions to the self-discipline.

    “It’s a fine approach to conclusion an educational profession, because you’ve taken all that you just’ve been learning and researching for 3 or five years and built it into that project that helps transition you into what you want to do along with your profession,” says Brian Lonsway, associate professor and graduate chair at Syracuse architecture.

    via a mixture of research and inventive exploration, students enhance a question, habits research throughout varied disciplines and produce an brilliant volume of design work, ranging from sketches to digital models to fabric reviews, scale models, sophisticated renderings and writing.

    “I concentrated on trying to organize my challenge around tangible traits in follow and the academic discourse in architecture,” says Kokeith Perry II, 2019 BArch candidate.

    on the last studies, which might be open to the public, the initiatives are presented to a gaggle of school who critique their work and vote on its merits for inclusion within the Thesis Prize Jury.

    “You become an authority at some thing…you're able to name that Thesis—it’s a contribution to the better field,” says Jennifer Bonner, director of MALL and assistant professor at Harvard institution Graduate faculty of Design.

    the whole agenda of thesis shows can be found at soa.syr.edu/calendar.

    Thesis Prize Jury

    The annual Thesis Prize Jury competition may be held on Friday, might also 3, in Slocum hall. A opt for group of undergraduate and graduate students from the type of 2019 will present their theses before a panel of guest jurors and Syracuse structure college.

    visitor jurors:

  • Joe Day teaches design and thought at SCI-Arc and is a companion at Deegan Day Design, l. a..
  • Jia Gu is director and curator at substances & applications, la, and co-director of Spinagu.
  • Nina-Marie Lister is affiliate professor within the school of urban and Regional Planning at Ryerson institution and founding most important of PLANDFORM.
  • Maxi Spina teaches design at SCI-Arc and is co-director of Spinagu.
  • Brittany Utting teaches on the institution of Michigan Taubman faculty of structure + urban Planning and is co-founding father of the design collaborative home-workplace.
  • Gretchen Wilkins is head of the architecture branch and architect-in-home at the Cranbrook Academy of artwork.
  • students who take part in the Thesis Prize Jury adventure compete for awards that can be introduced at the 2019 convocation ceremony—the Dean’s Thesis Citations and James A. Britton Memorial Awards. This year’s Brittons will encompass the Jury Prize, college Prize and gold standard Thesis.

    The Thesis Prize Jury adventure is open to the public. displays will take region from 10 to 11:30 a.m. in Slocum Auditorium. There could be an opportunity to view projects all the way through Slocum hall from 11:30 a.m. to 12:30 p.m., followed with the aid of a panel dialogue with the jurors from 1 to 2 p.m.

    ‘Shelf life’ Exhibition

    moreover Thesis Prize Jury, the college of structure will host an conclusion-of-yr exhibition titled “Shelf life” that’s a collaborative construction of the total category of 2019 thesis college students.

    This yr’s “Shelf lifestyles” is the third version of a framework for college students to playfully compile and gather quite a number objects that may bring or display the pursuits which have inspired their thesis investigations, or been produced alongside the way. The remaining form of this yr’s exhibition is a large-scale video projection that mixes and compares those objects in a dynamic and dramatic means.

    “It celebrates a key transitional moment in the lives of the college students and the value of thesis to that transition, when they are moving into the primary levels of their skilled careers and, confidently, will proceed to pursue their thesis pastimes in enjoyable ways,” says Professor Mark Linder, “Shelf lifestyles” co-curator and thesis director at Syracuse architecture.

    “Shelf lifestyles” opens at 5 p.m. on Thursday, might also 2, within the traveling Critics Studio on the first ground of Slocum hall and may remain open to the general public as a part of the reception that automatically follows Syracuse architecture’s 2019 convocation ceremony on Saturday, may eleven.


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    A CTO's Tips For Getting Stuff Done | killexams.com real questions and Pass4sure dumps

    As a globe-traveling software executive, London-based Luis Augusto Weir has seen service-oriented architectures (SOAs) evolve from complexity to ubiquity. The old SOA model has been reborn via several approaches to middleware and APIs—and he’s happy to be part of the booming API economy.

    Luis Weir, chief technology officer for Capgemini’s Oracle Practice Cloud Solutions team, says the main way to inspire is by example.

    Oracle/Matt Lever

    Weir has penned several books on middleware, including the forthcoming Enterprise API Management (Packt Publishing, July 2019), thanks to his experience with building SOA, middleware, and API solutions for Fortune 500 companies. And he started young, building one of the country’s first social media websites in his native Venezuela as well as starting a small development firm before he graduated from college. How does he stay so productive while keeping current with changing technology?

    Set the Direction

    “I’m the CTO, so I manage everyone but I don’t manage anyone,” laughs Weir. As chief technology officer for Capgemini’s Oracle Practice Cloud Solutions team, “I have four projects going on right now, so I’m indirectly managing several people.” His role is to set the technology direction, defining where his practice should invest, based on market understanding and then engaging the technology team leads to ensure that staff is trained and enabled. He does this by getting his hands dirty, so to speak.

    “I think the era of software architects who just do PowerPoint is gone. I use it to sell a concept or an idea and to draw diagrams,” Weir says. But the main way to inspire is by example, he believes. “More and more I see CTOs who are like me. A good example is Lucas Jellema @lucasjellema, CTO of Amis, who is even more hands-on than I am.”

    Understand Digital Natives

    Getting hands-on is also key to managing the next generation of developers, according to Weir. “What we get from university is young talent who want to get inspired and play with cool tech. They are digital-born; they’ve never known anything else.” However, he feels it’s also important to guide developers toward not trying to reinvent the wheel. “For many, especially if you are inexperienced, you try to solve a problem from scratch without investigating whether others have solved the problem already,” he says.

    Although “managing conflict is a whole other topic,” he says, “one thing I am always battling with is design decisions. I hate accidental decisions.” He misses the focus on software architecture that he says used to be more prevalent.

    “Developers today tend to forget about architecture a little bit. I love developing, but making the right decisions can save a lot of time and effort down the line,” Weir says. That’s why he has what he calls a “red-tape process for design decisions,” where he asks questions such as “Why are you using JavaScript as opposed to Java?” or “Why did you choose REST APIs over GraphQL APIs?” The key, he says, is to keep an open mind and make decisions that are justified for the goal you are trying to achieve.

    Use Your Professional Network

    Staying abreast of the changing technology landscape and how other executives are managing change is critical for a CTO. “You need to go out there and meet people at conferences such as Oracle OpenWorld Europe,” says Weir. As a longstanding Oracle ACE director and now an Oracle Groundbreaker Ambassador, he appreciates the opportunities that having a close relationship with a software vendor such as Oracle brings and the chances to interact with peer Oracle ACEs and Groundbreakers.

    “Groundbreakers is a brilliant network for learning and collaborating,” Weir says. He also reads magazines online and is a Slack and Twitter enthusiast—but like most of us, he admits to struggling to shut off those information sources at times.

    Don’t Exhaust Yourself

    Indeed, for people such as Weir, knowing when he is able to concentrate and when to back off is key. “Mornings are best. I’m more creative, I’m rested, and I don’t have 100 things in my head,” Weir says. That focus has a limit, however: “Sometimes at the end of the day, my wife complains that I don’t want to talk. I find it difficult to think, because I’m mentally exhausted. I couldn’t do something creative at night.”

    His favorite way to find flow is to isolate himself from office distractions. “If, for example, I have to deliver a hard-core demo, like a sample pattern to show my developers how to implement something the right way, I stay home, isolate myself in my home studio, shut off email, and just focus,” he says.

    When you put your head down, time flies, Weir finds—but that, too, has risks. He’s found it critical to take breaks for meals and “to disconnect a little and come back fresh. Your creativity can be affected if you don’t look after yourself a little. That’s a common problem. You can exhaust yourself without knowing it.”


    Avoiding Double Payments in a Distributed Payments System | killexams.com real questions and Pass4sure dumps

    Background

    Airbnb has been migrating its infrastructure to a Service Oriented Architecture (“SOA”). SOA offers many upsides, such as enabling developer specialization and the ability to iterate faster. However, it also poses challenges for billing and payments applications because it makes it more difficult to maintain data integrity. An API call to a service that makes further API calls to downstream services, where each service changes state and potentially has side effects, is equivalent to executing a complex distributed transaction.

    To ensure consistency among all services, protocols such as two-phase commit might be used. Without such a protocol, distributed transactions present challenges to maintaining data integrity, allowing graceful degradation, and achieving consistency. Requests also inevitably fail within distributed systems — connections will drop and timeout at some point, especially for transactions that consist of multiple network requests.

    There are three different common techniques used in distributed systems to achieve eventual consistency: read repair, write repair, and asynchronous repair. There are benefits and trade-offs to each approach. Our payments system uses all three in various functions.

    Asynchronous repair involves the server being responsible for running data consistency checks, such as table scans, lambda functions, and cron jobs. Additionally, asynchronous notifications from the server to the client are widely used in the payments industry to force consistency on the client side. Asynchronous repair, along with notifications, can be used in-conjunction with read and write repair techniques, offering a second line of defense with trade-offs in solution complexity.

    Our solution in this particular post utilizes write repair, where every write call from the client to the server attempts to repair an inconsistent, broken state. Write repair requires clients to be smarter (we’ll expand on this later), and allows them to repeatedly fire the same request and never have to maintain state (aside from retries). Clients can thus request eventual consistency on-demand, giving them control over the user experience. Idempotency is an extremely important property when implementing write repair.

    What is idempotency?

    For an API request to be idempotent, clients can make the same call repeatedly and the result will be the same. In other words, making multiple identical requests should have the same effect as making a single request.

    This technique is commonly used in billing and payment systems involving money movement — it is crucial a payments request gets processed completely exactly once (also known as “exactly-once delivery”). Importantly, if a single operation to move money is called multiple times, the underlying system should move money at most once. This is critical for Airbnb Payments APIs in order to avoid multiple payouts to the host, and even worse, multiple charges to the guest.

    By design, idempotency safely allows multiple identical calls from clients using an auto-retry mechanism for an API to achieve eventual consistency. This technique is common among client-server relationships with idempotency, and something that we use in our distributed systems today.

    At a high level, the below diagram illustrates some simple, example scenarios with duplicate requests and ideal idempotent behavior. No matter how many charge requests are made, the guest will always be charged at most once.

    An idempotent request is a request that is made with identical parameters and the outcome will always be the same, consistently (the guest is charged at most once). The Problem Statement

    Guaranteeing eventual consistency for our payments system is of the utmost importance. Idempotency is a desirable mechanism to achieve this in a distributed system. In an SOA world, we will inevitably run into problems. For example, how would clients recover if it failed to consume the response? What if the response was lost or the client timed out? What about race-conditions resulting in a user clicking “Book” twice? Our requirements included the following:

  • Instead of implementing a single, custom solution specific for a given use case, we needed a generic yet configurable idempotency solution to be used across Airbnb’s various Payments SOA services.
  • While SOA-based payment products were being iterated on, we couldn’t compromise on data consistency since this would impact our community directly.
  • We needed ultra low latency, so building a separate, stand-alone idempotency service wouldn’t be sufficient. Most importantly, the service would suffer from the same problems it was originally intended to solve.
  • As Airbnb is scaling its engineering organization using SOA, it would be highly inefficient to have every developer specialize on data integrity and eventual consistency challenges. We wanted to shield product developers from these nuisances to allow them to focus on product development and iterate faster.
  • Additionally, considerable trade-offs with code readability, testability and ability to troubleshoot were all considered non-starters.

    Solution Explained

    We wanted to be able to identify each incoming request uniquely. Additionally, we needed to accurately track and manage where a specific request was in its lifecycle.

    We implemented and utilized “Orpheus”, a general-purpose idempotency library, across multiple payments services. Orpheus is the legendary Greek mythological hero who was able to orchestrate and charm all living things.

    We chose a library as a solution because it offers low latency while still providing clean separation between high-velocity product code and low-velocity system management code. At a high level, it consists of the following simple concepts:

  • An idempotency key is passed into the framework, representing a single idempotent request
  • Tables of idempotency information, always read and written from a sharded master database (for consistency)
  • Database transactions are combined in different parts of the codebase to ensure atomicity, using Java lambdas
  • Error responses are classified as “retryable” or “non-retryable”
  • We’ll detail how a complex, distributed system with idempotency guarantees can become self-healing and eventually consistent. We’ll also walk through some of the trade-offs and additional complexities from our solution that one should be mindful of.

    Keep database commits to a minimum

    One of the key requirements in an idempotent system is to produce only two outcomes, success or failure, with consistency. Otherwise, deviations in data can lead to hours of investigation and incorrect payments. Because databases offer ACID properties, database transactions can be effectively used to atomically write data while ensuring consistency. A database commit can be guaranteed to succeed or fail as a unit.

    Orpheus is centered around the assumption that almost every standard API request can be separated into three distinct phases: Pre-RPC, RPC, and Post-RPC.

    An “RPC”, or Remote Procedural Call(s), is when a client makes a request to a remote server and waits for that server to finish the requested procedure(s) before resuming its process. In the context of payments APIs, we refer to an RPC as a request to a downstream service over a network, which can include external payments processors and acquiring banks. In brief, here is what happens in each phase:

  • Pre-RPC: Details of the payment request are recorded in the database.
  • RPC: The request is made live to the external processor and the response is received. This is a place to do one or more idempotent computations or RPCs (for example, query service for the status of a transaction first if it’s a retry-attempt).
  • Post-RPC: Details of the response from the external service are recorded in the database, including its successfulness and whether a bad request is retryable or not.
  • To maintain data integrity, we adhere to two simple ground rules:

  • No service interaction over networks in Pre and Post-RPC phases
  • No database interactions in the RPC phases
  • We essentially want to avoid mixing network communication with database work. We’ve learned the hard way that network calls (RPCs) during the Pre and Post-RPC phases are vulnerable and can result in bad things like rapid connection pool exhaustion and performance degradation. Simply put, network calls are inherently unreliable. Because of this, we wrapped Pre and Post-RPC phases in enclosing database transactions initiated by the library itself.

    We also want to call out that a single API request may consist of multiple RPCs. Orpheus does support multi-RPC requests, but in this post we wanted to illustrate our thought process with only the simple single-RPC case.

    As shown in the example diagram below, every database commit in each of the Pre-RPC and Post-RPC phases is combined into a single database transaction. This ensures atomicity — entire units of work (here the Pre-RPC and Post-RPC phases) can fail or succeed as a unit consistently. The motive is that the system should fail in a manner it could recover from. For example, if several API requests failed in the middle of a long sequence of database commits, it would be extremely difficult to systematically keep track of where each failure occurred. Note that the all network communication, the RPC, are explicitly separated from all database transactions.

    Network communication is strictly kept separate from database transactions

    A database commit here includes an idempotency library commit and application layer database commits, all combined in the same code block. Without being careful, this could actually begin to look really messy in real code (spaghetti, anyone?). We also felt that it shouldn’t be the responsibility of the product developer to call certain idempotency routines.

    Java Lambdas to the Rescue

    Thankfully, Java lambda expressions can be used to combine multiple sentences into a single database transaction seamlessly, with no impact to testability and code readability.

    Here is an example, simplified usage of Orpheus, with Java lambdas in action:

    At a deeper level, here is a simplified excerpt from the source code:

    We did not implement nested database transactions, but instead combined database instructions from Orpheus and the application into a single database commit, strictly passing Java functional interfaces (lambdas).

    The separation of these concerns does offer some trade-offs. Developers must use forethought to ensure code readability and maintainability as other new ones constantly contribute. They also need to consistently evaluate that proper dependencies and data get passed along. API calls are now required to be refactored into three smaller chunks, which could arguably be restrictive on the way developers write code. It might actually be really difficult for some complex API calls to effectively be broken down into a three-step approach. One of our services has implemented a Finite State Machine with every transition as an idempotent step using StatefulJ, where you could safely multiplex idempotent calls in an API call.

    Handling Exceptions — To Retry or Not to Retry?

    With a framework like Orpheus, the server should know when a request is safe to retry and when it isn’t. For this to happen, exceptions should be handled with meticulous intention — they should be categorized as either “retryable” or “non-retryable”. This undoubtedly adds a layer of complexity for developers and could create bad side-effects if they are not judicious and prudent.

    For example, suppose a downstream service was offline temporarily, but the exception raised was mistakenly labeled as “non-retryable” when it really should have been “retryable”. The request would be “failed” indefinitely, and subsequent retry requests would perpetually return the incorrect non-retryable error. Conversely, double payments could occur if an exception was labeled “retryable” when it actually should have been “non-retryable” and requires manual intervention.

    In general, we believe unexpected runtime exceptions due to network and infrastructure issues (5XX HTTP statuses) are retryable. We expect these errors to be transient, and we expect that a later retry of the same request may eventually be successful.

    We categorize validation errors, such as invalid input and states (for example, you can’t refund a refund), as non-retryable (4XX HTTP statuses) — we expect all subsequent retries of the same request to fail in the same manner. We created a custom, generic exception class that handled these cases, defaulting to “non-retryable”, and for certain other cases, categorized as “retryable”.

    It is essential that request payloads for each request remain the same and are never mutated, otherwise it would break the definition of an idempotent request.

    Categorizing “retryable” and “non-retryable” exceptions

    There are of course more vague edge cases that need to be handled with care, such as handling a NullPointerException appropriately in different contexts. For example, a null value returned from the database due to a connectivity blip is different from an erroneous null field in a request from a client or from a third party response.

    Clients Play a Vital Role

    As alluded to at the beginning of this post, the client must be smarter in a write repair system. It must own several key responsibilities when interacting with a service that uses an idempotency library like Orpheus:

  • Pass in a unique idempotency key for every new request; reuse the same idempotency key for retries.
  • Persist these idempotency keys to the database before calling the service (to later use for retries).
  • Properly consume successful responses and subsequently unassign (or nullify) idempotency keys.
  • Ensure mutation of the request payload between retry attempts is not allowed.
  • Carefully devise and configure auto-retry strategies based on business needs (using exponential backoff or randomized wait times (“jitter”) to avoid the thundering herd problem).
  • How to Choose an Idempotency Key?

    Choosing an idempotency key is crucial — the client can choose either to have request-level idempotency or entity-level idempotency based on what key to use. This decision to use one over the other would depend on different business use-cases, but request-level idempotency is the most straightforward and common.

    For request-level idempotency, a random and unique key should be chosen from the client in order to ensure idempotency for the entire entity collection level. For example, if we wanted to allow multiple, different payments for a reservation booking (such as Pay Less Upfront), we just need to make sure the idempotency keys are different. UUID is a good example format to use for this.

    Entity-level idempotency is far more stringent and restrictive than request-level idempotency. Say we want to ensure that a given $10 payment with ID 1234 would only be refunded $5 once, since we can technically make $5 refund requests twice. We would then want to use a deterministic idempotency key based on the entity model to ensure entity-level idempotency. An example format would be “payment-1234-refund”. Every refund request for a unique payment would consequently be idempotent at the entity-level (Payment 1234).

    Each API Request Has an Expiring Lease

    Multiple identical requests can be fired due to multiple user-clicks or if the client has an aggressive retry policy. This could potentially create race conditions on the server or double payments for our community. To avoid these, API calls, with the help of the framework, each need to acquire a database row-level lock on an idempotency key. This grants a lease, or a permission, for a given request to proceed further.

    A lease comes with an expiration to cover the scenario where there are timeouts on the server side. If there is no response, then an API request can be retryable only after the current lease has expired. The application can configure the lease expiration and RPC timeouts according to their needs. A good rule of thumb is to have a higher lease expiration than the RPC timeout.

    Orpheus additionally offers a maximum retryable window for an idempotency key to provide a safety net in order to avoid rogue retries from unexpected system behavior.

    Recording the Response

    We also record responses, to maintain and monitor idempotent behavior. When a client makes the same request for a transaction that has reached a deterministic end-state, such as a non-retryable error (validation errors, for example) or a successful response, the response is recorded in the database.

    Persisting responses does have a performance trade-off — clients are able to receive quick responses on subsequent retries, but this table will have growth proportional to the growth of the application’s throughput. This table can quickly become bloated the table if we’re not careful. One potential solution is to periodically remove rows older than a certain timeframe, but removing an idempotent response too early has negative implications, too. Developers should also be wary not to make backwards-incompatible changes to the response entities and structure.

    Avoid Replica Databases — Stick to Master

    When reading and writing idempotency information with Orpheus, we chose to do this directly from the master database. In a system of distributed databases, there is a tradeoff between consistency and latency. Since we couldn’t tolerate high latency or reading uncommitted data, using master for these tables mades the most sense for us. In doing so, there is no need for using a cache or a database replica. If a database system is not configured for strong read-consistency (our systems are backed by MySQL), using replicas for these operations could actually create adverse effects from an idempotency perspective.

    For example, suppose a payments service stored its idempotency information on a replica database. A client submits a payment request to the service, which ends up being successful downstream, but the client doesn’t receive a response due to a network issue. The response, currently stored on the service’s master database, will eventually be written to the replica. However, in the event of replica lag, the client could correctly fire an idempotent retry to the service and the response would not be recorded to the replica yet. Because the response “does not exist” (on the replica), the service could mistakenly execute the payment again, resulting in duplicate payments. The below example illustrates how just a few seconds of replica lag could cause significant financial impact to Airbnb’s community.

    A duplicate payment created as a result from replica lag Response 1 is not found on the replica in the retry attempt (Request 2) Duplicate payment avoided by storing idempotency information only on master Response 1 found immediately on master and returned in the retry attempt (Request 2)

    When using a single master database for idempotency, it was pretty clear that scaling would undoubtedly and quickly becomes an issue. We alleviated this by sharding the database by idempotency key. The idempotency keys we use have high cardinality and even distribution, making them effective shard keys.

    Final thoughts

    Achieving eventual consistency does not come without introducing some complexity. Clients need to store and handle idempotency keys and implement automated retry-mechanisms. Developers require additional context and must be surgically precise when implementing and troubleshooting Java lambdas. They must be deliberate when handling exceptions. Additionally, as the current version of Orpheus is battle-tested, we are continuously finding things to improve on: request-payload matching for retries, improved support for schema changes and nested migrations, actively restricting database access during RPC phases, and so on.

    While these are considerations at top of mind, where has Orpheus gotten Airbnb Payments so far? Since the launch of the framework, we have achieved five nines in consistency for our payments, while our annual payment volume has simultaneously doubled (read this if you’d like to learn more on how we measure data integrity at scale). If you’re interested in working on the intricacies of a distributed payments platform and helping travelers around the world belong anywhere, the Airbnb Payments team is hiring! Shoutout to Michel Weksler and Derek Wang for their thought leadership and architectural philosophy on this project!


    Is Car Insurance on the Horizon for Automakers? | killexams.com real questions and Pass4sure dumps

    Autonomy and vehicle data are setting the stage for a change in the way car insurance premiums are assessed and administered.

    Forget the gecko, the good hands, and the mayhem guy. Your next car insurer might be an automaker.

    A combination of technical and economic forces is conspiring to change the way car insurance is administered, and automakers are moving closer than ever to playing a key role in that process.

    Prime among those forces is the rise of the autonomous car. But a second force has also begun to emerge: An unprecedented amount of data is making its way into the vehicle, creating a foundation for change. And automakers may hold the key to that data.

    “The combination of autonomous driving and data changes the whole game,” Brian Carlson, director of product line management for connectivity and security at NXP Semiconductors N.V., told Design News. “So we’re starting to see where automotive OEMs will take more responsibility for insurance.”

    It’s not yet clear how that would happen. The two could work cooperatively, enabling automakers to sell name-brand insurance along with vehicles. Or automakers could decide to do it themselves, bankrolling and selling insurance in the same way they now provide new-car financing. Either way, experts believe it would be a natural product extension for the industry.

    “If they want to get into insurance, they will, and they should,” noted Sam Tawfik, CEO of LMP Motors, an e-commerce platform for buying and renting vehicles. “They already have the installed base of distribution. And if vehicles become autonomous, they can just roll the insurance onto that.”

    The New Role of Real-Time Data

    To be sure, the idea of automakers in car insurance is hardly new. The industry has floated the idea for years. Toyota, for example, started a jointly-held car insurance services company called Toyota Insurance Management Solutions USA, LLC in 2016. And Tesla, Inc. launched a program called Insure My Tesla, also in 2016.

    In 2016, Toyota took a small step toward insurance, launching Toyota Insurance Management Solutions. (Image source: Toyota Corp.)

    More recently, however, the concept has begun to pick up steam as automakers roll further down the road to autonomy. The reason is simple: Autonomy takes the burden of driving away from the human, and places responsibility for it squarely on the shoulders of the automaker. “Autonomous cars change the equation because the OEM is basically making the driving decisions,” Carlson said. “So the question becomes: Is the automaker going to have to self-insure the vehicle?”

    Moreover, as part of their autonomous effort, automakers are now collecting mountains of vehicle and driver data that would have been unthinkable only a decade ago. To some degree, the data is there for the study of human driving, as a means to improve robotic systems.

    But there’s also an opportunity for insurers and automakers to monetize that data, using it to reduce the premiums for human drivers while autonomy is still on the drawing board. The key is the existence of data buses, already in place on all vehicles, and new electronic gateways, which can extract sensor data and convert it to meaningful information.

    Such gateways are available today. NXP, for example, rolled out a chipset in February that serves as a foundation for automotive “service-oriented gateways.” The chipset processes vehicle data from CAN, LIN, and FlexRay buses, which contain a constant stream of data bits from every sensor around the vehicle.

    In February, NXP rolled out a chipset that acts as a “service-oriented gateway” to enable automakers to collect data from sensors around the vehicle, and convert it to usable information. (Image source: NXP Semiconductors)

    In many cases, the data tells a story that insurers want to hear. Using a combination of wheel speed sensors, engine data, GPS information, and brake sensing, among others, the car itself can now paint a portrait of the occupant’s driving habits. Is the driver aggressive? Does he or she speed? Brake hard? Accelerate fast? Or is the driver cautious and law-abiding?

    “There are a lot of activities within the vehicle that can indicate a driver’s behavior,” Carlson said.  

    Insurers believe that real-time data would provide a more complete portrait of the driver than can be had with simple historical information, such as traffic tickets and accident rates. As a result, they hope to apply it, ultimately lowering the cost of vehicle ownership for certain drivers, who now find insurance to be one of their biggest ongoing vehicle bills.

    “The auto company can leverage the data to provide lower-cost insurance capability,” Carlson said. “Whether they do that through a partner company, or whether they take on the whole thing themselves, that remains to be seen.”

    Competition or Cooperation?

    Analysts who follow the insurance industry are uncertain about how it will play out —whether it will be a competitive or cooperative relationship between insurance companies and automakers. “I don’t think anyone can truly imagine all the implications associated with this – in terms of infrastructure, regulation, and risk,” noted Michelle Krause, a senior managing director and insurance specialist at Accenture. “That’s why we believe they are more likely to lean toward cooperation.”

    Krause questions whether data will play a big role in the transformation, but she’s convinced that autonomy will be a game-changer. The big reduction in accidents brought by automation means that collision premiums will drop, and insurers will have to find other products to sell – such as liability and cyber security protection.

    “Once cars become more and more autonomous, the need for insurance will fade into the background,” Krause told us. “There’s a lot of speculation about when that will happen, but everybody agrees it will happen.”

    Either way, most observers see this as a golden opportunity for automakers to migrate toward insurance. “It would be a brilliant product extension for the auto industry,” Tawfik told us. “Whether the automakers do the brilliant thing…that I can’t predict.”.

    Senior technical editor Chuck Murray has been writing about technology for 35 years. He joined Design News in 1987, and has covered electronics, automation, fluid power, and auto.

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    SOA S90-03A Exam (SOA Design & Architecture) Detailed Information



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