Splunk Core Certified Power User Exam Dumps

SPLK-1002 Exam Format | Course Contents | Course Outline | Exam Syllabus | Exam Objectives

EXAM NUMBER : SPLK-1002
EXAM NAME : Splunk Core Certified Power User
EXAM TIME : 60 Minutes

Exam Description: The Splunk Core Certified Power User exam is the final step towards completion of the Splunk Core Certified Power User certification. This next-level certification exam is a 57-minute, 65-question assessment which evaluates a candidates knowledge and skills of field aliases and calculated fields, creating tags and event types, using macros, creating workflow actions and data models, and normalizing data with the CIM. Candidates can expect an additional 3 minutes to review the exam agreement, for a total seat time of 60 minutes. It is recommended that candidates for this certification complete the lecture, hands-on labs, and quizzes that are part of the Splunk Fundamentals 2 course in order to be prepared for the certification exam. Splunk Core Certified Power User is a required prerequisite to the Splunk Enterprise Certified Admin certification track. This course focuses on searching and reporting commands, as well as on the creation of knowledge objects. Major topics include using transforming commands and visualizations, filtering and formatting results, correlating events, creating knowledge objects, using field aliases and calculated fields, creating tags and event types, using macros, creating workflow actions and data models, and normalizing data with the Common Information Model (CIM).

The following content areas are general guidelines for the content to be included on the exam:
- Transforming commands and visualizations
- Filtering and formatting results
- Correlating events
- Knowledge objects
- Fields (field aliases, field extractions, calculated fields)
- Tags and event types
- Macros
- Workflow actions
- Data models
- Splunk Common Information Model (CIM)

The following topics are general guidelines for the content likely to be included on the exam; however, other related topics may also appear on any specific delivery of the exam. In order to better reflect the contents of the exam and for clarity purposes, the guidelines below may change at any time without notice.
1.0 Using Transforming Commands for Visualizations 5%
1.1 Use the chart command
1.2 Use the timechart command
2.0 Filtering and Formatting Results 10%
2.1 The eval command
2.2 Use the search and where commands to filter results
2.3 The fillnull command
3.0 Correlating Events 15%
3.1 Identify transactions
3.2 Group events using fields
3.3 Group events using fields and time
3.4 Search with transactions
3.5 Report on transactions
3.6 Determine when to use transactions vs. stats
4.0 Creating and Managing Fields 10%
4.1 Perform regex field extractions using the Field Extractor (FX)
4.2 Perform delimiter field extractions using the FX
5.0 Creating Field Aliases and Calculated Fields 10%
5.1 Describe, create, and use field aliases
5.2 Describe, create, and use calculated fields
6.0 Creating Tags and Event Types 10%
6.1 Create and use tags
6.2 Describe event types and their uses
6.3 Create an event type
7.0 Creating and Using Macros 10%
7.1 Describe macros
7.2 Create and use a basic macro
7.3 Define arguments and variables for a macro
7.4 Add and use arguments with a macro
8.0 Creating and Using Workflow Actions 10%
8.1 Describe the function of GET, POST, and Search workflow actions
8.2 Create a GET workflow action
8.3 Create a POST workflow action
8.4 Create a Search workflow action
9.0 Creating Data Models 10%
9.1 Describe the relationship between data models and pivot
9.2 Identify data model attributes
9.3 Create a data model
10.0 Using the Common Information Model (CIM) Add-On 10%
10.1 Describe the Splunk CIM
10.2 List the knowledge objects included with the Splunk CIM Add-On
10.3 Use the CIM Add-On to normalize data

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Splunk Core test

Splunk Core test :: Article Creator

forget Mesos And OpenStack, Hashi Stack Is the brand new subsequent Platform

while a lot of software for creating and managing scale comes out of supercomputing centers, hyperscalers, and the largest public cloud builders, there is still a number of innovation being executed via individuals who should handle scale outside of these higher echelon agencies. Two of them are Mitchell Hashimoto and Armon Dadgar, the co-founders of HashiCorp, and that they have spent more than a decade constructing what's growing to be the seemingly commercial alternative to the Kubernetes stack – which also helps Kubernetes if you in fact are looking to do this, too.

Like many open supply projects that have made the leap to business success – and we don't seem to be asserting that there are lots of these – the primary assignment within the Hashi Stack, known as Vagrant, turned into a personal project of Hashimoto that created a kind of consistent configuration wrapper around application software that made it less demanding to equipment and update. finally Engine Yard – bear in mind that platform cloud choice to crimson Hat’s usual OpenShift and VMware’s Cloud Foundry? – sponsored Vagrant, which initially ran on Oracle’s VirtualBox hypervisor however which became accelerated to encompass VMware’s ESXi, pink Hat’s KVM, and Microsoft’s Hyper-V hypervisors as neatly as the customized Xen hypervisor used by Amazon web functions.

Hashimoto and Dadgar both acquired their bachelor’s levels in computing device science from the university of Washington and they additionally worked collectively at Kiip, which is a cell advert tech and facts platform provider based in San Francisco and which has Coca-Cola, Kellogg’s, Proctor & Gamble, McDonald’s, and Johnson & Johnson as its marquee clients. The Kiip advert engine become built in Python, Ruby, Bash, and Puppet, and when it became first grew to become on in 2010 (when Vagrant became a facet venture for Hashimoto), it might system a measly 1 question per 2nd at 200 milliseconds of typical latency, which is right at the impatience restrict of the human attention span. And after they based HashiCorp two years later, that Kiip equipment they left within the hands of their former agency become revved as much as 2,000 queries per second at a 20 millisecond common response time. That’s a 2,000X growth in throughput and a 10X improvement in latency, which is not too shabby.

Which is why the ambitions of the two HashiCorp co-founders had been not absurd after they explicitly got down to build a modular utility toolbox that can be the kernel of a real application platform, impressed with the aid of Unix, not Linux. (we will get to that in a moment.) neatly, might be a little absurd. but so is co-founding a brand new IT booklet in 2015 to take on the upper echelon of computing architecture. . . .

The Hashi Stack now has ten core add-ons, and here they're so as of unlock:

  • Vagrant, released in 2010, for growing virtual packaged utility building environments
  • Packer, released in 2013, for constructing virtual machine pictures
  • Serf, released in 2013, a failure detection device for clusters in response to a gossip protocol, identical to the small town or neighborhoods that many of us grew up in
  • Consul, released in 2014, a provider mesh with service discovery and remote method calls and experience propagation and a distributed key-cost shop
  • Terraform, launched in 2014, for provisioning virtual infrastructure throughout on-premises amenities and public clouds using “infrastructure as code” options
  • Vault, released in 2015, is a protection device that does secrets management, identification primarily based access, encryption, and security auditing – again, identical to the small towns and neighborhoods where many of us grew up
  • Nomad, additionally released in 2015, is a container and cluster administration device impressed by using Google’s Borg and Omega tools, which might be observed to have impressed the introduction and opening up of Kubernetes.
  • Sentinel, released in 2017, which is a policy as code framework that makes policy workflow for infrastructure malleable programmatically similar to Terraform does for the provisioning of infrastructure.
  • Boundary, launched in 2020, is a depended on identification platform for at ease remote entry to techniques
  • Waypoint, released in 2020, is an application workflow platform that stages code from build to install and thru unencumber updates – the type of issue HashiCorp vital for itself and now that you may use.
  • That’s a gorgeous constant beat of tool additions and a fairly comprehensive stack. And HashiCorp isn't trying to do every thing, as Dadgar explains to The next Platform, however rather do the core things smartly that others haven't and then combine with the different first rate tools that are needed to make a true and complete application platform.

    Timothy Prickett Morgan: correct off the bat, we haven't accomplished a very good job protecting the rise of HashiCorp, and in particular the Terraform provisioning tool, so we owe you an apology. however for what it's worth, we have been paying consideration. The stack that you've constructed is wonderful and is as finished as anything any one has put collectively. it's certainly now a platform in its own correct.

    My spider feel goes off and in some unspecified time in the future somebody large goes to are looking to take control of Terraform. i'm surprised it hasn’t took place already, to be sincere. Doesn’t someone need to counterbalance pink Hat’s OpenShift and build a big enterprise?

    Armon Dadgar: I consider we wish to construct a big business. [Laughter]

    TPM: Cisco systems is a likely healthy, and that they have a partnership with you. Hewlett Packard and Dell don’t need to be in the utility enterprise, which indicates they don’t be aware the contemporary IT company at some stage. Microsoft may be a pretty good fit. however we want a reprise of the OpenStack-Mesos-Kubernetes showdown. So possibly the VMware stack versus the IBM pink Hat OpenShift stack versus the Cisco Hashi stack.

    Anyway, is Terraform the de facto ordinary for provisioning infrastructure in the datacenter these days?

    Armon Dadgar: I believe this is a “yes” at this element, but it is more than that.

    once we begun, we wanted to construct a full portfolio that covers all of those pieces. I think we had been intentional about laying out all the components. within the first few years of our lifestyles, and basically from 2013 through 2016, we just stored expanding except we bought to the stack because it’s wide-spread nowadays. After that, we really shifted gears, and have been super-concentrated on making this aspect the de facto regular after which constructing a commercial enterprise on correct of that. We in fact didn’t focal point on commercialization up unless 2016 in any meaningful method.

    From there, we had a three-pronged approach, which has bought us where we're these days. One become relentless open supply evangelism. we've an immense developer family members crew. Mitchell and that i nonetheless do a ton of developer evangelism ourselves, and it’s vital to construct developer love. I suppose the second piece turned into engaging all of our tech companions and the ecosystem around about building Terraform integrations. Now we've smartly over one hundred technology partners, and Terraform has over a thousand integrations via that. And the third prong turned into after we did start focusing commercially in 2016, we centered the international 2000 and we started winning the lighthouse bills, like knocking over a huge bank.

    TPM: that you may’t say “knock over a huge bank.” It skill you've got robbed it!

    Armon Dadgar: smartly, they willingly gave us the funds.

    TPM: whatever they gave you, it's pocket alternate they can cover with the aid of elevating our bank fees.

    Armon Dadgar: JP Morgan Chase is a superb example. They gave us their innovation award remaining year as a result of they’ve standardized how they provision with Terraform. and then they inform all their vendors, similar to carriers like Cisco and NetApp and VMware, to build Terraform integrations.

    we've been driven by means of the backside-up groundswell of the community, followed via the ecosystem lean in to construct out a network impact after which we knocked over a bunch of these global 2000 valued clientele.

    TPM: the place are you at nowadays? give us some metrics about the place you are the hockey stick? Are you in that bizarre vicinity where each time you flip round, there’s like 2X more americans working on the enterprise?

    Armon Dadgar: relatively tons. We had around 800 personnel final year and that is now pushing up to 1,four hundred personnel. I lose tune myself. I think we are able to end the 12 months at near 2,000 americans depending on how instantly we can keep hiring. we're smartly north of 1,000 paying enterprise purchasers, and we now have close to 250 of the world 2000. So we're previous the early startup part that we have been in 2016.

    TPM: this is where any company becomes entertaining to me. i love issues once they’re first starting and there is the idea and the ambition. It’s enjoyable writing about initiatives as they emerge and then turn into agencies, however then it turns into a blizzard of element releases and we let a while move before we take a look once again on what's occurring and how the market is receiving something know-how they have created.

    Armon Dadgar: In that center part, you don’t know in the event that they’re going to sink or swim. I’d like to feel we’re previous the sink or swim.

    TPM: We spent lots of time with CoreOS once we started The subsequent Platform as a result of we thought that appeared critical, and the equal for Mesos and OpenStack and few different evolving Kubernetes stacks.

    I believe it's protected to say that HashiCorp is swimming. I imply, you’re now not jogging on water yet, however, you know, VMware is not going to be in a position to try this much longer. VMware can persist for a long time, because of the tremendous 300,000-potent client base and its lengthy historical past of using vSphere. however ultimately, VMware expenses must come down to compete with more suitable and improved container platforms.

    Armon Dadgar: I believe of CA, which proves you will also be round for a very long time means after you're beside the point. Decline can be very sluggish, gradual.

    TPM: and strange. How within the hell did laptop buddies grow to be being received with the aid of Broadcom?

    Armon Dadgar: A merger of two Titanics [Laughter]

    TPM: Let’s now not go there. [Laughter]

    So what do you do now? simply preserve doing what you’re already doing? you're growing to be like crazy, you have got raised a fair amount of cash. . . .

    Armon Dadgar: Our contemporary funding changed into our series E financing in March 2020 for $175 million. In total, we have raised $349.2 million.

    TPM: after I beginning seeing sequence F and collection G, that makes me pause apart from in special cases. sequence E is typical. Are you attempting to move public? You understand, there’s probably a SPAC or two that’s desperate for you. . . .

    Armon Dadgar: [Laughter] Our finance crew is having to hit delete an awful lot, going through these items. however severely, Dave McJannet, our CEO, has said going public. We’ve always been of the intellect that our chance is so big that we are looking to build a standalone, independent business.

    There’s definitely some thing to handle and complete ownership of your fate – these are very beneficial things.

    TPM: well, the VC guys probably are looking to money out on a high be aware.

    Armon Dadgar: That all the time becomes the counterbalance. At some element, they need their liquidity. So it’s all the time a careful steadiness. Going public helps with employee retention as neatly over time.

    TPM: it really is, if somebody doesn’t try to make you an offer which you can’t refuse, like EMC did to VMware means returned when. Google? doubtless not. Microsoft? might be. they're acquisitive.

    Armon Dadgar: I feel it’s value speakme concerning the cloud relationships in that in that appreciate. The value that HashiCorp brings is that we're that neutral Switzerland. We don’t have a cloud affiliation. We don’t promote you a cloud. I all the time describe our relationship with the clouds like this: they promote power, we promote power lines. and i feel from the customer viewpoint, that’s positive as a result of they know they will have a relationship with all of them and that they don’t need to be deeply wedded to CloudFormation or some thing because then they have no true leverage with the public clouds.

    So I think HashiCorp being owned by using a hyperscaler would break that. rapidly, we'd no longer actually be neutral. It’s very nearly what took place with red Hat put up the IBM acquisition. . . .

    TPM: And what almost came about with VMware when Dell acquired its hands on it.

    Armon Dadgar: yes, exactly. but with that market, people have been to date down the VMware highway that it didn’t rely that Dell owned them.

    TPM: Are you the actual and most effective Switzerland at this point when it involves systems? I had a hope for Mesos and OpenStack and was awaiting a Kubernetes stack to emerge. i thought somehow these might glue together in a captivating means, but they didn’t Borg neatly, so as to speak.

    Armon Dadgar: [Laughter] I consider purple Hat can also have had the most beneficial shot pre-IBM as a result of they nevertheless weren’t affiliated with a cloud and that they had CoreOS and its Kubernetes implementation. but for the reason that they've been a part of IBM, they’ve acquired the Blue Wash effect, and i think that clients view crimson Hat like they’re no longer actually neutral.

    TPM: With the Terraform 1.0 unlock, are you right down to fit and finish and polish? is that this issue equipped for prime time, able for enterprise? That’s what 1.0 continually means.

    Armon Dadgar: HashiCorp has been probably the most traditionally conservative dealer of what we call 1.0. and that i suppose we tease ourselves about this because like most corporations IPO earlier than we consider a product 1.0. appear on the scope of Terraform. It doesn’t even make feel – we've well over a hundred million downloads, a thousand company integrations, and smartly over a thousand business valued clientele, and simplest now do we call this a 1.0 product? The bar that we set is awfully, very excessive.

    TPM: I’ve by no means heard of it. It’s basically legacy utility at this point. here is like your 4.0 unencumber.

    Armon Dadgar: We funny story within the group that we were off through a decimal area and here's basically liberate 10.0. [Laughter]

    look in any respect of our products. None of them have executed it in under 5 years. Our view is this: except the items are extensively deployed with production hardening time, it'll now not be a free up 1.0. Some of those tasks we see come out of the Linux foundation, it’s just like the first code commit and the ultimate code commit had been five minutes ago and the challenge is 6.0 liberate. How can or not it's at 6.0? There’s no user operating it in creation and also you’re calling this element a 6.0? supply me a ruin.

    TPM: How advanced is this stack? Is it as complicated as OpenStack, as massive as OpenStack. As you recognize, OpenStack had every little thing in there however a blender and the kitchen sink. . . .

    Armon Dadgar: [Laughter] Please don’t associate us with OpenStack. . . .

    TPM: ok, adequate, I’m making an attempt to get a evaluation. So let’s use a Linux or windows working device, which has tens of thousands and thousands of strains of code depending on the way you count it and cut it.

    Armon Dadgar: The Hashi stack is actually millions of traces of code.

    what is greater important is what we call the Tao of HashiCorp, our design ethos. and that i believe a key piece of that design ethos changed into just like the Unix philosophy: We need each tool to be elementary, focused on a single factor, but then we make them composable. We might construct the Hashi Platform, which may be a monolithic, OpenStack sort of play, however we want to be tremendous-mindful to do the accurate contrary.

    every of these tools will do one issue and do it actually well – after which compose with the others. So if I analyze Terraform. it’s nevertheless very, very focused on just the provisioning. supply me an infrastructure as code definition of what you want it to seem like, Terraform will figure out the way to get there – and it will do the provisioning and lifecycle engine, but it stops there. It’s now not going to do graphic management. It doesn’t do patching. It doesn’t do app installation. if you desire a picture administration device, we now have Packer. You need service discovery and network automation, we've Consul. you have app installation? Use Kubernetes or Nomad. We didn’t desire the OpenStack impact that here is monolithic, big bang code base – all in or all out. These are very narrowly focused, do one aspect and do it elegantly in preference to are attempting to boil the ocean.

    There are 4 layers that we care about: provisioning, safety, networking, and app set up. And there’s layers that we feel different people do in fact neatly, like observability and telemetry. Go use DataDog or Splunk or whatever thing. And we’re also now not truly in preproduction world. So it’s an outstanding let’s compose a really tightly with GitHub and GitLab and Artifactory and the CI/CD companies.

    TPM: You’re no longer messing in the hypervisor. You’re not messing in firmware management for servers. You’re not messing in configuration of switches or any of that stuff.

    Armon Dadgar: or even configuration management. We integrate tightly with Ansible, Chef, and Puppet. Use Terraform for the provisioning, after which let’s combine tightly with these. We deeply integrate with Kubernetes throughout the stack, but we've our Nomad choice, which is our container and application scheduler.

    TPM: Is Nomad more advantageous than Kubernetes?

    Armon Dadgar: i'd say, “sure,” however most likely i am biased.

    TPM: I anticipate you consider that otherwise you wouldn’t trouble. So then what is it that you simply’re doing with Nomad that's stronger than Kubernetes?

    Armon Dadgar: For me, it comes down to three definitely fundamental issues. One is barely the class of adventure. Kubernetes is OpenStack 2.0. It’s just as complex. It’s just as seller managed. It’s simply as groundwork led.

    TPM: It’s Seven of nine. . . . Or Six of one and A Half A Dozen Of a further.

    Armon Dadgar: It’s a horse designed by committee.

    To me, I also locate it so disingenuous the style they talk about Kubernetes. It’s the successor to Borg and Google took every thing they learned from it. If that’s real, then why does everything nonetheless run on Borg internal of Google?

    TPM: Google must have kept probably the most respectable stuff.

    Armon Dadgar: Let’s ignore the usability of Kubernetes, which is a large number. Let’s discuss its exact operational scalability. It’s also a funny story. Borg runs on 10 million nodes, Kubernetes falls over you probably have just a few hundred. And so in what sense did Google learn from Borg when Kubernetes only scales to 1/a thousandth of what Borg does?

    simplest a few weeks in the past, we published a two million container benchmark, which we did in partnership with Amazon net services. We had 100,000 CPU cores and 10,000 nodes and we deployed two million containers throughout it. In 2017, we did 1,000,000 container version of this.

    Nomad in fact operates at size and scale, it’s really based mostly off of the Borg and Omega papers from Google. Ours is definitely a real implementation of Borg as adversarial to an implementation of Borg. And the user journey is barely much simpler, extra dependent.

    TPM: what's the nerd equal of a mic drop? A desktop drop examine? anything it is, that became one in every of them.


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