How Cloud Computing will change how you and your team will run IT
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The inevitable coming of cloud computing. See also YouTube channel ClubCloudComputing.
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How Cloud Computing will change how you and your team will run IT
- 1. Clouds and the future of IT Dr. Peter H.J. van Eijk CCSK, CCSP, CC, CL Cloud Computing and Security
- 3. Gangam style
- 5. Cloud is a state of mind
- 6. Your job Let’s assume that you work with IT. As an IT manager, systems or solutions architect, QA, or any other IT role. Or you are involved in procuring IT or as an auditor or on the legal side of IT.
- 8. How did we get here? Each of these steps was a disruptive innovation … 1970-80s Mainframe 1990s Client/Server 2000s Internet 2010s Cloud, Social, Mobile
- 9. Disruptive innovations Characteristics • Not as good (initially) • Much cheaper • Addresses ‘over-served’ customers • Rapidly improving • Eventually drives original out of the market Examples • Wikipedia • PC • Internet • Cloud computing https://en.wikipedia.org/wiki/Disruptive_innovation
- 12. The new cloud world: everything is connected
- 13. Moore’s law
- 14. IT is getting more complicated • Moore’s law • More technology • More components • More programming languages • More interfaces and devices • More pervasive IT • More threats • More brainpower required • More productivity required
- 20. Control in the supply chain
- 21. Today’s car • Cheaper • More fuel efficient • More functional • Safer • Better • More colors
- 22. A simple cloud supply chain IaaS SaaS Consumers
- 23. A more realistic supply chain IaaS Paas SaaS Consumers
- 24. CCM in a simple supply chain IaaS SaaS Consumers “pass through compliance”
- 25. Examples of the CSA GRC Stack components GRC stack component Example element CCM AAC-02: Independent reviews and assessments shall be performed at least annually […] CAIQ AAC-02.3: Do you conduct regular application penetration tests of your cloud infrastructure as prescribed by industry best practices and guidance? Cloud Audit http:/… /cloudaudit/org/cloudsecurityalliance/guidance/AAC-02.3 CTP "It is 11 pm, when was the last pentest on this application done?"
- 26. The Cloud, what is it? Cloud computing is a service based delivery model (outsourcing) for IT with 5 essential characteristics leading to new business value. (and new risk )
- 27. NIST Model of Cloud Computing
- 28. 5 essential characteristics lead to new value and new risk • Resource pooling. Multiple customers • On-demand self-service. Unilateral provisioning, programmable infrastructure • Broad network access. Network and client • Rapid elasticity. Speedy provisioning and deprovisioning • Measured Service. Pay per use
- 30. Programmable infrastructure →Automated deployment and DevOps Capacity at scale → Big Data, ML, AI Out on the network → Social and IOT
- 31. DEVOPS
- 32. Feature velocity through continuous delivery Number of deployments per day (source: “The Phoenix Project”, 2012) Company Deploy Frequency Deploy Lead Time Amazon 23.000/day Minutes Google 5.500/day Minutes Netflix 500/day Minutes Twitter 3/week Minutes Typical enterprise 1/9 months Months At higher deploy frequency, reliability increases
- 33. From code to production Source code External libraries Trusted base OS Repository, i.e. Github Build and test server, i.e. Jenkins, Circleci Source code Static and dynamic testing Security testing
- 34. Old School Auditor shock • Testing in production? • No patching of servers? • No weekly CAB meetings?
- 35. Lean production & the three ways of DevOps 1. Systems thinking: reduce Muda 2. Rapid feedback loops: Jidoka 3. Continuous improvement: Kaizen, Chaos engineering
- 36. Elementsof CloudSecurity • Controls instead of ownership • Hyper segregation andautomated deployment Infrastructure • Encryption • Key management at scale Data • Ecosystem includes Security as a Service • DevSecOps andArchitect for failure Application • Federated IDM • Account androle segregation User • Contracts, SLA, Exit plan • Continuous monitoring andlogging Governance
- 37. C o u r s e s t r u c t u r e Infrastructuresecurityforcloud Managingcloud security& risk Data securityforcloud Introto cloudcomputing Securingcloudapplications,users,&relatedtechnologies Cloudsecurity operations 1 • NIST definitions • Essential characteristics • Service models • Deployment models 2 3 4 5 6 • Securing base infrastructure • Management plane security • Securing virtual hosts & networks • IaaS, PaaS, SaaS security • Risk & governance • Legal & compliance • Audit • Data governance • Cloud data architectures • Data security & encryption • CASB and data loss prevention • BC/DR • Application security • Identity & access management • Related technologies • What to look for in a cloud provider • Security as a Service • Incident response CCSK Course Structure
- 38. Summary • Cloud computing is just part of the industrialization of IT • Automated testing and quality control is essential to move to the next level of productivity
- 39. More on CCSK and CSA • Meet Eirik Gulbrandsen
- 40. More info Q & A
Editor's Notes
- My name is Peter van Eijk, and I am one of the world’s most experienced independent cloud computing trainers. Let me talk to you about why cloud computing is the future of IT, and why it is the future of your job in IT. IT has always been a pretty dynamic environment, but cloud computing may well be the biggest change in the industry so far. So what do you think? Is cloud computing the next wave in Information technology?
- is it a load of marketing hype,
- or is it a jump into the deep? There is truth in all of these. Personally
- I think that Cloud computing is primarily a state of mind, a way of thinking. And for some reason or another, this picture is more funny in Amsterdam
- Let’s assume that you work with IT. As an IT manager, systems or solutions architect, or any other IT role. Or you are involved in procuring IT or as an auditor or on the legal side of IT. I will give you a new perspective on how to organize IT, and that view will allow you to figure out which part of your job will disappear, and which part of your job will grow. So, cloud computing is a revolutionary change. Or is it? Maybe cloud computing is following the same rules as other maturing industries. To understand the future, we must first understand the past.
- The first commercial applications of IT were on the mainframe. Which is a single computer filling a large room. There was one department running it, and it was serving an entire company. It had lots of people managing it. This is the kind of hardware that I wrote my first computer program on in 1973.
- Then we move to client server, in the eighties, where basically every department had a computer. And each computer had its own system manager. So ownership changed a lot here, as well as the way in which decisions were made on computing. Then came the PC, and a little later: the internet. One of the things that happened there was that companies no longer owned all the computers that users worked on. We moved stuff to customers that worked on their own computers. People at home owned them. Once again a shift in the way ownership and responsibility for it was organized. Then we get the breakthrough of cloud computing. Where companies no longer even own the servers that they work on. One way of looking at this whole shift is looking at who runs it, who pays the electricity bill? Is it a central department? Is it each business unit? Is it the user? Or is it totally outsourced to another company? In a few minutes we will look at how the amount of people changes that we need to run one computer. Just remember that it took a whole team to manage a single mainframe computer. Now each of these steps: mainframe, client/server, PC, cloud, is a disruptive change.
- It is a big step change, it is not a gradual change. It is a change that really brings us to a different level of understanding and management. And disruptive change is not a trendy marketing word, it is a solid business innovation concept developed by Harvard Business School Professor Clayton Christensen. According to Christensen, and I am simplifying here, A disruptive innovation is about something that is not as good, initially, as the thing that it replaces. But it is much cheaper, so it appeals to people who were “overserved” by the original product. Customers Who could not afford the original product. And because of this, there is a good business model, and the new provider can afford to innovate further. Which means it can be rapidly improving. And when it is rapidly improving, it will eventually overtake the original and replace it and drive it out of the market. Let’s look at some examples here. Like Wikipedia, to start with. What was Wikipedia to begin with? It was nothing more than a handful of articles. Nowhere near the completeness of the encyclopedia Britannica. But it was good enough for a lot of people, and it was definitely a lot cheaper than the encyclopedia Britannica. Fast forward a couple of years, and which is the one that survives? Is it Wikipedia or is it the encyclopedia Britannica? The PC is another example. The original PC was a really simple machine. It had only 64 Kilobytes of memory. I remember that I saw one and I was thinking: you cannot take this seriously. This is not a real computer, It cant even multitask. 64 Kilobytes? Are you joking? My bootloader is bigger than that. But is has innovated and innovated and innovated, and we have now come to the point that your average server is a souped up PC that is more powerful than the mainframe that it replaces. That is what we call a disruptive innovation. (6’12). Of course, then we have the internet replacing leased lines at a fraction of the cost. And the next thing up: cloud computing. In the beginning, it did not sound like much, but it has evolved and evolved, and right now we have to understand that cloud computing can actually be better, cheaper, and safer than the style of computing it replaces. A few years ago for example, I was measuring the uptime of cloud services, and back then they were already better than most corporate IT. Each of these disruptive innovations has something you might call a tipping point.
- Disruptive innovation leads to Tipping Points (Malcolm Gladwell). Each of these disruptive innovations has something you might call a tipping point. For a long time the world is on one side, and suddenly, like a seesaw, it has tipped to the other side. Once it passes the threshold, most of it suddenly moves to the other side. You go like, hey, what happened? And if you are one of the people whose job is involved in that change, you can complain about it. You can say, it is a change for the worse, the mainframe was such a good machine. You can start complaining about it, you can keep complaining about it, or you can try to find out what you have learned in your last job, and carry that over to the next generation of technology. I think you can do that, but that is a different story. So the end result for this, for IT, is that it is not your daddy’s datacenter anymore.
- So the end result for this, for IT, is that it is not your daddy’s datacenter anymore. You know, the big fortress on the hill, protected by a large moat and big walls. It is no longer there. This is no longer the model for IT. Digital data is no longer confined to the walls of the data center. It is the whole world that is being connected,
- It is the whole world that is being connected, and your systems are basically plugged in to that giant world wide grid of interconnected machines. Now what makes these developments happening? The biggest driver for information technology is Moore’s law
- https://www.flickr.com/photos/jurvetson/25046013104 The biggest driver for information technology is Moore’s law (8:17). [plaatje nodig] Where we can see that every two years the number of components on a chip doubles. As a result, the capacity in terms of processing and storage, increases by more than an order of magnitude every decade. In my lifetime I have seen the price/performance ratio of computing, storage and bandwidth improve by a factor of 1 million. That drop in price, goes hand in hand with an increase in the amount of IT stuff that we have to manage. And you can imagine, is also is like orders of magnitude. And what does that mean for the number of people that have to manage this? Is that increasing by orders of magnitude as well? No, it is not, because we don’t have that many people. The productivity of managing that IT really has to go up. And it actually does go up. We started out with 10 people managing one computer, a little later it was one person managing one computer, then one person managing 10 computers. And now we see for specific functions people managing thousands or even tens of thousands of computers. So that productivity has to go up. At the same time, we need a lot more skills to run that stuff.
- At the same time, we need a lot more skills to run that stuff. We have more technology, more components, more programming languages, more interfaces, more different devices, more existing software. And our IT is having more of an impact on business and society. From the back office, it expanded into the front office, and from the front office, it moved to * being * the product for some companies. Think Netflix, Uber, Airbnb. But just about every company cannot go back to manual order taking or production control. And the threat landscape in terms of the number of people that are trying to hack and abuse that technology is also increasing rapidly. Not to mention * their* skill level. That means that we need a lot more brain power to manage all that IT. A lot more brainpower. And it is no longer feasible anymore to run that IT entirely in your own shop. We need a way to organize IT that does not force us to deploy a hundred skilled people for a one hundred person company. (11:39) Now let’s look at how that problem has been addressed historically.
- Henry Ford allegedly invented, or at least made big, the assembly line method of automobile production. Where a lot of people were working on very specialist jobs in that assembly line. And that made productivity really go up massively. In IT it is no different. We have specialists for just about everything. Network engineers, server and storage admins. Database administrators, front end and back end software developers. And so on. But the parallels go much deeper.
- Ford, River Rouge plant In this picture here you can see how Ford’s assembly line was laid out in his River Rouge factory. It was built out between 1910 and 1920. It is still there. The River Rouge plant was the first full assembly line cranking out cars. On one end of the factory, through the River Rouge, ships would come in with iron ore. On the other end T-Fords would come out. In between was the assembly line and everything needed to produce the car. The Ford company had its own steel mill, its own electricity plant, its own glass factory. Everything was there on the River Rouge plant. At the time it was the largest industrial estate in the world. But after the assembly line was introduced, other changes started happening. Fast forward a couple of decades later, and this plant is no longer exclusively owned by the Ford Motor Company. What happened was that that division of labor was extended beyond the company. Components of the whole factory were outsourced. The Ford company no longer owns the steel mill; it is outsourced to another company with more steel mills. It no longer owns the electricity plant, that is now part of a large electricity company.
- Again we see specialization, this time beyond the borders of a specific company. The assembly line has now become part of a supply chain of companies, each of which delivers to the next company downstream in the flow of goods. Specialization of labor above the level of an individual company. And currently only twenty percent of the value of the car is produced by the car company, the rest is outsourced. The same has happened with Apple.
- First 50 Apple I were soldered together in the kitchen of steve jobs parents. The same has happened with Apple. The original Apple 1 computer, was developed around 1978 by Steven Jobs and Steve Wozniak. The first order was 50 of these, by an electronics shop. They soldered these together on the kitchen table in Steven Jobs parent’s house. Again, fast forward a few decades, and this is what the iPhone supply chain looks like now. It
- First 50 Apple I were soldered together in the kitchen of steve jobs parents. Again, fast forward a few decades, and this is what the iPhone supply chain looks like now. It is produced around the entire world. Apple no longer manufactures these; it is all outsourced. The only thing that Apple does is design them, and market them. They are produced in Global supply chains. But this also creates its own new problems. In a supply chain we can no longer solve production glitches by having one department head talk to another department head.
- We need to make the control over that supply chain more explicit. I ran into an example of that last year, when I was delivering a course in Tunisia. At night in the hotel I chatted up with a German guy. Turns out he was there to audit the supply chain of a big German car manufacturer. A company in Tunisia was producing a part of the electrical system of the car. Not even the whole electrical system. The guy was out there to audit their process; he did not even look much at the product, only at the process. If the process is good, the product will be good. And he was coming back every couple of months or so to audit that part of the supply chain. He also explained that if this company stopped delivering, the assembly line in Germany would stop in 48 hours. So they had strict delivery agreements, and fines when they failed.
- The upshot of all this is that today’s car is not only cheaper, comparatively, it is also more fuel efficient, more functional, safer, it is better in all dimensions. You can even get it in another color than black. And this is how specialization of labor in a supply chain works. And with cloud computing, it is a similar thing. Cloud companies basically create an IT services supply chain. And here is a diagram that shows how that might look like, simplified.
- As a cloud customer, you consume services from a Software as a Services provider. And a lot of these SaaS providers actually have their infrastructure sourced upstream. Of course, the reality is a little bit more complicated than this. It more looks like this picture.
- Where you have a ton of SaaS providers, the average company has a few hundred. Similarly a lot of Platform providers upstream. And then it is all hosted on Amazon. No, just kidding, there is also hosting on Microsoft, Google and a few others. And some SaaS providers actually host it themselves. So there you have it, the IT services supply chain. The new model for delivering IT services. Better, cheaper, safer (potentially). More complicated, more moving parts, more people to manage it. Different ways to control it. Now once we have this, what happens (17:56)? Once we have this, new things become possible. New things that might include your future job role.
- This could be an animation with Powtoon.
- AAC-02 Independent reviews and assessments shall be performed at least annually to ensure that the organization addresses nonconformities of established policies, standards, procedures and compliance obligations.
- Updated to the Guidance v4 sequence
- Once we have this, new things become possible. New things that might include your future job role.
- Once we have programmable infrastructure, we can do automated integration, automated testing, automated deployment. We can do DevOps. Once we have flexible capacity at scale, we can do Big Data. Once we have that stuff out there, on the network, it makes more sense to develop social and mobile applications. For individuals as well as for companies. And as a consequence, it has never been cheaper, or easier, to start a software company. Or set up any company’s IT, for that matter. I reckon that, if you put your mind to it, even with a team of just 2 or 3 people, you can start a company, including its development pipeline, in less than a day, just by procuring the right cloud services. Let’s focus on one of these. The one that is really driving this IT transformation, from the business perspective, is the devops revolution. Back in the old days, a new version of the software was released once a year. It took a while to implement. It had to be installed on all the machines, databases migrated and so on. Very complicated. With DevOps, you automate a lot of the entire software development and deployment pipeline. This is called continuous integration, or even continuous delivery. And it allows companies such as Amazon, Netflix, banks, to deploy new services, or bits of services, literally thousands of times a day.
- And that creates, for their business, enormous agility. Enormous feature velocity. Which allows them to innovate quicker and better, and adapt quicker to the market. And as you remember from Darwin, it is not the strongest of species that survive, but the ones that can adapt to changing circumstances quicker. It is the same for companies. Now if you are in IT, or related to IT, what are you going to do with this? What should you do? This is the new world, this is inevitable. It is already there. This is the new way that IT will be ran. Of course, it will take another 10 years for this to reach 95% saturation, but there is only one way, one direction, that this is going. We still have mainframes, but there is not a lot of work in mainframes. We still have minicomputers, but there is not a lot of work in minicomputers anymore. We still have PCs, but there is not so much work in managing these anymore. In fact we are often leaving that to the users. Cloud computing is where the new action is. If you want to succeed in that world, you have to know about the nuts and bolts, how is it pieced together. You have to know how to control suppliers, and everybody in that ecosystem upstream from you. And demonstrate to the people downstream that you are in control. You have to know how to control all kinds of risks. And you need to know where you fit in that ecosystem. Don’t be stuck. And once you get it, there is a great new world out there.
- Check-in source code into repository (i.e. github) Repository triggers build server (i.e. jenkins or codeship (service)) Build server runs build (i.e. ‘make’ ), includes external components and patches Build server runs tests (unit, integration, performance, security) Tests that fail get notified back to developer (might also be github) Build server then pushes runnable image to image repository (VM or container) ‘The other side of the wall’ picks up the images (note Mark Coleman had sheets hier over) Autoscaler decides to instantiate more instances and orchestrates the workflow around that (notifying load balancer, security policies etc). Example ecosystems here are Mesos ? Kubernetes? Once image boots up (this is almost always a firstboot), it will update for patches, runs a health check / security scan and reports for duty to the orchestrator. The load balance can have additional intelligence in actually directing traffic to the various (versions) of instances.