Technology (22)

If you’re like most businesses, you already have at least one workload running in the cloud. However, that doesn’t mean that cloud migration is right for everyone. While cloud environments are generally scalable, reliable, and highly available, those won’t be the only considerations driving your decision.
For companies considering their first cloud migration, there are a lot of factors that you’ll want to take into account, from the benefits and the risks, to the cloud service model and type that is right for your business. In this post, we’ll look at the high-level elements that you should consider as you contemplate a move to the cloud.

Potential Benefits of Cloud Migration

There are many problems that moving to the cloud can solve. Here are some typical scenarios that will benefit from cloud migration.

• • Your application is experiencing increased traffic and it’s becoming difficult to scale resources on the fly to meet the increasing demand.
  • You need to reduce operational costs, while increasing the effectiveness of IT processes.
  • Your clients require fast application implementation and deployment, and thus want to focus more on development while reducing infrastructure overhead.
  • Your clients want to expand their business geographically, but you suspect that setting up a multi-region infrastructure – with all the associated maintenance, time, human, and error control effort – is going to be a challenge.
  • It’s becoming more difficult and expensive to keep up with your growing storage needs.
  • You’d like to build a widely distributed development team. Cloud computing environments allow remotely located employees to access applications and work via the Internet.
  • You need to establish a disaster recovery system but setting it up for an entire data center could double the cost. It would also require a complex disaster recovery plan. Cloud disaster recovery systems can be implemented much more quickly and give you much better control over your resources.
  • Tracking and upgrading underlying server software is a time consuming, yet essential process that requires periodic and sometimes immediate upgrades. In some cases, a cloud provider will take care of this automatically. Some cloud computing models similarly handle many administration tasks such as database backup, software upgrades, and periodic maintenance.
  • Capex to Opex: Cloud computing shifts IT expenditure to a pay-as-you-go model, which is an attractive benefit, especially for startups.

Potential Risks of Cloud Migration

While your specific environment will determine the risks that apply to you, there are some general drawbacks associated with cloud migrations that you will want to consider.

• • If your application stores and retrieves very sensitive data, you might not be able to maintain it in the cloud. Similarly, compliance requirements could also limit your choices.
  • If your existing setup is meeting your needs, doesn’t demand much maintenance, scaling, and availability, and your customers are all happy, why mess with it?
  • If some of the technology you currently rely on is proprietary, you may not be legally able to deploy it to the cloud.
  • Some operations might suffer from added latency when using cloud applications over the internet.
  • If your hardware is controlled by someone else, you might lose some transparency and control when debugging performance issues.
  • Noisy “neighbors” can occasionally make themselves “heard” through shared resources.
  • Your particular application design and architecture might not completely follow distributed cloud architectures, and therefore may require some amount of modification before moving them to the cloud
  • Cloud platform or vendor lock-in: Once in it might be difficult to leave or move between platforms.

What Cloud Service Model Do You Need?

Now that you’ve decided to try the cloud, you’ll have to choose the cloud computing service model that you would like to deploy it in. These are the most common service models:

• • IaaS: Infrastructure as a service is a form of cloud computing that provides virtualized computing resources over the internet.
  • PaaS: Platform as a Service is a category of cloud computing services that provides a platform allowing customers to develop, run, and manage applications without the complexity of building and maintaining the infrastructure associated with developing and launching an app.
  • SaaS: Software as a service is a software licensing and delivery model in which software is licensed on a subscription basis and is centrally hosted.

Here’s where you’ll have to make an important choice.
IaaS is best for companies that don’t mind hosting their applications in third-party data centers, but would prefer to outsource the care of their physical infrastructure to concentrate more completely on developing, deployment, and monitoring.
However, if you prefer your applications to be portable, you might want to simply drop your code onto a robust PaaS platform that provides a full (and invisible) infrastructure environment. SaaS is a delivery model through which centrally hosted productivity software is licensed on a subscription basis.

Public, Private, or Hybrid?

Assuming you’ve chosen a cloud model, it’s time to choose the cloud type. There are three basic options:
Public: Your resources are entirely hosted by a cloud provider like Amazon Web Services (AWS).
Private: You create your own private cloud using a platform like OpenStack or VMware’s vCloud.
Hybrid: Your resources are spread over both private and public platforms.
With its healthy mix of on-demand reliability, high availability, security, and reduced operations costs, hybrid cloud implementations can be attractive. Going hybrid can sometimes give you the best of both worlds.I’ll illustrate how hybrid can work through a hypothetical scenario.
Let’s imagine that your web app is quickly gaining popularity and users. In order to keep up with the growing demand, you need the underlying resource to scale up dynamically. During peak usage, you should be able to deploy maximum resources to serve requests, and when demand drops, you should ideally be able to simply drop unneeded resources to save costs. This is possible within a public cloud. But suppose the data your app gathers is highly confidential and can’t just be stored off-premise. This is where a hybrid solution can help. In this case, you can choose which components you want to live in the public cloud, and which will remain in your data center.
RightScale reported that enterprises are increasingly adopting a multi-cloud strategy (81%), and 51% plan to use hybrid clouds.

Assessing Applications for a Cloud Migration

Having chosen a cloud model and cloud type, the real struggle is about to begin. Now, it’s time to see if your applications are cloud-ready. Here are some factors that you will need to consider:

• Application design complexity: Some traditional applications are so complicated and tightly coupled that customers might not be willing to rework it. However, the foremost requirement for any successful migration is that the app should follow a distributed architecture and should be scalable by design. Tools like PaaSLane and Cloudamize can help you assess your applications’ cloud-readiness. AWS’s Migration Hub service is a one-stop shop for everything you might need tool-wise to discover and assess your application’s readiness for cloud migration.
• Integration complexity: Every application has its integration points, such as payment gateways, SMTP servers, web services, external storage, and third party vendors. It’s very important to analyze the impact your cloud migration will have on those dependencies. Sometimes you will experience unexpected connectivity or authentication challenges that you should identify and solve up front.The most critical (and tedious) task is to identify all of those integration points. Since older applications might be poorly documented and the developers familiar with the end-to-end functional and non-functional details may no longer be available, you might have to go through each module manually. The task gets complicated if you’re considering migrating hundreds of applications currently running in your data center.

  Many of these issues can be addressed through a combination of the familiarity your team has with the apps and an asset discovery tool (either open source or commercial). An asset discovery tool can help you identify entire server configurations within a network, along with connectivity details.

  For example, say that you have a data center within a network that is hosting around 100 applications. A discovery tool can give you the bird’s eye view of the entire system. It can also provide granular details that can be helpful for a general capacity management assessment.

  Some of the better-known asset discovery tools include BMC Atrium and HP DDMA. Cloudamize provides a tool that can perform automated discovery of applications and machines, and additionally perform automated application dependency mapping to discover dependencies between applications.

• The host operating system: Once you have decided on a cloud migration, it’s important to know whether you will be able to deploy your applications on the same OS. Your applications may only run on a specific OS (or OS release). If it’s not compatible with your cloud provider, then you need to find a workable substitute OS, a different cloud provider, or simply give up the whole project.For instance, most cloud providers don’t provide 32-bit OS options and others might have unexpected subscription requirements. It’s best to do your research in advance.
• The application database: A database is obviously a critical part of any application. Customers invest a great deal on database servers and, often, licenses. Moreover, given the complexity and sensitivity of your data, you just might not want to move it right now: migrating petabytes of data is no trivial undertaking.In either case, you should make sure that the migration methods you use are highly reliable and come with the possibility of roll backs to deal with any unexpected chaos. Most cloud providers offer their own migration services. Therefore, it’s very important to evaluate those services before pushing the “start” button.
• Network: Most cloud environments don’t support multicasting, so if your application relies on multicast, then I would say “think twice.”

Cost Comparison

Aphelion like many cloud providers have pricing calculators that can help you to estimate the real costs you’ll face after a cloud migration vs. your current costs so you can decide which option is the best fit based on your current application workload profiles.

Proof of Concept

It’s always a great idea to build a small proof of concept (POC) before you actually migrate your workload to the cloud. I know such models won’t anticipate all possible issues, but it will give you greater clarity and understanding about the challenges you may face. Some of the things you should look for during your POC include:
• Performance comparisons with your existing application
• Complexity levels involved in migrating the application
• Network challenges that need to be worked out
• Reliability
• Cloud provider support evaluation
Addressing all the real-time challenges of a cloud migration cannot be captured in one post, but we have tried to address some common issues you should consider before you start the process. Contact us to see how we can help with your migration strategy.

If you are planning to deliver digital services of any kind, you’ll need to calculate resources including CPU, memory, storage, and network connectivity. Which resources you choose for your delivery, cloud-based or local, is up to you. But you’ll definitely want to do your homework first.
Cloud computing has benefited many enterprises by reducing costs and enabling a focus on core business competence, rather than IT and infrastructure issues. Despite the general hype, there can be disadvantages to cloud computing, especially in smaller operations. In this post, we will explore some of the key disadvantages and share tips and best practices that your teams can employ to address them.

Disadvantages of Cloud Computing Explained

1) Downtime

Downtime is often cited as one of the biggest disadvantages of cloud computing. Since cloud computing systems are internet-based, service outages are always an unfortunate possibility and can occur for any reason.
Can your business afford the impacts of an outage or slowdown? An outage on Amazon Web Services in 2017 cost publicly traded companies up to $150 million dollars and no organization is immune, especially when critical business processes cannot afford to be interrupted.
Best Practices for minimizing planned downtime in a cloud environment:

• Design services with high availability and disaster recovery in mind. Leverage the multi- availability zones provided by cloud vendors in your infrastructure.
• If your services have a low tolerance for failure, consider multi-region deployments with automated failover to ensure the best business continuity possible.
• Define and implement a disaster recovery plan in line with your business objectives that provide the lowest possible recovery time (RTO) and recovery point objectives (RPO).
• Consider implementing dedicated connectivity. These services provide a dedicated network connection between you and the cloud service point of presence. This can reduce exposure to the risk of business interruption from the public internet.

2) Security and Privacy

Any discussion involving data must address security and privacy, especially when it comes to managing sensitive data. We must not forget what happened at Code Space and the hacking of their AWS EC2 console, which led to data deletion and the eventual shutdown of the company. Their dependence on remote cloud-based infrastructure meant taking on the risks of outsourcing everything.
Of course, any cloud service provider is expected to manage and safeguard the underlying hardware infrastructure of a deployment. However, your responsibilities lie in the realm of user access management, and it’s up to you to carefully weigh all the risk scenarios.
Though recent breaches of credit card data and user login credentials are still fresh in the minds of the public, steps have been taken to ensure the safety of data. One such example is the General Data Protection Rule (GDPR), recently enacted in the European Union to provide users more control over their data. Nonetheless, you still need to be aware of your responsibilities and follow best practices.
Best practices for minimizing security and privacy risks:

• Understand the shared responsibility model of your cloud provider outlining which security controls are their responsibility and which are yours.
• Implement security at every level of your cloud deployment.
• Know who is supposed to have access to each resource and service and limit access to least privilege.
• Make sure your team’s skills are up to the task: Solid security skills and regular training for your team is one of the best ways to mitigate security and privacy concerns in the cloud.
• Take a risk-based approach to securing assets used in the cloud
• Extend security through to the device.
• Implement multi-factor authentication for all accounts accessing sensitive data or systems.

3) Vulnerability to Attack

In cloud computing, every component is online, which exposes potential vulnerabilities. Even the best teams suffer severe attacks and security breaches from time to time. Since cloud computing is built as a public service, it’s easy to run before you learn to walk. After all, no one at a cloud vendor checks your administration skills before granting you an account: all it takes to get started is generally a valid credit card.
Best practices to help you reduce cloud attacks:

• Make security a core aspect of all IT operations.
• Keep ALL your teams up to date with cloud security best practices.
• Ensure security policies and procedures are regularly checked and reviewed.
• Proactively classify information and apply access control.
• Prevent data exfiltration.
• Integrate prevention and response strategies into security operations.
• Discover rogue projects with audits.
• Remove password access from accounts that do not need to log in to services.
• Review and rotate access keys and access credentials.
• Follow security blogs and announcements to be aware of known attacks.
• Apply security best practices for any open source software that you are using.

These practices will help your organization monitor for the exposure and movement of critical data, defend crucial systems from attack and compromise, and authenticate access to infrastructure and data to protect against further risks.

4) Limited control and flexibility

To varying degrees (depending on the particular service), cloud users may find they have less control over the function and execution of services within cloud-hosted infrastructure. A cloud provider’s end-user license agreement (EULA) and management policies might impose limits on what customers can do with their deployments. Customers retain control of their applications, data, and services, but may not have the same level of control over their back-end infrastructure.
Best practices for maintaining control and flexibility:

• Consider using a cloud provider partner to help with implementing, running, and supporting cloud services.
• Understanding your responsibilities and the responsibilities of the cloud vendor in the shared responsibility model will reduce the chance of omission or error.
• Make time to understand your cloud service provider’s basic level of support. Will this service level meet your support requirements? Most cloud providers offer additional support tiers over and above the basic support for an additional cost.
• Make sure you understand the service level agreement (SLA) concerning the infrastructure and services that you’re going to use and how that will impact your agreements with your customers.

5) Vendor Lock-In

Vendor lock-in is another perceived disadvantage of cloud computing. Differences between vendor platforms may create difficulties in migrating from one cloud platform to another, which could equate to additional costs and configuration complexities. Gaps or compromises made during a migration could also expose your data to additional security and privacy vulnerabilities.
Best practices to decrease dependency:

• Design with cloud architecture best practices in mind. All cloud services provide the opportunity to improve availability and performance, decouple layers, and reduce performance bottlenecks. If you have built your services using cloud architecture best practices, you are less likely to have issues porting from one cloud platform to another.
• Properly understanding what your vendors are selling can help avoid lock-in challenges.
• Employing a multi-cloud strategy is another way to avoid vendor lock-in. While this may add both development and operational complexity to your deployments, it doesn’t have to be a deal breaker. Training can help prepare teams to architect and select best-fit technologies and services.
• Incorporate flexibility as a matter of strategy when designing applications to ensure portability now and in the future.

6) Costs

Adopting cloud solutions on a small scale and for short-term projects can be perceived as being expensive. Pay-as-you-go cloud services can provide more flexibility and lower hardware costs, however, the overall price tag could end up being higher than you expected. Until you are sure of what will work best for you, it’s a good idea to experiment with a variety of offerings.
Best practices to reduce costs:

• Try not to over-provision, instead of looking into using auto-scaling services
• Scale DOWN as well as UP
• Pre-pay if you have a known minimum usage
• Stop your instances when they are not being used
• Create alerts to track cloud spending

Disadvantages of Cloud Computing: Closing Thoughts

Many organizations benefit from the agility, scale, and pay-per-use billing that cloud services offer. However, as with any infrastructure service, the suitability of cloud computing for your specific use case should be assessed in a risk-based evaluation.  Build in time for research and planning to understand how the cloud will affect your business.

Over the last several years, the clouds have rolled in over enterprise IT. These clouds aren’t dark ones obscuring the sun, however; in fact they’ve made the enterprise computing horizon much brighter. Going from a relatively unheard-of concept ten years ago, the cloud has become a popular buzzword seizing hold of the collective conscious of CIOs and directors of IT at companies across industries, sizes, and revenues for its promise of organizational transformation.

A large amount of enterprises have already built their own private cloud networks, hosting essential applications and providing anywhere, anytime access to mission critical data for employees scattered across the world. While it’s a large undertaking, in many cases the effort pays off, resulting in increased productivity and ease of access.

And there’s no shortage of companies that have built public cloud offerings to leverage this trend, with tech giants like Amazon, Google, Microsoft, and Oracle all having entered into the market in the last few years, not to mention the thousands of smaller service providers offering more niche solutions for the organizations that need them. These services can be a cheaper alternative to building an internal private cloud infrastructure, or can provide a necessary extension of the limits of a private cloud, allowing for occasional bursts in computing power.

Many organizations have started to blend both private and public cloud offerings to create a hybrid cloud infrastructure. These hybrid clouds exploit the control and security of a private cloud, along with the flexibility and low cost of public cloud offerings. Together they form a powerful solution to meet the increased demands on IT from the rest of the organization.

Cloud computing has a seemingly endless list of reasons for why companies should adopt it: cost savings, improved security, enhanced agility, greater accessibility and flexibility, among many others. Implementing newer technology always poses risks and challenges that must be taken into account and built into the plan for rollout though. For that reason, we’ve put together this helpful guide with the best practices for building a hybrid cloud for your organization. Read on to learn more.

Benefits of Building a Hybrid Cloud

One of the foremost benefits of implementing a hybrid cloud approach is cost savings. Instead of having to spend the money and build infrastructure to withstand occasional bursts in system usage that only happen a small fraction of the time, organizations can leverage public cloud offerings to offload some of the heavy usage, and only have to pay for it when they need it. With less money spent on infrastructure, more funds can be devoted to other critical projects that help move the business forward, instead of holding it back.

Improved Security is another major benefit of hybrid clouds. While the perception that the cloud is insecure is a persistent one among members of traditional IT teams, TechTarget reports that users of service-provider environments actually suffer from less attacks than on-premise users do. The myth that cloud computing is less secure than traditional approaches can lend itself to the fact that having things stored off-premises feels less secure, however this is not the case. Cloud computing can offer increased security for organizations utilizing it.

Another major benefit of hybrid clouds is enhanced organizational agility. By leveraging the public cloud in times of heavy usage, the organization can experience fewer outages and less downtime. For developing and testing new applications, the hybrid cloud also offers an attractive option for hosting them–buying time until a decision is eventually made as to where to host it permanently.

With employees becoming increasingly mobile, greater accessibility to business-critical applications is a necessity for any 21st century enterprise. Gone are the days when employees only need to access their email when they’re at their desks, or only need to update a spreadsheet or access an application during business hours. Business happens 24/7 nowadays, and for companies to compete effectively, the cloud offers the advantage of anywhere, anytime access.

Although the benefits outweigh the negatives in most cases, building a hybrid cloud poses a number of challenges, and for this reason, it may not be the solution for every company.

Challenges of Building a Hybrid Cloud

It takes tools and skills to effectively operate a hybrid cloud solution. Not everyone has these skills, and it can cost a pretty penny to get them. If your organization has recently decided to make the move to the cloud, it might be necessary to look for outside talent that has the necessary skillset to accomplish it. Moreover, the team implementing the project will probably need additional training to learn the systems, and all of this costs money; bringing us to our next point…

Cost plays a major role in planning to execute a hybrid cloud strategy. While the public cloud can offer an attractive option for its flexibility and relatively low cost to operate, building a private enterprise cloud requires significant expenditure and can become expensive very quickly with all the physical hardware necessary. At the same time, heavy use of public cloud resources can rack up unexpectedly high usage bills that may not have been planned for. When outlining a budget for a hybrid cloud project, make sure to factor in all of these difficult-to-plan for costs.

Security is at the forefront of everyone’s mind these days when they think of the cloud. While we’ve already seen that cloud computing is not inherently any less secure than traditional computing, and in fact faces fewer attacks, there are still considerations to take into account when building out a hybrid cloud. The proper precautions must be taken to ensure data is properly protected and that control is maintained by the right people. Additionally, depending on the industry, there may be certain regulatory requirements that prohibit data from being stored off-site, which would prevent the use of a public cloud entirely.

Data and application integration serves as a second challenge to take into account while building a hybrid cloud. Applications and data exist in a symbiotic relationship, with each one being useless without the other. Oftentimes they’re chained together. So when considering where to store each of them, it’s essential to ask whether the infrastructure they’re placed on matters. For example, if an application lives in a private cloud and it’s data lives in an on-prem data center, is the application built in order to access the data remotely? Technologies like copy data virtualization can decouple data from infrastructure and make this problem less of a headache.

Compatibility across infrastructure can prove itself to be a major issue when building a hybrid cloud. With dual levels of infrastructure, a private cloud that the company controls, and a public one that the company doesn’t, the chances are that they will be running different stacks. Can you manage both using the same tools, or will your team have to learn a new set in order to effectively oversee them?

Networking is another factor to consider in hybrid integration and there are a number of questions one must ask while designing the network around it. For instance, will very active applications be living in the cloud? It’s necessary to consider the bandwidth usage that this could take up on the network, and whether or not it could cause problems in bottlenecking other applications.

Like every IT project, building an enterprise hybrid cloud brings along many benefits and challenges. When properly accounted for during planning, organizations can minimize these difficulties and maximize the benefits they bring for the company.

The growing and evolving cyber security risk facing global businesses can be stemmed by the integration of AI into security systems 

Hyper-connected workplaces and the growth of cloud and mobile technologies have sparked a chain reaction when it comes to security risks. The vast volume of connected devices feeding into networks provide a dream scenario for cyber criminals — new and plentiful access points to target. Further, security on these access points is often deficient.

For businesses, the desire to leverage IoT is tempered by the latest mega breach or DDoS attack creating splashy headlines and causing concern.

However, the convenience and automation IoT affords means it isn’t an ephemeral trend. Businesses need to look to new technologies, like AI, to effectively protect their customers as they broaden their perimeter.

The question becomes, how can enterprises work with, and not against, artificial intelligence?

>See also: How AI has created an arms race in the battle against cybercrime

The emergence of AI in cyber security

Machine learning and artificial intelligence (AI) are being applied more broadly across industries and applications than ever before as computing power, data collection and storage capabilities increase. This vast trove of data is valuable fodder for AI, which can process and analyse everything captured to understand new trends and details.

For cyber security, this means new exploits and weaknesses can quickly be identified and analysed to help mitigate further attacks. It has the ability to take some of the pressure off human security “colleagues.” They are alerted when an action is needed, but also can spend their time working on more creative, fruitful endeavours.

A useful analogy is to think about the best security professional in your organisation. If you use this star employee to train your machine learning and artificial intelligence programs, the AI will be as smart as your star employee.

Now, if you take the time to train your machine learning and artificial intelligence programs with your 10 best employees, the outcome will be a solution that is as smart as your 10 best employees put together. And AI never takes a sick day.

It becomes a game of scale and leveraging these new tools can give enterprises the upper hand.

AI under attack

AI is by no means a cyber security panacea. When pitted directly against a human opponent, with clear circumvention goals, AI can be defeated. This doesn’t mean we shouldn’t use AI, it means we should understand its limitations.

AI cannot be left to its own devices. It needs human interaction and “training” in AI-speak to continue to learn and improve, correcting for false positives and cyber criminal innovations.

This hybrid approach already has proven itself to be a valuable asset in IT departments because it works efficiently alongside threat researchers.

Instead of highly talented personnel spending time on repetitive and mundane tasks, the machine takes away this burden and allows them to get on with the more challenging task of finding new and complex threats.

Predictive analytics will build on this by giving security teams the predictive insight needed to stop threats before they become an issue as opposed to reacting to a problem. This approach is not only more cost effective in terms of resources, but also is favourable for the business due to the huge reputational and financial damage a breach can cause in the long term.

Benefits of machine learning

Alongside AI, machine learning is becoming a vital tool in a threat hunter’s tool box. There is no doubt machine learning has become more sophisticated in the past couple of years and will continue to do so as its learnings are compounded and computing power increases.

Organisations face millions of threats each day, so it would be impossible for threat researchers to analyse and categorise them all. As each threat is analysed by the machine, it learns and improves. This not only helps protect organisations now, but compiles this valuable data for use in predictive analytics.

However, just staying ahead of the hackers and the threats they pose is not enough to protect organisations as the new vulnerabilities and new devices that come online will make this more and more difficult.

The continued and enhanced standardisation on data formats and communication standards is crucial to this effort. Once data flows and formats are clearly defined, not just technically but also semantically, machine learning systems will be far better placed to effectively police the operations of such systems.

The industry needs to work towards finding the sweet-spot between unsupervised and supervised machine learning so that we can fully benefit from our knowledge of current threat types and vectors and combine that with the ability to detect new attacks and uncover new vulnerabilities.

Much like AI, machine learning in threat hunting must be guided by humans. Human researchers are able to look beyond the anomalies that the machine may pick up and put context around the security situation to decide if a suspected attack is truly taking place.

The future

For the security industry to get the most out of AI, they need to recognise what machines do best and what people do best. Advances in AI can provide new tools for threat hunters, helping them protect new devices and networks even before a threat is classified by a human researcher.

Machine learning techniques such as unsupervised learning and continuous retraining can keep us ahead of the cyber criminals. However, hackers aren’t resting on their laurels. Let’s give our threat researchers the time to creatively think about the next attack vector while enhancing their abilities with machines.