Category: Cloud

The emergence of IoT devices, self-driving cars, and the likes, opened the floodgates of various user data. IoT devices brought-in so much data that even seemingly boundless computing capabilities of the cloud were not enough to maintain an instantaneous process and timely results. This is bad news in the case of data-reliant devices such as self-driving cars. 

Hopefully, there is a workaround solution – edge computing.

In this article, we will explain: 

• What edge computing is?
• The most prominent examples of edge computing;
• Benefits and challenges of implementing edge computing applications.

What is Edge Computing?

“Edge computing” is a type of distributed architecture in which data processing occurs close to the source of data, i.e., at the “edge” of the system. This approach reduces the need to bounce data back and forth between the cloud and device while maintaining consistent performance. 

With regards to infrastructure, edge computing is a network of local micro data centers for storage and processing purposes. At the same time, the central data center oversees the proceedings and gets valuable insights into the local data processing.

The term “edge” originates from the network diagrams. In it, “edge” is a point at which traffic comes in and goes out of the system. Since its location is at the edges of the diagram – its name reflects this fact.  

Edge Computing vs Cloud Computing: What’s the difference?

Edge computing is a kind of expansion of cloud computing architecture – an optimized solution for decentralized infrastructure. 

The main difference between cloud and edge computing is in the mode of infrastructure. 

• Cloud is centralized.
• Edge is decentralized.

The edge computing framework’s purpose is to be an efficient workaround for the high workload data processing and transmissions that are prone to cause significant system bottlenecks. 

• Since applications and data are closer to the source, the turnaround is quicker, and the system performance is better.

The critical requirement for the implementation of edge computing data processing is the time-sensitivity of data. Here’s what it means:

• When data is required for the proper functioning of the device (such as self-driving cars, drones, et al.);
• When information stream is a requirement for proper data analysis and related activities (such as virtual assistants and wearable IoT devices);

The time-sensitivity factor has formed two significant approaches to edge computing:

• Point of origin processing – when data processing happens within the IoT device itself (for example, as in self-driving cars);
• Intermediary server processing – when data processing is going through a nearby local server (as with virtual assistants). 

In addition to that, there is “non-time-sensitive” data required for all sorts of data analysis and storage that can be sent straight to the cloud-like any other type of data.

The intermediary server method is also used for remote/branch office configurations when the target user base is geographically diverse (in other words – all over the place). 

• In this case, the intermediary server replicates cloud services on the spot, and thus keeps performance consistent and maintains the high performance of the data processing sequence.

Why edge computing matter?

There are several reasons for the growing adoption of edge computing:

• The increasing use of mobile computing and “the internet of things” devices; 
• The decreasing cost of hardware.
• Internet of Things devices requires a high response time and considerable bandwidth for proper operation. 
• Cloud computing is centralized. Transmitting and processing massive quantities of raw data puts a significant load on the network’s bandwidth. 
• In addition to this, the constant movement of large quantities of data back and forth is beyond reasonable cost-effectiveness. 
• On the other hand, processing data on the spot, and then sending valuable data to the center, is a far more efficient solution.

Some edge computing examples

Voice Assistants

Voice assistant conversational interfaces are probably the most prominent example of edge computing at the consumer level. The most prominent examples of this type are Apple Siri, Google Assistant, Amazon Dot Echo, and the likes. 

• These applications combine voice recognition and process automation algorithms. 
• Both processes rely on data processing on the spot for initial proceedings (i.e. decode the request) and connection to the center to further refinement of the model (i.e. send results of the operation).

Self-driving cars 

At the moment, Tesla is one of the leading players in the autonomous vehicle market. The other automotive industry giants like Chrystler and BMW are also trying their hand at self-driving cars. In addition to this, Uber and Lyft are testing autonomous driving systems as a service.

• Self-driving cars process numerous streams of data: road conditions, car conditions, driving, and so on. 
• This data is then worked over by a mesh of different machine learning algorithms. This process requires rapid-fire data processing to gain situational awareness. Edge computing provides a self-driving car with this.

Healthcare

Healthcare is one of those industries that takes the most out of emerging technologies. Mobile edge computing is no different. 

Internet-of-things devices are extremely helpful when it comes to such healthcare data science tasks as patient monitoring and general health management. In addition to organizer features, it is able to check the heart and caloric rates. 

• Wearable IoT devices such as smartwatches are capable of monitoring the user’s state of health and even save lives on occasions if necessary. Apple smartwatch is one of the most prominent examples of a versatile wearable IoT. 
• IoT operation combines data processing on the spot (for initial proceedings) and subsequently on the cloud (for analytical purposes). 

Retail & eCommerce

Retail and eCommerce applies various edge computing applications (like geolocation beacons) to improve and refine customer experience and gather more ground-level business intelligence. 

Edge computing enables streamlined data gathering. 

• The raw data stream is sorted out on the spot (transactions, shopping patterns, etc);
• Known patterns like “toothbrushes and toothpaste being bought together” then go to the central cloud and further optimize the system.

As a result, the data analysis is more focused, which makes for more efficient service personalization and, furthermore, thorough analytics regarding supply, demand, and overall customer satisfaction. 

Here’s how different companies apply edge computing:

• Amazon is operating worldwide. As such, the system needs to be distributed regionally in order to balance out the workload. Because of that, Amazon is using intermediary servers to increase the speed of processing efficiency of the service on the spot.
• Walmart is using edge computing to process payments at the stores. This enables a much faster customer turnaround with lesser chances of getting into a bottleneck at the counter. 
• The target applies edge computing analytics to manage their supply chain. This contributes to their ability: 
• to react quickly to changes in product demand; 
• to offer customers different tiers of discounts, depending on the situation;

Benefits and challenges of edge computing

Edge computing Benefits

The benefits of edge computing form five categories:

1. Speed – edge computing allows processing data on the spot or at a local data center, thus reducing latency. As a result, data processing is faster than it would be when the data is ping-ponged to the cloud and back.
2. Security. There is a fair share of concerns regarding the security of IoT (more on that later). However, there is an upside too. The thing is – standard cloud architecture is centralized. This feature makes it vulnerable for DDoS and other troubles (check out our article on cloud security threats to know more). At the same time, edge computing spreads storage, processing, and related applications on devices and local data centers. This layout neutralizes the disruption of the whole network.  
3. Scalability – a combination of local data centers and dedicated devices can expand computational resources and enable more consistent performance. At the same time, this expansion doesn’t strain the bandwidth of the central network.
4. Versatility – edge computing enables the gathering of vast amounts of diverse valuable data. Edge computing handles raw data and allows the device service. In addition to this, the central network can receive data already prepared for further machine learning or data analysis. 
5. Reliability – with the operation proceedings occurring close to the user, the system is less dependent on the state of the central network. 

Edge computing challenges

Edge computing brings much-needed efficiency to IoT data processing. This aspect helps to maintain its timely and consistent performance. 

However, there are also a couple of challenging issues that come with the good stuff.

Overall, five key challenges come with the implementation of edge computing applications. Let’s take a closer look:

1. Network bandwidth – the traditional resource allocation scheme provides higher bandwidth for data centers, while endpoints receive the lower end. With the implementation of edge computing, these dynamics shift drastically as edge data processing requires significant bandwidth for proper workflow. The challenge is to maintain the balance between the two while maintaining high performance.
2. Geolocation – edge computing increases the role of the area in the data processing. To maintain proper workload and deliver consistent results, companies need to have a presence in local data centers. 
3. Security. Centralized cloud infrastructure enables unified security protocols. On the contrary, edge computing requires enforcing these protocols for remote servers, while security footprint and traffic patterns are harder to analyze.
4. Data Loss Protection and Backups. Centralized cloud infrastructure allows the integration of a system-wide data loss protection system. The decentralized infrastructure of edge computing requires additional monitoring and management systems to handle data from the edge. 
5. The edge computing framework requires a different approach to data storage and access management. While centralized infrastructure allows unified rules, in the case of edge computing, you need to keep an eye on every “edge” point.

In conclusion

The adoption of cloud computing brought data analytics to a new level. The interconnectivity of the cloud enabled a more thorough approach to capturing and analyzing data. 

With edge computing, things have become even more efficient. As a result, the quality of business operations has become higher.

Edge computing is a viable solution for data-driven operations that require lightning-fast results and a high level of flexibility, depending on the current state of things.

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PUBLIC VS. PRIVATE VS. HYBRID CLOUD COMPUTING

The adoption of cloud computing in the healthcare industry has brought a variety of options to the table – public, private and hybrid solutions, each with its pros and cons. Healthcare cloud computing new possibilities for organizations to refine their workflows and boost the efficiency of the operation. 

The healthcare industry is a good example of the effective implementation of hybrid cloud solutions. The thing is – each medical workflow has its own requirements in terms of needs and goals. Because of this, the solution needs to be both diverse in its application and efficient in providing scalable infrastructure for it.

We have already covered the differences between public, private, and hybrid clouds. This time, we are going to tell you: 

• Why a hybrid cloud model is the best option for healthcare? 
• Explain the benefits of cloud computing in healthcare.  

Why Hybrid Cloud is the best cloud solution for Healthcare?

As was stated previously, healthcare is one of those industries that embraces all sorts of innovations in order to refine operations and make them reliable and effective. Hybrid Cloud is no different in that regard. 

In the past, the healthcare industry used costly legacy infrastructures comprised of disparate elements. For a while, its use was justified by a lack of better options. However, with the emergence of cloud computing in healthcare – things have changed. 

The biggest issue with legacy infrastructures was that they were unable to handle an exponentially growing volume of medical data. 

• The thing is – healthcare operations produce vast amounts of data – patient admissions, diagnosis info, online interactions, discharges, the list goes on. The scope of data only goes on to expand. 

In essence, hybrid cloud infrastructure is a natural solution for the healthcare industry. It can bring the efficiency of the healthcare workflow pipeline to a new level – faster, more scalable, and more productive.

Here’s why.

What is the problem with cloud computing in healthcare?

One of the inherent features of healthcare workflow is its complexity. There are numerous elements involved – all tied together in complex systems. This medical cloud computing needs to handle lots of flows at the same time.

Let’s take patient treatment for example.  

• The patient treatment plan is a customized workflow designed according to the patient’s condition and medical needs. The pipeline involves numerous examinations, medical tests, treatment sessions, data analysis, and further optimization of the treatment strategy according to test results. 
• Every element of this pipeline has a workflow of its own. For example, blood testing facility:
• There is a general workflow. Its operational requirements figure in: 
• the needs of the facility itself for proper functioning (regarding the expertise and use of resources); 
• needs of patients it serves (get accurate results and effective treatment as a result); 
• the needs of healthcare institutions in general (overarching “save people’s lives”). 
• Then there is a workflow for a particular sample. 
• There is a queue of samples. Each set of samples has its own set of requirements (i.e., what kind of tests to make, the urgency of results for a particular case). 
• Overall, the samples are organized according to: 
• the priority in the general pipeline (for the most part, it is either routine or emergency tests); 
• The complexity of the testing; 
• available resources.

That’s just one of the examples. Pretty much every other component of healthcare institutions is operating this way. 

Such process overlap and dependency creates a necessity of having a cost-effective, easily manageable system with clearly defined and transparent processes. Which is exactly what cloud infrastructure is aimed at achieving.

Now let’s look at how the hybrid cloud for healthcare solves all these issues.

Benefits of the Hybrid Cloud Computing

1 Cost-Effectiveness

Cost-effectiveness is one of the key benefits of adopting cloud computing in the healthcare industry. Due to the intricacy of the workflow – It is much less taxing on the budget to use cloud infrastructure than to maintain your own hardware infrastructure. 

The reason why a hybrid cloud is the preferable type of infrastructure for healthcare is simple – it provides more flexibility in terms of arranging and managing operations. The other important aspect is control over data. 

• On one hand, you can use the public cloud for resource-heavy operations and avoid overpaying for cloud services. 
• The volume of resource use for each element differs. This aspect makes it reasonable to keep components on a “pay as you use model”.
• On the other hand, you can keep sensitive data on the private cloud safe with regulated access management. 

The higher level of flexibility allows much better use of resources and, as a result, much more efficient budget spending. With hybrid cloud infrastructure, each element is presented as a self-contained application that interacts with the rest of the system via API. 

2 Manageability 

The other crucial benefit of using hybrid cloud infrastructure is the better manageability of the workflow and its infrastructure. Given the fact of how many moving parts healthcare operation involves – this is one of the key requirements for the medical cloud computing pipeline.

Here’s why.

• In the hybrid cloud configuration, the system is broken down into self-contained components. 
• Each of them is doing its own thing using as many resources as it requires to do it properly. Because of the use of the public cloud, the workload of the particular element is not affecting the other components of the system. 
• At the same time, the interaction between the system components is strictly regulated through a constellation of APIs. 

For example: 

• there is a request for several different tests for the patient – blood test, liver function test, and MRI. Each of them is handled by its own component. 
• There is a central element in the form of patients’ electronic health records. This one is on a private cloud. 
• There are also contributing elements that handle the test. They operate on a public cloud and rely on its autoscaling features. The resulting data is sent back to patient’s EHR on a private cloud. The cycle repeats over the course of treatment. 

With the general pipeline and workflow of the particular elements set apart and clearly defined – it is far easier to oversee the operation in its full scope, analyze its effectiveness and plan its further optimization and transformation.

3 Reliability

Reliability is one of the key requirements for the operational infrastructure of cloud computing in healthcare. For the most part, the reliability requirements manifest themselves in the following needs:

1. Work results of each component need to be accurate and contribute to the accomplishment of the overarching goal of the workflow (to treat patients and ultimately cure them of their ailments).
2. The workflow needs to be uninterrupted and capable of handling as much workload as it needs, whether it is a regular or emergency level. At the same time, the system needs to be optimized and refined according to the ever-changing operational needs (i.e. more or fewer resources, etc)

Because the workflow elements are intertwined and codependent on each other, it is important to keep the consequences of one element failing from spreading to the entire system.

• For example, in a monolithic structure, this means that if one of the elements fails for some reason – this throws a wrench into the entire workflow. The database goes down and you’re busted. The aftermath of such downtime in healthcare might be dire. 
• On the other hand, if something happens to one of the self-contained cloud components – it is contained in the component and not spreading elsewhere (aside from API call error messages).

Here’s how a hybrid cloud for healthcare makes it work like clockwork.

1. The accuracy of results is secured by the use of public cloud resources. Whatever the operation requires to do, the job will be handled with public cloud autoscaling features.
2. The consistency of the workflow and optimization of its elements is maintained through the blue-green deployment approach. Here’s how. In essence, there are two versions of an application. One of them is server A and it is operating at the forefront. Then there is server B with another version that undergoes all sorts of refinement, expansions, optimizations, etc. When it comes to upgrading the component, the servers are seamlessly switched with little to no downtime. While this approach wasn’t originally designed for healthcare, in this industry it can be used to test out experimental features of the application and apply them to real data, without affecting the workflow. 

4 Security / Regulatory compliance / Privacy and confidentiality

Maintaining patient privacy is one of the most problematic aspects of modern healthcare operations. With the increasing scope of digital transformation and cloud adoption, growing cybersecurity threats, and implementation of government regulations regarding patient data usage – this is a considerable challenge. 

We live in the age of big data breaches. Every once in a while some company gets into hot water, either because of some security compromise or because it was downright hacked. 

In the case of healthcare, data breaches and other types of security compromises can be extremely damaging, both for the reputation of the institution, and the safety of its patients.

Here’s how a hybrid cloud solution can handle cybersecurity requirements.

• The structure of the hybrid cloud combines public and private cloud servers. The majority of resource-heavy operation is done on public servers, while sensitive information like patient data is kept on the private cloud with limited access.
• In this configuration, there is more control over data and access to it. This approach provides more transparency regarding who is using sensitive data and where it is used.
• In addition to that, keeping sensitive data on a private cloud allows taking more security and data loss prevention solutions (you can read more about it in our article on DLP). 

Then there is regulatory compliance. Such regional data protection regulations as GDPR (EU), PIPEDA (Canada) and HIPAA (USA) clearly define how patient data should be handled, and describe the consequences of misusing or compromising sensitive data. 

Here’s how a hybrid cloud makes it easier to be compliant with such regulations.

• In the hybrid cloud configuration, sensitive data of any kind is kept on private cloud servers with limited access for the applications operating on public cloud servers. 
• The cloud computing applications in the healthcare process only that data they require for proper functioning (for example, MRI for medical images requires input images and so on). 
• The processed data is then transmitted back to the private cloud and added to the patient’s file.   

5 Digital transformation

Most healthcare institutions have a mix of old and new equipment that uses different software. This aspect complicates the process of digital transformation towards the cloud for healthcare.

For instance, there are elements that you can implement into one system and then there are older elements that are incompatible due to age or software specifications. This is the case with some of the older, larger equipment. 

With a hybrid cloud, it becomes less of a problem as you can balance out the system according to its state. For example, you can tie together the compatible elements into a set of microservice applications. The elements that you can’t transform on the spot can use conversion points in order to feed data into the system and maintain workflow efficiency at the required scope.

In conclusion

Healthcare is probably one of the biggest beneficiaries of cloud adoption as it relies on technical innovation by design. The adoption of cloud computing in healthcare has made each aspect of it bigger, better, and much more efficient in terms of performance and reliability. 

With a hybrid cloud, healthcare operations can handle immense workloads without compromising the integrity and safety of data. At the same time, hybrid cloud infrastructure makes the workflow of each component more balanced and transparent, which makes it easier to manage and refine.

Cloud technology turned cybersecurity on its head. The availability and scope of data, and its interconnectedness, also made it extremely vulnerable to many threats. And it took a while for companies to take this issue seriously. 

The transition to the cloud has brought new security challenges. Since cloud computing services are available online, this means anyone with the right credentials can access it. The availability of enterprise data attracts many hackers who attempt to study the systems, find flaws in them, and exploit them for their benefit.  

One of the main problems that come with assessing the security risks of cloud computing is understanding the consequences of letting these things happen within your system. 

In this article, we will look at six major cloud security threats, and also explain how to minimize risks and avoid them.

What are the main cloud computing security issues? 

1. Poor Access Management

Access management is one of the most common cloud computing security risks. The point of access is the key to everything. That’s why hackers are targeting it so much. 

In 2016 LinkedIn experienced a massive breach of user data, including account credentials (approximately 164 million). 

The reasons were:

• insufficient crisis management 
• ineffective information campaign 
• the cunningness of the hackers

As a result, some of the accounts were hijacked, and this caused quite a hunt for their system admins in the coming months. 

Here’s another example of cloud security threats. A couple of months ago, the news broke that Facebook and Google stored user passwords in plaintext. While there were no leaks, this practice is almost begging to cause some. 

These are just a few of the many examples. 

So how to handle this issue?

Multi-factor authentication is the critical security component on the user’s side. It adds a layer to system access. In addition to a regular password, the user gets a disposable key on a private device. The account is locked down, and the user is sent a notification in case of an attempted break-in.  

Distinct layout for access management on the service side. This layout means determining the availability of information for different types of users. For example, the marketing department doesn’t need to have access to the quality assurance department protocols and vice versa. 

2. Data Breach and Data Leak – the main cloud security concerns

The cloud security risk of a data breach is a cause and effect thing. If the data breach happens – this means the company had neglected some of the cloud security flaws, and this caused a natural consequence.

What is a data breach? 

It is an accident in which the information is accessed and extracted without authorization. This event usually results in a data leak (aka data located where it is not supposed to be). 

Confidential information can be open to the public, but usually, it is sold on the black market or held for ransom. 

While the extent of the consequences depends on the crisis management skills of the particular company, the event itself is a blemish on a company’s reputation. 

How data breaches occur? 

The information in the cloud storage is under multiple levels of access. You can’t just stumble upon it under normal circumstances. However, it is available from various devices and accounts with cryptographic keys. In other words, a hacker can get into it if he knows someone who has access to it. 

Here’s how a data breach operation can go down:

• It all starts with a hacker studying the company’s structure for weaknesses (aka exploits). This process includes both people and technology. 
• Upon identifying a victim, the hacker finds a way to approach a targeted individual. This operation includes identifying social media accounts, interests, and possible flaws of the individual.
• After that, the victim is tricked into giving access to the company’s network. There are two ways of doing that:
• Technological, via malware sneakily installed on a victim’s computer;
• Social engineering, by gaining trust and persuading someone to give out their login credentials;

That’s how a cybercriminal exploits a security threat in cloud computing, gets access to the system, and extracts the data.

The most prominent recent data breach is the one that happened in Equifax in 2017. It resulted in a leak of personal data of over 143 million consumers. Why? Equifax’s developers hadn’t updated their software to fix the reported vulnerability. Hackers took advantage of this and the breach happened.

How to avoid data breaches from happening? 

A cloud security system must have a multi-layered approach that checks and covers the whole extent of user activity every step of the way. This practice includes:

Multi-factor Authentication – The user must present more than evidence of his identity and access credentials. For example, typing a password and then receiving a notification on a mobile phone with a randomly generated single-use string of numbers active for a short period. This has become one of cloud security standards nowadays. 

Data-at-Rest Encryption. Data-at-rest is a type of data that is stored in the system but not actively used on different devices. This process includes logs, databases, datasets, etc. 

Perimeter firewall between a private and public network that controls in and out traffic in the system;

Internal firewall to monitor  authorized traffic and detect anomalies; 

3. Data Loss

If a data breach wasn’t bad enough, there is an even worse cloud security threat – it can get irreversibly lost like tears in the rain. Data loss is one of the cloud security risks that are hard to predict, and even harder to handle. 

Let’s look at three of the most common reasons for data loss:

Data alteration – when information is in some way changed, and cannot be reverted to the previous state. This issue may happen with dynamic databases.

Unreliable storage medium outage – when data gets lost due to problems on the cloud service provider’s side.

Data deletion – i.e.,  accidental or wrongful erasure of information from the system with no backups to restore. The reason is usually a human error, messy database structure, system glitch, or malicious intent. 

Loss of access – when information is still in the system but unavailable due to lack of encryption keys and other credentials (for example, personal account data)

How to prevent data loss from happening? 

Backups. 

Frequent data backups are the most effective way of avoiding data loss in the majority of its forms. You need a schedule for the operation and a clear delineation of what kind of data is eligible for backups and what is not. Use data loss prevention software to automate the process. 

Geodiversity – i.e., when the physical location of the cloud servers in data centers is scattered and not dependent on a particular spot. This feature helps in dealing with the aftermath of natural disasters and power outages. 

One of the most infamous examples of data loss is the recent MySpace debacle. 

It resulted in 12 years of user activity and uploaded content getting lost. Here’s what happened. During a cloud migration process in 2015, it turned out that a significant amount of user data, (including media uploads like images and music), got lost due to data corruption. Since MySpace wasn’t doing backups – there was no way to restore it. When users started asking questions, customer support said that the company is working on the issue, and a couple of months later, the truth came out. This incident is considered to be another nail in the coffin of an already dying social network. 

Don’t be like MySpace, do backups.

4. Insecure API

Application User Interface (aka API) is the primary instrument used to operate the system within the cloud infrastructure. 

This process includes internal use by the company’s employees and external use by consumers via products like mobile or web applications. The external side is critical due to all data transmission enabling the service and, in return, providing all sorts of analytics. The availability of API makes it a significant cloud security risk. In addition to that, API is involved in gathering data from edge computing devices.

Multi-factor authentication and encryption are two significant factors that keep the system regulated and safe from harm.

However, sometimes the configuration of the API is not up to requirements and contains severe flaws that can compromise its integrity. The most common problems that occur are:

• Anonymous access (i.e., access without Authentication) 
• Lack of access controls (may also occur due to negligence)
• Reusable tokens and passwords (frequently used in brute force attacks)
• Clear-text Authentication (when you can see input on the screen)

The most prominent example of insecure API in action is the Cambridge Analytica scandal. Facebook API had deep access to user data and Cambridge Analytica used it for its own benefit. 

How to avoid problems with API? 

There are several ways:

• Penetration testing that emulates an external attack targeting specific API endpoints, and attempting to break the security and gain access to the company’s internal information.
• General system security audits
• Secure Socket Layer / Transport Layer Security encryption for data transmission
• Multi-factor Authentication to prevent unauthorized access due to security compromises. 

5. Misconfigured Cloud Storage

Misconfigured Cloud Storage is a continuation of an insecure API cloud security threat. For the most part, security issues with cloud computing happen due to an oversight and subsequent superficial audits.  

Here’s what happens.

Cloud misconfiguration is a setting for cloud servers (for storage or computing purposes) that makes it vulnerable to breaches. 

The most common types of misconfiguration include: 

Default cloud security settings of the server with standard access management and availability of data; 

Mismatched access management – when an unauthorized person unintentionally gets access to sensitive data;

Mangled data access – when confidential data is left out in the open and requires no authorization. 

A good example of cloud misconfiguration is the National Security Agency’s recent mishap. A stash of secure documents was available to screen from an external browser.  

Here’s how to avoid it.

Double-check cloud security configurations upon setting up a particular cloud server. While it seems obvious, it gets passed by for the sake of more important things like putting stuff into storage without second thoughts regarding its safety.

Use specialized tools to check security configurations. There are third-party tools like CloudSploit and Dome9 that can check the state of security configurations on a schedule and identify possible problems before it is too late.  

6. DoS Attack – Denial-of-service attack

Scalability is one of the significant benefits of transitioning to the cloud. The system can carry a considerable workload. 

But that doesn’t mean it can handle more unexpectedly. It can overload and stop working. That’s a significant cloud security threat. 

Sometimes, the goal is not to get into the system but to make it unusable for customers. That’s called a denial-of-service attack. In essence, DoS is an old-fashioned system overload with a rocket pack on the back. 

The purpose of the denial-of-service attack is to prevent users from accessing the applications or disrupting their workflow. 

DoS is a way of messing with the service-level agreement (SLA) between the company and the customer. This intervention results in damaging the credibility of the company. The thing is – one of the SLA requirements is the quality of the service and its availability. 

Denial-of-Service puts an end to that. 

There are two major types of DoS attack:

• Brute force attack from multiple sources (classic DDoS),
• More elaborate attacks targeted at specific system exploits (like image rendering, feed streaming, or content delivery) 

During a DoS attack, the system resources are stretched thin. Lack of resources to scale causes multiple speed and stability issues across the board. Sometimes it means an app works slow or it simply cannot load properly. For users, it seems like getting stuck in a traffic jam. For the company, it is a quest to identify and neuter the sources of the disruption, and also increased spending on the increased use of resources. 

2014 Sony PlayStation Network attack is one of the most prominent examples of denial-of-service attacks. It is aimed at frustrating consumers by crashing the system by both brute forces and being kept down for almost a day.

How to avoid a DoS attack?

Up-to-date Intrusion Detection System. The system needs to be able to identify anomalous traffic and provide an early warning based on credentials and behavioral factors. It is a cloud security break-in alarm.

Firewall Traffic Type Inspection features to check the source and destination of incoming traffic, and also assess its possible nature by IDS tools. This feature helps to sort out good and bad traffic and swiftly cut out the bad.

Source Rate Limiting – one of the critical goals of DoS is to consume bandwidth. 

Blocking of the IP addresses, that are considered to be a source of an attack, helps to keep the situation under control.

Other security risks and threats 

To get a clear picture, you should be aware of the following network security threats and risks that may appear on the cloud, as well as on-premise servers. 

Cloud-Unique Threats and Risks

• Reduced Visibility and Control from customers
• Separation Among Multiple Tenants Fails
• Data Deletion is Incomplete

Cloud and On-Premise Threats and Risks

• Credentials are Stolen
• Vendor Lock-In Complicates Moving to Other CSPs
• Increased Complexity Strains IT Staff
• CSP Supply Chain is Compromised
• Insufficient Due Diligence Increases Cybersecurity Risk

In conclusion

The adoption of cloud technology was a game-changer both for companies and hackers. It brought a whole new set of security risks for cloud computing and created numerous cloud security issues. 

The shift to cloud technology gave companies much-needed scalability and flexibility to remain competitive and innovative in the ever-changing business operations. At the same time, it made enterprise data vulnerable to leaks and losses due to a variety of factors. 

Following the standards of cloud security is the best way to protect your company from reputational and monetary losses.

Read also:

What are Secure Messengers Apps

What Is GDPR and Why It Should Not Be Ignored

Data Security and Privacy 

 These days data breaches are as common as natural events like rain and snow. Every week you hear a story about it. The result is all the same – databases hacked and exposed. 

The consequences of company data breaches are pretty dire.

• Sometimes it is the company’s reputation that suffers. 
• Other times, the breach results in product shut down, as happened with Google+ when the news broke that there were some critical security issues.

Oddly enough, until very recently, companies weren’t taking the threat of data breaches seriously. Awareness of the real danger of data breaches started to grow after the frequency of data breach events began to grow exponentially.

In this article, we will explain: 

• Why data breaches are happening? 
• What are the seven major types of data leaks? 
• How to avoid data breaches? 

What is a data breach?

A data breach is an abnormal event caused by a variety of factors connected by one common factor – inherent flaws of the security system that can be exploited.

The standard definition of a data breach is “a security event in which data intended for internal use is for some reason available for unauthorized access.” 

The nature of the so-called “internal data” may vary, but it is always something related to business operation. It might be:

• Customer or employee personal data (for example, name, address, social security number, other identifiable data)
• Payment or credit information (for example, in-app payments)
• Access data (login, password, et al.) 
• Corporate information (any internal documentation regarding projects or estimates, workflow process, status reports, audits, performance reviews, any financial or legal information, etc.)
• Communication logs.

Why data breaches occur?

There are five most common causes of data breaches. Let’s look at them one by one:

1. Human error

Believe it or not, human error and oversight are usually among the main reasons why data breaches happen. 

Here’s why. 

The imposing nature of the corporate structure provides a false sense of security and instills confidence that nothing bad is going to happen inside of it. 

This detail paves the way for some slight carelessness in employee behavior. Technically, human error is an unintentional misconfiguration of document access. It may refer to: 

• general storage accessibility (for example, private data being publicly available) 
• the accessibility of specific documents (for example, sending data to the wrong person by accident).

2. Insider Threat

In this case, you have an employee with an agenda who intentionally breaches confidential and otherwise sensitive data. 

Why does it happen? 

Disgruntled employees are one of the reasons. One worker may feel wronged about his treatment and position in the company and this may lead to leaking information to the public or competition. 

Then there is corporate spying. The competition may convince one of the employees to disclose insider information for some benefits. 

In both cases, it is important to identify the source of data leaks (more on that later on).  

3. Social Engineering / Phishing

Social engineering is probably the gentleman’s way of doing company data breaches. 

This is when a criminal, who pretends to be an authorized person gains access to data or other sensitive information by duping the victim. 

Old-fashioned SE is when a criminal poses as somebody else and exploits the trust of the victim, as when Kevin Mitnick accessed the source code of the Motorola mobile phone by simply asking for it. 

Social engineering in electronic communication is known as phishing. 

In this case, the perpetrator imitates trustworthy credentials (the style of the letter, email address, logos, corporate jargon, etc.) to gain access to the information. Phishing is usually accompanied by malware injections to gain further access to the company’s assets (more on phishing later on.)

4. Physical action

Physical action data breach (aka “old school data breach”) – when the papers or device (laptop, smartphone, tablet, etc.) with access to sensitive information is stolen. 

Since companies encourage employee omnipresence and work on the go, this is a severe threat. How does it happen? A combination of sleight of hand and employee inattentiveness. 

However, due to increased security practices, and multi-factor authentication, the threat of stolen devices has significantly decreased. 

5. Privilege Misuse Data Breach

What is data privilege misuse? It is the use of sensitive data for purposes beyond the original corporate intent (like subscribing a corporate email list to a personal newsletter or changing the documents without following the procedure). 

Improper use of information is one of the most common ways corporate data breaches occur. The difference between privilege misuse and human error is the intention. However, privilege misuse is not always due to malicious intent. Sometimes the cause is inadequate access management and misconfigured storage settings. 

Privilege misuse results in various forms of data mishandling – like copying, sharing, and accessing data by unauthorized personnel. Ultimately, this may lead to a data leak to the public or a black market. 

How to Prevent Data Breaches? Solutions for 7 types of Breaches

In this section, we will describe the 7 most common types of data breaches and explain the most effective methods of preventing cyber breaches.

1.  Spyware malware

Spyware is a type of malicious software application designed to gather information from the system in a sneaky way. In a nutshell, spyware is keeping logs on user activity. This type of information includes: 

• Input information – access credentials like logins and passwords. This type of spyware is also known as keyloggers.
• Data manipulation of all sorts (working on documents, screening analytics, etc.) 
• In addition, this can be used to capture an employee’s communication. 
• Also, spyware can monitor video and audio input (specific for communication applications). Skype was known to have this vulnerability a couple of years ago. 
• Files opened – to analyze the structure of the information and understand specific business processes; 

How does it happen?

The most common way of getting a piece of spyware is by unknowingly downloading a software program with a bit of spyware bundled with it. Also, spyware can be automatically uploaded through a pop-up window or redirect sequence. In a way, tracking cookies and pixels are similar to the spyware that acts almost in broad daylight. However, actual spyware is much more penetrative and damaging.

Usually, spyware is used in the initial stages of a hacking attack to gain necessary intelligence. In addition to that, spyware is one of the tools used for corporate spying.

An excellent example of a spyware attack is the WhatsApp messenger incident.  In May 2019, Pegasus spyware attacked WhatsApp. As a result, the malware had access to user’s ID information, calls, texts, camera, and microphone. 

How to fight spyware? 

• Two-factor authentication to prevent straight-up account compromise;
• Keep login history with details regarding IP, time, and device ID to identify and neutralize the source of unauthorized access;
• Limit the list of authorized devices;
• Install anti-malware software to monitor the system; 

2. Ransomware

Ransomware is a type of malware used to encrypt data and hold it for ransom in exchange for the decryption key. The ransom is usually paid in cryptocurrency because it is harder to trace. 

Ransomware is a no-brainer hacking option – its goal is to profit from the user’s need to regain access to the sensitive data. Since modern cryptography is hard to break with brute force, in the majority of cases, victims have to comply.

Usually, ransomware is spread by phishing emails with suspicious attachments or links. It can proceed due to careless clicking. Ransomware is also distributed through so-called drive-by downloads when a piece of malware is bundled with the software application or automatically uploaded by visiting an infected webpage.

For years, ransomware attacks were happening to individual users. Recently, ransomware attacks became frequent on larger structures. 

In March and May of 2019, ransomware virus, RobbinHood, attacked the government computer systems of Atlanta and Baltimore. It encrypted some of the cities databases and virtually paralyzed some aspects of the infrastructure. 

The cities governments were forced to pay the ransom to regain control over their systems. As it turned out, a combination of the following factors made the breach and subsequent ransomware attack possible:

• lack of cybersecurity awareness of the personnel; 
• outdated anti-malware software; 
• general carelessness regarding web surfing.

How to avoid getting ransomware?

• Use anti-malware software and keep it regularly updated.
• Make a white list of allowed file extensions and exclude everything else.
• Keep data backups in case of emergencies like ransomware infections. This detail will keep the damage to a minimum.
• Set up a schedule for updating restoration points.
• Segment network access and provide it with different entry credentials to limit the spread of malware. 

3. SQL Injection

These days, SQL injection is probably one of the most dangerous types of malware. It aims for data-driven applications. The use of such tools in business operations makes SQL injection a legitimate threat to a company’s assets. Data analytics, machine learning datasets, knowledge base – all can be in danger.

SQL is one of the oldest programming languages. Its field is data management in relational databases (i.e., the ones with data that relates to certain factors, like user IDs, prices for products, time-series data, etc.). These are the majority of databases. 

It is still in use because of its versatility and simplicity. These very same factors exploited by cybercriminals. The SQL injection is used to perform malicious SQL operations in the database and extract valuable information.

Here’s how it works:

• To begin with, there is a flaw in the security of the page, and exploit. Usually, it is when the page involves a user’s direct input into the SQL query. The perpetrator identifies it and creates his input query known as the malicious payload.
• Due to the simplicity of the system, this type of command is executed in the database.
• With the help of the malicious payload, a hacker can access all sorts of data ranging from user credentials to targeting data. In more sophisticated cases, it is possible to gain an administrator-level of control over the server and run roughshod over it. 
• In addition to this, a hacker can alter and delete data, which is a piece of awful news when it comes to financial and legal information.

One of the most infamous incidents of SQL injections, that led to a massive data breach, is the 2012 LinkedIn incident. It resulted in a data leak of over six million passwords. 

Curiously, LinkedIn had never confirmed that the leak was caused by SQL injection despite all the facts pointing to it. The reason for this is simple. SQL injections happen because they are allowed to occur by negligence and overconfidence. They are straightforward to predict – if there is the possibility, sooner or later it will be exploited. This nuance makes SQL injection a very embarrassing type of breach.

How to prevent data breaches with SQL injection? There are several ways:

• Apply the principle of least privilege (POLP) – each account has access limited to one specific function and nothing more. In the case of a web account, it may be a read-only mode for the databases with no writing or editing features by design.
• Use stored procedures (aka prepared statements) to limit SQL command variables. This feature excludes the possibility of exploiting the input query. 

4. Unencrypted backup data breaches

Backup storage is one of the critical elements in the disaster recovery strategy. It is always a good thing to have a copy of your data just in case something terrible happens to it. 

On the other hand, encryption is one of the critical requirements of modern asset management. It is a reasonable approach. If the data is encrypted, it hurts less if it leaks since it not useful in that state. And, it seems obvious to have storage and transmission channels encrypted by default. 

However, backups are usually left out of the equation. Why? Because, by their nature, backups seem to be a precaution in and of themselves and thus treated as a lesser asset for the company’s current affairs. 

Add to that the aforementioned false feeling of safety behind a corporate firewall. Also, backup encryption is an additional weight on the security budget, which is often already strained. The latter is usually the reason why encrypted backups are not a persistent practice. 

This is a big mistake because one party’s carelessness is another person’s precious discovery. 

The most common problem with backups is weak authentication like a simple combo of login and password without any additional steps. 

How to prevent data breaches due to unencrypted backups? There are several ways:

• Encrypt your backups with specialized software
• Keep the backup storages to the same security standard as main servers (i.e., internal network-only type of access with two-factor authentication by default)

The most egregious example of a data breach via unencrypted backup happened in 2018. The Spanish survey software company Typeform had experienced a massive data breach due to unencrypted backups being exposed and downloaded by cybercriminals. Numerous companies and even government organizations were using the service. That made surveys a rather diverse source of sensitive information, including person-identifying data and payment-related information. 

The breach had severe repercussions for the company. In addition to being forced to apologize to the customers, Typeform started losing their clients. Many of the companies had decided to opt-out of the service. Don’t be like Typeform, encrypt your backups.

5. API Breaches due to unrestricted calls 

In some ways, API is almost like Pandora’s box. You know what it is supposed to do, but you never really know what kind of trick can be pulled off with its help. As one of the essential tools for the application operation, API is a treasure trove of information for those who know where to look.

That is how the whole Cambridge Analytica debacle happened with Facebook. Hackers had exploited the progressive structure of Facebook API (which provided rather deep access to user data) and turned it into a powerful tool for diverse data mining. 

As a result, they managed to collect the data of more than 50 million users. Among the data gathered were such things as likes, expressed interests, location data, interpersonal relationship data, and much more.  

What happened next? The scandal got so big, Facebook CEO Mark Zuckerberg was forced to discuss the matter at Senate hearings. In addition to that, the company received a permanent stain on their reputation and a massive user withdrawal. The subsequent investigation led to a whopping $5 billion fine by the Federal Trade Commission. 

Such API breaches could have been avoided if it was a bit more thought-through. 

How can API become a data breach risk? 

• Anonymous access (i.e., access without authentication) 
• Lack of access monitoring (may also occur due to negligence)
• Reusable tokens and passwords (frequently used in brute force attacks)
• Clear-text authentication (when you can see input on the screen)

How to prevent data breaches and make API safe and secure? There are several ways:

• Provide thorough access restriction and delimit what kind of data is accessible via API and that which is not; 
• Use rate-limiting to keep data transmission under reasonable boundaries. This feature will prevent API from being used in a data mining operation. 
• Use anomaly and fraud detection tools to identify suspicious behavior in the API to block it.  
• Perform audit trail to understand what kind of request is going through API 
• Clearly explain to users which types of data you are sharing with third parties via API

6. Access Management and Misconfigured cloud storage

Cloud security is probably the most robust field of cybersecurity as it requires a lot of auditing and constant testing of the system for all sorts of weaknesses. One of the biggest problems with cloud storage is access management due to misconfigured cloud storage settings. 

Here’s what it means: 

• Access management in cloud infrastructure is a mess. All users in the system have certain levels of access to certain kinds of data. 
• Because there is a need to share information to enable business operation, there is a high volume of access turnaround. 
• Sometimes it goes unchecked, and unauthorized users may end up having access to sensitive data they are not supposed to have access to. 

At the same time, there is a thing with cloud security settings. Maintaining databases and storage in the cloud means you need to keep an eye on the accessibility of the information. Since there is a lot of data coming in and out, it is essential to keep things strict. 

Here’s what may happen. 

• Some of the data may end up on the public side due to oversight and inadequate default accessibility settings. 
• The data may be visible on the outside, and it is a significant exploit for cybercriminals. 
• With a little help of specialized search engine requests, one can get a lot of exciting stuff. 

A good example of cloud misconfiguration is the U.S. Army’s Intelligence and Security Command AWS server security mishap. A stash of classified NSA documents was publicly accessible due to an access configuration oversight. It was that simple. Upon sharing the folder, someone failed to check the accessibility status and made the thing public.

• Here’s how to avoid this kind of data breach
• Check the cloud security configurations upon setting up particular storage. Be sure it is strictly private. 
• Use access management tools to keep an eye on security configuration. There are third-party tools that can routinely check the state of security configurations and detect issues upon their occurrence.  

7. Malicious Insider Threat

Insider Threat is probably the most persistent source of data breaches. You never know what may trigger this kind of behavior. While the aforementioned types of data breaches are all about the technology, this one is about a person being nasty and acting maliciously. 

Aside from human error and negligence (that leads to such types of data breaches as malware and access misconduct), there are three main types of malicious insider threat:

• Disgruntled Employees – this kind of insider threat is all about getting back at those who did the particular employee wrong. According to a study by Gartner, 29 percent of employees have stolen corporate data for personal gain after quitting. Then there is the 9% of those who just wanted to sabotage the process one last time. 
• Second streamers are much more serious trouble. These are the people who systematically disclose sensitive information for personal gain and supplementary income. According to the Gartner study, these are 62% of all insider threats. Second streamers are dangerous because they know what they are doing and they try to remain in the system for as long as possible without getting caught. In this case, data breaches occur in a slow, barely detectable manner, disguised as a casual business process. 

There are several ways to avoid data breaches caused by insider threat:

• Implement strict access control over sensitive data. If there is a document to be shared with an unauthorized person – set a limit of accessibility and disable copying of the document.
• Keep thorough activity logs on what is going on within a system. Set an alarm for suspicious activity like unusually large data exports and copying (like the whole contact database transfer and so on) or unauthorized access. Every cloud platform has its own logging tools. For example, here’s how this thing works on Google Cloud.
• Perform an audit trail to identify the source and determine the context and content of the anomalous event, and identify the source of anomalous activity. This can be handled by Data Loss Protection software like McAfee DLP.

Conclusion

In the age of big data and exponentially growing cloud services – data breach is just one aspect of everyday life. It is definitely an unfortunate thing if it happens, but as it was explained above – it is far from inevitable. 

All it takes to avoid data breaches from happening is keeping a close eye on what is going on with the data and where it is going. Knowledge is half the battle won – you need to be cautious about the value of your data and the ways it can be exposed. 

In this article, we have shown you exactly how to lessen the risks of data breaches and wholly avoid such events. 

Read also:

WHY DATA SECURITY AND PRIVACY MATTERS?

HOW DO SECURE MESSENGERS LIKE WIRE AND SIGNAL MAKE MONEY?

Imagine that you recently launched a social networking app. To host the app’s infrastructure, you decided to use the existing on-premise server because you do not expect it to handle many users immediately. Your app is going viral and, during just one month, over 1000, 000 users downloaded and used it on a daily basis. Do you know what will happen next? Since your server infrastructure was not ready for such huge loads, it will now not work correctly. Thus, instead of your apps’ interface, users will see an error message and you will lose a significant amount of them because your app failed to live up to their expectations. 

To avoid situations where you jeopardize user trust, use cloud platforms for both hosting databases and running app infrastructure. 

Such data giants as Facebook, Netflix, and Airbnb, already adopted a migration strategy to the cloud due to cheap costs, auto-scaling features, and addons as real-time analytics. Oracle research says 90% of enterprises will run their workloads on the cloud by 2025. If you already run data centers or infrastructure with an on-premise environment, and you will need more capacity in the future, consider migrating to the cloud as a solution.  

Yet, to migrate to the cloud is not as simple as it seems. To successfully migrate to the cloud you need, not only an experienced developer but also a solid cloud application migration strategy. 

If you are ready to leverage cloud solutions for your business, read this article to the end. 

By the end of this blog post, you will know about cloud platform types and how to successfully migrate to cloud computing.

Cloud migration strategies: essential types

Migration to the cloud means transferring your data from physical servers to a cloud hosting environment. This definition is also applicable for migrating data from one cloud to another platform. Migration in cloud computing includes different types, due to the number of code changes developers need to conduct. The main reason is that not all data is ready to be moved to the cloud by default.

Let’s go through the main types of application migration to the cloud one by one. 

• Rehosting. This is the process of moving data from on-premise storage and redeploying it on cloud servers. 
• Restructuring. Such a migration requires changes in the initial code to meet the cloud requirements. Only then can you move the system to a platform-as-a-service (PaaS) cloud model. 
• Replacement migration means switching from existing native apps to third-party apps. An example of replacement is migrating data from custom CRM to Salesforce CRM. 
• Revisionist migration. During such a migration, you make global changes in the infrastructure to allow the app to leverage cloud services. By ‘cloud services’ we mean auto-scaling, data analytics, and virtual machines. 
• Rebuild is the most drastic type of cloud migration. This type means discarding the existing code base and building a new one on the cloud. Apply this strategy if the current system architecture does not meet your goals. 

How to nail cloud computing migration: essential steps

For successful migration to the cloud, you need to go through the following steps of the cloud computing migration strategy. 

Step 1. Build a cloud migration team 

First, you need to hire the necessary specialists and employ the distribution of roles. In our experience, a cloud migration team should include: 

• Executive Sponsor, a person who handles creating a cloud data migration strategy. If you have enough tech experience, you can take this role. If not, your CTO or a certified cloud developer will ideally suit you. 
• Field General handles project management and migration strategy execution. This role will suit your project manager if you have one. If not, you can hire a dedicated specialist with the necessary skills. 
• Solution Architect is an experienced developer who has completed several cloud migration projects. This person will build and maintain the architecture of your cloud. 
• Cloud Administrator ensures that your organization has enough cloud resources. You need an expert in virtual machines, cloud networking, development, and deployment on IaaS and PaaS. 
• Cloud Security Manager will set up and manage access to cloud resources via groups, users, and accounts. This team member configures, maintains, and deploys security baselines to a cloud platform. 
• Compliance Specialist ensures that your organization meets the privacy requirements. 

Step 2.Choose cloud service model 

There are several types of cloud platforms. Each of them provides different services to meet various business needs. Thus, you need to define your requirements for a cloud solution and select the one with the intended set of workflows. However, this step is challenging, especially if you have no previous experience with cloud platforms. To make the right decision, receive a consultation from experienced cloud developers. But, to be on the same page with your cloud migration team, you need to be aware of essential types of cloud platform services, such as SaaS, PaaS, IaaS, and the differences between them.

• SaaS (Software as a Service)

Chose SaaS to receive advantages of running apps without maintaining and updating infrastructure. SaaS providers also offer you cloud-based software, programs, and applications. SaaS platforms charge a monthly or yearly subscription fee. 

• IaaS (Infrastructure as a Service)

This cloud model suits businesses that need more computing power to run variable workloads with fewer costs. With IaaS, you will receive a ready-made computing infrastructure, networking resources, servers, and storage. IaaS solutions apply a pay-as-you-go pricing policy. Thus, you can increase the cloud solution’s capacity anytime you need it. 

• PaaS (Platform as a service)

Chose this cloud platform type for adopting agile methodology in your development team, since PaaS allows the faster release of app updates. You will also receive an infrastructure environment to develop, test, and deploy your apps, thus increasing the performance of your development team.

Step 3. Define cloud solution type

Now you need to select the nature of your cloud solution from among the following:

• Public Cloud is the best option when you need a developing and testing environment for the app’s code. Yet, the public cloud migration strategy is not the best option for moving sensitive data. Public clouds include high risks of data breaches. 
• Private Cloud providers give you complete control over your system and its security. Thus, private clouds are the best choice for storing sensitive data.
• The hybrid cloud migration strategy combines both public and private cloud solutions characteristics. Chose a hybrid cloud to use using a SaaS app and get advanced security. Thus, you can operate your data in the most suitable environment. The main drawback is tracking various security infrastructures at once, which is challenging.

Step 4. Decide the level of cloud integration

Before moving to cloud solutions you need to choose the level of cloud integration among shallow and deep integration. Let’s find out what the difference is between them. 

• Shallow cloud integration (lift-and-shift). To complete shallow cloud migration, developers need to conduct minimal changes to the server infrastructure. However, you can not use the extra services of cloud providers. 
• Deep cloud integration means adding changes to an app’s infrastructure. Chose this strategy if you need serverless computing capabilities (Google Cloud Platform services), and cloud-specific data storage (Google Cloud Bigtable, Google Cloud Storage).

Step 5. Select a single cloud or multi-cloud environment

You need to choose whether to migrate your application on one cloud platform or use several cloud providers at once. Your choice will impact the time required for infrastructure preparation for cloud migration. Let’s look at both options in more detail. 

Running an app on one cloud is a more straightforward option. Your team will need to optimize it to work with the selected cloud provider and learn one set of cloud API. But, this approach has a drawback – a vendor lock-in. It means that it will be impossible to change the cloud provider. 

If you want to leverage multiple cloud providers, choose among the following options: 

• To run one application set on one cloud, and another app’s components on another cloud platform. The benefit is that you can try different cloud providers at once, and choose where to migrate apps in the future. 
• To split applications across many different cloud platforms is another option. Thus, you can use the critical advantages of each cloud platform. However, consider that the poor performance of just one cloud provider may increase your app’s downtime. 
• To build a cloud-agnostic application is another option that allows you to run the app’s data on any cloud. The main drawback is the complicated process of app development and feature validation.

Step 6. Prioritize app services

You can move all your app components at once, or migrate them gradually. To find out which approach suits you the best, you need to detect the dependencies of your app. You can identify the connections between components and services manually or generate a dependencies diagram via a service map. 

Now, select services with the fewest dependencies to migrate them first. Next, migrate services with more dependencies that are closest to users.

Step 7. Perform refactoring

In some cases, you will need to make code refactoring before moving to the cloud. In this way, you ensure all your services will work in the cloud environment. The most common reasons for code refactoring are: 

• Ensuring the app performs well with different running instances and supports dynamic scaling 
• Defining the apps’ resource use dynamic-cloud capabilities, rather than allocating them beforehand

Step 8. Create a cloud migration project plan

Now, you and your team can outline a migration roadmap with milestones. Schedule the migration according to your data location and the number of dependencies. Also, consider that, despite the migration, you need to keep your app accessible to users. 

Step 9. Establish cloud KPIs

Before moving data to a cloud, you need to define Key Performance Indicators. These indicators will help you to measure how well it performs in the new cloud environment. 

In our experience, most businesses track the following KPI’s:

• Page loading speed
• Response time
• Session length
• Number of errors
• Disc performance
• Memory usage

And others. You can also measure your industry-specific KPIs, like the average purchase order value for mobile e-commerce apps.

Step 10. Test, review, and make adjustments as needed

After you’ve migrated several components, run tests, and compare results with pre-defined KPIs. If the migrated services have positive KPIs, migrate other parts. After migrating all elements, conduct testing to ensure that your app architecture runs smoothly. 

Cloud migration checklist from The APP Solutions

Cloud providers provide different services to meet the needs of various businesses. You need help from professionals to choose the right cloud solution. 

We often meet clients who have trouble with selecting a cloud provider. In these cases, we do an audit of a ready-made project’s infrastructure. Next, we help clients to define their expectations for the new cloud environment. To achieve this, we show a comparison of different cloud providers and their pros and cons. Then, we adopt a project for a cloud infrastructure, which is essential for a successful migration. 

When looking for a cloud provider, consider the following parameters: 

• Your budget, which means, not only the cost of cloud solutions but also the budget for cloud migration
• The location of your project, target audience, and security regulations (HIPAA, GDPR)
• The number of extra features you want to receive, including CDN, autoscaling, backup requirements, etc. 

Migration to a cloud platform is the next step for all business infrastructures. However, you need to consider that cloud migration is a comprehensive process. It requires, not only time and money but also a solid cloud migration strategy. To ensure your cloud migration is going right, you need to establish and track KPIs. Fill in the contact form to receive a consultation or hire a certified cloud developer.

EMR integration’s significance is undeniable; it enables better decision-making, reduces medical errors, and boosts patient engagement. Electronic Medical Systems function independently, but for optimal results, they need to interact. Regrettably, many hospitals don’t practice this.

Our experience with Bueno clarified the issue. Bueno applies machine learning to analyze user’s EHR data, ensuring timely preventive care. The app shares this data with the healthcare team to advise patients on check-ups, lab tests, or symptom watch.

But there was a hurdle. Healthcare providers could see the data, but accessing records from different platforms was a struggle. To solve this, we merged various solutions, consolidating all data in one spot. We used platforms like Orb Health, Validic, and Mayo Clinic.

Today, we’re aware that EMR integration issues still persist in many medical firms. In this article, we’ll guide you on connecting different EMRs, explain its necessity, and discuss potential challenges.

What is the EMR system?

An EMR system is a digital platform stored in the cloud, holding patient medical data. In the not-so-distant past, medical data was etched on paper, stored in bulky folders, and piled high on shelves. Clinicians had to leaf through these volumes, laboriously seeking the information they needed to make swift diagnoses. However, with EMR systems, this relic of a practice is no longer a necessity.

Imagine no longer battling with ink and paper, but rather smoothly navigating a sleek digital platform. This digital library, or EMR, neatly organizes and securely stores patient data. It’s a resource for medical history, diagnostic data, lab test results, appointments, billing details, and more.

It’s not only doctors who have access to this knowledge. Patients, too, can step into this library. Through a digital door known as a patient portal, they can glance at their health story unfolded.

Every prescribed medicine, every immunization, every treatment plan is at their fingertips, as well as the doctors’. Informed decisions can then be made, not only based on a single page of information but the entire medical narrative of the patient. The EMR system, hence, is a potent tool empowering both the healthcare provider and the recipient, and typically includes:

• Medical history
• Diagnostic information
• Lab test results
• Appointments
• Billing details
• Prescription and refill data from pharmacies
• Patient portals
• Treatment plans
• Immunization records

What Are Examples of EMR Platforms?

There are over 600 EMR vendors according to review sites. However, we’ll focus on discussing those we’ve successfully integrated at The APP Solutions. We’ll share our experiences with CernerAmbulatory, Epic EMR, DrChrono, and eClinicalWorks.

Cerner

Cerner, a US medical software titan, delivers digital health data solutions. It caters to multispeciality and smaller practices. Key offerings include Cerner Powerchart, Caretracker, and Cerner Millenium.

Key Features: population health, revenue cycle, medical reporting, lab information, and patient portal.

Cerner Pros:

• Strong interoperability promotes collaboration.
• Cost-effective for small practices.
• Advanced patient portal for health information.
• Software can mimic practice’s branding.

Cerner Cons:

• Fewer integrations, such as CRM.
• Regular updates can pose learning challenges.

Epic EMR

Epic EMR is a hospital favorite, holding medical records for over 253 million Americans. It shines in large settings. Notable features are telemedicine, billing, e-prescription, templates, and analytics.

Epic EMR Pros:

• Detailed patient information reports.
• Telehealth for remote consultations.
• AI and analytics to enhance decision-making.

Epic EMR Cons:

• High setup cost.
• Steep learning trajectory.
• Limited interoperability.

  EPIC VS. CERNER: WHICH EHR SYSTEM IS RIGHT FOR YOUR HEALTHCARE PRACTICE?Read also:

DrChrono

DrChrono provides web and app-based EMR systems. It assists with appointments, reminders, and billing, automating routine tasks.

Key Features: patient charting, telehealth, appointment scheduling, and reminders.

DrChrono Pros:

• Affordability benefits small or new practices.
• Comprehensive training for software admins.
• Secure direct messaging for patients and doctors.

DrChrono Cons:

• No Android app for doctors.
• Limitation on appointment reminder methods.

eClinicalWorks

eClinicalWorks supplies digital health records, patient management, and population health solutions. It caters to over 4000 US clients. Key features are revenue cycle management, patient portal, wellness tracking, activity dashboard, and telehealth.

eClinicalWorks Pros:

• Operates on multiple platforms like Mac and Windows.
• User-friendly interface.
• Interoperability connects with other systems.

eClinicalWorks Cons:

• Pricey for small practices.
  What Solution can We Offer

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Why Is EMR Integration Important for Healthcare Companies?

The healthcare sector is one of the world’s top data generators. It is critical that the data generated is collected and accessible from a single point. The main reasons why integrating EMR is important will be discussed below.

Securing Sensitive Information 

Healthcare, a prime target for cyberattacks, experienced 5.8% of total cyber-attacks in 2022. They focused on health records. EMR systems, HIPAA-compliant, strengthen data security. They safeguard patient records against cyber threats and natural disasters.

Streamlining Data Access

EMR integration offers a solution for data fragmentation. It consolidates patient records, making them easily accessible. So, doctors can view complete patient histories at a glance. This aids in accurate diagnoses.

Enhancing Workflow

Consider the effect of a unified report system. It would compile laboratory, pharmaceutical, and dental department data. This results in efficiency. Doctors make quicker decisions. They don’t wait for paper-based results. Automated record collection lightens staff workload too.

Safeguarding Patient Safety

Keeping patient data in different systems can cause errors. In fact, medical mistakes are the third leading cause of death in the U.S. EMR integration helps. It detects errors in record keeping, thereby promoting patient safety.

Improving Healthcare Outcomes

Access to complete patient information benefits healthcare providers. It leads to better understanding of patients’ conditions and helps doctors diagnose accurately. Also, timely access to records informs the design of preventive measures.

Boosting Patient Engagement

EMR systems do not just serve healthcare professionals. Patients also access their information. This breeds interest and empowerment. Patients become proactive in managing their health. Plus, easy doctor access via telehealth lessens the stress of physical consultations.

Are There Any Challenges?

Healthcare providers often hesitate to integrate Electronic Medical Records due to its complexity. Let’s explore the most common issues.

Cost Barrier: How Affordable Are EMR Solutions?

Deploying an EMR system can burn a hole in your pocket. Initial implementation may require you to shell out around $100,000. Small-sized practices might find this cost daunting. But, don’t worry. More wallet-friendly options like pre-built systems exist. Take Dchrono for instance. With a monthly fee of just $19, it’s a suitable pick for growing establishments.

However, be mindful if you’re eyeing free EHRs. In fact, we don’t recommend open source systems. They usually come with restrictions – lack of customization and a ceiling on patient data storage. Moreover, the choices for free EHR systems are slim. Due to their vital role in healthcare – with lives at stake – most prefer not to risk relying on a totally free, open-source EMR.

Compatibility with Legacy Systems 

Facilities already having EMR systems might wish to unite them through a single solution. However, finding one that fits all systems like a glove is a considerable challenge. The different systems might store data in diverse formats, complicating the integration process.

Transitioning Data

Migrating data from paper to digital, while linking it all, demands considerable effort. It might take weeks or months to transfer all health information completely. During this phase, potential information loss could shake patient trust. Careful planning and adequate time allocation can help manage this issue effectively.

Data Protection 

A tough nut to crack in EMR integration is securing private data. With medical records susceptible to breaches, it’s crucial to ensure watertight security. As an illustration, in 2021 alone, cyber-attacks exposed over 45 million records. To combat this, opt for a HIPAA-compliant vendor with a strong security framework.

Human Errors (Training and Adaptation)

Human-related challenges could put a spoke in the wheel of EMR integration. Resistance from staff towards the new system, incorrect data entry, and lack of training are common obstacles. Implementing a thorough training regimen can help staff adjust to the EMR software, ensuring accurate health record entry.

Navigating Interoperability

Interoperability lets healthcare providers share patient data. For interoperability to be comprehensive, FHIR and HL7, and other interoperability standards come into play.  

If you want to know more about them, check out our post on the differences between HL7 and FHIR. 

That said, achieving smooth data exchange isn’t that simple.

Firstly, not all systems speak the same ‘language’. We’ve got multiple data formats to deal with. Translating them so they align is a Herculean task.

Additionally, ensuring data safety while exchanging it between systems is tough. Security has to be top-notch. A single leak can breach patient privacy.

It’s also about change – old habits die hard. Many healthcare providers are still adjusting to new protocols. It takes time to shift from traditional methods.

Step-By-Step Guide to EMR Implementation 

Here’s a roadmap to help you through integrating your EMR.

Phase 1: Blueprint of Preparation

Begin your EMR integration journey with meticulous planning. Identify the needs of your practice, devise your strategy, set goals, and allocate time for staff training and the overall implementation process. The size of your practice and the volume of data to handle are crucial to your planning.

Phase 2: Structuring the Design

The next stage is design. You’ll need to consider the features you want in your EMR system. Focus on developing a tailor-made solution that connects all your EMRs and ensures an easy-to-navigate interface for your staff.

Should you desire a patient portal and telehealth functionalities, incorporate a mobile-friendly design. Consider engaging a development team to help with coding architecture at this stage.

Phase 3: Building the Infrastructure

Next, transform your design into functional software. This phase entails converting data from diverse formats across various EMRs. Given the potential risk of errors, which could compromise patient safety, it’s paramount to ensure accurate conversion of data. Always double-check to mitigate mistakes.

Phase 4: Testing the Functionality

Post-construction, the system needs to be rigorously tested. This step aims to identify any bugs, gauge user interactions, and evaluate the system’s reliability, data precision, and impact on your operations.

Phase 5: Activation and Launch

Finally, you’re ready to go live. Ensure your system complies with HIPAA regulations for health data security. Be open to feedback from users to facilitate continuous improvement.

Upon successful implementation, your new system should improve operational efficiency for your staff and enhance patient health outcomes.

Phase 6: Empowering through Training

Staff training is a critical aspect of EMR integration. Compile a comprehensive training manual to guide your staff through the new system. As not all employees may be tech-savvy, split the training into manageable segments for ease of comprehension.

EHR Vs. EMR Integration: Which Is Right for Your Practice?

Before going digital, you must pick. Is EHR or EMR right for you? Here’s how they compare. 

EMR	EHR
Data Scope	Records patient data in one practice.	Stores patient data from all providers.
Sharing	Shares data within one practice.	Shares data with multiple health professionals.
Data Transfer	Transferring data is difficult.	Transferring data is easier.
Data Focus	Focuses on diagnosis and treatment.	Gives a broad view of patient’s care.
Patient Access	Mainly for providers’ use.	Patients can also access their records.
Care Continuity	Good for tracking data in one practice.	Better for sharing updates with other caregivers.

Your choice between an EHR and an EMR depends on the needs of your practice and your patients. If you value a comprehensive, shareable, and patient-involved approach, an EHR might be a better fit. On the other hand, if you’re a single practice focusing on diagnosis and treatment, an EMR may suit you best.

Choosing a Healthcare Integration Service

Healthcare integration services, like EMR, ERP, and EHR, manage health information. When selecting one, you need to consider several key factors:

Growth Capability

When setting up an integration system, think long-term. Partner with an experienced vendor. They can help you grow your operations without losing data.

Data Safety

You will handle private data. So, your vendor must prioritize security. They should have proper industry certification. Also, they must understand HIPAA and other compliance needs.

Trustworthiness

Don’t entrust data management to an inexperienced vendor. Read reviews of different vendors. Talk to their current or past clients to judge their skills.

Adaptability

Avoid vendors with slow, inflexible systems. Choose a vendor that can adapt to your specific needs. This prevents unnecessary additions and keeps costs down.

Customer Service

Your vendor should provide excellent support. Fast responses to issues can prevent major downtime. This keeps your patients satisfied.

Conclusion

Implementing an EMR system brings great benefits to healthcare providers. Despite challenges like costs, the rewards are greater. To implement the steps we discussed, you need a skilled software development company.

The APP Solutions is that company. We’re qualified to build your EMR integration system. We support you through every development stage, from defining business goals to selecting the best vendor for your practice.