Disaster Recovery for Modern Digital IT

A Disaster Recovery strategy includes policies, tools and processes for recovery of data and restoration of systems in the event of a disruption. The cause of disruption could be natural, like earthquakes/floods, or man-made like power outages, hardware failures, terror attacks or cybercrimes. The aim of Disaster Recovery(DR) is to enable rapid recovery from the disaster to minimize data loss, extent of damage, and disruption to business. DR is often confused with Business Continuity Planning(BCP). While BCP ensures restoration of the entire business, DR is a subset of that, with focus on IT infrastructure, applications and data.

IT disasters come at the cost of lost revenue, tarnished brand image, lowered customer confidence and even legal issues relating to data privacy and compliance. The impact can be so debilitating that some companies never fully recover from it. With the average cost of IT downtime running to thousands of dollars per minute, it goes without saying that an enterprise-grade disaster recovery strategy is a must-have.

Why do companies neglect this need?

Inspite of the obvious consequences of a disaster, many organizations shy away from investing in a DR strategy due to the associated expenditure. Without a clear ROI in sight, these organizations decide to risk the vulnerability to catastrophic disruptions. They instead make do with just data backup plans or secure only some of the most critical elements of their IT landscape.

Why is Disaster Recovery different today?

The ripple effects of modern digital infrastructure have forced an evolution in DR strategies. Traditional Disaster Recovery methods are being overhauled to cater to the new hybrid IT infrastructure environment. Some influencing factors:

  • The modern IT Landscape

o Infrastructure – Today’s IT environment is distributed between on-premise, colocation facilities, public/private cloud, as-a-service offerings and edge locations. Traditional data centres are losing their prominence and are having to share their monopoly with these modern technologies. This trend has significant advantages such as reduced CapEx in establishing data centers, reduced latency because of data being closer to the user, and high dynamic scalability.

o Data – Adding to the complexity of modern digital infrastructure is the exponential growth in data from varied sources and of disparate types like big data, mobile data, streaming content, data from cloud, social media, edge locations, IoT, to name a few.

  • Applications – The need for agility has triggered the shift away from monolith applications towards microservices that typically use containers to provide their execution environment. Containers are ephemeral and so scale, shrink, disappear or move between nodes based on demand.
  • While innovation in IT helps digital transformation in unimaginable ways, it also makes it that much harder for IT teams to formulate a disaster recovery strategy for today’s IT landscape that is distributed, mobile, elastic and transient.
  • Cybercrimes are becoming increasingly prevalent and are a big threat to organizations. Moderntechnologies fuel increasing sophistication in malware and ransomware. As their complexity increases, they are becoming harder to even detect while they lie low and do their harm quietly inside the environment. By the time they are detected, the damage is done and it’s too late. DR strategies are also constantly challenged by the lucrative underworld of ransomware.

Solution Strategies for Disaster Recovery

  • On-Premise DR: This is the traditional option that translates toheavy upfront investments towardsthe facility, securing the facility, infrastructure including the network connectivity/firewalls/load balancers, resources to scale as needed, manpower, test drills, ongoing management and maintenance, software licensing costs, periodic upgrades for ongoing compatibility with the production environment and much more.

A comprehensive DR strategy involves piecing together several pieces of a complex puzzle. Due to the staggering costs and time involved in provisioning and managing infra for the duplicate storage and compute, companies are asking themselves if it is really worth the investment, and are starting to explore more OpEx based solutions. And, they are discovering that the cloud may be the answer to this challenge of evolving infra, offering cost-effective top-notch resiliency.

  • Cloud-based DR: The easy availability of public cloud infrastructure & services, with affordablemonthly subscription plans and pay per use rates, has caused an organic switch to the cloud for storage, infra and as a Service(aaS) needs. To complement this, replication techniques have also evolved to enable cloud replication. With backup on the cloud, the recovery environment needs to be paid for only when used in the event of a disaster!

Since maintaining the DR site is the vendor’s responsibility, it reduces the complexity in managing the DR site and the associated operating expenses as well. Most DR requirements are intrinsically built into cloud solutions: redundancy, advanced networks, bandwidth, scalability, security & compliance. These can be availed on demand, as necessitated by the environment and recovery objectives. These features have made it feasible for even small businesses to acquire DR capabilities.

Disaster Recovery-as-a-Service(DRaaS) which is fast gaining popularity, is a DR offering on the cloud, where the vendor manages the replication, failover and failback mechanisms as needed for recovery, based on a SLA driven service contract .

On the flip side, as cloud adoption becomes more and more prevalent, there are also signs of a reverse drain back to on-premise! Over time, customers are noticing that they are bombarded by hefty cloud usage bills, way more than what they had bargained for. There is a steep learning curve

in assimilating the nuances of new cloud technologies and the innumerable options they offer. It is critical for organizations to clearly evaluate their needs, narrow down on reliable vendors with mature offerings, understand their feature set and billing nitty-gritties and finalize the best fit for their recovery goals. So, it is Cloud, but with Caution!

  • Integrating DR with the Application: Frank Jablonski, VP of Global Marketing, SIOS Technology Corppredicts that applications will soon have Disaster Recovery architected into their core, as a value-add. Cloud-native implementations will leverage the resiliency features of the cloud to deliver this value.

The Proactive Approach

Needless to say, investing in a proactive approach for disaster prevention will help mitigate the chances for a disaster in the first place. One sure-fire way to optimize IT infrastructure performance, prevent certain types of disasters and enhance business services continuity is to use AI augmented ITOps platforms to manage the IT environment. GAVS’ AIOps platform, Zero Incident FrameworkTM(ZIF) has modules powered by Advanced Machine Learning to Discover, Monitor, Analyze, Predict, and Remediate, helping organizations drive towards a Zero Incident EnterpriseTM. For more information, please visit the ZIF website.

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CCPA for Healthcare

The California Consumer Privacy Act (CCPA) is a state statute intended to enhance consumer protection and data privacy rights of the residents of California, United States. It is widely considered one of the most sweeping consumer privacy laws, giving Californians the strongest data privacy rights in the U.S.

The focus of this article is CCPA as it applies to Healthcare. Let’s take a quick look at what CCPA is and then move onto its relevance for Healthcare entities. CCPA is applicable to any for-profit organization – regardless of whether it physically operates out of California – that interacts with, does business with and/or collects, processes or monetizes personal information of California residents AND meets at least one of these criteria: has annual gross revenue in excess of $25 million USD; collects or transacts with the personal information of 50,000 or more California consumers, households, or devices; earns 50% or more of its annual revenue by monetizing such data. CCPA also empowers California consumers with the rights to complete ownership; control; and security of their personal information and imposes new stringent responsibilities on businesses to enable these rights for their consumers.

Impact on Healthcare Companies

Companies directly or indirectly involved in the healthcare sector and dealing with medical information are regulated by the Confidentiality of Medical Information Act (CMIA) and the Health Insurance Portability and Accountability Act (HIPAA). CCPA does not supersede these laws & does not apply to ‘Medical Information (MI)’ as defined by CMIA, or to ‘Protected Health Information (PHI)’ as defined by HIPAA. CCPA also excludes de- identified data and information collected by federally-funded clinical trials, since such research studies are regulated by the ‘Common Rule’.

The focus of the CCPA is ‘Personal Information (PI)’ which means information that “identifies, relates to, describes, is capable of being associated with, or could reasonably be linked, directly or indirectly, with a particular consumer or household.” PI refers to data including but not limited to personal identifiers such as name, address, phone numbers, email ids, social security number; personal details relating to education, employment, family, finances; biometric information, geolocation, consumer activity like purchase history, product preferences; internet activity.

So, if CCPA only regulates personal information, are healthcare companies that are already in compliance with CMIA and HIPAA safe? Is there anything else they need to do?

Well, there is a lot that needs to be done! This only implies that such companies should continue to comply with those rules when handling Medical Information as defined by the CMIA, or Protected Health Information, as defined by HIPAA. They will still need to adhere to CCPA regulations for personal data that is outside of MI and PHI. This will include

employee personal information routinely obtained and processed by the company’s HR; those collected from websites, health apps, health devices, events; clinical studies that are not funded by the federal government; information of a CCPA-covered entity that is handled by a non-profit affiliate, to give a few examples.

There are several possibilities – some not so apparent – even in healthcare entities, for personal data collection and handling that would fall under the purview of CCPA. They need to take stock of the different avenues through which they might be obtaining/handling such data and prioritize CCPA compliance. Else, with the stringent CCPA regulations, they could quickly find themselves embroiled in class action lawsuits (which by the way, do not require proof of damage to the plaintiff) in case of data breaches, or statutory penalties of up to $7500 for each violation.

The good news is that since CCPA carves out a significant chunk of data that healthcare companies/those involved in healthcare-related functions collect and process, entities that are already complying with HIPAA and CMIA are well into the CCPA compliance journey. A peek into the kind of data CMIA & HIPAA regulate will help gauge what other data needs to be taken care of.

CMIA protects the confidentiality of Medical Information (MI) which is “individually identifiable information, in electronic or physical form, in possession of or derived from a provider of health care, health care service plan, pharmaceutical company, or contractor regarding a patient’s medical history, mental or physical condition, or treatment.”

HIPAA regulates how healthcare providers, health plans, and healthcare clearinghouses, referred to as ‘covered entities’ can use and disclose Protected Health Information (PHI), and requires these entities to enable protection of data privacy. PHI refers to individually identifiable medical information such as medical records, medical bills, lab tests, scans and the like. This also covers PHI in electronic form(ePHI). The privacy and security rule of HIPAA is also applicable to ‘business associates’ who provide services to the ‘coveredentities’ that involve the use or disclosure of PHI.

Two other types of data that are CCPA exempt are Research Data & De-Identified Data. As mentioned above, the ‘Common Rule’ applies only to federally-funded research studies, and the CCPA does not provide much clarity on exemption status for data from clinical trials that are not federally-funded.

And, although the CCPA does not apply to de-identified data, the definitions of de-identified data of HIPAA and CCPA slightly differ which makes it quite likely that de-identified data by HIPAA standards may not qualify under CCPA standards and therefore would not be exempt from CCPA regulations.

Compliance Approach

Taking measures to ensure compliance with regulations is cumbersome and labour-intensive, especially with the constantly evolving regulatory environment. Using this opportunity for a proactive, well-thought-out approach for comprehensive enterprise-wide data security and governance will be strategically wise since it will minimize the need for policy and process rehaul with each new regulation.

The most crucial step is a thorough assessment of the following:

  • Policies, procedures, workflows, entities relating to/involved in data collection, sharing and processing, in order to arrive at clear enterprise-wide data mapping; to determine what data, data activities, data policies would fall under the scope of CCPA; and to identify gaps and decide on prioritized action items for compliance.
  • Business processes, contracts, terms of agreement with affiliates, partners and third-party entities the company does business with, to understand CCPA applicability. In some cases,

HIPAA and CMIA may be applicable to only the healthcare-related business units, subjecting other business units to CCPA compliance.

  • Current data handling methods, not just its privacy & security. CCPA dictates that companies need to have mechanisms put in place to cater to CCPA consumer right to request all information relating to the personal data collected about them, right to opt-out of sale of their data, right to have their data deleted by the organization (which will extend to 3rd parties doing business with this organization as well).

Consumer Consent Management

With CCPA giving full ownership and control of personal data back to its owners, consent management mechanisms become the pivot of a successful compliance strategy. An effective mechanism will ensure proper administration and enforcement of consumer authorizations.

Considering the limitations of current market solutions for data privacy and security, GAVS has come up with its Blockchain-based Rhodium Framework (pending patent) for Customer Master Data Management and Compliance with Data Privacy Laws like CCPA.

You can get more details on CCPA in general and GAVS’ solution for true CCPA Compliance in our White Paper, Blockchain Solution for CCPA Compliance.

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Proactive Monitoring

Is your IT environment proactively monitored?

It is important to have the right monitoring solution for an enterprise’s IT environment. More than that, it is imperative to leverage the right solution and deploy it for the appropriate requirements. In this context, the IT environment includes but is not limited to Applications, Servers, Services, End-User Devices, Network devices, APIs, Databases, etc. Towards that, let us understand the need and importance of Proactive Monitoring. This has a direct role in achieving the journey towards Zero Incident EnterpriseTM. Let us unravel the difference between reactive and proactive monitoring.

Reactive Monitoring – When a problem occurs in an IT environment, it gets notified through monitoring and the concerned team acts on it to resolve the issue.The problem could be as simple as slowness/poor performance, or as extreme as the unavailability of services like web site going down or server crashing leading to loss of business and revenue.  

Proactive Monitoring – There are two levels of proactive monitoring, 

  • Symptom-based proactive monitoring is all about identifying the signals and symptoms of an issue in advance and taking appropriate and immediate action to nip the root-cause in the bud.
  • Synthetic-based proactive monitoring is achieved through Synthetic Transactions. Performance bottlenecks or failures are identified much in advance; even before the actual user or the dependent layer encounters the situation

Symptom-based proactive monitoring is a USP of the ZIF Monitor module. For example, take the case of CPU related monitoring. It is common to monitor the CPU utilization and act based on that. But Monitor doesn’t just focus on CPU utilization, there are a lot of underlying factors which causes the CPU utilization to go high. To name a few,

  • Processor queue length 
  • Processor context switches
  • Processes that are contributing to high CPU utilization

It is important to arrest these brewing factors at the right time, i.e., in the case of Processor Queue length, continuous or sustained queue of greater than 2 threads is generally an indication of congestion at processor level.Of course, in a multiple processor environment, we need to divide the queue length by the number of processors that are servicing the workload. As a remedy, the following can be done

1) the number of threads can be limited at the application level

2) unwanted processes can be killed to help close the queued items

3) upgrading the processor will help in keeping the queue length under control, which eventually will control the CPU utilization.

Above is a sample demonstration of finding the symptom and signal and arrest them proactively. ZIF’s Monitor not only monitors these symptoms, but also suggests the remedy through the recommendation from SMEs.

Synthetic monitoring (SM) is done by simulating the transactions through the tool without depending on the end-user to do the transactions. The advantages of synthetic monitoring are, 

  • it uses automated transaction simulation technology
  • it helps to monitor the environment round-the-clock 
  • it helps to validate from across different geographic locations 
  • it provides options to choose the number of flows/transactions to be verified
  • it is proactive – identifies performance bottlenecks or failures much in advance even before the actual user or the dependent layer encounters the situation

How does Synthetic Monitoring(SM) work?

It works through 3 simple steps,

1) Record key transactions – Any number of transactions can be recorded, if required, all the functional flows can be recorded. An example of transaction in an e-commerce website could be, as simple as login and view the product catalogue, or,as elaborate as login, view product catalogue, move item to cart, check-out, make-payment and logout. For simulation purpose, dummy credit cards are used during payment gateway transactions.

2) Schedule the transactions – Whether it should run every 5 minutes or x hours or minutes.

3) Choose the location from which thesetransactions need to be triggered – The SM is available as on-premise or cloud options. Cloud SM provides the options to choose the SM engines available across globe (refer to the green dots in the figure below).

This is applicable mainly for web based applications, but can also be used for the underlying APIs as well.

SM solution has engines which run the recorded transactions against the target application. Once scheduled, the SM engine hosted either on-premise or remotely (refer to the green dots in the figure shown as sample representation), will run the recorded transactions at a predefined interval. The SM dashboard provides insights as detailed under the benefits section below.

Benefits of SM

As the SM does the synthetic transactions, it provides various insights like,

  • The latency in the transactions, i.e. the speed at which the transaction is happening. This also gives a trend analysis of how the application is performing over a period.
  • If there are any failures during the transaction, SM provides the details of the failure including the stack trace of the exception. This makes fixing the failure simpler, by avoiding the time spent in debugging.
  • In case of failure, SM provides insights into the parameter details that triggered the failure.
  • Unlike real user monitoring, there is the flexibility to test all flows or at least all critical flows without waiting for the user to trigger or experience it.
  • This not only unearths the problem at the application tier but also provides deeper insights while combining it with Application, Server, Database, Network Monitoring which are part of the ZIF Monitor suite.
  • Applications working fine under one geography may fail in a different geography due to various factors like network, connectivity, etc. SM will exactly pinpoint the availability and performance across geographies.

For more detailed information on GAVS’Monitor, or to request a demo please visit, https://zif.ai/products/monitor/

About the Author

Suresh Kumar Ramasamy


Suresh heads the Monitor component of ZIF at GAVS. He has 20 years of experience in Native Applications, Web, Cloud and Hybrid platforms from Engineering to Product Management. He has designed & hosted the monitoring solutions. He has been instrumental in conglomerating components to structure the Environment Performance Management suite of ZIF Monitor.

Suresh enjoys playing badminton with his children. He is passionate about gardening, especially medicinal plants.

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