How does the BurnMed mobile app compare to traditional burn assessment methods. What are the key features and benefits of using BurnMed for measuring burn surface area. Can BurnMed improve accuracy and efficiency in burn assessment compared to the Lund and Browder chart.

The Evolution of Burn Assessment: From Lund and Browder to BurnMed

Accurate assessment of burn surface area is crucial for proper treatment and management of burn injuries. Traditionally, healthcare professionals have relied on the Lund and Browder chart for estimating the percentage of total body surface area (TBSA) affected by burns. However, this method has limitations in terms of accuracy and ease of use, especially for inexperienced practitioners.

Enter BurnMed, a revolutionary mobile software application designed to streamline and enhance the burn assessment process. This innovative tool leverages modern technology to provide a more precise and user-friendly approach to measuring burn surface area.

What is BurnMed?

BurnMed is a mobile app that utilizes a three-dimensional model of the human body to calculate burn surface area. Users can manipulate the model on their mobile device and simply touch the areas corresponding to the patient’s burns. The app then calculates the surface area in real-time, providing a quick and accurate assessment.

Comparing BurnMed to the Lund and Browder Chart: A Study in Efficiency and Accuracy

To evaluate the effectiveness of BurnMed, a study was conducted involving 18 first-year medical students with no prior experience in burn assessment. The participants were tasked with measuring burn surface area using both the traditional Lund and Browder chart and the BurnMed app.

Study Methodology

• Participants: 18 first-year medical students
• Experience level: No prior burn assessment training
• Assessment methods: Lund and Browder chart vs. BurnMed app
• Evaluation criteria: Accuracy and time taken for assessment

Key Findings

1. Time efficiency: BurnMed significantly reduced assessment time
2. Accuracy: BurnMed showed improved accuracy compared to the Lund and Browder chart
3. User-friendliness: Participants found BurnMed more intuitive and easier to use

The Science Behind BurnMed: Three-Dimensional Modeling for Enhanced Precision

BurnMed’s innovative approach to burn assessment relies on advanced three-dimensional modeling technology. This allows for a more accurate representation of the human body, taking into account variations in body shape and size that may affect burn surface area calculations.

How does BurnMed’s 3D modeling improve accuracy?

The three-dimensional model used in BurnMed offers several advantages over traditional two-dimensional charts:

• Better representation of body contours and proportions
• Ability to account for individual patient variations
• More precise localization of burn areas
• Real-time calculation of surface area percentages

By incorporating these features, BurnMed addresses many of the limitations associated with traditional burn assessment methods, potentially leading to more accurate diagnoses and treatment plans.

User Experience: Navigating BurnMed’s Interface

One of the key factors contributing to BurnMed’s effectiveness is its user-friendly interface. The app is designed to be intuitive and easy to use, even for those with limited experience in burn assessment.

Key features of BurnMed’s user interface:

• Interactive 3D model that can be rotated and zoomed
• Touch-based input for marking burn areas
• Real-time calculation and display of burn surface area
• Clear visual representation of affected areas
• Option to save and export assessment results

These features combine to create a seamless user experience, allowing healthcare professionals to focus on accurate assessment rather than struggling with complex charts or calculations.

Implications for Burn Care: Potential Impact of BurnMed on Treatment Outcomes

The introduction of BurnMed has the potential to significantly impact burn care practices and outcomes. By providing a more accurate and efficient method of burn surface area assessment, this innovative tool may lead to several improvements in patient care.

How can BurnMed improve burn treatment?

1. More precise fluid resuscitation calculations
2. Better-informed decisions regarding treatment modalities
3. Improved monitoring of burn progression and healing
4. Enhanced communication between healthcare providers
5. Potential for standardization of burn assessment practices

These improvements could ultimately lead to better patient outcomes, reduced complications, and more efficient use of healthcare resources in burn treatment centers.

Training and Implementation: Integrating BurnMed into Clinical Practice

While BurnMed offers numerous advantages over traditional burn assessment methods, its successful implementation in clinical practice requires careful consideration and planning. Healthcare institutions looking to adopt this technology should focus on comprehensive training programs and gradual integration into existing workflows.

Steps for successful BurnMed implementation:

1. Conduct thorough staff training on BurnMed usage
2. Develop clear protocols for when and how to use the app
3. Establish quality control measures to ensure accurate assessments
4. Integrate BurnMed data with existing electronic health record systems
5. Monitor and evaluate the impact of BurnMed on clinical outcomes

By following these steps, healthcare providers can maximize the benefits of BurnMed while ensuring a smooth transition from traditional assessment methods.

Future Directions: Expanding BurnMed’s Capabilities

As technology continues to advance, there are numerous possibilities for expanding and improving BurnMed’s functionality. Future iterations of the app could incorporate additional features to further enhance its utility in burn care.

Potential future developments for BurnMed:

• Integration with artificial intelligence for burn depth assessment
• Incorporation of augmented reality for more immersive visualization
• Expansion to include pediatric-specific models and calculations
• Addition of telemedicine capabilities for remote consultations
• Integration with wearable devices for continuous monitoring of burn healing

These potential advancements could further revolutionize burn assessment and management, leading to even better outcomes for burn patients.

Challenges and Limitations: Addressing Concerns About BurnMed

While BurnMed offers numerous advantages, it is important to acknowledge and address potential challenges and limitations associated with its use. By understanding these issues, healthcare providers can make informed decisions about implementing and using the app in clinical practice.

Potential challenges of BurnMed adoption:

1. Initial cost of implementation and device procurement
2. Resistance to change from healthcare professionals accustomed to traditional methods
3. Potential for over-reliance on technology at the expense of clinical judgment
4. Need for regular software updates and maintenance
5. Concerns about data security and patient privacy

Addressing these challenges will be crucial for the widespread adoption and success of BurnMed in clinical settings.

Comparative Analysis: BurnMed vs. Other Digital Burn Assessment Tools

While BurnMed represents a significant advancement in burn assessment technology, it is not the only digital tool available. A comparative analysis of BurnMed and other similar applications can provide valuable insights into its strengths and potential areas for improvement.

Features to compare across digital burn assessment tools:

• Accuracy of surface area calculations
• Ease of use and user interface design
• Compatibility with various devices and operating systems
• Integration capabilities with existing healthcare systems
• Additional features beyond basic surface area calculation
• Cost and licensing models

By evaluating BurnMed against other available options, healthcare providers can make informed decisions about which tool best suits their needs and practice environment.

The Role of BurnMed in Burn Research and Education

Beyond its clinical applications, BurnMed has the potential to play a significant role in burn research and medical education. The app’s ability to provide standardized, accurate measurements could enhance the quality and consistency of burn-related studies.

How can BurnMed contribute to burn research and education?

1. Facilitating more accurate data collection in clinical trials
2. Providing a standardized tool for comparing burn assessment techniques
3. Offering a realistic training platform for medical students and residents
4. Enabling virtual simulations for burn management scenarios
5. Supporting the development of new treatment protocols based on precise surface area calculations

By leveraging BurnMed in these areas, the burn care community can accelerate advancements in treatment approaches and improve the overall quality of burn education and research.

Global Impact: BurnMed’s Potential in Resource-Limited Settings

While BurnMed was developed in a high-resource setting, its potential impact in resource-limited environments should not be overlooked. The app’s ability to provide accurate assessments with minimal training could be particularly valuable in areas where access to specialized burn care is limited.

Benefits of BurnMed in resource-limited settings:

• Improved accuracy of burn assessment by non-specialist healthcare providers
• Potential for remote consultation and telemedicine applications
• Standardization of burn assessment practices across diverse healthcare settings
• Enhanced triage capabilities for burn patients in mass casualty events
• Support for training and education of local healthcare workers

By considering the global applications of BurnMed, developers and healthcare organizations can work towards making this valuable tool accessible to a wider range of practitioners and patients worldwide.

Ethical Considerations: Balancing Technology and Human Judgment in Burn Care

As with any technological advancement in healthcare, the introduction of BurnMed raises important ethical considerations. It is crucial to strike a balance between leveraging the benefits of this innovative tool and maintaining the importance of clinical expertise and human judgment in burn care.

Key ethical considerations for BurnMed usage:

1. Ensuring that technology enhances rather than replaces clinical decision-making
2. Maintaining patient privacy and data security in digital burn assessments
3. Addressing potential disparities in access to BurnMed technology
4. Considering the impact on healthcare provider-patient relationships
5. Developing guidelines for responsible use and interpretation of BurnMed results

By thoughtfully addressing these ethical considerations, the burn care community can ensure that BurnMed is implemented in a way that truly benefits patients and healthcare providers alike.

The Economic Impact of BurnMed: Cost-Benefit Analysis for Healthcare Systems

While the clinical benefits of BurnMed are clear, healthcare administrators and policymakers must also consider the economic implications of adopting this technology. A comprehensive cost-benefit analysis can help inform decisions about implementing BurnMed in various healthcare settings.

Factors to consider in a BurnMed cost-benefit analysis:

• Initial investment costs (software licenses, compatible devices, training)
• Potential savings from improved accuracy and efficiency in burn assessment
• Impact on length of hospital stay and resource utilization
• Reduction in complications due to more precise fluid resuscitation
• Long-term outcomes and potential reduction in readmission rates
• Cost savings from standardization of burn assessment practices

By carefully evaluating these factors, healthcare systems can make informed decisions about the financial viability and potential return on investment of implementing BurnMed.

BurnMed and Patient Empowerment: Enhancing Understanding and Engagement in Burn Care

Beyond its clinical applications, BurnMed has the potential to play a role in patient education and empowerment. By providing clear, visual representations of burn injuries, the app can help patients better understand their condition and actively participate in their care.

How can BurnMed contribute to patient empowerment?

1. Facilitating clearer communication between healthcare providers and patients
2. Helping patients visualize their burn injuries and healing progress
3. Providing a tool for patients to track and document their recovery
4. Supporting patient education about burn care and treatment options
5. Enhancing patient engagement in shared decision-making processes

By leveraging BurnMed as a patient education tool, healthcare providers can foster greater understanding and engagement, potentially leading to improved adherence to treatment plans and better overall outcomes.

The Future of Burn Assessment: Integrating BurnMed with Emerging Technologies

As technology continues to advance at a rapid pace, the future of burn assessment is likely to involve the integration of BurnMed with other emerging technologies. This convergence could lead to even more sophisticated and comprehensive burn care solutions.

Potential integrations and advancements for BurnMed:

• Combination with 3D scanning technology for even more precise body modeling
• Integration with machine learning algorithms for predictive burn progression analysis
• Incorporation of virtual reality for immersive burn assessment training
• Coupling with biomedical sensors for real-time monitoring of burn wound healing
• Development of a BurnMed ecosystem connecting various aspects of burn care management

By staying at the forefront of technological advancements, BurnMed can continue to evolve and provide increasingly valuable tools for burn assessment and management.

Mobile App for Measuring the Surface Area of a Burn in Three Dimensions | Journal of Burn Care & Research

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Harry Goldberg, PhD,

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Justin Klaff, MD,

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Aaron Spjut, BS,

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Journal of Burn Care & Research, Volume 35, Issue 6, November-December 2014, Pages 480–483, https://doi. org/10.1097/BCR.0000000000000037

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01 November 2014

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Abstract

The aim of this study was to compare the ease and accuracy of measuring the surface area of a severe burn through the use of a mobile software application (BurnMed) to the traditional method of assessment, the Lund and Browder chart. BurnMed calculates the surface area of a burn by enabling the user to first manipulate a three-dimensional model on a mobile device and then by touching the model at the locations representing the patient’s injury. The surface area of the burn is calculated in real time. Using a cohort of 18 first-year medical students with no experience in burn care, the surface area of a simulated burn on a mannequin was made using BurnMed and compared to estimates derived from the Lund and Browder chart. At the completion of this study, students were asked to complete a questionnaire designed to assess the ease of use of BurnMed. Users were able to easily and accurately measure the surface area of a simulated burn using the BurnMed application. In addition, there was less variability in surface area measurements with the application compared to the results obtained using the Lund and Browder chart. Users also reported that BurnMed was easier to use than the Lund and Browder chart. A software application, BurnMed, has been developed for a mobile device that easily and accurately determines the surface area of a burn. This system uses a three-dimensional model that can be rotated, enlarged, and transposed by the health care provider to easily determine the extent of a burn. Results show that the variability of measurements using BurnMed is lower than the measurements obtained using the Lund and Browder chart. BurnMed is available at no charge in the Apple™ Store.

Copyright © 2014 by the American Burn Association

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Types of Burns | Burn Injury Attorneys San Francisco

There are several types of burn injuries. Previously, burns were categorized by degree, ranging in severity from first to third. Current medical terminology refers to the depth of the burn:

• Superficial (first-degree) burns: The mildest form of burn, this type produces redness of the skin and pain, but no blistering. It is considered a minor burn and may usually be treated at home.
• Partial thickness (second-degree) burns: This type of burn is more severe than a superficial burn. It affects both the outer skin layer (the epidermis) and the underlying layer (dermis), causing blisters, swelling, redness and pain. If left untreated, these burns may progress into more serious full-thickness burns.
• Full thickness (third-degree) burns: These burns involve destruction of the skin and underlying tissues. They are termed “full-thickness” because all levels of the skin are damaged. These burns are extremely serious; they typically require prolonged hospitalization and skin grafting surgeries. They often result in extensive scarring.

Several factors are used to determine the severity of a burn injury, including the patient’s age, size and depth of burn, and the location of the burn. For adults, a “Rule of Nines” chart is used to determine the total body surface area (TBSA) that has been burned. The chart divides the body into sections that each represent nine percent of the body surface area. In determining the TBSA of children and infants, a different reference, the Lund-Browder chart, is used.

Inhalation Injuries

Burn injuries are obvious. But another type of fire-related injury may not produce immediately visible symptoms. Inhalation injuries can cause extensive damage to the lungs and airways.

There are three types of inhalation injuries: damage from heat inhalation, damage from systemic toxins and damage from smoke inhalation. Outward symptoms of these injuries – such as fainting, shortness of breath, headache, coughing and hoarseness – often do not appear until 24 to 36 hours after exposure.

Inhalation injuries can be just as severe – if not more so – than burns. According to recent literature, the leading cause of death in structural fires is not thermal injury, but smoke inhalation. Burn victims frequently suffer both types of injury.

Rely On Our Proven Experience As Advocates For Burn Injury Victims

At Walkup, Melodia, Kelly & Schoenberger, a leading personal injury law firm in San Francisco, we have obtained multimillion-dollar recoveries for burn injury victims and their families. Our legacy of excellence extends back more than five decades.

The legal team at Walkup includes talented attorneys who consistently rank among the top California lawyers. One of our attorneys is also a physician with two decades of experience in the medical field. This combination of medical and legal knowledge gives us a thorough understanding of all types of burn and inhalation injuries.

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Burn injuries take an extreme financial toll. Explore your options for financial recovery with the help of our seasoned legal team. For a free initial consultation, please contact us online today or by calling (415) 981-7210.

Determination of burn area: rule of nines and palm

Table of contents

1. Degrees
2. Symptoms
3. Determination of area
4. Rule of hundreds
5. Rule of nines 90 006
6. Palm rule
7. Postinkov method
8. Dolinin method
9. Conclusion

Last Updated on 06/23/2017 by Perelomanet

A burn is an injury to the soft tissues of the human body resulting from negative thermal, electrical or chemical effects. For the correct provision of first aid and the choice of the method of subsequent treatment, it is necessary to determine the severity of the injury and the area affected by it. There are many techniques that allow you to accurately subtract the area of ​​burns.

The area of ​​the human body is approximately 21,000 square centimeters. Scientists have invented many schemes and formulas that help calculate the burn area in children and adults. If you correctly calculate the size of the injured area, then you can determine the severity of the injury that has arisen.

Degrees

There are several degrees of severity of this damage:

• first degree burn – slight swelling and redness form on the skin;
• the second degree is accompanied by the formation of minor blisters with a special internal fluid that protects the wound of infection. With a burn of this type, the skin begins to exfoliate and pain is present;
• third degree type A – characterized by a fairly deep damage to the skin, the formation of a brown crust and pain;
• third degree type B – with a burn of this type, complete death of the skin occurs;
• 4th degree burns are the most serious damage to the skin, affecting blood vessels, muscles, joints, and sometimes even bones. Pain is not observed due to complete charring of the skin.

First, second and third A degrees are called superficial burns, while degrees 3B and fourth, respectively, are called deep. Superficial injuries are always associated with pain, but deep ones are not. The absence of pain in this case is explained by the complete necrosis of the affected epidermis.

Symptoms

Signs of a burn depend on the type of burn surface and the nature of the injury, but there are a number of main symptoms that most often appear with such an injury:

• change in skin color from reddish to black. The color depends on the nature and severity of the damage;
• the appearance of blisters (see burn blister: what to do), which are filled with a special liquid;
• formation of a dryish crust in the injured area;
• severe pain;
• death of the skin;
• charring of the skin.

Determining the area

Injury treatment is prescribed only after an accurate determination of the nature of the injury, in order to determine the depth of the injury and its severity – the area of ​​the burn should be subtracted.

Hundred rule

The simplest way to calculate the injured surface in adults is the “hundred rule”. In the event that, adding up the age of the victim and the total area of ​​\u200b\u200bthe injury, a number close to a hundred comes out, then the lesion is considered unfavorable, and it requires special treatment.

The Rule of Nines

In 1951, scientist A. Wallace invented a computational method called the Rule of Nines for Burns. This type of calculation of the wounded surface is quite fast and easy. The data obtained as a result of the calculation is inaccurate, but quite approximate.

This method consists in dividing the human body into separate zones. Each such plot in relation to the percentage is equal to nine. Neck and head – 9%, each individual limb – 9%, the torso front and back results in 36%, and 1% is allocated to the genital area.

This method is not suitable for determining burns in children, because the proportions of their bodies are slightly different.

Rule of the palm

In 1953, I. Glumov invented an even simpler method for calculating the injured surface. According to the rule of the palm, the burn zone is equal to the palm of the victim. Its size is approximately considered one percent of the entire surface of the human body. This method is used as often as the “rule of nine”.

Postinkov’s method

Postnikov’s method is a rather old determination of the burn area and is not easy. It is based on the application of a gauze bandage to the wounded surface, and a contour drawing of the injury is applied on top of it. After that, the resulting shape is superimposed on graph paper and a general calculation of the surface is carried out in relation to the damaged skin. Due to the difficulties that arise during such a calculation, it is practically not used.

Dolinin method

In 1983 the Dolinin method was invented. It consists in dividing by 100 a special stamp of rubber material, which contains the silhouette of the back and front of the human body. The front side collects 51 sections, and the back side – 49. Each of the sections in a percentage ratio is 1%. In the diagram, the affected area is painted over and, after completion, the filled-in numbers added together are counted.

Land and Browder burn areas are calculated for young children. In a child under one year old, the surface of the neck and head is equal to 21%, the torso in front and behind – 16%, the femoral region – 5%, the areas of the lower leg and feet – 9%, the place of the perineum – 1%.

Conclusion

The complexity and effectiveness of treatment depends on the place where the injury was received and the area of ​​the burn. For example, if parts of the face, hands or genital areas are affected during an injury, the ability to work is often impaired, the skin cannot be restored, complete disability is possible, and in some cases death. Lethal outcome occurs mainly when the area of ​​injury is 40% or more.

translation of the article “Calculation of service reliability” / Habr

The main task of commercial (and non-commercial too) services is to be always available to the user. Although failures happen to everyone, the question is what does the IT team do to minimize them. We have translated an article by Ben Traynor, Mike Dahlin, Vivek Rau and Betsy Beyer “Calculating Service Reliability”, which explains, including using the example of Google, why 100% is the wrong benchmark for a reliability indicator, what the “four nines rule” is, and how, in practice, to mathematically predict the acceptability of major and minor outages of a service and/or its critical components — the expected amount of downtime, failure detection time, and service recovery time.

Service Reliability Calculation

Your system is only as reliable as its components

Ben Traynor, Mike Dalin, Vivek Rau, Betsy Beyer

As described in Site Reliability Engineering: Reliability and reliability like in Google ” (hereinafter referred to as the SRE book), Google’s product and service development can achieve a high release rate of new features while maintaining aggressive SLOs (service-level objectives) for high reliability and responsiveness. SLOs require the service to be almost always up and almost always fast. At the same time, SLOs also indicate the exact values ​​\u200b\u200bof this “almost always” for a particular service. SLOs are based on the following observations:

In general, for any software service or system, 100% is the wrong benchmark for reliability, because no user can tell the difference between 100% and 99.999% availability. Between the user and the service there are many other systems (his laptop, home Wi-Fi, provider, power grid …), and all these systems in the aggregate are not available in 99.999% of cases, but much less often. Therefore, the difference between 99.999% and 100% is lost to random factors due to the unavailability of other systems, and the user does not receive any benefit from the fact that we spent a lot of effort achieving this last fraction of a percent of system availability. Serious exceptions to this rule are anti-lock brake control systems and pacemakers!

For a detailed discussion of how SLOs relate to SLIs (service-level indicators) and SLAs (service-level agreements, service level agreements), see the SRE Book’s Service Level Target chapter. This chapter also details how to select the metrics that matter for a particular service or system, which in turn determines the selection of the appropriate SLO for that service or system.

This article expands on the SLO topic to focus on the building blocks of services. In particular, we will look at how the reliability of critical components affects the reliability of a service, as well as how to design systems to mitigate the impact or reduce the number of critical components.

Most of the services offered by Google aim to provide 99.99 percent (sometimes called “four nines”) availability for users. For some services, a lower number is specified in the user agreement, but the target of 99.99% is maintained internally. This higher bar is an advantage in situations where users express dissatisfaction with the performance of the service long before the breach of agreement occurs, since the #1 goal of the SRE team is to ensure that users are satisfied with the services. For many services, internal goal 99.99% is the sweet spot that balances cost, complexity, and reliability. For some others, notably global cloud services, the internal goal is 99.999%.

99.99% Reliability: Observations and Conclusions

Let’s look at a few key observations and conclusions about designing and operating a service with 99.99% reliability, and then move on to practice.

Observation #1: Causes of failures

Failures occur for two main reasons: problems with the service itself and problems with critical components of the service. A critical component is a component that, in the event of a failure, causes a corresponding failure in the operation of the entire service.

Observation #2: The Math of Reliability

Reliability depends on the frequency and duration of downtime. It is measured in terms of:

• Downtime frequency, or inverse of it: MTTF (mean time to failure, mean time between failures).
• Downtime, MTTR (mean time to repair, average recovery time). The duration of downtime is determined by the user’s time: from the onset of a malfunction to the resumption of normal operation of the service.
  Therefore, reliability is mathematically defined as MTTF/(MTTF+MTTR) using the appropriate units.

Conclusion #1: The Rule of Complementary Nines

A service cannot be more reliable than all of its critical components put together. If your service is aiming for 99.99% availability, then all critical components must be available significantly more than 99.99% of the time.
Inside Google, we use the following rule of thumb: critical components should provide additional 9s compared to your service’s claimed reliability – in the example above, 99.999 percent availability – because any service will have several critical components, as well as its own specific problems. This is called the “additional nines rule”.
If you have a critical component that doesn’t deliver enough 9s (a relatively common problem!), you need to minimize the negative impact.

Conclusion #2: The Math of Frequency, Detection Time, and Recovery Time

A service cannot be more reliable than the product of incident frequency times detection and recovery time. For example, three total shutdowns per year of 20 minutes result in a total of 60 minutes of downtime. Even if the service worked perfectly during the rest of the year, 99.99 percent reliability (no more than 53 minutes of downtime per year) would be impossible.
This is a simple mathematical observation, but it is often overlooked.

Conclusion from Findings #1 and #2

If the level of reliability your service relies on cannot be achieved, efforts should be made to correct the situation, either by increasing the level of service availability or by minimizing the negative impacts as described higher. Lowering expectations (i.e., advertised reliability) is also an option, and often the best one: make it clear to your dependent service that it must either rebuild its system to compensate for the error in your service’s reliability, or reduce its own service level goals . If you do not eliminate the discrepancy yourself, a sufficiently long failure of the system will inevitably require adjustments.

Practical application

Let’s look at an example of a service with a target reliability of 99.99% and work out the requirements for both its components and its failure handling.

Digits

Assume your 99.99% available service has the following characteristics:

• One major outage and three minor outages per year. It sounds intimidating, but note that the 99.99% reliability target implies one 20-30 minute massive downtime and several short partial outages per year. (The math indicates that a) the failure of one segment is not considered a failure of the entire system in terms of SLO and b) the overall reliability is calculated by the sum of the reliability of the segments.)
• Five critical components as other independent services with 99.999% reliability.
• Five independent segments that cannot fail one after the other.
• All changes are made incrementally, one segment at a time.

The math for reliability would be:

Component requirements

• The total error limit for a year is 0.01 percent of 525,600 minutes per year, or 53 minutes (based on a 365-day year, with worst scenarios).
• The limit allocated to critical component outages is five independent critical components with a limit of 0.001% each = 0.005%; 0.005% of 525,600 minutes per year, or 26 minutes.
• Your service’s remaining error limit is 53-26=27 minutes.

Outage response requirements

• Expected downtime: 4 (1 total outage and 3 outages affecting only one segment)
• Cumulative impact of expected outages: (1×100%) + (3×20%) = 1.6
• Fault detection and recovery time: 27/1.6 = 17 minutes
• Time allotted for monitoring to detect and report a failure: 2 minutes
• Time given to the duty specialist to start analyzing the notification: 5 minutes. (The monitoring system must monitor for SLO violations and send a pager to the attendant each time the system fails. Many Google services are supported by shifts on duty SR engineers who respond to urgent issues.)
• Remaining time to effectively mitigate adverse effects: 10 minutes

Conclusion: levers to increase service reliability

It’s worth taking a close look at these numbers because they highlight a fundamental point: there are three main levers to increase service reliability.

• Reduce the frequency of outages through release policies, testing, periodic project design reviews, and more.
• Reduce average downtime by sharding, geo-isolation, gradual degradation, or customer isolation.
• Reduce recovery time – through monitoring, one-button rescue actions (e.g. rollback or adding standby power), operational readiness practices, etc.
  You can balance between these three methods to simplify the implementation of fault tolerance. For example, if reaching the 17-minute MTTR is difficult, focus your efforts on reducing your average downtime. Strategies for minimizing negative impacts and mitigating the impact of critical components are discussed in more detail later in this article.

Refinement of the “Additional 9s Rule” for nested components

The casual reader may infer that each additional link in the dependency chain requires additional 9s, so second-order dependencies require two additional 9s, third-order dependencies require three additional 9s etc.

This is not a valid conclusion. It is based on a naive tree component hierarchy model with constant branching at each level. In such a model, as shown in Fig. 1, there are 10 unique first-order components, 100 unique second-order components, 1,000 unique third-order components, and so on, resulting in a total of 1,111 unique services, even if the architecture is limited to four layers. An ecosystem of highly reliable services with so many independent critical components is clearly unrealistic.

Fig. 1 – Component Hierarchy: Invalid Model

A critical component by itself can cause an entire service (or segment of a service) to fail, no matter where it is in the dependency tree. Therefore, if a given component X appears as a dependency of multiple first-order components, X should only be counted once, as its failure will eventually cause the service to fail, no matter how many intermediate services are also affected.

The correct reading of the rule is as follows:

• If a service has N unique critical components, then each one contributes 1/N to the unreliability of the entire service caused by that component, no matter how low it is in the component hierarchy.
• Each component must only be counted once, even if it appears multiple times in the component hierarchy (in other words, only unique components are counted). For example, when counting the components of Service A in Fig. 2, Service B should only be counted once.

Fig. 2 – Components in the hierarchy

For example, consider a hypothetical service A with an error limit of 0.01 percent. Service owners are willing to spend half of this limit on their own errors and losses, and half on critical components. If the service has N such components, then each of them gets 1/N of the remaining error limit. Typical services often have 5 to 10 critical components, and so each can only fail to the power of one tenth or one twentieth of Service A’s error limit. Therefore, as a general rule, critical parts of a service should have one additional nine of reliability.

Error limits

The concept of error limits is covered in some detail in the SRE book, but it should be mentioned here as well. Google’s SR engineers use error limits to balance the reliability and pace of updates. This limit defines the acceptable failure rate for the service over a period of time (usually a month). The error limit is simply 1 minus the SLO of the service, so the previously discussed 99. 99 percent available service has a 0.01% “limit” for unreliability. As long as the service has not used up its error limit within a month, the development team is free (within reason) to launch new features, updates, etc.

If the error limit is used up, changes to the service are suspended (except for emergency security fixes and changes that target what caused the breach in the first place) until the service replenishes the error limit or until the month changes. Many services in Google use a sliding window method for SLO so that the error limit is restored gradually. For serious services with an SLO of more than 99.99%, it is advisable to apply a quarterly rather than a monthly reset of the limit, since the number of acceptable downtimes is small.

Error limits eliminate interdepartmental tensions that might otherwise arise between SR engineers and product developers by providing them with a common, data-driven mechanism for evaluating the risk of a product launch. They also give both SR engineers and development teams a common goal of developing methods and technologies that will allow them to innovate faster and launch products without “blowing the budget”.

Critical component reduction and mitigation strategies

So far, in this article, we have established what can be called the “Golden Rule for Component Reliability” . This means that the reliability of any critical component must be 10 times the target reliability level of the entire system in order for its contribution to the unreliability of the system to remain within the error level. It follows that, ideally, the goal is to make as many components as possible non-critical. This means that components can adhere to a lower level of reliability, giving developers the freedom to innovate and take risks.

The simplest and most obvious strategy to reduce critical dependencies is to eliminate single points of failure (SPOF) whenever possible. The larger system must be able to work acceptably without any specified component that is not a critical dependency or SPOF.
In fact, you most likely cannot get rid of all critical dependencies; but you can follow some system design guidelines to optimize reliability. While this is not always possible, it is easier and more efficient to achieve high system reliability if you build reliability into the design and planning stages, rather than after the system is running and impacting actual users.

Project Design Evaluation

When planning a new system or service, or redesigning or improving an existing system or service, an architecture or design review can reveal common infrastructure and internal and external dependencies.

Shared infrastructure

If your service uses a shared infrastructure (for example, a core database service used by multiple products available to users), consider whether that infrastructure is being used correctly. Clearly identify the owners of the shared infrastructure as additional contributors to the project. Also, beware of overloading components by carefully coordinating the launch process with the owners of those components.

Internal and external dependencies

Sometimes a product or service depends on factors outside your company’s control, such as third party software libraries or services and data. Identification of these factors will minimize the unpredictable consequences of their use.

Plan and design systems carefully
When designing your system, pay attention to the following principles:

Redundancy and isolation

You can try to reduce the impact of a critical component by creating multiple independent instances of it. For example, if storing data in a single instance provides 99.9 percent availability of that data, then storing three copies in three widely dispersed instances would, in theory, provide an availability level of 1 – 0.013, or nine nines, if instance failures are independent at zero correlation.

In the real world, the correlation is never zero (consider backbone failures that affect many cells at the same time), so the actual reliability will never get close to nine nines, but will far exceed three nines.

Similarly, sending an RPC (remote procedure call) to one pool of servers in the same cluster can achieve 99% availability of results, while sending three simultaneous RPCs to three different pools of servers and accepting the first response received helps achieve accessibility level higher than three nines (see above). This strategy can also reduce the latency tail of the response if the server pools are equidistant from the RPC sender. (Because the cost of sending three RPCs at the same time is high, Google often times these calls strategically: most of our systems wait a fraction of the allotted time before sending a second RPC, and a little more time before sending a third RPC.)

Fallback and its use

Set up startup and software migration so that systems continue to work when individual parts fail (fail safe) and isolate automatically when problems occur. The basic principle here is that by the time you get a person to turn on the reserve, you will probably have already exceeded your error limit.

Asynchrony

To prevent components from becoming critical, design them to be asynchronous wherever possible. If a service is waiting for an RPC response from one of its non-critical parts that exhibits a dramatic slowdown in response time, that slowdown will unnecessarily degrade the performance of the parent service. Setting the RPC for a non-critical component to asynchronous will free the parent service’s response times from being tied to those of that component. And although asynchrony can complicate the code and infrastructure of the service, it is still worth the trade-off.

Resource planning

Make sure all components are provided with everything you need. When in doubt, it is better to have an excess reserve – but without increasing costs.

Configuration

Standardize component configuration where possible to minimize discrepancies between subsystems and avoid one-time failure/error handling modes.

Troubleshooting

Make error detection, troubleshooting and diagnosing problems as easy as possible. Effective monitoring is essential for the timely identification of problems. Diagnosing a system with deeply embedded components is extremely difficult. Always have at the ready a way to level errors that does not require detailed intervention by the attendant.

Fast and reliable rollback

Incorporating the manual work of attendants into the disaster recovery plan significantly reduces the ability to meet hard SLO targets. Build systems that can easily, quickly and seamlessly return to a previous state. As your system improves and confidence in your monitoring method grows, you can lower your MTTR by developing a system to automatically trigger safe rollbacks.

Systematically check for all possible failure modes

Examine each component and determine how a failure in its operation can affect the entire system. Ask yourself the following questions:

• Can the system continue to operate in degraded mode if one of them fails? In other words, design for gradual degradation.
• How do you solve the problem of component unavailability in different situations? When starting the service? During the service?

Test extensively

Design and implement a rich testing environment that ensures that each component is covered by tests that include the main usage scenarios for that component by other components of the environment. Here are some recommended strategies for such testing:

• Use integration testing to work out troubleshooting – make sure the system can survive if any of the components fail.
• Perform crash testing to identify weaknesses or hidden/unplanned dependencies. Record the course of action to correct the identified deficiencies.
• Do not test normal load. Intentionally reboot the system to see how its functionality decreases. One way or another, your system’s response to overload will become known; but it is better not to leave load testing to users, but to test the system yourself in advance.

The way forward

Expect changes to scale: A service that started out as a relatively simple binary on a single machine can develop many obvious and non-obvious dependencies when deployed at a larger scale. Each order of scale will reveal new constraints—not just for your service, but for your dependencies. Think about what happens if your dependencies can’t scale as fast as you need them to.