Your system architecture is at risk of data loss. How can you protect it?

To safeguard your system architecture against data loss, it's essential to combine preventive and corrective strategies. Start with preventive measures: implement robust data backups, ensure data redundancy, and establish reliable disaster recovery plans. These steps help in minimizing the risk of data loss. In addition, focus on corrective actions for unforeseen incidents. Set up comprehensive logging and monitoring systems in critical areas prone to data loss. This approach not only helps in identifying and addressing issues promptly but also aids in understanding the root causes of any data loss, enabling more effective prevention in the future.

Risk assessments start with understanding your data. Identify your data components (systems, servers, endpoints) and classify them according to compliance and availability needs. Next, use assessment frameworks such as NIST SP 800-30 or OCTAVE to analyze and prioritize possible threats based on impact and likelihood. The last step is risk mitigation and prioritization. It involves identifying and enforcing controls. These controls can be technical (encryption, firewalls, DLPs), administrative (governance, training, etc.), or physical (secure facilities, access control systems, and environmental controls). It's important to keep ourself updated and involve all relevant stakeholders in this process to have a comprehensive assessment .

Assessing data loss risk involves continuous monitoring & surveillance of system activities to detect anomalies or potential security threats. Implement data loss prevention solutions to monitor, detect, prevent unauthorised access or transfer of sensitive info. Securing data is an ongoing process that requires a combination of technical measures, proactive monitoring, user awareness & education—security best practices, phishing threats, the importance of safeguarding sensitive information. Regularly review user permissions to ensure least privilege access, review logs to identify suspicious behaviour & ensure compliance. Setup monitoring systems to regularly check the status of backups; configure alerts to notify administrators promptly.

Data loss in distributed systems can occur due to service crashes or race conditions. To mitigate service crashes, implement a recovery strategy using Write-Ahead Logging (WAL) logs and replication logs. For race conditions, design your system to ensure operations are serializable, using strategies like acquiring locks. These are preventative or recovery measures to consider in system architecture design. However, uncontrollable scenarios may still cause data loss. To address these, establish robust monitoring mechanisms to alert digital operations teams, enabling them to execute recovery tools.

Add redundancy at the storage layer by using the storage vendor's redundancy approach. Add it also to the compute and network layers to not use data inflight. If you are worried about losing data via security breeches, add all the things that will make it secure such as MFA, DLP, a SIEM, and end point monitoring.

Strategies: ?Regular Backups—schedule these to ensure data is captured frequently ?Automated Backups—use such solutions to reduce the chance of human error & ensure consistency in backup schedule ?Offsite Backups—store backups in a location physically separate from the primary data center to protect against disasters like fires, floods, other catastrophic events ?Periodic Backups—combine incremental with periodic full backups to balance efficiency & completeness ?Versioning—keep multiple versions of files to facilitate recovery from accidental data corruption/deletion; data is restored to a specific point in time ?Encryption—safeguard data during storage & transmission, especially for cloud storage ?Testing Backups—ensure backups are viable

The magical numbers here are "3-2-1": - 3 copies; - 2 different medias; - 1 off-site location. Depending on the data volume, its frequency of use, and updating, some additional strategies should be considered: redundancy, regularity, automation, testing, monitoring, encryption, versioning and incremental techniques, documentation, training, education, and policies. Here it is the opinion part: the policy is the most relevant item above because it will cover all other else in addition to other such as: contingency plan, access control, retention policies, data classification, legal and compliance issues, auditing, and much more.

Based on my risk assessment and recovery objectives, I'd implement a cloud backup strategy adhering to the well-known 3-2-1 rule: maintain three copies of data, on two different media, with one stored offsite. I'd regularly back up crucial data using suitable methods (e.g., full, incremental) and verify backups for integrity. Additionally, I'd choose a reliable cloud storage provider ensuring data redundancy and security, aligning with my business needs. For automation, I recommend leveraging Duplicity, an open-source tool I'm comfortable with, given its reliability and flexibility in managing cloud backups efficiently.

Backing up your important files is crucial to ensure that you don't lose any critical data. That's why it's essential to use periodic backup services like iCloud, Google Drive, and AWS Backup. These services offer reliable storage solutions that can keep your data safe and accessible from anywhere. Moreover, keeping an offline backup of your files is always a good idea. It provides an extra layer of security and ensures that you have a backup in case of any unforeseeable event. So don't take any chances with your data - make sure to use backup services and keep an offline backup today!

Really review your backup strategy to ensure that you have no gaps. Determine if catastrophe happens what is the amount of lost work. Ensure that you are accounting for all the reasons you may lose data (local event, regional event, ransomware, etc) and use that to ensure your backup strategy accounts for those scenarios. Most importantly test your backups, all of them. Ensure you can backup quickly from a temporary outages as well as testing the need to restore from your offsite backups.

Leverage data recovery services as a crucial step in protecting your system architecture from data loss. These specialized services can restore data from various sources—hard drives, servers, cloud storage, databases—in scenarios like deletion, formatting, corruption, encryption, or physical damage. Select a data recovery provider that is not only reliable and secure but also compatible with your system architecture, ensuring swift and efficient data restoration in the event of a disaster.

Data recovery is integral to your backup and restore strategy, aligning with the initial risk assessment that defines Recovery Point Objectives (RPOs) and Recovery Time Objectives (RTOs) for various data types. This assessment informs the selection of appropriate backup and restore methods, such as full, incremental, selective, differential, point-in-time, and instant restore. Depending on the available solutions and requirements, these processes can be automated or manual, and may also incorporate cloud services for enhanced flexibility and efficiency.

Backed up data that you cannot recover - is useless. If you have shipped a hard copy to a remote isolated destination, you must make sure you can recover it. That goes without saying, otherwise it is useless. The services you use to transport the data should provide the means to recover it back in its original form. It might be professional services back and forth or any other physical or digital means but make sure you can get your backup back and in it's original form. Those services job it to get your original data in its original state. Corruption, encryption, any damage should be transpetent to you and you must make sure it is in the fine print of the solution you choose.

After setting up my backup strategy, the next step I'd take to safeguard my system architecture from data loss is to utilize data recovery services. These services are crucial in restoring data in case of a disaster. Specifically, I'm also comfortable leveraging the data recovery solution offered by Google Cloud Platform (GCP). In the GCP ecosystem, they provide recovery services that can handle various scenarios, from accidental deletion to physical damage and their solution integrates seamlessly with my system architecture, ensuring reliability and security. This adds an extra layer of protection to my data, giving me peace of mind knowing that I have a reliable recovery option in place.

An untested Disaster Recovery (DR) strategy is as ineffective as having no strategy at all. Just as successful implementation requires thorough planning and testing, so too does a DR setup. It is essential to regularly update the DR strategy to incorporate enhancements, fixes, and adjustments due to various factors, including new legal requirements. These updates should be integrated into your Enterprise Architecture practice and undergo regular evaluation and testing. Incorporating resiliency testing can provide a deeper understanding of system and data dependencies, further strengthening your DR strategy.

Regularly test and update your backup and recovery plan to ensure your system architecture's protection against data loss. Verify the functionality of backups, the ability to quickly access and restore data, and the capacity to resume operations post-recovery. Adapt your plan to reflect changes in system architecture, data volume, or business needs. Conduct periodic audits, reviews, and drills to assess and enhance your plan's effectiveness, keeping your data protection strategies aligned with current requirements.

A good plan is not enough. It might be good for some checkboxes or to please your managers but if you cannot execute it on the spot when it is needed it is useless. Test it. Execute it. Multiple times. Make sure you are able to go through with it even after hours. Your goal should be getting the Crown Jewel if you have lost it. That's it. That's the goal. And if something doesn't work, change the plan, change the means, change whatever is needed to make it work the next time you test it. Every DR drill should be treated as a real incident. No shortcuts.

IMHO, I'd test and update my backup and recovery plan in this way: 1 - Schedule regular tests, adjusting frequency based on data criticality. 2 - Simulate diverse disaster scenarios to ensure plan efficacy. 3 - Verify data restoration accuracy during testing. 4 - Update documentation to reflect system changes promptly. 5 - Conduct drills to evaluate personnel response and address gaps. 6 - Perform regular audits to review compliance and identify areas for improvement, ensuring plan robustness.

Team work is crucial. You back up your data, you should have a backup for yourself. If it's a team work, train the team, go over things before the drill and have a retro afterwards that counts - take notes and implement them. Make sure everybody knows their part. Help and train them if they don't. Stress the importance and the urgency of their parts and roles. Train them technically but also make them understand the importance and the consequences. Most importantly, trust them, they are part of success.

What I've already done? Workshops: I hosted workshops to emphasize the importance of data backup and recovery and how we can implement it. Docs: I've created guides detailing backup and recovery procedures, roles, and our protection policies. Hands-On: We've had practical sessions where team members learned to use backup tools and services, with data recovery exercises. Skill Tests: I've administered quizzes to gauge team understanding and identify areas needing improvement. Simulations: We've simulated data loss scenarios, allowing the team to practice their strategies in a controlled environment. Feedback & Tweaks: I've asked team feedback to refine our training approach, ensuring everyone stays proficient in backup and recovery.

Discuss around which data is generated and needed by which internal project. Should be discussed when designing the product, as the monitoring stuff should too, to ease up integration with backup & surveillance teams/tools.

To prevent data loss in a system architecture it is necessary to apply security practices, as well as implement appropriate technologies. As far as training goes, it's fine to train the team on backup and recovery, but it's not enough. It is necessary to train the team on cybersecurity and it is necessary to promote awareness among users (and among members of the same work team) to reduce the risk of attacks based on social engineering. With widespread awareness of cybersecurity issues, the risks of data loss can be reduced.

Write down your procedures. Don’t rely on a few experts to get you through the event. Well documented procedures allows you to leverage a broader set of people to help restore your data.

Implementing security measures: ?Access Controls—restrict access based on roles & responsibilities ?Encryption—for sensitive data both in transit & at rest that helps protects information even if unauthorised access occurs ?Network Security—implement firewalls, intrusion detection systems, regular monitoring to identify/mitigate potential threats ?Logging & Auditing—maintain detailed logs of system activities ?Endpoint Security—protect individual/isolated devices with antivirus software, regular updates, user training on potential threats ?Incident Response Plan—develop & regularly test plan to efficiently address & mitigate security incidents ?Periodic Security Audits—identify vulnerabilities & assess the effectiveness of security measures

Monitor and secure your data throughout its lifecycle to safeguard your system architecture from data loss. Track activities like creation, modification, deletion, and transfer, and shield your data from unauthorized access, modification, or theft. Implement encryption, authentication, authorization, and logging measures for robust data security. Additionally, ensure compliance with relevant data protection regulations and standards, such as GDPR, HIPAA, or PCI DSS, to maintain integrity and prevent legal issues.

Si una arquitectura de sistema tiene riesgo de perder datos, hay una falencia de fondo que no es admisible. Probablemente la mejor solución sea la drástica de renovar el equipo responsable, a uno que pueda dise?ar una arquitectura que prevenga cualquier pérdida de datos. Un sistema puede tener tolerancia a errores, pero nunca debe correr el riesgo de pérdida de información. Si no está en nuestra esfera de acción el cambio de equipo, hay que elevar los planes de acción que sean proactivos en detección de riesgos a priori: nunca se pueden tomar medidas reactivas a la pérdida de datos, deben ser proactivas sin discusión.

When protecting your system architecture from data loss, consider implementing a multi-layered security approach, including firewalls, anti-malware tools, and intrusion detection systems. Regularly update and patch all software to close security vulnerabilities. Employ a robust data backup strategy with offsite storage options to ensure data redundancy. Train employees on data security best practices and phishing awareness to minimize human error risks. Finally, establish a clear incident response plan to quickly address any data breach or loss, minimizing downtime and ensuring business continuity.

IMHO, the article is misleading and not coherent. First of all, it's unclear if the "system architecture" here refers to the actual system architecture definition and design or the implemented system (both can be subject to risks). On the other hand, as a system architect, you must ensure that data loss prevention processes and measures processes are already in place before designing a system (infrastructure level) or integrate into the design; NFRs must be defined for security and reliability to ensure safety and compliance by design.