Key Controls for Ensuring Cloud Resilience

Hi 👋 🚀 Resiliency Engineering: Why Top Tech Companies Never Fail Their Users In today’s software landscape, failures are inevitable. What separates the giants like Netflix, Google, and Amazon from the rest is not that they avoid failures, but that they anticipate, measure, and recover from them. ⭐ What is Resiliency Engineering? It’s the practice of designing systems that continue to operate correctly even when parts of the system fail, and can recover quickly. 🟢 Real-world Usage: In microservices, if one service goes down, the rest keep running. In cloud systems, even if an entire data center fails, uptime is preserved. In e-commerce and fintech, payment failures or network issues are handled gracefully to ensure a seamless user experience. 🟠Key Techniques & Tools: Retry with Backoff Circuit Breakers Timeouts & Fallbacks Bulkhead Isolation Rate Limiting 🟣 Monitoring Resiliency: Measure what matters: Availability / Uptime Error Rate Latency / P95 / P99 MTTR (Mean Time To Recovery) MTBF (Mean Time Between Failures) 🔵 Case Study: Netflix uses Chaos Engineering with tools like Chaos Monkey to intentionally fail services and test system resilience. Result? 99.99% uptime for millions of users worldwide. ⭕ Practical Steps to Improve Resiliency: 🔸Define SLOs & SLIs for every service 🔸Implement retry, timeout, circuit breaker, and fallback mechanisms 🔸Set up monitoring and observability (Prometheus, Grafana, OpenTelemetry) 🔸Run Chaos Engineering experiments 🔸Conduct blameless postmortems to learn and improve continuously Resiliency isn’t optional. It’s a competitive advantage. The question is: How resilient is your system today? #ResilienceEngineering #SRE #ChaosEngineering #Microservices #CloudNative #Reliability #Observability #SiteReliabilityEngineering #TechLeadership #HighAvailability

Dear Business & IT Audit Leaders, Cloud environments are not inherently secure. They are only as resilient as the questions we ask. As a cybersecurity audit leader, I don’t begin any cloud assessment without interrogating the architecture through 8 critical dimensions. These aren’t just technical checks, they’re strategic filters that reveal business risk, regulatory exposure, and operational blind spots. Whether you're migrating, auditing, or optimizing your cloud stack, these questions reveal the real posture of your environment. They cut through vendor promises and dashboards to expose what matters: risk, resilience, and regulatory readiness. Here’s the framework I use to guide CISOs, CTOs, and audit teams: 📌 Business Purpose & Data Sensitivity Every cloud asset must be mapped to its business function and data classification. If you don’t understand the value and risk of what’s hosted, you’re auditing in the dark. 📌 Cloud Service Model & Deployment Type IaaS, PaaS, SaaS, and Public, Private, Hybrid, each shift the shared responsibility model. Misidentifying this leads to control gaps and audit failures. 📌 Identity, Access & Privileged Account Management IAM policies, MFA enforcement, and least privilege aren’t optional, they’re the backbone of cloud security. I assess not just design, but operational discipline. 📌 Encryption at Rest & In Transit I validate cryptographic standards, key lifecycle management, and segregation of duties. Weak encryption is a silent breach waiting to happen. 📌 Network & Perimeter Defense Firewalls, segmentation, and intrusion prevention must be tested for effectiveness, not just existence. I look for real-world resilience, not checkbox compliance. 📌 Vulnerability Management & Threat Detection Scanning cadence, patch velocity, and incident response maturity determine whether threats are contained or compounded. I benchmark against threat intelligence and business risk. 📌 Business Continuity & Disaster Recovery Validation RTO/RPO metrics are meaningless without tested recovery capabilities. I simulate failure scenarios to assess readiness under pressure. 📌 Regulatory Compliance & Governance Frameworks From HIPAA to NIST to ISO 27001, I verify not just policy alignment but operational execution. Governance must be embedded, not just documented. These 8 dimensions form the backbone of my cloud audit methodology. They help organizations move from reactive security to proactive resilience. If you're leading cloud transformation, audit readiness, or cybersecurity strategy, this is where your assessment should begin. Let’s discuss: Which of these questions do you think is most overlooked in your organization? #CloudSecurity #CyberAudit #ITAudit #AIaudit #RiskManagement #CloudSecurityRisk #CyVerge #CloudSecurityAudit #Cyberverge #Governance #CloudResilience #CloudGovernance

Announcing a new role at Intellias as a VP of Global Cloud Strategy on the same day Amazon Web Services (AWS) works through an outage feels like a direct message and a reminder that provider uptime is only part of the story. Real resilience is a business strategy. It is easy to point at a cloud provider. The harder and more valuable work is looking inward and asking what we could have designed differently so customers feel a brief pause, not pain. Think utility power. Most of the time the lights come on without a thought. When they do not, outcomes depend on what you put in place: a fresh bulb, the right breaker, a UPS, a small generator, maybe solar plus batteries. Cloud is the same. Choices you make before the storm determine how you ride it out. What we control: (1) Resilience by design: retries with backoff, idempotency, timeouts, load shedding. (2) Blast radius limits: cell-based architecture and per Region isolation. (3) Right-sized redundancy: Multi AZ as baseline; warm standby or active active for critical journeys. (4) Data protection targets: clear RTO and RPO mapped to customer journeys. (5) Operational muscle: chaos and game days, runbooks, crisp communications plans. (6) Cost clarity: compare the price of resilience with the cost of downtime and decide explicitly. Resilience Menu (in increasing cost and complexity): (1) Hygiene and graceful degradation: health checks, feature flags, fallback content, read-only modes, rate limits, capacity buffers, synthetic monitoring. (2) Multi AZ fundamentals: AZ-aware shards, queue-first patterns, dead-letter queues, warm pools, circuit breakers, bulkheads, structured timeouts and backoff. (3) Multi Region warm standby: cross Region backups, pilot light, async replication, prepared DNS or traffic manager failover, rehearsed runbooks with target RTO/RPO. (4) Active active multi Region: global data strategies and conflict resolution, partition-tolerant stores, global service discovery, continuous chaos at scale, contractual SLOs. (5) Targeted multi cloud (when concentration risk is unacceptable): selective diversification for control planes such as DNS, CDN, or identity. Outages will happen. The question is whether customers experience a slowdown or a well-practiced plan. In my new role, I am doubling down on making resilience intentional, measured, and worth the money. As Werner Vogels says, "Everything fails, all the time" Chaos is inevitable. Chaos engineering makes it intentional and survivable, turning resilience into a competitive edge: faster recovery, steadier customer experience, and the ability to ship when others stall. #cloudstrategy #resilience #aws #architecture #SRE #devops #businesscontinuity

☁️ Every major cloud outage is a reminder that resilience isn’t something you can enable with a checkbox, it’s something you need to explicitly design, test, and adapt as dependencies evolve. A recent “thermal event” in Microsoft Azure’s West Europe region, caused by a cooling system fault triggered hardware shutdowns, took storage units offline, and resulted in broader service disruption across VMs, databases, and Azure Kubernetes Service. Even impacting dependent services in other Availability Zones. Serving as a reminder that zone-redundancy alone isn’t going to be enough when underlying storage fabrics or control-plane dependencies span across availability zones. If your replication strategy still relies on locally-redundant storage (LRS) within a single zone, or even multiple zones in the same region, you're exposed to environmental failures like this. As organizations migrate more critical workloads to the cloud, now is the moment to revisit resilient architecture. Invest in services that span multiple regions to avoid this kind of exposure, and test failover under realistic conditions, so that teams can build muscle-memory and to expose unexpected dependencies. https://lnkd.in/eUsDQ-gH https://lnkd.in/eBz8J3kD

After the war, everyone’s a general… but true leaders learn before the next battle. Just a few hours ago, AWS US-EAST-1 experienced a 16-hour outage that began with a seemingly simple DNS failure and ended up impacting more than 12 key services — EC2, Lambda, RDS, IAM, SQS, CloudWatch, and more. The timeline published by Prabh Nair reveals how a single DNS resolution error in DynamoDB cascaded through multiple layers: DNS → Identity (IAM) → Compute (EC2) → Network (NLB) → Applications. Beyond the technical autopsy, the report highlights several lessons that no CISO or Cloud Operations team should ignore: 🔹 Understand your dependency depth. “High availability” ends where your single point of failure begins — even if it’s buried in IAM or DNS. 🔹 Separate your control planes. Identity, telemetry, and logging must survive a regional failure. 🔹 Validate recovery. “Operational” doesn’t mean “recovered”: measuring backlog drain times, latency, and queue depth is essential. 🔹 Practice chaos. Tabletop and simulation exercises should include DNS and authentication failures. 🔹 Review SLAs and regional distribution. US-EAST-1 remains AWS’s busiest — and most failure-prone — region. The question isn’t if your infrastructure will fail, but whether you’ve already mapped how it will — and how you’ll respond when it does. #CloudResilience #AWS #CyberSecurity #IncidentResponse #CISO #ChaosEngineering #ResilienceByDesign

The internet wobbled today. A DNS issue in a single AWS region cascaded across otherwise “safe” regions and availability zones. This was not just another regional outage. It was a practical lesson in the cloud's hidden, centralized dependencies. We build for multi-region resilience, but we are often betrayed by "global" services that are not as distributed as they appear. The gap between perceived autonomy and actual entanglement is where resilience fails. My lessons learned from today’s AWS outage: 1. The Control Plane Chokepoint AWS separates data planes (serving traffic) from control planes (the APIs managing resources). Many global control planes live in one region, often us-esst-1. When that hub is impaired, your automation fails. You cannot scale, deploy, or modify resources, even in perfectly healthy regions. 2. The Hidden Dependency Chain The obvious risk is your application failing. The hidden risk is the failure of a core service you do not directly use. Today’s DNS and networking issue rhymes with the 2020 Kinesis outage. A foundational service failed, and higher level systems like Cognito, Lambda, and Auto Scaling began to error simply because they relied on it internally. 3. The Myth of the "Island" Application Even a perfect multi-AZ application is not an island. It must resolve DNS, fetch IAM tokens, pull container images, and push logs. These core functions often rely on shared, centralized services. When those services choke, your redundant application times out. History provides a classic intelligence analog. During WWII, Allied planners knew German communications were heavily encrypted. But they also knew most signals could only transit a few central relay stations. By targeting those nodes, they could blind the entire network without breaking a single code. The cloud's core services are these modern relay stations. We are not just choosing between regional availability and multi-region reliability. We are choosing between apparent distribution and actual fault isolation. The core principle is to understand your actual blast radius. A system is only as resilient as its most critical, least visible dependency. Today is a reminder that resilience is not an architectural diagram. It is the verified, tested ability to withstand the failure of a dependency you probably forgot you had.

"Your cloud isn’t resilient. It’s just redundant. 🔄 Last year, a single misconfigured script took a client’s API offline for 3 hours—despite their ‘99.99% uptime’ SLA and triple backups. Why? They’d engineered for hardware failure, not human error. Resilience isn’t backups or multi-AZ setups. It’s designing for the disasters you can’t predict: *The DevOps lead who deletes a prod database… on their last day. *The cloud region that goes dark… during Black Friday. *The third-party API that leaks… and takes your auth tokens with it. The game-changer? 1️⃣ Run chaos experiments weekly: Netflix’s Chaos Monkey isn’t a tool—it’s a mindset. Intentionally crash non-critical systems to find hidden dependencies. (Pro tip: Do this on Fridays. Teams fix issues faster when weekends are at risk.) 2️⃣ Back up to a competitor’s cloud: Multi-cloud redundancy isn’t about loyalty—it’s survival. When one provider’s API buckles, your failover shouldn’t beg for permission. 3️⃣ Treat infrastructure as a crime scene: Version-control every change with tools like Terraform. If a deployment fails, you’ll know who did what in 8 seconds flat. The stats don’t lie: 1. 70% of outages trace back to config errors, not hackers (Gartner, 2023). 2. Companies using 3+ cloud regions reduce downtime costs by 99% (AWS Global Infrastructure Report). 3. NASA recovered 99.9% of “lost” Mars data in 2021 by automating cross-region syncs after a storage failure. Resilience isn’t a checkbox. It’s a culture. Build systems that bend, not break. 🌪️ #CloudComputing #DevOps #Resilience"

I recently led a couple of cloud-incident workshops, got a lot of great questions, had wonderful exchanges, frankly learned a lot myself, and wanted to share a few takeaways: • 𝗔𝘀𝘀𝘂𝗺𝗲 𝗯𝗿𝗲𝗮𝗰𝗵 - 𝘀𝗲𝗿𝗶𝗼𝘂𝘀𝗹𝘆: Treat "when, not if" as an operating principle and design for resilience.    • 𝗖𝗹𝗮𝗿𝗶𝗳𝘆 𝘀𝗵𝗮𝗿𝗲𝗱 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆: Most gaps aren’t exotic zero-days - they’re governance gray zones, handoffs, and multi-cloud inconsistencies.    • 𝗜𝗱𝗲𝗻𝘁𝗶𝘁𝘆 𝗶𝘀 𝘁𝗵𝗲 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝗽𝗹𝗮𝗻𝗲: MFA everywhere (but not enough), push passwordless, least privilege by default, regular access reviews, strong secrets management, and a push to passwordless.    • 𝗠𝗮𝗸𝗲 𝗳𝗼𝗿𝗲𝗻𝘀𝗶𝗰𝘀 𝗰𝗹𝗼𝘂𝗱-𝗿𝗲𝗮𝗱𝘆: Extend log retention, preserve/analyze on copies, verify what your CSP actually provides, and rehearse with legal and IR together.    • 𝗗𝗲𝘁𝗲𝗰𝘁 𝗮𝗰𝗿𝗼𝘀𝘀 𝗽𝗿𝗼𝘃𝗶𝗱𝗲𝗿𝘀: Aggregate logs (AWS/Azure/GCP/Oracle), layer in behavior-based analytics/CDR, and keep a cloud-specific IR/DR runbook ready to execute.    • 𝗕𝗼𝗻𝘂𝘀 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝗰𝗵𝗲𝗰𝗸: host/VM escapes are rare - but possible. Don’t build your program around unicorns; prioritize immutable builds, hardening, and hygiene first. If you’d like my cloud IR readiness checklist or the TM approach I’ve been using, drop a comment, and we’ll share. Let’s raise the bar together. #CloudSecurity #IncidentResponse #ThreatModeling #CISO #DevSecOps #DigitalForensics #MDR EPAM Systems Eugene Dzihanau Chris Thatcher Adam Bishop Julie Hansberry, MBA Ken Gordon Sharon Nimirovski Aviv Srour

Title: "Navigating the Cloud Safely: AWS Security Best Practices" Adopting AWS security best practices is essential to fortify your cloud infrastructure against potential threats and vulnerabilities. In this article, we'll explore key security considerations and recommendations for a secure AWS environment. 1. Identity and Access Management (IAM): Implement the principle of least privilege by providing users and services with the minimum permissions necessary for their tasks. Regularly review and audit IAM policies to ensure they align with business needs. Enforce multi-factor authentication (MFA) for enhanced user authentication. 2. AWS Key Management Service (KMS): Utilize AWS KMS to manage and control access to your data encryption keys. Rotate encryption keys regularly to enhance security. Monitor and log key usage to detect any suspicious activities. 3. Network Security: Leverage Virtual Private Cloud (VPC) to isolate resources and control network traffic. Implement network access control lists (ACLs) and security groups to restrict incoming and outgoing traffic. Use AWS WAF (Web Application Firewall) to protect web applications from common web exploits. 4. Data Encryption: Encrypt data at rest using AWS services like Amazon S3 for object storage or Amazon RDS for databases. Enable encryption in transit by using protocols like SSL/TLS for communication. Regularly update and patch systems to protect against known vulnerabilities. 5. Logging and Monitoring: Enable AWS CloudTrail to log API calls for your AWS account. Analyze these logs to track changes and detect unauthorized activities. Use AWS CloudWatch to monitor system performance, set up alarms, and gain insights into your AWS resources. Consider integrating AWS GuardDuty for intelligent threat detection. 6. Incident Response and Recovery: Develop an incident response plan outlining steps to take in the event of a security incident. Regularly test your incident response plan through simulations to ensure effectiveness. Establish backups and recovery mechanisms to minimize downtime in case of data loss. 7. AWS Security Hub: Centralize security findings and automate compliance checks with AWS Security Hub. Integrate Security Hub with other AWS services to streamline security management. Leverage security standards like AWS Well-Architected Framework for comprehensive assessments. 8. Regular Audits and Assessments: Conduct regular security audits to identify vulnerabilities and assess the effectiveness of security controls. Use AWS Inspector for automated security assessments of applications. 9. Compliance and Governance: Stay informed about regulatory requirements and ensure your AWS environment complies with relevant standards. Implement AWS Config Rules to automatically evaluate whether your AWS resources comply with your security policies.