#fault-tolerant-architecture

#fault-tolerant-architecture

Apache Kafka has cemented itself as the de facto platform for event streaming, often referred to as the 'universal data substrate' due to its extensive ecosystem that enables connectivity and processing capabilities.

Uber's engineering team has transformed its data replication platform to move petabytes of data daily across hybrid cloud and on-premise data lakes, addressing scaling challenges caused by rapidly growing workloads. Built on Hadoop's open-source Distcp framework, the platform now handles over one petabyte of daily replication and hundreds of thousands of jobs with improved speed, reliability, and observability.

It was the time of Novell networks, RG58 cables, and bulky tower PCs. It was also a time before the telemarketer's IT department employed specialists. Carter and his two colleagues - boss Mike and part-time student Stefan - therefore handled tasks ranging from programming to support, and everything in between.

Red Hat AI Enterprise provides a foundation for modern AI workloads, including AI life-cycle management, high-performance inference at scale, agentic AI innovation, integrated observability and performance modeling, and trustworthy AI and continuous evaluation. Tools are provided for dynamic resource scaling, monitoring, and security.

There is a growing emphasis on database compliance today due to the stricter enforcement of compliance rules and regulations to safeguard user privacy. For example, GDPR fines can reach £17.5 million or 4% of annual global turnover (the higher of the two applies). Besides the direct monetary implications, companies also need to prioritize compliance to protect their brand reputation and achieve growth.

For years, reliability discussions have focused on uptime and whether a service met its internal SLO. However, as systems become more distributed, reliant on complex internet stacks, and integrated with AI, this binary perspective is no longer sufficient. Reliability now encompasses digital experience, speed, and business impact. For the second year in a row, The SRE Report highlights this shift.

An observability control plane isn't just a dashboard. It's the operational authority system. It defines alert rules, routing, ownership, escalation policy, and notification endpoints. When that layer is wrong, the impact is immediate. The wrong team gets paged. The right team never hears about the incident. Your service level indicators look clean while production burns.

Almost a quarter of those surveyed said they had experienced a container-related security incident in the past year. The bottleneck is rarely in detecting vulnerabilities, but mainly in what happens next. Weeks or months can pass between the discovery of a problem and the actual implementation of a solution. During that period, applications continued to run with known risks, making organizations vulnerable, reports The Register.

A North American manufacturer spent most of 2024 and early 2025 doing what many innovative enterprises did: aggressively standardizing on the public cloud by using data lakes, analytics, CI/CD, and even a good chunk of ERP integration. The board liked the narrative because it sounded like simplification, and simplification sounded like savings. Then generative AI arrived, not as a lab toy but as a mandate. "Put copilots everywhere," leadership said. "Start with maintenance, then procurement, then the call center, then engineering change orders."

A future-proof IT infrastructure is often positioned as a universal solution that can withstand any change. However, such a solution does not exist. Nevertheless, future-proofing is an important concept for IT leaders navigating continuous technological developments and security risks, all while ensuring that daily business operations continue. The challenge is finding a balance between reactive problem solving and proactive planning, because overlooking a change can cost your organization. So, how do you successfully prepare for the future without that one-size-fits-all solution?

The Harness Resilience Testing platform extends the scope of the tests provided to include application load and disaster recovery (DR) testing tools that will enable DevOps teams to further streamline workflows.

Over the past few years, I've reviewed thousands of APIs across startups, enterprises and global platforms. Almost all shipped OpenAPI documents. On paper, they should be well-defined and interoperable. In practice, most fail when consumed predictably by AI systems. They were designed for human readers, not machines that need to reason, plan and safely execute actions. When APIs are ambiguous, inconsistent or structurally unreliable, AI systems struggle or fail outright.

When I manage infrastructure for major events (whether it is the Olympics, a Premier League match or a season finale) I am dealing with a "thundering herd" problem that few systems ever face. Millions of users log in, browse and hit "play" within the same three-minute window. But this challenge isn't unique to media. It is the same nightmare that keeps e-commerce CTOs awake before Black Friday or financial systems architects up during a market crash. The fundamental problem is always the same: How do you survive when demand exceeds capacity by an order of magnitude?

The main advantage of going the Multi-Cloud way is that organizations can "put their eggs in different baskets" and be more versatile in their approach to how they do things. For example, they can mix it up and opt for a cloud-based Platform-as-a-Service (PaaS) solution when it comes to the database, while going the Software-as-a-Service (SaaS) route for their application endeavors.

Running a global observability platform means one thing above all: your infrastructure must never go down. When you're responsible for monitoring thousands of customers' applications 24/7, network failures aren't just inconvenient, they're existential threats. At New Relic, hundreds of clusters run on multiple clouds, and regions. These clusters depend on a complex web of network connections: regional transit gateways, inter-regional hubs, and cross-cloud links.