Cloud and Infrastructure

Storage Solutions for Modern Applications Modern applications rely on fast, reliable data storage. The right mix of storage types helps keep apps responsive, costs predictable, and data safe. Teams often combine object storage for unstructured data, block storage for databases, and file storage for shared access. A thoughtful blend, plus solid governance, makes a big difference in daily operations. Types of storage for modern apps Object storage: stores large amounts of unstructured data with high durability and simple access. It’s great for media, logs, backups, and static assets. Use lifecycle policies to move cold data to cheaper tiers and a CDN to accelerate delivery. Block storage: attached to compute instances or databases. It offers low latency and high IOPS, but at a higher cost per gigabyte. File storage: a shared file system for teams and legacy software that expects a mounted drive. Useful for content repositories and analytics pipelines. Archive or cold storage: long-term data that is rarely accessed. Costs are low, but access times are slower. Ideal for compliance records and older backups. Hybrid and multi-cloud: a common pattern to balance control, latency, and disaster recovery. Keep hot data near the app and move older data to cheaper storage in another region or cloud. Choosing the right storage for your workload Begin with data categories and access patterns. Critical data and frequently used assets may stay hot, while older logs can move to cheaper tiers. Durability and availability should match your recovery goals. Consider latency from the user or service, and plan caching to smooth spikes. Costs vary by tier, region, and egress, so map total cost of ownership. Data governance matters too: encryption, access controls, and versioning help protect sensitive information. ...

Serverless and FaaS: Rethinking Application Architecture Serverless and Function as a Service (FaaS) offer fast scaling and less operational work. They push much of the infrastructure into the hands of cloud providers, letting teams focus on code and business value. But to use them well, we should rethink how we design apps, not just swap a server for a function. With this shift, applications become a collection of small tasks that run briefly and independently. Each function performs a single job and communicates with others through events or queues. This pattern helps scale each step as demand changes and reduces bottlenecks. ...

Virtualization and Containers: From VMs to Kubernetes Technology changes fast, but the goal remains simple: run software reliably while making updates easy. Virtual machines use a hypervisor to run separate operating systems on a single physical host. They provide strong isolation and broad compatibility, but each VM carries a full OS, so they can use more memory and storage. Containers shrink this footprint by packaging the app and its dependencies, sharing the host OS kernel. They start quickly and move easily from a developer laptop to a data center or cloud, making continuous delivery smoother. ...

Serverless Computing: When to Use It and How It Works Serverless computing lets you run code without managing servers. In practice, you write small functions that respond to events or HTTP requests, and the platform handles provisioning, load balancing, and automatic scaling. You pay only for compute time and invocations, not idle capacity. This model helps teams move faster and reduce ops work. Think about where it fits. Good uses include lightweight APIs and webhooks, bursty or unpredictable traffic, background processing, data pipelines, and quick prototypes. If you need rapid iteration or want to offload routine tasks to a managed platform, serverless can be a strong choice. It also works well for microservices that perform short tasks without long-running state. ...

Demystifying Operating Systems for Modern Workloads Today’s software relies on the operating system to manage CPU time, memory, and I/O. The job of an OS is to keep many tasks running fairly, securely, and with predictable latency. For modern workloads—from HTTP APIs to data pipelines—the OS also becomes a platform for virtualization and isolation. Understanding a few core ideas helps teams optimize performance without chasing every new tool. Key areas to watch are process scheduling, memory management, and I/O handling. Scheduling decides who runs when; memory brings speed and safety; I/O governs how fast data moves in and out. These foundations shape how responsive your services feel under load, and how well they scale. ...

Zero Trust Networking in Practice Zero Trust is not a single gadget. It is a mindset: trust no user or device by default, verify every access, and apply the least privilege needed. In practice this means continuous verification, strong identities, and tight network controls, even inside the company perimeter. The goal is to reduce blast radius if something is compromised and to simplify security across diverse apps and clouds. Key practices include verifying access explicitly, enforcing least privilege, assuming breach, inspecting and logging, and encrypting traffic both in transit and at rest. Identity becomes the primary gate: use a central identity provider, enable MFA, and map access to specific applications rather than broad networks. Devices must meet posture checks—updated OS, current security patches, and a compliant security status. Networks should be segmented into tiny boundaries, so each app or service has its own policy. ...

Incident Response for Cloud and On-Prem In hybrid environments, cyber incidents can move between cloud services and on-site systems. A clear incident response plan helps teams act quickly and stay coordinated. This article offers practical steps you can use. Be prepared Prepare with a written IR playbook that covers detection, triage, containment, eradication, recovery, and lessons learned. Keep roles and contact lists current. Inventory key assets in both environments and ensure log sources feed a central view. Practice tabletop exercises to stress the plan. ...

SRE and DevOps: Building Reliable Systems SRE and DevOps share a common goal: to deliver software quickly while staying reliable. SRE brings engineering rigor to reliability, using error budgets and clear service level objectives. DevOps emphasizes collaboration, automation, and fast feedback loops. When teams combine these ideas, they move from firefighting to steady, measurable improvement. Reliability is a property of the whole system, not a single tool. Build it on four pillars: clear ownership, automated workflows, strong observability, and a culture of learning. Ownership avoids confusion about who fixes components. Automation reduces human error in deployment and recovery. Observability gives us useful signals—simple dashboards, not a wall of logs. Learning comes from blameless postmortems and concrete follow-up actions. ...